SERVICE FAILURES AND RECOVERY STRATEGIES- A STUDY OF INDIAN
AVIATION INDUSTRY SINCE 2000
A
Ph. D. THESIS SUBMITTED TO THE UNIVERSITY OF JAMMU
FOR THE AWARD OF DEGREE OF
DOCTOR OF PHILOSOPHY
IN
TOURISM MANAGEMENT
BY
POONAM SHARMA
UNDER THE SUPERVISION OF
PROF. DEEPAK RAJ GUPTA
PROFESSOR
SCHOOL OF HOSPITALITY & TOURISM MANAGEMENT
UNIVERSITY OF JAMMU
JAMMU
SCHOOL OF HOSPITALITY AND TOURISM MANAGEMENT
UNIVERSITY OF JAMMU
JAMMU
2012
ACKNOWLEDGEMENT
Dedicated to Ganpati, Satya Sai Baba, Bawewali Mata, Datta and Datti ji.
To write an acknowledgement, recalls the contribution of all the persons in the completion of first milestone
of my journey towards the research. The results of this work will be judged by others, but I can definitely say
that the process was enjoyable. So I am glad to complete it by remembering many wonderful people who
have contributed to it in various ways.
First of all, I express my gratitude and indebtedness to my teacher and my supervisor Professor Deepak Raj
Gupta, Director, School of Hospitality and Tourism Management. I feel blessed and enlightened to be
associated with him for more than a decade and his continuous guidance both in the professional and the
personal matters that helps me in resolving all the worries of my life.
Words cannot express my deep regard and admiration for Dr. Anil Gupta. His selfless guidance in every
aspect made me to complete this thesis. His better half, Dr. Neelika Gupta constantly encouraged and
motivated me to compile the work. I am very thankful for their never ending support.
I also acknowledge my thanks to the Director of The Business School, Prof. Neelu Rohmetra for her constant
inspiration and guidance. I would like to extend warm thanks to Prof. R.D. Sharma, Dean Academic Affairs
and also Dean, Faculty of Business Studies, for his guidance and encouragement in the accomplishment of
my work.
I extend my thanks to all the teachers in the faculty of SHTM and The Business School, University of Jammu
ever since I got associated with the Department, including Prof. Ashok Aima, Prof. Keshav Sharma, Prof.
Versha Mehta, Prof. B.C. Sharma, Dr. Alka Sharma, Dr. Rajendra Mishra, Dr. Sameer Gupta, Dr. Parikshit
Singh Manhas, Dr. Vinay Chauhan, Dr. Amisha Gupta, Dr. Jaya Bhasin and Dr. Rachana Sharma.
My special thanks to Dr. Desh Bandhu Gupta, Professor, Department of Commerce, University of Jammu
whose encouragement and help made me feel confident in completing my research programme.
I owe my thanks to Mrs. Preeti Gupta, Librarian, SHTM and Mrs. Anju Gupta, Librarian, The Business
School, University of Jammu in helping me with the books and journals from the library. My thanks are also
reserved for the Librarians of the Commerce Department, University of Jammu; Ratan Tata Library; Faculty
of Management Studies; MDI, Gurgoan; IITTM, Gwalior for providing me the required literature whenever I
approached them. My special thanks are also due to Mr. Sanjay Sharma who always supported and helped in
lots of things during the last five years. In addition to it I would also like to thank Mrs. Anju Choudhary and
non-teaching staff for helping me through out the process.
I owe a very special thanks to Mr. Ramjit for his valuable inputs and assistance from time to time in several
ways.
I express with lot of love, my gratitude to Dr. Pooja Jain, Mrs Manmeet Kour, Dr. Suvidha Khanna Sondhi,
Mr. Abhishek Sharma, Mr. Mukesh Sharma, Mrs Neetu Khajuria, Mr. Risheesh Khajuria, Dr. Komal Nagar,
Dr. Saranpreet Kaur Broca, Mrs Sudamini Mahey, Dr. Bindiya Kohli, Dr. Anuradha Sharma, Dr. Sonia
Sharma who have always been encouraging and contributed with their moral support.
I also owe my thanks to my juniors Ms. Milly, Ms. Nazuk, Mr. Surjeet, Mr. Sourabh, Mr. Arun and those
whom I didn’t know by face but they helped in one way or the other for the completion of the thesis.
On the home front, I owe my biggest debt of gratitude to my father Sh. Om Dutt Baru and my mother Smt.
Shashi Bala for what I am today and every support in life that I needed. I extend my very special thanks to
my grandfather Sh. Ishwar Dass Baru for his guidance and constant moral support.
I shall never be able to express to any degree of satisfaction my thankfulness for the love, care and blessings
of Smt. Rekha Sharma (my mother-in-law) and divine blessings of Late Sh. Bansi Lal Sharma (my father-
in-law).
My love and special thanks are due to my sisters Mrs. Meenakshi Vaid, Mrs. Rachana Khajuria, Mrs.
Archana Sehgal, Ms. Arti Sharma and Ms. Radhika Gudda; my bhabhi’s Mrs. Madhu Badial, Mrs. Shiwani
Sharma, Mrs. ShrutiNidhi Sharma, Mrs. Ruchi Dhamija Sharma, my brothers Mr. Atal Khajuria, Col.
Ashutosh Badial, Mr. Abhinav Vaid, Mr. Ajay Sehgal, Mr. Puneet Sharma, Mr. Munish Sharma, Mr. Vivek
Sharma, Mr. Ashish Sharma, Mr. Aniket Gudda and little gems of my family Abhishek, Aishwarya,
Rakshita, Ananay, Apurva and Parth.
I owe thanks to my uncle Mr. Rajesh Oswal and aunt Mrs. Suman Oswal for their encouragement and moral
support.
The best outcome of these past five years has been to find my best friend, soul-mate and husband, Mukul.
Staying away is the most difficult thing for us, thanks for being patient, supportive and helping at every stage
of life. Arrival of our angel, Mani is the most joyous part of our life. There is feeling of guilt in me, because
of my work schedule on account of which I kept a father and a daughter separated from each other. I truly
thank Mukul for standing by my side, even when I was irritable and depressed. Your unconditional love and
support without any complaint or regret has enabled me to complete this Ph.D thesis. I owe my every
achievement to my love, Mukul and Mani.
I am also grateful to all the respondents who came forward to provide me with the desired information on the
topic with sincerity and clarity. I wish to thank to all the academicians, scholars, writers and authors to whom
I have referred and quoted.
I thank one and all, for their explicit or implicitly associated with this work.
POONAM SHARMA
TABLE OF CONTENTS
Chapter Particulars Page No.
Acknowledgement
Preface
List of Tables
List of Figures
List of Abbreviations
(i-ii)
(iii-vii)
(vii)
(ix)
1 Introduction
1.1 Statement of the Problem
1.2 Rationale of the Present Study
1.3 Scope of the Study
1.4 Concept of Service
1.5 Model of Service Consumption
1.5.1 The Pre purchase Stage
1.5.2 The Service Encounter Stage
1.5.3 The Post-encounter Stage
1.6 Attribution Theory
1.7 Perceived Justice
1.8 Global Aviation Industry
1-42
3
3
4
6
10
10
10
17
20
22
26
2 Indian Aviation Sector
2.1 Introduction
2.2 A Brief History of Aviation Industry in India
2.3 Civil Aviation in India
2.3.1 Ministry of Civil Aviation
43-105
43
45
48
48
2.3.2 Organizations Under Ministry of Civil
Aviation
2.4 Civil Aviation Policy in India
2.5 Reasons for Boom in Indian Aviation Industry
2.6 Future of Aviation Industry in India
2.7 Nature of Airlines
2.8 Airlines in India
2.8.1 Air India
2.8.2 Jet Airways
2.8.3 Kingfisher Airline
2.8.4 Indigo
2.8.5 GoAir
2.8.6 Spice Jet
2.8.7 Jagson Airlines
2.8.8 Paramount Airways
2.9 Air Traffic Trends
50
50
56
58
61
65
69
74
79
86
89
92
95
97
98
3 Review of Literature
3.1 Service Encounter
3.2 Service Failure and Service Recovery
3.2.1 Perceived Justice
3.3 Highlights of the Present Study
3.4 Research Gap
106-178
107
125
151
163
164
4 Research Design and Methodology
4.1 Research Purpose
4.2 Research Objectives
179-204
179
180
4.3 Research Hypothesis
4.4 Research Design
4.5 Research Methods
4.5.1 Sampling
4.6 Instrument Development
4.7 Statistical Techniques Used
4.7.1 Critical Incident Technique
4.7.2 Analysis of Variance
4.7.3 Multiple Regression
4.7.4 Factor Analysis
180
180
181
182
183
187
187
191
196
199
Chapter 5: Data Analyses and Interpretation
5.1 Identification of Various Types of Service Failures
5.2 Section I- Demographic Profile of the Respondents
5.3 Section II- Descriptive Statistics of Level of
Seriousness, Frequency of Service Failures Encountered
and Effect on Satisfaction
5.4 Descriptive Statistics of Consumer Complaint
Behaviour (CCB) Intentions of Airline Passengers
5.5 Descriptive Statistics for Airline Passenger’s
Perceived Justice
5.6 Dimension Recovery Strategies
5.7 Dimension of Perceived Justice of Airline Passengers
5.8 Regression Analysis
5.9 Descriptive Statistics of Dimension Overall Airline
Satisfaction w.r.t. Each Airline
5.9.1 Comparison of Airlines on the Basis of
Overall Airline Satisfaction
205-282
205
224
227
247
254
259
260
266
270
271
5.10 Descriptive Statistics of Dimension Satisfaction
with Overall Quality of Airline
5.10.1 Comparison of Airlines on the Basis of
Satisfaction With the Overall Quality of Airline
274
276
Chapter 6: Conclusion and Suggestions
6.1 Objectives of the Study and their Achievement
6.2 Validity of Hypothesis Tested
6.3 Conclusion
6.4 Recommendations
6.5 Research Contributions
6.6 Limitations/Future Research Directions
283-301
283
286
288
293
296
296
Annexure
Questionnaire (Study I)
Questionnaire (Study II)
Bibliography
302-334
302
303
309
PREFACE
During the past few decades, interest has been growing among researchers and
practitioners towards the subject of service encounter, service failures and the
recovery actions taken by the service providers. And the consequences of service
failures and recovery strategies on the customer in terms of their satisfaction, trust,
loyalty, repurchase intentions and word of mouth are of great interest to marketing
managers and researchers alike. In this context, it becomes imperative to undertake a
synoptic view of the subject of service encounter and service failure.
It is inevitable that while providing services to customers, no failure occurs. But the
success of a firm depends on its capability to avoid failure and if occurred how to
rectify it successfully to make the customer satisfied. In particular, it is critical for the
survival of a company not only to retain its current customers but also to make them
loyal to the company. According to NOP, reducing customer defections can boost
profits by 25-85%. In 73% of cases, the organisation made no attempt to persuade
dissatisfied customers to stay; even though 35% said that a simple apology would
have prevented them from moving to the competitor.
The current research work is an attempt to find out the various types of service
failures which the customers of domestic airlines encounter while consuming their
services during travelling in domestic sectors of India and also study the effect of
service failures and recovery strategies on customer satisfaction. To take the research
to its logical conclusion, the entire study is divided into six chapters.
The first chapter contains a discussion on the introduction of the subject service and
model of service consumption.
The second chapter focuses entirely on the scenario of Indian Aviation sector.
The third chapter contains an expanded discussion on the literature with a completed
and comprehensive review of the various researches that have been carried out in the
related subject.
The fourth chapter contains the research methodology adopted to achieve the
objectives of the study and test the hypotheses framed.
The fifth chapter is about analysis and interpretation of results derived from applying
relevant statistical tools and techniques to the data.
The last chapter highlights conclusion and suggestions emerging from the
discussions.
LIST OF TABLES
S.No. Table No. Table Title Page No.
1. 2.1 Sources of Non-Ticket Revenue for LCA and FSC
Airlines
64
2. 2.2 Operational Airlines- List of Airlines Today in the
Market
65
3. 2.3 Air Traffic Trends: World Vs India 2000-2010 98
4. 2.4 Monthly Traffic and Operating Statistics of All
Indian Carriers on Scheduled Domestic Services
During 2009-2010
101
5. 2.5 Comparative Statement of Domestic Traffic on
Scheduled Services of All Indian Carriers During
2009-10
102
6. 2.6 Comparative Statement of Total Traffic on
Scheduled Services of All Indian Carriers During
2009-2010
103
7. 3.1 Bitner et al’s (1990) Group and Category
Classification by Type of Incident Outcome
112
8 5.1 Bitner et al’s (1990) Group and Category
Classification by Type of Incident Outcome
206
9. 5.2 Demographic Profile of Respondents 211
10. 5.3 Group and Category Classification by Type of
Incident Outcome
213
11. 5.4 Group 1 – Sample Incidents: Employee Response to
Service Delivery Failures
216
12. 5.5 Group 2– Sample Incidents: Employee Response to
Customer Needs and Requests
217
13. 5.6 Group 3 – Sample Incidents: Unprompted and
Unsolicited Employee Actions
218
14. 5.7 Comparison of Failure Frequency in Percentage 220
15. 5.8 Classification of Service Failures in Bitner et al’s
(1990) Group and Category Classification by Type
of Incident Outcome
221
16. 5.9 Classification of Twenty-six Identified Service
Failures into Groups and Categories
223-224
17. 5.10 Demographic Profile of the Respondents 226
18. 5.11 Statement Wise Response (Mean and Standard
Deviation) to Level of Seriousness, Frequency of
Failures Encountered and Effect on Satisfaction
228-229
19. 5.12 Statement Wise Response (Mean and Standard
Deviation) to Level of Seriousness, Frequency of
Failure Encountered and Effect on Satisfaction on
the basis of gender
231-232
20. 5.13 Statement Wise Response (Mean and Standard
Deviation) to Level of Seriousness on the Basis of
Travel Frequency
233-234
21. 5.14 Statement Wise Response (Mean and Standard
Deviation) to Frequency of Failure Encountered on
the Basis of Travel Frequency
235-236
22. 5.15 Statement Wise Response (Mean and Standard
Deviation) to Effect on Satisfaction on the Basis of
Travel Frequency
237-238
23. 5.16 Descriptive Statistics (Mean and Standard
Deviation) of Three Groups
245
24. 5.17 Comparison of Failure Frequency in Percentage 247
25. 5.18 Demographic Composition of Complainants and
Non-Complainants
248
26. 5.19 Statement wise response to Consumer Complaint
Behaviour (CCB) Intentions
249
27. 5.20 Descriptive Statistics (Mean and Standard
Deviation) of CCB Intentions of Complainants and
Non-Complainants
250
28. 5.21 Independent t-test Between Complainants and Non
Complainants
250
29. 5.22 Comparison of Descriptive Statistics (Mean and
Standard Deviation) of CCB intentions of
Complainants on the Basis of Gender
251
30. 5.23 Comparison of Descriptive Statistics (Mean and
Standard Deviation) of CCB Intentions of
Complainants On the Basis of Age
252
31. 5.24 Statement wise response to Perceived Justice of
Complainants
254
32. 5.25 Statement wise response to Perceived Justice of
Complainants on the Basis of Gender
255
33. 5.26 Statement wise response to Perceived Justice of
Complainants on the Basis of Age
256-57
34. 5.27 Recovery strategies used by airlines after service
failure
259
35. 5.28 Reliability of Perceived Justice Construct of Airline
Passengers
261
36. 5.29 Kaiser-Meyer-Olkin and Bartlett's Test of Sphericity 261
37. 5.30 Summary of Results from Scale Purification 264
38. 5.31 Regression Coefficient of Seriousness of the Service
Failure
267
39. 5.32 Regression Model for Seriousness of the Service
Failure (Summary)
267
40. 5.33 Regression Coefficient of Perceived Justice 268
41. 5.34 Regression Model for Perceived Justice (Summary) 268
42. 5.35 Regression Coefficient of Satisfaction with
Recovery
269
43. 5.36 Regression Model for Satisfaction with Recovery
(Summary)
269
44. 5.37 Descriptive Statistics (Mean and Standard
Deviation) of Overall Airline Satisfaction w.r.t Each
Airline
270
45. 5.38 Test of Homogeneity of Variances 271
46. 5.39 One Way ANOVA Results for Overall Airline
Satisfaction
271
47. 5.40 Tukey HSD Multiple Comparisons Test for Overall
Airline Satisfaction
272-274
48. 5.41 Descriptive Statistics (Mean and Standard
Deviation) of Satisfaction With the Overall Quality
of Each Airline
275
49. 5.42 Test of Homogeneity of Variances 275
50. 5.43 One Way ANOVA results for Satisfaction with
Overall Quality of Airline
276
51. 5.44 Tukey HSD Multiple Comparisons Test for
Satisfaction with Overall Quality of Airline
277-278
52. 5.45 Comparison of Number of Service Failures in Each
Group w.r.t. Each Airline
280
LIST OF FIGURES
S.No Figure
No.
Figure Title Page No.
1 1.1 Levels of Customer Contact with Service Organizations 13
2 2.1 Location of Domestic Airports in India 54
3 2.2 Location of International Airports in India 55
4 2.3 Forces Shaping the Future of the Airline Industry 60
5 2.4 Market Share of Scheduled Domestic Airlines (Dec, 2011) 67
6 2.5 Worldwide Passenger Traffic: % Growth Total 2000 to
2010F
99
7 2.6 India Passenger Traffic: % Growth Total 2000 to 2010F 99
8 2.7 Strong Domestic Passenger Traffic Growth 100
9 2.8 Load Factor at the Highest Level in a Decade 100
10 3.1 The Research Model 157
11 5.1 Comparison of Failure Frequency in Percentage (Study I) 219
12. 5.2 Comparison of Failure Frequency in Percentage (Study II) 246
13. 5.3 Recovery Actions taken by Airlines after Service Failure 258
14. 5.4 Scree Plot Representing the Factors of Perceived Justice 265
15. 5.5 Comparison of Number of Service Failures in each Group
w.r.t. Airline
279
LIST OF ABBREVATIONS
S.No. Abbreviation Full Form
1. ATF Aviation Turbine Fuel
2. ATM Automated Teller Machine
3. AVOD Audio Video On Demand
4. CAA Civil Aviation Authority
5. CAGR Compound Annual Growth Rate
6. CAPA Centre for Asia Pacific Aviation
7. CCB Consumer Complaint Behaviour
8. CIT Critical Incident Technique
9. DGCA Director General of Civil Aviation
10. DJ Distributive Justice
11. F/C First Class
12. FDI Foreign Direct Investment
13. FSA Full Service Airline
14. GDP Gross Domestic Product
15. IATA International Air Transport Association
16. IFE In Flight Entertainment
17. IJ Interactional Justice
18. LCA Low Cost Airline
19. NACIL National Aviation Company of India Limited
20. NRI Non Resident Indian
21. PJ Procedural Justice
22. SAARC South Asian Association for Regional Cooperation
23. SSTs Self Service Technologies
24. VFR Visiting Friends and Relatives
1
Customer complaints are the schoolbooks from which we learn.
-- Anon
Service organizations are facing more intense customer service pressures than ever
before. It does not matter how excellent the service a company delivers, every
company still often makes mistakes in meeting the expectations of today’s customers
who tend to be more demanding and less loyal than ever before. Bitner (1993) argues
that due to the unique nature of services it is impossible to ensure 100% error-free
service. The retention of customers, for any business, can be a critical activity,
promoting the long-term health of the business organization. In the service sector,
retention of customers can be extremely profitable: a slight reduction in customer
losses (5%) could lead to an increase of profits of 25 to 85% as reported by Reichheld
and Sasser (1990).
For all service firms and the airline industry in particular, the provision and delivery
of high quality service has become a requisite for competing effectively (Zeithaml,
Berry and Parasuraman, 1993). The airline industry is a complex business where the
airport, airline companies and ground staff need to work closely to provide effective
services to passengers. In today’s scenario, the airline industry faces a number of
challenges like intense competition, the fact that the demand for air transport has
decreased during the past few years due to a global economic decline (Fodness and
Murray, 2007); the lower profitability in the industry (the world’s airlines
cumulatively lost $43 billion between 2001-2005- Anon, 2006); the rising price of oil
CHAPTER-1
INTRODUCTION
2
(accounting for approximately 15% of an airline’s costs; oil costs for the industry
which surged to $97 billion in 2005 at an average price of $57 per barrel of oil-Anon,
2006); the reality that supply far exceeds demand and demand fluctuates by season,
day of the week and time of the day (Tierman, Rhoades and Waguespack, 2008;
Anon, 2006). Therefore, it becomes necessary for the airline companies that they
should deliver their services more efficiently to customers because customer is a
source of profitability for the organization, as costs can be reduced by offering
customers delight and retaining them, rather than continuously acquiring new
customers. Chang, Chen and Chang (2008) suggest that airlines face a very specific
problem that could influence the satisfaction of customers, namely that they offer
multiple opportunities for mistakes to occur during service delivery and are therefore
particularly prone to service failures, and many internal mistakes or external
disruptions could cause customers to experience service failures. It is specifically the
response to a service failure (service recovery) that could give airlines a competitive
advantage, as an organisation’s response to a service failure could either restore
customer satisfaction and reinforce loyalty, or aggravate the situation by driving the
customer to a competitor. Currently, there is no research that has examined the
service failures and their effect on customer satisfaction in the Indian context with
special reference to the services provided by the airline companies to the customers.
Thus the primary purpose of this research is to find out the type of service failures that
are encountered by the customers of airlines and their effect on satisfaction and what
recovery actions are taken by the airlines to overcome these failures from the
customer’s point of view. This would help the airline companies to know the types of
failures which effect the satisfaction of customers the most and they can take
appropriate actions to improve upon them.
3
1.1 STATEMENT OF THE PROBLEM
It is the intent of this research to study the types of service failures that are
encountered by the customers and their effect on satisfaction in the context of services
provided by the airline companies to the passengers in the domestic sectors of India
and the recovery actions taken by the airlines to overcome the failures. Further,
following the work of Bitner, Booms and Tetreault (1990) the research work will
classify the failures in the group and category classification by type of incident
outcome. Since there is no known study addressing this issue, this study will attempt
to answer the following research questions
1. Does the perceived justice effect the satisfaction of customers after recovery?
2. Does the satisfaction with recovery of customers effect the overall airline
satisfaction?
1.2 RATIONALE OF THE PRESENT STUDY
It is inevitable that in aviation industry like other service sectors there is no service
failure occurring. The top-flight companies provide us with several lessons on how to
give a company the direction it needs to stay customer focused. They base decisions
on what their customers want and expect. Service leaders have long known that if
their customers don’t like the experience provided, value it and think it meets their
needs and experience, they won’t come back. Not only that, a happy customer
typically tells 5 or 6 other potential customers about a happy experience, and an
unhappy customer tells 10 to 15 others (Stephen W. Brown, 2003). The analysis of
service failures and service recoveries is beneficial to service organizations as it
allows management to identify and rectify common failure situations (Hoffman, Kelly
4
and Rotalsky, 1995). Goodwin and Ross (1992) conducted an experiment
investigating consumer responses to service failures using an equity theory
framework. Their findings suggest when consumers are offered an apology or are
provided with the opportunity to express their concerns to a service representative
those perceptions of satisfaction and fairness are enhanced, particularly when
recovery outcomes are favourable. Many researches have consistently found a
relationship between satisfaction and repurchase intentions, satisfaction and word of
mouth (Spreng, Harrell and Mackoy, 1995).
There are many empirical researches conducted on service failures and service
recoveries in various service sectors (like restaurants, hotels, airlines, medical, self-
service technologies etc.) and their effect on consumer satisfaction. These studies
provide a guideline to the present study to identify the service failures and recovery
actions taken by airlines to overcome the service failures and their effect on
customer’s overall satisfaction in the context of passengers travelling in domestic
sectors of India.
1.3 SCOPE OF THE STUDY
This research focuses on the service failures and recovery strategies adopted by the
airlines to overcome the various failures and their effect on customer’s overall
satisfaction. This study focused on those service encounters faced by passengers that
occurred during the last five years of their travelling in domestic sectors of India only.
Bejou and Palmer (1998) explain that the airline industry is especially prone to
service failures due to the service processes employed in service delivery. Although
airline passengers may hold certain expectations prior to their impending travel
5
(Coye, 2004), research indicates a number of causes leading to service failures in the
airline industry, including flight cancellations, diversions or delays, attitudes of
ground and cabin staff, strikes, reservation problems and overbooking of flights
(Bamford & Xystouri, 2005). At present, there are number of carriers operating in
domestic sectors of India and many new airlines are ready to join the carnival because
of open sky policy and deregulation of aviation industry. Carriers operating in
domestic sectors of India can be categorized in to many ways like government and
private airlines, high budget and low cost carriers, value and regional carriers etc. for
example govt. domestic carriers operating in India are Air India where as private
domestic carriers include Jet Airways, Jetlite, Spice Jet, Go Air, Kingfisher Airlines,
Indigo, Paramount Airways etc.
The main aim of this study is to analyze the service failures encountered by customers
(passengers) of airlines and thus create a basis for quality improvement. Although it is
highly unlikely that organisations can eliminate service failures, they can learn to deal
with these failures effectively (through service recovery) in an attempt to maintain
and even enhance customer satisfaction (Bamford & Xystouri, 2005; Maxham 2001;
Miller, Craighead & Karwan, 2000). This study is not limited to the service
encounters of Jammu and Delhi sectors only but for the collection of incidents the
respondents were approached from both the cities only.
The present chapter highlights the concept of service, model of service consumption,
attribution theory, perceived justice and present and future scenario of global aviation
industry.
6
1.4 CONCEPT OF SERVICE
Services refer to all economic activities whose output is not a physical product or
construction, is generally consumed at the time it is produced, and provides added
value in forms (such as convenience, amusement, timeliness, comfort or health) that
are essentially intangible concerns of its first purchase. Features like intangibility,
perishability, variability and inseparability distinguish the services from other
physical goods. The concept of service defined by Heskette (1986) as the way in
which the organisation would like to have its services perceived by its customers,
employees, shareholders and lenders i.e. the organisation’s business proposition. In
the words of Edvardsson et al (2000) service concept as a detailed description of the
customer needs to be satisfied, how they are to be satisfied, what is to be done for the
customer and how this is to be achieved.
Customer service has a direct impact on the customer’s level of satisfaction, which in
turn, ultimately reflects on the service provider’s bottom line. Although, it is difficult
to measure the true impact of customer service, quality customer service has been
cited as a means for improving a variety of aspects of a business. The following are
the several objectives of services like:-
• The key to getting closer to one’s customers is making it easier for them to do
business with the service provider, better known as convenience (Anton,
1996).
• The number and quality of services offered, establishes the image of the
service provider.
7
• Multiple services reinforce customer’s sense of security. Protective services
such as security staff, emergency medical facilities, clearly marked exits instil
confidence in customers.
• Quality customer service has the potential to generate increased traffic for the
service provider. Further, the delivery of quality service and customer
satisfaction has been clearly linked with profits, cost savings and market share
(Sager, 1994).
• Service providers who extend their services beyond minimal expectations
have a far better chance of satisfying their customers. The critical differences
in customer/guest service are what often separate hospitality industry leaders
from industry followers.
Service industries and companies include those industries and companies typically
classified with in the service sector whose core product is a service like lodging,
transportation, insurance and financial services, health care services etc. certain
services require customers to enter the service factory and stay there until service
delivery is complete (Zeithaml et al, 2008).
The size of the service sector is increasing around the world, in both developed and
emerging countries. The Indian economy is the second fastest growing economy in
the world with the growth rate of the GDP at 8.5% in 2006-07. The economy of India
is the 12th largest in the world (GDP of US $ 1.09 trillion in 2007). India ranks 15th in
the services output and it provides employment to around 23% of the total workforce
in the country. The various services under this sector are construction, trade,
hospitality, food & beverage services, communication, social and personal services,
insurance, financing and other business services. The service sector contributes the
8
most to the Indian GDP, only 15% in 1950 increased from 43.695% in 1990-1991 to
around 51.16% in 1998-1999. In 2005, it was 53.8% and now the contribution reaches
to 57% (2010).
Burkart and Medlik (1974) had rightly said that tourism is about being elsewhere and
a major component of any tourist activity must necessarily be an element of
transportation. Transport industry provides services for all and sundry, it is not
possible to provide exclusive transport facility for the tourists except the provision of
special coaches, fare concessions and other incentives.
A well known and co-ordinated system of transport plays an important role in the
sustained economic growth of a country. The present transport system of India
comprises several modes of transport including rail, road, coastal shipping, air
transport, etc. Transportation in India has recorded a substantial growth over the years
both in spread of network and in output of the system. The Ministry of Civil Aviation
is responsible for the formulation of national policies and programmes for
development and regulation of civil aviation and for devising and implementing
schemes for orderly growth and expansion of civil air transport. Its functions also
extend to overseeing the provision for airport facilities, air traffic services, carriage of
passengers and goods by air, safeguarding civil aviations operations, regulations of air
transport services, licensing of aerodromes, air carriers, pilots and aircrafts
maintenance engineers.
An airline is a significant component which provides air transport services for
travelling passengers and/or freight. Airlines lease or own their aircraft with which to
supply these services and may form partnerships or alliances with other airlines for
mutual benefit. Generally, airline companies are recognized with an air operating
certificate or license issued by a governmental aviation body. Airlines vary from those
9
with a single aircraft carrying mail or cargo, through full-service international airlines
operating hundreds of aircraft. Airline services can be categorized as being
intercontinental, intra-continental, domestic, regional, or international, and may be
operated as scheduled services or charters. (Airline-www.en.wikipedia.org)
An airline company provides services to its passengers at the airport (check-in, during
boarding and on arrivals), F/C class lounge services, ground staff service, cabin staff
service, services at the airline website and onboard products offered to the passengers.
India is expected to be the fastest growing civil aviation market in the world by 2020
with about 420 million passengers being handled by the Indian airport system,
according to the Economic survey 2010-11. The number of passengers carried by the
domestic airlines during Jan-Feb 2011 was 9.51 million as against 7.95 million in the
corresponding period in 2010, thereby registering a growth of 19.6%, according to the
data released by DGCA. The domestic airlines registered a growth of almost 16 %
year-on-year (y-o-y), carrying a record 5.2 million passengers in Dec. 2009. The
domestic air passenger traffic grew by 19% in 2010, registering 51.53 million
passengers as compared to 43.3 million in 2009, according to economic survey 2010-
11. (Aviation, March 2011)
In today’s scenario, around 12 domestic airlines and above 60 international airlines
are operating in India. The growth of airlines traffic in aviation industry in India is
almost four times above international average. Aviation industry in India holds around
69% of the total share of the airlines traffic in the region of South Asia.
(business.mapsofindia.com)
10
1.5 MODEL OF SERVICE CONSUMPTION
Consumption of services is different from the consumption of products. In the context
of transportation sector for consumption of services, customers are required to enter
the service factory (transportation modes like cars, coaches, cruises, airlines etc.) and
stay there until service delivery is complete. According to Lovelock et al (2010),
service consumption can be divided into three principal stages:
1.5.1 Prepurchase Stage
1.5.2 Service Encounter Stage
1.5.3 Post-encounter Stage
1.5.1 THE PREPURCHASE STAGE: This stage begins with need arousal and
continues through information search and evaluation of alternatives to a decision on
whether to make a service purchase. Like a person wants to go to a destination, for
this, first he searches the various modes of transportation (cars, coaches, railways,
cruise and airline) available to reach that destination and then evaluate each mode
according to the budget and time availability with him and finally he decides to go by
that airline.
1.5.2 THE SERVICE ENCOUNTER STAGE: After making a purchase decision,
customers move on to the core of the service experience – the service encounter stage.
A service encounter is a period of time during which a customer interacts directly
with a service provider (Shostack, 1985). Irrespective of the nature and length of the
contact, each ‘encounter’ represents an important ‘moment of truth’ for the customer.
The later term, originally used by Normann has more recently been termed the
11
‘bullfight metaphor’ by Mattsson as it underlines strongly “the uniqueness and the
importance of every encounter between the customer and the service provider’.
In some instances, the entire service experience can be reduced to a single encounter,
involving ordering, payment and execution of service delivery on the spot. In other
cases, the customer’s experience includes a sequence of encounters. This can mean an
extended process that may be spread out over a period of time, involving a variety of
employees, and even taking place in different locations. It is from these service
encounters that customers build their perceptions. Service processes usually consist of
a series of encounters such as experience with a flight, from making a reservation to
checking in, taking the flight and retrieving bags on arrival (Lovelock et al, 2010). It
is in these encounters that customers receive a snapshot of the airline’s service quality
and each encounter contributes to the customer’s overall satisfaction and willingness
to do business with the airline again. From the airline’s point of view, each encounter,
thus, represents an opportunity to prove its potential as a quality service provider and
to increase customer loyalty.
Although some researchers use the term “encounter” simply to describe personal
interactions between customers and employees (Suprenant and Solomon, 1987),
realistically encounters also involve interactions between customers and self-service
equipment (Meuter and Bitner, 1998).
Services can be grouped into three levels of customer contact, representing the extent
of interaction with service personnel, physical service elements, or both.
a. High Contact Services tend to be those in which customers visit the service
facility in person. It also involves significant interaction among customers,
service personnel, equipment and facilities. Customers are actively involved
12
with the service organization and its personnel throughout service delivery e.g.
medical services or airline services. There are also examples of services that
have traditionally been high contact but can be low contact today because of
technology and include retail banking, purchase of retail goods and higher
education.
b. Medium Contact Services- It involves a limited amount of contact between
customers and elements of the service organization. The purpose of such
contacts is often limited to:
(a) establishing a relationship and defining a service need;
(b) dropping off and picking up a physical possession that is being serviced, or
(c) trying to resolve a problem.
c. Low Contact Services- It involves minimal or no direct contact between
customers and the service organization. Both mental stimulus-processing (e.g.
radio, television) and information processing services (e.g. insurance) fall into
this category.
13
Fig 1.1 Levels of Customer Contact with Service Organizations
Source: Principles of Services Marketing and Management- Second Edition- Christopher Lovelock, Lauren Wright, Prentice Hall, 2002
Service encounters are critical in all industries, including those that have not been
traditionally defined as service industries. These are critical moments of truth in
which customers often develop indelible impressions of a firm. In fact, the encounter
frequently is the service from the customer’s point of view (Bitner, 1990). Service
encounters have been defined as the moment of interaction between a customer and a
firm (Shostack, 1985; Keaveney, 1995; Winstead, 1997). Encounters may take place
face-to-face in an actual service setting, over the phone, through the mail, or even
over the internet. Each encounter is an opportunity for a firm to sell it, to reinforce its
offerings, and to satisfy the customer. However, each encounter is also an opportunity
to disappoint.
14
Previous research illustrates how important individual service encounters are for
business success. Encounters have been shown to affect critical outcomes such as
customer satisfaction (Bitner, Booms and Tetreault, 1990; Bitner et al, 1994;
Parasuraman, Zeithaml, and Berry, 1988, 1994; Smith and Bolton, 1998, Kivela and
Chu, 2001; Holloway and Beatty, 2008), intention to repurchase (Bitner, 1990;
Keaveney, 1995; Meuter, Ostrom, Roundtree, and Bitner, 2000; Smith and Bolton,
1998, Petrick, Tonner and Quinn, 2006), word-of-mouth communications (Bitner,
1990; Keaveney, 1995; Meuter et al, 2000; Tax, Brown, and Chandrashekaran, 1998);
relationship quality (Czeipiel, 1990), and loyalty (Gremler and Brown, 1999).
Ineffective or unsuccessful service encounters can result in significant costs to the
firm such as performing the service again, compensating customers for poor
performance, lost customers and negative word of mouth (Bitner et al, 1994,
Keaveney, 1995; Tax and Brown, 1998; Tax et al, 1998). Empirical research also
affirms the importance of service encounters in the global assessment of service
quality (Parasuraman et al, 1994). “in most services, quality occurs during service
delivery, usually in an interaction between the customer and contact personnel of the
service firm”. (Zeithaml, Berry and Parasuraman, 1998).
Service quality researchers have suggested that “the proof of service (quality) is in its
flawless performance” (Berry and Parasuraman, 1991), a concept akin to the notion of
“zero defects” in manufacturing. Others have noted that “breakthrough” service
managers pursue the goal of 100% defect-free service (Heskett, Sasser and Hart,
1990). From the customer’s point of view, the most immediate evidence of service
occurs in the service encounter or the “moment of truth” when the customer interacts
with the firm. Thus one central goal in the pursuit of “zero defects” in service is to
work toward 100% flawless performance in service encounters. Here, flawless
15
performance is not meant to imply rigid standardization, but rather 100% satisfying
performance from the customer’s point of view. The cost of not achieving flawless
performance is the “cost of quality” which includes the costs associated with redoing
the service or compensating for poor service, lost customers, negative word of mouth,
and decreasing employee morale.
Situations arise in which quality is low and the problem is recognized by both the firm
(i.e. employees) and the customer, but there may be disagreement on the causes of the
problem and the appropriate solutions. In service encounters such disagreements, are
sure to diminish customer satisfaction; underscore the importance of understanding
the types of events and behaviors that cause customers to be satisfied or dissatisfied.
Because the service encounter involves at least two people, it is important to
understand the encounter from multiple perspectives. Armed with such understanding,
firms are better able to design processes and educate both employees and customers to
achieve quality in service encounters (Berry and Parasuraman, 1991).
Types of Service Encounters: - There are three general types of service encounters:
a.) Remote Encounters- It can occur without any direct human contact such as when
customer interacts with a bank through the ATM system, with ticketron through an
automated ticketing machine, with a retailer through its internet website, or with a
mail-order service through automated touch-tone phone ordering. Remote encounters
also occur when the firm sends its billing statements or communicates other types of
information to customers by mail. Although there is no direct human contact in these
remote encounters, each represents an opportunity for the firm to reinforce or
establish quality perceptions in the customer. In remote encounters the tangible
evidence of the service and the quality of the technical processes and systems become
the primary basis for judging quality. More and more services are being delivered
16
through technology, particularly with the advent of internet applications. Retail
purchases, airline ticketing, repair and maintenance, troubleshooting, and package and
shipment tracking are just a few examples of services available via the internet.
b.) Phone Encounters- In many organizations (such as insurance companies, utilities,
and telecommunications), the most frequent type of encounter between an end
customer and a firm occurs over the telephone. Almost all firms (whether goods
manufacturers or service businesses) rely on phone encounters to some extent for
customer service, general inquiry, or order-taking functions. The judgement of quality
in phone encounters is different from remote encounters because there is great
potential variability in the interaction. Tone of voice, employee knowledge, and
effectiveness/efficiency in handling customer issues become important criteria for
judging quality in these encounters.
c.) Face-to-face Encounters- It occurs between an employee and a customer in direct
contact. At Disney theme parks, face-to-face encounters occurs between customers
and ticket takers, maintenance personnel, actors in Disney character costumes, ride
personnel, food and beverage servers, and others. For a company such as IBM, in a
business-to-business setting direct encounters occur between the business customer
and sales people, delivery personnel, maintenance representatives, and professional
consultants. Determining and understanding service quality issues in face-to-face
contexts is the most complex of all. Both verbal and non verbal behaviours are
determinants of quality, as are tangible cues such as employee dress and other
symbols of service (equipment, information brochures, physical setting). In face-to-
face encounters, the customer also plays a role in creating quality service for
herself/himself through her/his own behaviour during the interaction.
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Characteristics of Service Encounters: - (customer-employee service encounters)
a. Service encounters are purposeful.
b. Service providers for their past are not generally altruistic.
c. In a service encounter, prior acquaintance between participants is not required.
d. In most encounters, task related information exchange dominates.
e. Service encounters are limited in scope, with the scope of interchange being
restricted by the nature and content of the service to be delivered.
f. The roles played by a service provider and a client, in an encounter, are
generally well defined and understood by both parties.
g. A temporary suspension of the normal social status of participants often
occurs in service encounters (Baron and Harris, 2007).
1.5.3 THE POST-ENCOUNTER STAGE: In this stage, customers evaluate the
service performance they have received and compare it with their prior expectations.
The terms ‘quality’ and ‘satisfaction’ are sometimes used interchangeably. It is
believed that perceived service quality is just one component of customer satisfaction,
which also reflects price/quality trade-offs, and personal and situational factors.
Consumer satisfaction and service quality has each been the subject of extensive, but
separate research, although many studies of consumer satisfaction have been
conducted in service settings. Most researchers in the services domain have
maintained that these two constructs are distinct (Bitner, 1990; Parasuraman, Zeithaml
& Berry, 1988). Customers perceive services in terms of the quality of the service and
how satisfied they are overall with their experiences.
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Satisfaction is generally viewed as a broader concept, where as service quality focuses
specifically on dimensions of service. Service quality is a focused evaluation that
reflects the customer’s perceptions of: reliability, assurance, responsiveness, empathy
and tangibles. Satisfaction, on the other hand, is more inclusive. It is influenced by
perceptions of service quality, product quality and price as well as situational factors
and personal factors.
Both satisfaction and service quality literatures have emphasized the idea that
consumers make a comparison between the performance of the product or service and
some standard. The service quality literature has maintained that the distinction
between perceived service quality and satisfaction is that they use different standards
of comparison (Bitner, 1990; Zeithaml et al, 1993). These authors have argued that
the standard of comparison in forming satisfaction is predictive expectations, or what
the consumer believes will happen, while perceived service quality is the result of a
comparison of performance and what the consumer feels a firm should provide.
The success of service firms depends greatly on their ability to deliver consistent,
satisfying consumption experiences to their customers. However, even the companies
with the best strategic plans and the tightest quality control procedures cannot avoid
mistakes in all interactions with customers. Recognizing that completely eliminating
service mistakes or failures is an insurmountable task, service firms should learn to do
the next best thing- rectify the service delivery mistakes (Webster and Sundaram,
1998).
A customer may or may not report these service failures to the organisation. A service
failure is reported to a firm in the form of complaints. A complaint to an airline
company is any type of formal complaint filed by an airline customer either to an
airline responsible for the grievance or a government office responsible for overseeing
19
the airlines national industry. Airline complaints generally arise out of problems
experienced during air travel that were left unresolved.
And service failures are specific events that lead to dissatisfying service encounters
from the customer’s point of view (Bitner et al, 1990). It is the efficiency of an airline
company to immediately identify and rectify the service failures encountered by a
customer which termed as service recovery, defined as:
……..the actions of a service provider to mitigate and/or repair the damage to a
customer that results from the provider’s failure to deliver a service as is designed
(Johnston and Hewa, 1997)
Service failure can occur in several ways, such as when customer requested service is
unavailable, when the service is unreasonably delayed, or when the core service is
delivered below a minimum acceptable level (Bitner, Booms, and Tetreault, 1990).
Whether the initial reaction to service failure is one of mere disappointment or one of
anger, a customer’s negative attitude can become much stronger if the firms fail to
resolve the service failure. Fortunately, the use of appropriate service failure recovery
efforts can convert a problematic situation into a favourable service encounter, thus
enhancing repurchase intentions and positive word-of-mouth communications
(Spreng, Harrell, and Mackoy, 1995) and restoring or even enhancing customer
loyalty (Kelley, Hoffman, and Davis, 1993). Responding to service failure tends to
result in secondary satisfaction which helps the firm build strong, long-standing and
beneficial relations with customers. (Etzel and Silverman, 1981; Gilly, 1987;
Westbrook, 1987)
Past research reveals a linkage between customer satisfaction and two specific
activities performed by a firm, customer complaint handling procedures and the
20
nature of compensation. For example, providing an opportunity for customers to
express their feelings and then listening conscientiously to customers’ complaints has
been found to increase customers’ perceptions of fairness and satisfaction (Goodwin
and Ross, 1992). Further offering customers a marginal discount and an apology as
compensation for service failure, as compared to a mere apology, results in greater
customer satisfaction and perceived fairness. The monetary amount of restitution (i.e.
percentage of initial service charge) and prior usage experience were found to also
influence perceptions of satisfaction, appropriateness of compensation, reputation of a
firm, and intention to return. Unsurprisingly, a greater monetary compensation was
considered to be more appropriate by customers and consequently resulted in
heightened customer satisfaction (Goodwin and Ross, 1992; Meghee, 1994).
1.6 ATTRIBUTION THEORY
Attribution theory has been introduced in consumer research since the beginning of
1970s. Consumer researchers adopt attribution theory in many different areas. For
example, attribution theory has been adopted to explain consumer product purchase or
selection (Scott and Yalch, 1980; Tybout and Scott, 1983), the consequences of
product failure or success (Curren and Folkes, 1987; Richins, 1983), the reasons that
consumers switch brands (Mazursky et al, 1987), the endorser’s credibility
(Sparkman, 1982; Wiener and Mowen, 1986), and consumer responses to research
mail surveys (Allen et al, 1980; Furse et al, 1981; Hansen and Robinson, 1980).
Buyer, seller, and environmental situation can all contribute to a product/service
failure. Folkes (1984) suggested that the locus of causality influenced consumer
equity reactions and beliefs about who should solve problems. Consumers generally
21
hold that problems arising from consumer actions should be solved by consumers,
whereas problems arising from firms’ actions should be solved by firms.
According to Heider’s people perception, consumers in a service failure encounter
may reach a causal inference of the failure based on their observation of the service
delivery and their experience with the firm. Consumers can attribute the failure to any
entities involved in the service delivery process such as firms, themselves, and/or
environmental situations. The environmental situation factor may include anybody
who is responsible for the failure except firms and consumers. For example, weather
can cause a flight delay, a noisy customer in the restaurant can cause an unpleasant
service experience, and a power outage can cause the interruption of a surgery. All of
these factors listed can be classified as environmental situation factors.
When the delivery of a service does not match customers’ prior expectations or
normative standards, customers may engage in attribution processes to make sense of
what has occurred (Bitner, 1990). According to attribution theory (Hewstone, 1989;
Weiner, 1982), causes may be of two types-internal and external. Internal causes
include factors inherent to the service provider, such as the amount of effort put into
the delivery of a service, the strategies used to deal with service situations, and the
skill level demonstrated. External causes include factors outside the service
encounter; include the activities of other people such as suppliers, or bad luck.
Research into the fundamental attribution error (Heider, 1958) indicates that in
general, customers will attribute causes for service breakdowns to features that are
internal to the service provider (for example, the provider’s inexperience or the
organization’s poor training programs) rather than to luck or -organizational policy
past research indicates that the value of customer attribution depends upon the range
of information available regarding the cause of the problem including the frequency
22
of the problem, perception of whether the problem is preventable or due to bad luck
and the extent to which the service providers try to solve the problem (Bitner, 1990;
Folkes, 1984).
When the causal agent is anchored on the firm, consumers expect the firm to recover
service failures. How much consumers want to redress from the firm is based on the
norm of perceived justice governing the exchange relationship.
1.7 PERCEIVED JUSTICE
Another framework used to evaluate the service recovery process is that of justice.
What is perceived to be fair and reasonable in the circumstances will influence the
level of customer satisfaction. Service and organizational research studies (Bies and
Moag, 1986; Goodwin and Ross, 1990; Sparks and Callan, 1995; Tyler, 1994) have
confirmed that customer satisfaction is not merely based upon the ultimate outcome of
the service recovery but also upon the procedures used to reach an outcome, as well as
the interactions along the way. Clemmer and Schneider (1996) make the point that in
services marketing, what is important is the need to focus on processes and
relationships rather than outcomes, due to the intangible nature of services and the key
role played by service personnel. Hence, the effectiveness of service recovery
techniques used by tourism and hospitality firms may rely upon customers’
evaluations of both the intervention process and the outcomes of this exchange.
Structure of Perceived Justice
Justice is first conceptualized as a social and personal device designed to facilitate the
acquisition of other desired resources (Lerner, 1981). Justice is meaningful only when
23
it is defined in contrast with injustice (Karniol and Miller, 1981). Individuals can
perceive an injustice occurring along different dimensions.
a.) Distributive Justice- The first dimension of perceived justice is related to the
allocation of benefits and rewards which is called distributive justice. Adams (1965)
stated that social behaviour was affected by beliefs that the allocation of benefits and
costs within a group should be equitable. When an individual perceives that benefits
have not been allocated equitably, he/she experiences distress (Walster et al, 1973),
which in turn motivates him/her to restore the distributive justice.
Distributive justice is closely related to the outcome of service delivery. Consumers
make an exchange with a firm expecting to receive benefits that are equivalent to the
cost to the consumer (Goodwin and Ross, 1992). When a service failure occurs, the
customer does not receive equivalent benefits, and will perceive distributive injustice
that further leads to customer dissatisfaction. For example, airline passengers pay
tickets to exchange the transportation service from one place to another. If an airline
cancels a flight for some reason, the airline is supposed to arrange another flight for
all passengers. Otherwise, the outcome of the service delivery will be considered
unfairly distributed.
The violation of distributive justice indicates that the outcome of service delivery is
not the same as what consumers expect. Distributive justice only explains one aspect
of perceived justice in the social exchange relations. In many situations, even though
outcomes are perceived as just, individuals may still experience perceived injustice if
the procedure that reaches the outcome is unjust.
b.) Procedural Justice- The systematic study of procedural justice begins with the
work of Thibaut and Walker (1975). Procedural justice refers to the fairness judgment
24
of a decision making procedure. The initial study of procedural justice focuses on
dispute resolution procedures and legal procedures (Thibaut and Walker, 1975). Later
on, many of the explanations and prescriptions are extended to social decision-making
procedures in other contexts. Lind and Tyler (1988) reviewed procedural justice in
law, in the political arena, and in organizations. In general, individuals evaluate
procedural justice based on agreed-upon rules (Leventhal, 1980).
These rules can have a wide variety of manifestations in any given procedural
situation. Leventhal (1980) found that individuals evaluated procedures based on the
following rules: consistency, bias suppression, accuracy of information, correctability,
representativeness, and ethicality. Consistency requires that a fair procedure be
applied consistently across person and time. In other words, all individuals affected by
the procedure should have the same rights and be treated similarly. Meanwhile, the
procedure should be enacted the same way each time it is used. Bias suppression
refers to the concept that the decision makers should be unbiased. There are two
possible sources of bias. First, decision makers may have an interest in a specific
decision. Second, prior beliefs of decision makers may influence the decision making
process. The bias suppression rule requires a decision maker to avoid both types of
bias when making a decision. The rule of accuracy of information requires that a
decision be based on accurate information and on well-informed or expert opinion.
Correctability requires a fair procedure to include provisions for correcting bad
decisions. Representativeness ‘dictates that all phases of allocation process must
reflect the basic concerns, values, and outlook of important subgroups in the
population of individuals affected by the allocation process’ (Thibaut and Walker,
1975). Finally, ethicality requires a procedure to conform to personal standards of
ethics and morality. These rules guide an individual’s evaluation of procedural justice.
25
Studies in procedural justice generally find that the procedure used to allocate
outcomes has an influence on people’s judgement of the fairness of a decision that
was independent of outcome favourability (Folger and Greenberg, 1985). In other
words, given the same unfavourable outcome, individuals feel less dissatisfied when
they perceive the procedure to be fair than when they perceive the procedure to be
unfair.
c.) Interactional Justice Although the decision-making procedure is important in
understanding peoples’ reactions to the fairness of a decision, there is a growing
interest focusing on the enactment of a procedure. Bies and Moag (1986) referred the
fairness judgment of the enactment of a procedure as interactional justice which
concerns the decision makers’ behaviours during the enactment of procedures. For
example, people expect to be treated with truthfulness and respect in communication
(Bies and Moag, 1986). In addition to the two communication criteria (truthfulness
and respect) identified by Bies and Moag (1986), providing explanation or
justification for a decision can influence individuals’ interactional justice. Providing
reasons and information for a decision makes the decision understandable and
acceptable and enhances the perceived justice among parties. The distinction between
procedural justice and interactional justice is not clear-cut. The degree of perceptual
overlap between interactional and procedural fairness judgement has been articulated
by Bies and Moag (1986) as follows:
“Procedures become meaningful only when they are experienced by someone. That is,
people do not really know the procedure until it is implemented. Once the procedure
is enacted, people may make inferences about the fairness of the procedure from the
actions of decision makers. According to this reasoning, procedural fairness
26
judgements are based, in part, on people’s attributions regarding some action or
outcome.
Interactional fairness evaluations will generalize to the procedure itself only when a
person attributes the responsibility for the actions to an organization, a systemic
attribution, rather than a decision maker. For example, if a person believes that
deception and rudeness by recruiters are not isolated occurrences, but condoned by
the organization, then he or she will more likely to assume the decision-making
procedures are unfair. On the other hand, if a person attributes the deception and
rudeness solely to a decision maker and not an organization, then there should be less
implication for the procedure itself.”
1.8 GLOBAL AVIATION INDUSTRY
Air transport markets and the airline industry have been transformed over the last 40
years. The number of passengers has risen tenfold and cargo volumes have grown
fourteen fold, despite repeated shocks from recessions, terrorism and disease. Demand
is volatile but consistently returns to a rapidly growing trend. Supply has also changed
significantly. Having been a highly regulated industry during the first three post-war
decades, market access was increasingly liberalized starting with US domestic
markets in the late 1970s, followed by US ‘Open Skies’ policy on international
markets from the early 1990s, and the European single aviation market in the mid-
1990s. There have been many new entrant airlines in the past three decades, while exit
has been limited. As a result, the number of commercial airlines, flying Western-built
jets, has risen to over 1,000. Consumers and the wider economy have reaped the
benefits of a substantial increase in the choice of travel options by destinations,
27
frequencies, and business models available at lower cost, higher safety, and a smaller
environmental footprint per passenger mile travelled than ever before. Airline owners
have, however, not even been able to recover their cost of capital (Porter, 2011).
In the 66th IATA Annual General Meeting and World Air Transport Summit Berlin,
Germany, Director General and CEO of IATA Giovanni Bisignani submitted about
the global air transport industry- 2.4 billion passengers, 43 million tonnes of cargo, 32
million jobs, just 1 accident for every 1.4 million flights, 2% of global carbon
emissions, $545 billion in revenue and $217 billion in debt (State of the Air Transport
Industry, 2010).
The airline industry in 2050
An industry that carried 2.4 billion passengers and shipped 40 million tonnes of goods
in 2010 carried 16 billion passengers and shipped 400 million tonnes of goods this
year. Air transport has grown at almost twice the rate of GDP expansion, meaning that
more people are travelling than ever before and more frequently than ever before.
Global advances in general technology have been mirrored in the airline industry,
which has made the sector unrecognizable from what it was in 2035. Travelling by air
is faster (when desired), safer and more seamless than ever before.
Unsurprisingly, mobile technology available to air transport consumers is also
affecting their behaviour when they travel. LIMPs mean that they have the ability to
effortlessly and seamlessly change itineraries as and when they see fit. Passenger
information and transfer offices are a thing of the past. And fortunately so are queues.
In-flight entertainment systems are also no longer present on most aircrafts, because
passengers have all of their personal audio, video or virtual entertainment needs to
28
hand and available to take on board, downloaded directly from Internet 8, which
automatically charges them the correct amount.
Customers in 2050- The general aging of the world population has resulted in airline
customers being on average older than ever before. However, healthcare advances
mean that even though our customers are older, they are not necessarily less mobile.
Younger travellers are significantly more aware of air travel and more worldly-wise
than previous generations. Many are frequent fliers by the time they have learned to
talk. As a result, most 4-5 year olds have already established preferences about air
travel, including brand loyalty.
Increased access to advance communication tools and the widespread use of social
media has resulted in individuals and businesses having increasing networks of global
friends or business contacts. But no technology has been able to replace the human-to-
human contact facilitated by air travel.
Forty years ago the industry’s two largest markets were still the United States and
Europe. But this has not been the case for a long time. The shift eastward started early
in the century supported by strong growth in China and India. When Indians started
travelling with the same propensity as North Americans, that market alone jumped to
four billion passengers. A similar leap has already happened in the likes of Brazil,
Russia, and Mexico. It is starting to happen with Indonesia, the Philippines, Vietnam,
Iran, Turkey, Chile, and South Africa. The result is an increasingly socially,
culturally, and ethnically diverse pool of customers, with increasingly diverse
demands based on their culture, social background, or ethnicity that wish to visit an
increasingly diverse range of destinations. In turn, operators have made their product
29
offerings equally diverse to cater to such an array of demands. This has been best
achieved by the truly global operators with highly developed loyalty programs.
Increased access to information has also led to our customers being better informed
than ever before. And better informed customers are more demanding customers.
Customers’ priorities in 2050- In 2050, safety and security are still top priorities for
passengers, but the increasingly rare nature of safety and security incidents means that
these priorities are less frequently reinforced. Safety in particular is less of a concern,
as automation and new technology have continued to revolutionize safety standards.
The same technology has meant that reliability is also something that plays a
decreasing role in consumer choice, given that flights are almost always on time and
are almost never cancelled. There are still sporadic security threats regarding air
transport, but these threats have gradually decreased over the past 40 years, again due
in most part to technological advances that have improved the screening and tracking
of passengers and cargo.
Price is still a key driver of consumer choice, but access to information has made
price transparency almost absolute, which has made price differences between
comparable products almost extinct. As such, price has become more of a driver when
choosing between different product types, and operators have learned to offer a wider
array of products to cater to every need. Whether distinguishing between business and
leisure travellers, or between older and younger travellers, today pricing is more
reflective of what has become the most precious of commodities: time.
• Business people still value their time above all else and are, therefore, willing
to pay a premium for the fastest available transport options.
30
• Amongst leisure passengers, technological advances and the elimination of
security, customs, and immigration delays have fuelled a large increase in the
demand for international and cross-cultural travel.
• Older travellers are seeking greater comfort and convenience, as well as a
slower pace or travel. As pension ages have steadily climbed, some retirees
have had to become more price conscious than others, but many view the
journey as part of the experience as opposed to just a means of getting to their
final destination. And for this they are prepared to pay extra.
• For pre-adolescent travellers, priorities have not changed substantially over the
past 40 years. The method and the medium may have changed, but these
consumers still basically just want to be entertained. Many air carriers have
already moved away from investing in in-flight entertainment systems because
the majority of pre-adolescents have all of the entertainment they need on their
LIMPs.
• For adolescents, entertainment is also still a high priority, but entertainment
that is more about being social than individual. For these adolescents, this is
continuing the shift away from air travel just being a means of getting to their
destination; it is making the travel itself an important part of the whole trip.
• This trend is also the case for young adults, as more and more operators offer
the opportunity for them to use their journey to meet and socialize with
members of the opposite sex. This has become particularly popular amongst
young adults who are travelling in a group, as they are now able to ‘get the
party started’ on the aircraft instead of having to wait until they reach their
destination.
31
• Customers from what used to be called developing economies are trying air
transport services for the first time in ever-increasing numbers. Often, their
first trips are for VFR purposes, but rising living standards normally lead them
into the tourism market, some faster than others. These customers tend to seek
the lowest cost transport options.
• Those customers from developed economies are demanding more and more
authenticity and customization. For them, just travelling by air is not enough,
they want a personal and unique experience. Having visited every continent
and scores of different countries, these passengers are increasingly looking for
something ‘extra’, something ‘special’. Week-long ‘Aircations’ (cruises in the
sky) have become popular. Space travel is becoming more reasonably priced,
although stays in ‘Spatels’ (space hotels) are still reserved for the relatively
well off and week-long stays in Space Spas are only for the truly wealthy.
• One demand that has become consistently high among every type of traveller
is customer service. With almost no price differentials between comparable
products, operators have been forced to achieve ever greater levels of
customer service. In fact, customer service has become effectively ‘atomized’,
from mass to niche to individual.
• Ethical consumerism continues to be a growing trend. Once upon a time,
environmental concerns had an increasing influence over consumer choices.
Whilst aviation’s contribution to climate change has largely been addressed,
this kind of ethical consumerism was the start of the trend that now focuses on
such issues as the preservation of local cultures and livelihoods. In addition,
with widespread economic development across the planet, the definition of
32
‘rights’ has been expanded to include things like annual vacations and
minimum lifestyle standards (IATA Vision 2050, 2011).
33
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3
2.1 INTRODUCTION
India, the second largest economy in the world is a magnificent mix of authentic and
modern culture. It is the world’s second largest growing economy and the world’s
most populous democracy. India is a mix of so many different religions and over four
hundred different languages are spoken throughout the country. India consists of
seven union territories and twenty eight states. India is home to Indus valley
civilization and four of world’s major religions namely Jainism, Hinduism, Buddhism
and Sikhism originated here. India is world’s fourth largest economy by purchasing
power parity and eleventh largest economy in the world with GDP of over $1.3
trillion. India attracts an FDI of over twenty billion dollars on an annual basis. Over
the years India has witnessed a continuous increase in inflow of funds by the foreign
institutional investors who are very bullish on India’s long term growth story. It is
estimated that India will be world’s third largest economy after USA and China by
2020 (Vivek, 2011). The sub- continent of India is a wonder that attracts people from
around the world. The seventh largest country in the world, The Republic of India
comprises of 28 states. Different states in the country connected by the network of
railways, roads and air routes. With globalization and the emergence of economy
airlines, air transport has emerged as a popular mode of transport. (Anjali, 2011)
The aviation industry in India is one of those sectors that saw a constant pace of
growth among the other industries in the world over the past many years. Research
indicates the global aviation industry is poised to grow at a 5.6% CAGR (Compound
CHAPTER-2
INDIAN AVIATION SECTOR
44
Annual Growth Rate) over the next 15 years. While major conventional mature
markets such as the US and Europe will witness a significant fall in market share from
61% to 52%. Emerging markets such as India, China and the Middle East, offer a
great growth potential (Overview, 2008).
With the rise in the economy of the country and followed by liberalization in the
aviation sector, the aviation industry in India went through a complete transformation
in the recent period. The growth in the Indian economy has increased the GDP above
8% and this high growth rate will be sustained for a good number of years. The
growth of airlines traffic in aviation industry in India is almost four times above
international average (Role of aviation industry in India GDP, 2008). It has grown
enormously and expected to have a growth which would be above 25% in the travel
segment. This industry holds around 69% of the total share of the airlines traffic in the
region of South Asia. The liberalization of aviation industry in India has precipitated
the boom for domestic and international passenger carriers. The number of passengers
carried by the domestic airlines in the year 2011 (Jan-Dec) were 606.63 lakhs as
against 520.21 lakhs in the year 2010 there by registering a growth of +16.6%,
according to the latest data released by the Directorate General of Civil Aviation
(passengerdata/dgca, 2012). The domestic air passenger traffic grew by 19 percent in
2010, registering 51.53 million passengers as compared to 43.3 million in 2009,
according to the Economic Survey 2010-11 (Aviation, March 2011).
In India, the aviation sector continues to look promising. There was, and continues to
be a strong surge in demand by domestic passengers, primarily due to the burgeoning
middle class with its massive purchasing power, attractive low fares offered by the
low cost carriers, the growth of domestic tourism in India and increasing outbound
travel from India. In addition, the government has also focused on modernizing non
45
metro airports, opening up new international routes, establishing new airports and
renovating existing ones. According to Kapil Kaul, CEO India and Middle East,
Centre for Asia Pacific Aviation (CAPA), India’s civil aviation passenger growth is
among the highest in the world. “This sector is slated to cruise far ahead of other
Asian giants like China or even strong economies like France and Australia. The
number of passengers who will be airborne by 2020 is a whopping 400 million.” To
keep pace with this accelerated demand, existing players have been trying to increase
fleets and widen their footprint to regional destinations as well. There has also been
increasing attention from international low cost airlines such as Air Asia (Malaysian)
and JetStar Asia (Australian) to capture part of this lucrative opportunity (Overview,
2008).
2.2 A BRIEF HISTORY OF AVIATION INDUSTRY IN INDIA
The history of civil aviation in India dates back to 1912, when the first domestic flight
operated between Karachi and Delhi, by the Indian State Air Services in collaboration
with the Imperial Airways of United Kingdom. Since then, till the time of Indian
independence, in 1947, there were nine air carrier companies operating in India
(including both passenger and cargo). These were as follows:
• Tata Airlines
• Indian National Airways
• Air service of India
• Deccan Airways
• Ambica Airways
46
• Bharat Airways
• Mistry Airways
• Orient Airways
However, following partition, one of the airlines i.e. Orient Airways shifted to
Pakistan, leaving independent India with eight airlines. In early 1950s, the
government took to nationalize the airline industry in India. All airlines existing at the
time were merged into either Air India or Indian Airline; all aspect of Indian aviation
was under the control of the government. With the establishment of the Air
Corporation Act of 1953, this monopoly of the Indian Government existed for almost
four decades.
It was not until the early nineties, when the Indian economy experienced a boom and
started growing tremendously, that a need was felt for a more comprehensive air
transport system in order to complement the growing economy, that this monopoly of
the government was brought to an end, and the Air Corporation Act revoked. It was
after this, the private domestic airlines started operating in India once again. However,
even then, in case of foreign airlines, there were many restrictions as regards to the
number of flights they could operate, the types of aircraft they could fly in the
country, their point of call, capacity etc. India becoming a popular tourist destination,
such policies created major problems during the tourist seasons when it was difficult
for tourists to fly in and out of the country. It was then, that India started signing
bilateral agreements with many countries and came up with mutual agreements
regarding ownership, number of seats, ports of call, and number of flights etc. of
scheduled carriers from foreign countries. Now, India has signed more than 180
bilateral agreements with different countries (Pasari, 2005-06).
47
Small window of change was opened in 1986 when the air taxi scheme was
introduced, under which other airlines could run charter flights without fixed time
schedule and issue of the tickets. This state of affairs continued till 1993, when the
Air Corporation Act, 1953 was withdrawn (Gupta, 2008). In April 1990, India
introduced the Open Sky Policy. According to this policy, an air taxi operator could
operate flights, both chartered and non-chartered, from any airport. They were also
allowed discretion on matters relating to flight schedules as well as fares they charged
for passengers (or cargo). However, all such operators were required to conform to
some prescribed rules. They were also required to use airplanes with a minimum
capacity of 15 persons.
Prior to December 2004, any other airlines except Indian Airlines and Air India were
prohibited to fly to international destinations i.e. no private carriers could operate to
foreign countries. In December 2004, the Indian government changed its policy and
granted permission to those private carriers which had completed five years of
domestic operation, to operate flights to any destination worldwide (except the Gulf
Region and West Asia) (Pasari, 2005-06). Today, apart from Indian Airlines and Air
India, Jet Airways, Kingfisher Airline, IndiGo are also operating on international
routes.
At present, private airlines account for around 75% portion of the domestic aviation
market. The 9th largest aviation market in the world is India. The prediction stated
that international passengers will touch 50 million by 2015. More opportunities in the
aviation industry in India are likely to make way for about 69 foreign airlines from 49
countries (Role of aviation industry in India GDP, 2008).
48
2.3 CIVIL AVIATION IN INDIA
2.3.1 MINISTRY OF CIVIL AVIATION
Mission
To maintain a competitive civil aviation environment which ensures safety and
security in accordance with international standards, promotes efficient, cost-effective
and orderly growth of air transport and contributes to social and economic
development of the country.
Strategic Objectives
The objectives of this policy are the creation and continued facilitation of a
competitive and service-oriented civil aviation environment in which:
i. The interests of the users of civil aviation are the guiding force behind all
decisions, systems and arrangements,
ii. Safe, efficient, reliable and widespread quality air transport services are
provided at reasonable prices,
iii. There exists a well-defined regulatory framework catering to changing needs
and circumstances,
iv. All players and stakeholders are assured of a level playing field;
v. Private participation is encouraged and opportunities created for investors to
realize adequate returns on their investments;
vi. Recognizing that aviation today is an important element of infrastructure,
rapid upgradation of airport infrastructure to world class standards with
priority to the busiest airports and those handling international flights;
49
vii. Recognizing that transportation of air cargo is vital to the economic growth of
the country, creation and development of specific infrastructure for air
transportation of cargo and express cargo is encouraged;
viii. "Airline operations and acquisition of Aircraft" is conferred "infrastructure"
status for overall growth of civil aviation sector in the country.
ix. Domestic and international aviation in the country are encouraged to grow at
par with world aviation industry;
x. Inter-linkages with other modes of transport are encouraged and stimulated;
xi. Trade, tourism and overall economic activity and growth is encouraged;
xii. International cooperation in aviation and development in tune with
international trends and best practices, consistent with airspace sovereignty is
promoted;
xiii. Indigenous development of aircraft, components and aviation products is
encouraged;
xiv. Security of civil aviation operations is ensured through appropriate systems,
policies, and practices, and;
xv. Effective systems are put in place for timely crisis and disaster management,
including investigation of incidents/accidents.
Responsibility
• Formulation of National Policies and programmes for development and regulation
of Civil Aviation.
• Devising and implementing schemes for orderly growth and expansion of civil air
transport.
50
• Oversee the provision of airport facilities, air traffic services and carriage of
passengers and goods by air.
• Administratively responsible also for the Commission of Railway Safety, a
statutory body set up under the Railway Act (Civil Aviation Policy (Draft), 2000).
2.3.2 ORGANIZATIONS UNDER MINISTRY OF CIVIL AVIATION
• Attached Offices
� Directorate General of Civil Aviation
� Bureau of Civil Aviation Security
� Commission of Railway Safety
• Public Sector Undertakings
� Airports Authority of India
� National Aviation Company of India Ltd. and its subsidiaries
� Pawan Hans Helicopters Ltd.
• Autonomous Organization
� Indira Gandhi Rashtriya Uran Akademi
(Latest developments and policy initiatives in Civil Aviation in India, 2007)
2.4 CIVIL AVIATION POLICY IN INDIA
The Civil Aviation Ministry is evolving a draft Civil Aviation Policy that would
increase foreign direct investment, ceiling, liberalize bilateral and move towards an
51
`Open Sky,' encourage the promotion of Regional Airlines, lower fares to make
aviation affordable and remove price monopolies in respect of Aviation Turbine Fuel
(ATF).
Mission of Civil Aviation Policy
The main aim of the Civil Aviation Policy is to maintain a competitive Civil Aviation
Environment which ensures safety and security in accordance with international
standards, promotes efficient, cost-effective and orderly growth of air transport and
contributes to social and economic development of the country.
Strategic Objectives of Civil Aviation Policy
The objectives of this Civil Aviation Policy are the creation and continued facilitation
of a competitive and service-oriented Civil Aviation Environment in which:
• The interests of the users of civil aviation are the guiding force behind all
decisions, systems and arrangements
• Safe, efficient, reliable and widespread quality air transport services are
provided at reasonable prices
• There exists a well-defined regulatory framework catering to changing needs
and circumstances
• All players and stakeholders are assured of a level playing field
• Private participation is encouraged and opportunities created for investors to
realize adequate returns on their investments
Regulatory Framework
In the context of a multiplicity of airlines, airport operators (including private sector),
and the possibility of oligopolistic practices, there is need for an autonomous
52
regulatory authority which could work as a watchdog, as well as a facilitator for the
sector, prescribe and enforce minimum standards for all agencies, settle disputes with
regard to abuse of monopoly and ensure level playing field for all agencies.
Therefore, a statutory autonomous Civil Aviation Authority (CAA) will be
constituted. The basic objectives of setting up of the Authority will be to ensure
aviation safety, security and effective regulation of air transport in the country in a
liberalized environment.
Airport Infrastructure
The Government will aim at ensuring adequate world class Airport Infrastructure
capacity in accordance with demand, ensuring maximum utilization of available
capacities and efficiently managing the Airport Infrastructure by increasing
involvement of private sector.
Aviation Support Services
The role of Aviation Support Services like human resource development, maintenance
facilities and manufacture of aircraft is very important, as these are the backbone of
Civil Aviation Services. These services should be available in state-of-art condition in
adequate supply in accordance with demand. For this, the role of private sector needs
to be emphasized.
Co-ordination
• A number of department/ agencies are involved in the development of Civil
Aviation Infrastructure and facilitating the convenience of the travelling
public. Inter-linkages with other modes of transport for travel and trade need
to be emphasised.
53
• An Inter-Ministerial Standing Committee will be constituted for coordination
with Ministries of Commerce, Tourism, Industry, Railways, Surface
Transport, Defence, Home Affairs (Immigration and Security), Finance
(Customs) and External Affairs. (Civil Aviation Policy, 2011)
In 1990, the private air taxi-operators carried 15,000 passengers which rose to 4.1
lakhs, 29.2 lakhs, 36 lakhs and 48.9 lakhs in 1992, 1993, 1994 and 1995 respectively.
The Air Corporation Act 1956 was modified on 1st March, 1994 which enabled
private operators to provide air transport services. Six operators were given the status
of scheduled operators on 1 February, 1995. In 1996, private air taxi operators carried
49.08 lakhs passengers which amounted to 41.14 percent share in domestic air
passenger traffic. The task of managing airports in India vest with Airport Authority
of India which at present looks after 15 international airports, 8 custom airport, 25
civil enclaves and 80 domestic airports.
54
Fig 2.1 Location of Domestic Airports in India
Source: www.mapsofindia.com
55
Fig. 2.2 Location of International Airports in India
Source: www.mapsofindia.com
56
2.5 REASONS FOR BOOM IN INDIAN AVIATION INDUSTRY
The unprecedented boom in airlines and flyers is the result of following factors:
a. Foreign equity allowed- The RBI announced that foreign institutional
investors might have shareholdings more than the limited 49% in the domestic
sector. Foreign equity up to 100% is allowed by the means of automatic
approvals pertaining to establishment of Greenfield airports. Up to 49% of
foreign equity and up to 100% of NRI investment is allowed by the means of
automatic approvals pertaining to the domestic air transport services.
However, the government policy bars foreign airlines from taking a stake in a
domestic airline company.
b. Low entry barriers- Now a days, venture capital of $10 million or less is
enough to launch an airline. Private airlines are known to hire foreign pilots,
get expatriates or retired personnel from the Air Force or PSU airlines in
senior management positions. Further, they outsource such functions as
ground handling, check-in, reservation, aircraft maintenance, catering,
training, revenue accounting, IT infrastructure, loyalty and programme
management. Airlines are known to take on contract employees such as cabin
crew, ticketing and check-in agents.
c. Attraction of foreign shores- Kingfisher airline and Jet Airways have gone
international by starting operations, first to SAARC countries, and then to
South-East Asia, the UK and the US. After five years of domestic operations,
many domestic airlines too will be entitled to fly overseas by using unutilised
bilateral entitlements to Indian carriers.
57
d. Rising income levels and demographic profile- Though India’s GDP (per
capita) at $3,100 is still very low as compared to the developed country
standards, India is shining at least in metro cities and urban centres, where IT
and BPO industries have made the younger generation prosperous.
Demographically, India has the highest percentage of people in age group of
20-50 among its 50 million strong middle class, with high earning potential.
All this contributes for the boost in domestic air travel, particularly from a low
base of 18 million passengers.
e. Untapped potential of India’s tourism- Currently, India attracts more than 5.11
million tourists every year, while China gets 10 times the number. Tourist
arrivals in India are expected to grow exponentially, especially due to open
sky policy between India and SAARC countries and the increase in bilateral
entitlements with European countries and the US.
f. Glamour of the airlines- No industry other than film-making is as glamorous
as the airlines. Airline tycoons from the last century, like J.R.D. Tata, Howard
Hughes, Sir Richard Branson and Dr. Vijaya Mallaya today have been
idolized. Airlines have an aura of glamour around them and high net worth
individuals can always toy with the idea of owning an airline. All the above
factors seem to have resulted in a “me too” rush to launch domestic airlines in
India.
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2.6 FUTURE OF AVIATION INDUSTRY IN INDIA
The challenges of the Indian aviation industry are cited below:
• Passenger traffic is estimated to grow at a CAGR of over 15% in the coming
few years.
• The Ministry of Civil Aviation would handle around 280 million passengers
by 2020.
• US$ 110 billion investment is envisaged till 2020 with US$ 80 billion solely
for new aircraft and US$ 30 billion for developing the airport infrastructure.
Airports
• Foreign equity up to 100% is allowed by the means of automatic approvals
pertaining to establishment of Greenfield airports
• Foreign equity up to 74% is allowed by the means of automatic approvals
pertaining to the existing airports
• Foreign equity up to 100% is allowed by the means of special permission from
Foreign Investment Promotion Board, Ministry of Finance, pertaining to the
existing airports
Air Transport Services
• Up to 49% of foreign equity is allowed by the means of automatic approvals
pertaining to the domestic air transport services.
• Up to 100% of NRI investment is allowed by the means of automatic
approvals pertaining to the domestic air transport services.
(business.mapsofindia.com)
59
Role of Aviation Industry in India’s GDP-Future Challenges
• Initializing privatization in the airport activities
• Modernization of the airlines fleet to handle the pressure of competition in the
aviation industry
• Rapid expansion plans for the major airports for the increased flow of air
traffic
• Immense development for the growing Regional Airports
Role of Aviation Industry in India’s GDP-FDI Policy
• The Reserve Bank of India (RBI) announced that foreign institutional
investors might have shareholdings more than the limited 49% in the domestic
sector. (Gupta, 2008)
60
Source: IBM Institute for Business Value analysis
Figure 2.3 Forc
es Shaping the Futu
re of th
e Airline In
dustry
.
61
2.7 NATURE OF AIRLINES
An airline provides air transport services for passengers and/or freight. Airlines lease
or own their aircraft with which to supply these services and may form partnerships or
alliances with other airlines for mutual benefit. Generally, airline companies are
recognized with an air operating certificate or license issued by a governmental
aviation body. (Airline, 2010)
Airlines operations can be categorized into two heads:
a.) Domestic airlines
b.) International airlines
List of Airlines in India
a) Domestic Airlines- Kingfisher Airlines, Kingfisher Red (previously Air Deccan),
Jet Airways, Jetlite (previously Air Sahara), Air India, Indian (previously India
Airline), IndiGo, SpiceJet, GoAir, Paramount Airways, Air India Express,
Alliance.
b) International Airlines- Aeroflot Airline, Air Astana, Air Canada, Air France, Air
Mauritius, Alitalia, Ariana Afghan Airline, Asiana Airlines, British Airways,
Cathay Pacific Airways, China Airlines, China Eastern Airlines, Delta Airlines,
Druk Air, Egypt Air, El Al Airline, Emirates Airline, Ethiopian Airlines, Etihad
Airways, Gulf Air, Iran Air, Japan Airline (JAL), Kenya Airways, KLM, Korean
Air, Kuwait Airways, Lufthansa, Mahan Air, Malaysia Airlines, Northwest
Airlines, Oman Air, Pakistan Airlines, Qantas Airways, Qatar airways, Royal
Jordanian Airline, Royal Nepal Airlines, Saudi Arabian Airline, Singapore
Airlines, South African Airways, SriLankan Airlines, Swiss International Airlines,
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Syrian Arab Airlines, Thai Airways International, Turkish Airlines, Uzbekistan
Airways.
Full service Vs Low cost Airlines
Airlines are divided under two sub heads: Full service (FSA) and Low cost service
(LCA) depending upon the nature of services they provide.
The concept of low cost airlines (LCA) was coined in 1971 by the Southwest Airlines
in the United States and has been profitable every year since 1973. Though the
concept became very popular in Europe after the deregulation of aviation and the
most notable success being the Irish Ryan Air founded in 1985, its spread has been
slow in Asia baring few countries. The first to start low cost airlines in Asia was Air
Asia of Malaysia in 2003.
A typical low cost airline’s business model is based on:
a. A single passenger class so as to ensure maximum number of seats.
b. A single type of aircraft thereby reducing training and servicing cost.
c. A simple fare scheme.
d. Open seating which encourages passengers to board early.
e. Direct point to point flights.
f. Flying to less congested airports.
g. Short flights and fast turnaround times allowing maximum utilisation of planes.
h. No catering and complimentary services.
i. No frequent flier or other promotional schemes and;
j. Direct distribution.
63
The low cost carriers have captured the imagination of air travellers and most of these
airlines are showing robust growth. It is estimated that in the next 10 years, low cost
airlines will capture at least 50% market share in Europe, 25% in the US and 25% in
Asia.
In India, there are eight low cost carriers, while other nine are waiting for their
permission to penetrate the aviation sector. Air Deccan, a unit of Deccan Aviation
Private Limited, was the first low cost carrier in India. All low cost carrier operating
in India is following the above proposed business model.
DELAG was the world’s first full service airline. It was founded on November 16,
1909 with government assistance, and operated airship manufactured by Zepelin
Corporation. Its headquarters was in Frankfurt. The other four oldest operative full
service airlines are Netherlands’s KLM, Colombia’s Avianca, Auatralia’s Qantas and
Mexico’s Mexicana. A full service airline’s business model is based on:
a. A dual passenger class.
b. A large and technically advanced fleet.
c. Facilities of connected flights.
d. Flying to almost all airports of country.
e. Star catering and complimentary services and
f. Provision of frequent flier or other promotional schemes.
Rising of low cost airlines have threatened the market share of full service carrier. It is
estimated that in coming few years, large chunk of share of full service carrier will be
captured by low cost airlines. At present, there are 8 low cost carriers and 3 full cost
carriers operating in India. (Gupta, 2008)
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Table 2.1 Sources of Non-Ticket Revenue for LCA and FSC Airlines
Non-ticket and other ancillary revenues
(In-flight services related)
Ancillary revenues
(Frequent Flyer related)
• Onboard sales of food and beverages
• Checking of baggage or excess
baggage
• Assigned seats or better seats such as
aisle seats
• Fees charged for purchases made with
credit cards
• Commissions from the sale of hotel
accommodations, car rentals and
shuttle bus transfer reserved at the
airline website
• Commissions from the sale of travel
insurance and airport lounge access
• Advertising tied to passenger travel
such as onboard magazines and in-
cabin media.
• Miles or points sold to banks
issuing co-branded credit cards
• Travel partners such as hotel
chains and car rental companies
• Other partners such as online
malls, retailers and
communication services
Source: Gupta, 2008 (Source: www.airdeccan.net)
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2.8 AIRLINES IN INDIA
As of 30 October 2007, the total fleet size of commercial airlines in India was 439. In
1994 the Air Corporation Act of 1953 was repealed with a view to remove monopoly
of air corporations on scheduled services, enable private airlines to operate scheduled
service, convert Indian Airlines and Air India to limited company and enable private
participation in the national carriers. However, at the beginning of 1990, private
airline companies were allowed to operate air taxi services, resulting in the
establishment of Jet Airways and Air Sahara. These changes in the Indian aviation
policies resulted in the increase of the share of private airline operators in domestic
passenger carriage to 68.5% in 2005 from 0.4 of 1991. (Airline, 2010)
Table 2.2 Operational Airlines- List of Airlines Today in the Market
AIRLINE ICAO IATA Call Sign Commenced
Operations
Headquarters
Air India AIC AI AIRINDIA October 1932 Mumbai
Air India
Express
AXB IX EXPRESS
INDIA
April 2005 Mumbai
Air India
Regional
LLR CD ALLIED 1996
(As Alliance Air)
Mumbai
GoAir GOW G8 GOAIR June 2004 Mumbai
Indian IAC IC INDAIR May 1953 Mumbai
IndiGo IGO 6E IFLY August 2006 Gurgaon
Jagson JGN JA JAGSON November 1991 Delhi
66
Airlines
Jet Airways JAI 9W JET AIRWAYS May 1993 Mumbai
JetLite JLL S2 LITE JET 1991
(As Air Sahara)
Mumbai
Kingfisher
Airlines
KFR IT KINGFISHER May 2005 Mumbai
Kingfisher
Red
KFR IT KINGFISHER August 2003
(As Air Deccan.
Merged and
made
a low-cost brand
of Kingfisher)
Mumbai
SpiceJet SEJ SG SPICEJET May 2005 Gurgaon
Market Share of Scheduled Domestic Airlines (Dec, 2011)
Airline Share (%)
Air India (Dom) 17.4%
IndiGo 20.4%
Kingfisher Airline 12.1%
Go Air 5.7%
Jet Airways 20.5%
Jetlite 7.1%
Spice Jet 16.8%
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Market Share of Scheduled Domestic Airlines (Dec, 2011)
17%
20%
12%6%
21%
7%
17%
Air India (Dom) IndiGo Kingfisher Airline Go Air
Jet Airways Jetlite Spice Jet
Figure 2.4 Market Share of Scheduled Domestic Airlines (Dec, 2011)
Source: Statistics from DGCA website (www.dgca.org)
68
69
2.8.1 AIR INDIA
Air India is a state-owned flag carrier, the oldest and the largest airline of India. It is a
part of the Indian government-owned Air India Limited (AIL) which is renamed as
Air India Ltd. The airline operates a fleet of Airbus and Boeing aircrafts serving Asia,
Australia, Europe and North America. Its corporate office is located at the Air India
Building at Nariman Point in South Mumbai. It is the 16th largest airline in Asia.
Following its merger with Indian, Air India has faced multiple problems, including
escalating financial losses and discontent among employees. Between September
2007 and May 2011, Air India's domestic market share declined from 19.2% to 14%,
primarily due to stiff competition from private Indian carriers. In 2007, the
Government of India announced that Air India would be merged with Indian. As part
of the merger process, a new company called the National Aviation Company of India
Limited (NACIL) was established, into which both Air India (along with Air India
Express) and Indian (along with Alliance Air) would be merged. On 27 February
2011, Air India and Indian Airlines merged along with their subsidiaries to form Air
India Limited. In August 2011, Air India's invitation to join Star Alliance was
suspended due to its failure to meet the minimum standards for the membership. In
October 2011, talks between the airline and Star Alliance have resumed.
Subsidiaries
Air India Cargo
In 1954, Air India Cargo started its freighter operations with a Douglas DC-3 Dakota
aircraft, giving Air India the distinction of being the first Asian airline to operate
freighters. The airline operates cargo flights to many destinations. The airline also has
ground truck-transportation arrangements on select destinations.
70
Air India Express
Air India Express is the airline's low-cost subsidiary which was established in 2005
during the aviation boom in India. It operates scheduled passenger services primarily
to the Persian Gulf and South East Asia. Air India Express is currently the only airline
in Air India Limited which posts profits. It operates a fleet of Next Generation Boeing
737-800 aircraft. Cochin International Airport is the main hub of the airline from
which it has connections to almost all the Gulf countries.
Air India Regional
Air India Regional (formerly known as Alliance Air) serves mainly on regional
routes. Its main hub is Delhi's Indira Gandhi International Airport.
Destinations:
Air India serves 49 domestic destinations and 26 international destinations in 19
countries across Asia, Europe and North America.
Short-haul routes
Air India's short-haul routes mainly include domestic cities and cities in South East
Asia and South West Asia. For short-haul routes, its Airbus A310, Airbus A330,
Boeing 747-400 and Boeing 777-200LR are used apart from Airbus A320 family
aircraft of Indian which are operated with Air India call sign and code.
Long-haul routes
The airline has long-haul destinations in East Asia, Europe and North America which
are served using Boeing 777-200LR and -300ER aircraft.
Code share agreements- Air India has code sharing agreements with the following
airlines:
71
Aeroflot *, Adria Airways^^, Air India Regional, Air Mauritius, Austrian Airlines^^,
BMI ^^, GMG Airlines, Gulf Air, Ethiopian Airlines, Kuwait Airways, Lufthansa^^,
Singapore Airlines^^, South African Airways^^, Turkish Airlines^^, Uzbekistan
Airways (* SkyTeam member, ^^ Star Alliance members)
Services
Frequent flyer programme- Flying Returns is Air India's frequent flyer programme.
The programme is also shared by all other Air India Limited carriers.
Premium lounges- The Maharaja Lounge (English: "Emperor's Lounge") is offered
to First and Business class passengers. Air India shares lounges with other
international airlines at international airports that do not have a Maharaja Lounge
available. There are five Maharaja Lounges, one at each of the five major destinations
of Air India, which are as following:
International
Air India's Maharaja Lounge at New York City's John F. Kennedy International
Airport London Heathrow Airport
John F. Kennedy International Airport (New York)
India
Bengaluru International Airport (Bangalore)
Chhatrapati Shivaji International Airport (Mumbai)
Indira Gandhi International Airport (Delhi)
Rajiv Gandhi International Airport (Hyderabad)
In-flight entertainment Air India's Boeing 777-200LR/-300ER as well as some
refurbished Boeing 747-400 aircraft uses the Thales Top Series IFE systems for
72
onboard in-flight entertainment. Airbus A310s do not have personal LCD screens.
Airbus A330s have widescreen displays in Business and Economy classes but no
personal IFEs. (en.wikipedia.org/wiki/Air_India)
73
74
2.8.2 JET AIRWAYS
Jet Airways is a major Indian airline based in Mumbai, Maharashtra. It is India's
largest airline and the market leader in the domestic sector. It operates over 400
flights daily to 67 destinations worldwide. Its main hub is Chhatrapati Shivaji
International Airport.
Early years, Jet Airways was incorporated as an air taxi operator on 1 April 1992. It
started Indian commercial airline operations on 5 May 1993 with a fleet of four leased
Boeing 737-300 aircrafts. In January 1994, a change in the law enabled Jet Airways to
apply for scheduled airline status, which was granted on 4 January 1995. It began
international operations to Sri Lanka in March 2004. The company is listed on the
Bombay Stock Exchange, but 80% of its stock is controlled by Naresh Goyal (through
his ownership of Jet’s parent company, Tailwinds). It has 10,017 employees (as at
March 2007).
In October 2008, Jet Airways and rival Kingfisher Airlines announced an alliance
which primarily includes an agreement on code-sharing on both domestic and
international flights, joint fuel management to reduce expenses, common ground
handling, and joint utilisation of crew and sharing of similar frequent flier
programmes.
Subsidiaries
JetLite- JetLite was established as Sahara Airlines on 20 September 1991 and began
operations on 3rd December 1993 with two Boeing 737-200 aircrafts. Initially,
services were primarily concentrated in the northern sectors of India, keeping Delhi as
its base, and then operations were extended to cover all the country. Sahara Airlines
was rebranded as Air Sahara on 2nd October 2000. On 12th April 2007, Jet Airways
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took over Air Sahara and on 16th April 2007 Air Sahara was renamed as JetLite.
JetLite operates a fleet of mixed owned–leased Boeing 737 Next Generation aircraft
and Bombardier CRJ-200ER.
Jet Konnect- Jet Konnect is the low-cost brand of India-based Jet Airways. It was
launched on 8th May 2009, and shares the same airline code and call sign as Jet
Airways. It operates a mixed fleet of ATR 72-500s and Boeing 737-800s.
Services
Cabin-
Domestic & international short haul
Boeing 737 Next Generation aircrafts are configured in Economy Classes. Some
Boeing 737s have and all Economy Class cabin layout. The ATR 72-500 have
Economy class configuration only.
Première
The Première features 40-inch extra-wide seats with a personal Widescreen LCD
attached to each seat. The Première cabin is configured in a 2-2 abreast pattern.
Economy Class
Jet Airways Economy class on its Boeing 737 Next Generation features 30-inch seat
pitch with personal Widescreen LCD behind each seat. Jet Airways was the World's
first airline to introduce in-flight entertainment systems on the Boeing 737 aircraft.
The Economy class cabin is configured in a 3-3 abreast pattern on the Boeing 737
Next Generation and 2-2 abreast pattern on the ATR 72-500.
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International long haul
With the arrival of its new Airbus A330-200 and Boeing 777-300ER aircraft, Jet
Airways has introduced a new cabin with upgraded seats in all classes. The Airbus
A330-200 aircraft have two classes: Première and Economy. The Boeing 777-300ER
aircraft has three classes of service: First, Première (Business), and Economy. Jet
Airways has a three-star rated First and Business Class, and is in the top twenty-five
business classes reviewed by Skytrax. Economy class has been reviewed as a three-
star product by Skytrax. Being a Full Service Airline, meals are served on all classes
of travel.
First Class
First class is available on all Boeing 777-300ER aircraft. All seats convert to a fully-
flat bed, similar to Singapore Airlines first class seat but much smaller. It was the
twenty-second airline in the world to have private suites. All seats in First have a 23-
inch widescreen LCD monitor with audio-video on-demand systems (AVOD), BOSE
noise cancelling headphones, in seat power supply, and USB ports etc. Jet Airways is
the first Indian airline to offer fully-enclosed suites on its aircraft; each suite has a
closable door, making for a private compartment. Skytrax consumer airline reviewers
recently rated Jet Airways First Class as being 14th best in the world.
Première
Première on board the Boeing 777-300ERPremière (Business Class) on the Airbus
A330-200 and Boeing 777-300ER international fleet has a fully-flat bed with AVOD
entertainment. Seats are configured in a herringbone pattern (1-2-1 on the Boeing
777-300ER, and 1-1-1 on the Airbus A330-200), with each seat offering direct access
to the aisle. Première seats on the A330-200s leased from ILFC are configured
77
differently in a 2-2-2 non-herringbone pattern. Each Première Seat has a 15.4-inch flat
screen LCD TV with AVOD. USB ports and in-seat laptop power are provided. All
seats are standard recliner business-class seats with a few newer aircraft with
electronic recline and massager.
Economy Class
Economy class on Jet's A330-200/777-300ER aircraft has 32-inch seat pitch. Seats on
the A330-200/777-300ER have a "hammock-style" net footrest. Each Economy seat
on the A330-200/777-300ER has a personal 10.6-inch touch screen LCD TV with
AVOD. All three classes feature Mood lighting on the Airbus A330-200 and Boeing
777-300ER, with light schemes corresponding to the time of day and flight position.
In-flight entertainment- Jet Airways' Panasonic eFX IFE system on-board the
Boeing 737-700/800 and Panasonic eX2 IFE system on-board the Airbus A330-
200/Boeing 777-300ER, called "JetScreen", offers audio video on-demand
programming (passengers can start, stop, rewind, and fast-forward as desired). It has
over 100 movies, 80 TV programmes, 11 audio channels and a CD library of 125
titles.
Airport lounges- Jet Airways Lounges are offered to First and Première Class
passengers, along with JetPrivilege Platinum, Gold or Silver card members. The
international lounge at Brussels has showers, business centre, entertainment facilities
and children's play areas. Lounges are located in: Bangalore, Brussels, Chennai,
Cochin, Delhi, Hyderabad, Jaipur, Kolkata, Mumbai.
Frequent-flyer program- JetPrivilege is Jet Airways’ frequent-flyer program.
(en.wikipedia.org/wiki/Jet_Airways)
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79
2.8.3 KINGFISHER AIRLINE
Kingfisher Airlines is an airline group based in India. Its head office is The Qube in
Andheri (East), Mumbai and Registered Office in UB City, Bangalore. Kingfisher
Airlines, through its parent company United Breweries Group, has a 50% stake in
low-cost carrier Kingfisher Red.
Kingfisher Airlines is one of the seven airlines to be ranked as a 5-star airline by the
independent research consultancy firm Skytrax. Kingfisher operates more than 375
daily flights to 71 destinations, with regional and long-haul international services. In
May 2009, Kingfisher Airlines carried more than a million passengers, giving it the
highest market share among airlines in India. Kingfisher also owns the Skytrax award
for India's best airline of the year 2011.
Kingfisher Airlines is also the sponsor of F1 racing outfit, Force India, which Vijay
Mallya also owns.
History
Kingfisher Airlines was established in 2003. It is owned by the Bengaluru based
United Breweries Group. The airline started commercial operations on 9th May 2005,
with a fleet of four new Airbus A320-200s operating a flight from Mumbai to Delhi.
It started its international operations on 3rd September 2008, by connecting Bengaluru
with London.
On 7th June 2010, Kingfisher became a member elect of the Oneworld airline alliance
when it signed a formal membership agreement.
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Services
Cabin classes
Domestic
Kingfisher First
The domestic Kingfisher First seats have a 48 inch seat pitch and a 126 degree seat
recline. There are laptop and mobile phone chargers on every seat. Passengers can
avail of the latest international newspapers and magazines. There is also a steam
ironing service on board Kingfisher First cabins. Every seat is equipped with a
personalised IFE system with AVOD which offers a wide range of Hollywood and
Bollywood movies, English and Hindi TV programmes, 16 live TV channels and 10
channels of Kingfisher Radio. Passengers also get BOSE noise cancellation
headphones.
Domestic Kingfisher First is only available on selected Airbus A320 family aircraft.
Kingfisher Class
The domestic Kingfisher Class has 32-34 inch seat pitch.
Every seat is equipped with personal IFE systems with AVOD on-board the Airbus
A320 family aircraft. As in Kingfisher First, passengers can access the movies,
English and Hindi TV programmes, a few live TV channels powered by Dish TV and
Kingfisher Radio. The screen is controlled by a controller-console on the seat armrest.
Earcup headphones are provided free of cost to all passengers. The default channel
shows, alternating every few seconds, The aeroplane's ground speed, outside
temperature, altitude, distance and time to destination; the position of the aircraft on a
graphical map and one or more advertisements.
81
Passengers are served meals on most flights. Before take-off, passengers are served
bottled Lemonade.
On-board the ATR 72-500s, there are 17 colour LCD drop-down screens mounted
along with loudspeakers for audio in the cabin overhead, a head-end unit to handle
CDs and DVDs, and a crew control panel. The screens measure 12.7 cm by 9.3 cm,
weigh 0.2 kg each and are spaced every two or three seat rows along both sides of the
cabin.
Kingfisher Red
After Kingfisher Airlines acquired Air Deccan, its name was changed to Simplifly
Deccan and subsequently to Kingfisher Red. Kingfisher Red is Kingfisher Airline's
low-cost class on domestic routes. Passengers are given complimentary in-flight
meals and bottled water. A special edition of Cine Blitz magazine is the only reading
material provided.
Kingfisher Airlines is the first airline in India to extend its King Club frequent flyer
program to its low-cost carrier as well. Passengers can earn King Miles even when
they fly Kingfisher Red, which they can redeem for free tickets to travel on
Kingfisher Airlines or partner airlines.
International
Kingfisher First- The international Kingfisher First has full flat-bed seats with a 180
degree recline, with a seat pitch of 78 inches, and a seat width of 20-24.54 inches.
Passengers are given Merino wool blankets, a Salvatore Ferragamo toiletry kit, a
pyjama to change into, five-course meals and alcoholic beverages. Also available are
in-seat massagers, chargers and USB connectors.
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Every Kingfisher First seat has a 17 inch widescreen personal television with AVOD
touch screen controls and offers 357 hours of programming content spread over 36
channels, including Hollywood and Bollywood movies along with 16 channels of live
TV, so passengers can watch their favorite TV programmes live. There is also a
collection of interactive games, a jukebox with customisable playlists and Kingfisher
Radio. Passengers are given BOSE noise cancellation headphones.
The service on board the Kingfisher First cabins includes a social area comprising a
full-fledged bar staffed with a bartender, a break-out seating area just nearby fitted
with two couches and bar stools, a full-fledged chef on board the aircraft and any-time
dining. A turn-down service includes the conversion of the seat into a fully-flat bed
and an air-hostess making the bed when the passenger is ready to sleep.
Both Kingfisher First and Kingfisher classes feature mood lighting on the Airbus
A330-200 with light schemes corresponding to the time of day and flight position.
Kingfisher Class
The international Kingfisher Class seats offer a seat pitch of 34 inches, a seat width of
18 inches and a seat recline of 25 degrees (6 inches). Passengers get full length
blankets, full size pillows and business class meals.
Each Kingfisher Class seat has a 10.6 inch widescreen personal television with
AVOD touch screen controls. The IFE is similar to that of the international Kingfisher
First class. It can also be controlled by a detachable remote-control console fitted in
the armrest. This device can be used to control the IFE, reading-lights, play games
and even has a credit-card swipe for shopping on Kingfisher's 'Air Boutique'. It also
has a facility for sending text-messages, though the service isn't provided by
Kingfisher.
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In-flight entertainment
Kingfisher's IFE system is the Thales Top Series i3000/i4000 on-board the Airbus
A320 family aircraft, and Thales Top Series i5000 on-board the Airbus A330 family
aircraft provided by the France-based Thales Group.
Kingfisher was the first Indian airline to have in-flight entertainment (IFE) systems on
every seat even on domestic flights. All passengers were given a "welcome kit"
consisting goodies such as a pen, facial tissue and headphones to use with the IFE
system. Now, passengers of kingfisher class are not given "welcome kits" but as
mentioned earlier, a complimentary bottle of lemonade and earphones for use with the
IFE are still given. Initially, passengers were able to watch only recorded TV
programming on the IFE system, but later an alliance was formed with Dish TV to
provide live TV in-flight. And in a marked departure from tradition, Kingfisher
Airlines decided to have an on-screen safety demonstration using the IFE system,
however the conventional safety briefing by the flight attendants still exists on many
flights.
King Club
The Frequent-flyer program of Kingfisher Airlines is called the King Club in which
members earn King Miles every time they fly with Kingfisher or its partner airlines,
hotels, car rental, finance and lifestyle businesses. There are four levels in the scheme:
Red, Silver, Gold and Platinum levels. Members can redeem points for over a number
of schemes. Platinum, Gold and Silver members enjoy access to the Kingfisher
Lounge, priority check-in, excess baggage allowance, bonus miles, and 3 Kingfisher
First upgrade vouchers for Gold membership. Platinum members get 5 upgrade
vouchers.
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Kingfisher Lounge
Kingfisher Lounges are offered to Kingfisher First passengers, along with King Club
Silver and King Club Gold members. Lounges are located in:
• Bengaluru International Airport
• Chennai International Airport
• Chhatrapati Shivaji International Airport (Mumbai)
• Cochin International Airport (Kochi)
• Indira Gandhi International Airport (Delhi)
• London Heathrow Airport
• Netaji Subhash Chandra Bose International Airport (Kolkata)
• Rajiv Gandhi International Airport (Hyderabad)
(en.wikipedia.org/wiki/Kingfisher_Airline)
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2.8.4 INDIGO
IndiGo is a private domestic low-cost airline based in Gurgaon, Haryana, India. It
operates domestic services linking 31 destinations. Its main base is Delhi's Indira
Gandhi International Airport. It was awarded the title of the Best Domestic Low Cost
Carrier in India for 2008. IndiGo has the second largest share in India's domestic air
travel market, only behind Jet Airways and as of October 2011 it is the only airline in
India making profit.
Following Indian regulations, IndiGo received its license to operate international
flights upon completing five years of operations. Its main operational hub is New
Delhi's Indira Gandhi International Airport. IndiGo has been awarded numerous
airline and travel industry awards. IndiGo won the Skytrax Central Asia's best low-
cost airline award in 2011.
History
IndiGo commenced operation on 4th August, 2006 from Delhi to Imphal via
Guwahati. Rakesh Gangwal and Rahul Bhatia are the two founders of Indigo airlines.
The airline is owned by the Gurgaon-based InterGlobe Enterprises. It took delivery of
its first Airbus A320-200 aircraft on 28th July 2006 and received six aircraft during
2006. Nine more aircraft were delivered in 2007 taking the total to 15. Former US
Airways Executive, vice-President, Marketing and Planning Bruce Ashby joined
IndiGo as its Chief Executive Officer. The airline has also acquired three parking
spots at Indira Gandhi International Airport and Chhatrapati Shivaji International
Airport. Recently, IndiGo changed the outfits for their crew members on occasion of
its 4th anniversary.
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In-flight service
Being a low-cost carrier, IndiGo does not offer complimentary meal services to its
passengers. However, it does offer buy-on-board food services where items such as
sandwiches, parathas, cookies, nuts, soft drinks and mineral water can be purchased.
Purified drinking water is provided free of charge. (en.wikipedia.org/wiki/IndiGo)
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2.8.5 GOAIR
GoAir is an Indian low-cost airline based in Mumbai, Maharashtra. It operates
domestic passenger services to 21 cities with 156 daily flights and approximately
1092 weekly flights. Its main base is Chhatrapati Shivaji International Airport,
Mumbai.
Go Airlines (India) Ltd. is the aviation foray of the Wadia Group. The airline operates
its services under the brand GoAir. The airline's theme, 'Fly Smart', aims to offer
passengers a consistent, quality-assured and time-efficient service with low fares. The
airline uses Airbus A320 aircraft.
GoAir's business model is based on punctuality, affordability and convenience. The
airline has partnered with Radix International, a technology provider of automated
aviation and travel related software solutions, for the use of its Air Enterprise. The
adoption of such technology solutions enables GoAir to achieve higher process
efficiency, giving passengers increased time savings
History
The airline was established in 2005. It launched commercial operations in November
2005. It is now wholly owned by the Wadia Group, Mumbai based and majority
owners of Bombay Dyeing and Britannia Industries.
Service
Being a no-frills airline, Go does not offer any complimentary meal service to its
passengers. However, it does offer a buy-on-board food service, where items such as
sandwiches, parathas, cookies, nuts, soft drinks and Mineral water can be purchased.
But from 9th April 2009, Go has started a new premium service known as Go
Business in which the passengers, at a slightly higher fare, are assured of seats in the
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first two rows of the aircraft and the middle seat is always empty. Go provides free
meals on board to passengers travelling on Go Business.
(en.wikipedia.org/wiki/GoAir)
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2.8.6 SPICE JET
SpiceJet is a low-cost airline headquartered in Gurgaon, India. It began service in
May 2005 and by 2008, it was India's second-largest low-cost airline in terms of
market share. SpiceJet was voted as the best low-cost airline in South Asia and
Central Asia region by Skytrax in 2007. Following the acquisition by Kalanithi
Maran, SpiceJet went to be part of Kal Airways, Sun Group in 2010.
History
SpiceJet, India's leading low cost airline, is a reincarnation of ModiLuft. It is
promoted by Ajay Singh and the Kansagra family. SpiceJet marked its entry in the
Indian skies with 99 fares for the first 99 days, with 9,000 seats available at this rate.
This deal was followed up with a 999 promotional scheme on select routes. Their
marketing themes are "offering low 'everyday spicy fares' and great guest services to
price conscious travellers. SpiceJet now competes with IndiGo and the Indian
Railways. As India's economy and businesses are growing, the dream for flying has
become common and SpiceJet's mission is to ensure that flying is for everyone.
Destinations
SpiceJet operates over 264 flights daily to 32 Indian cities viz. Agartala, Ahmedabad,
Aurangabad, Bangalore, Bagdogra, Bhopal, Chennai, Coimbatore, Delhi, Guwahati,
Goa, Indore, Hyderabad, Jammu, Jaipur, Kochi, Kolkata, Madurai, Mumbai,
Mangalore, Nagpur, Pune, Rajahmundry, Srinagar, Surat, Trichy, Tirupati,
Trivandrum, Tuticorin, Varanasi, Vijaywada and Visakhapatnam. On the international
front, SpiceJet operates flights to Kathmandu and Colombo. Services
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Services
In order to keep the fares low and affordable, SpiceJet offers an assortment of
vegetarian/non-vegetarian sandwiches, cookies, flavoured nuts, soft drinks and juices
as a buy-on-board option. As a low-cost carrier, SpiceJet offers only complimentary
mineral water to passengers on board its flights. SpiceJet also allows food to be
carried on board. However, the food should be cold snacks, non-alcoholic drinks,
snack bars and biscuits. Messy, oily or smelly food items are not allowed on board.
Per Spicejet Baggage rules, a maximum of 20 kg of baggage is allowed per paying
passenger. However, international passengers can carry 2 bags weighing nothing more
than 23 kilograms each. The cost of carrying excess baggage is Rs 100 per kg for a
one-way trip. Also, the weight of the cabin baggage should not be exceeding 10 kg.
The size of the cabin baggage is as of now, 55 cm + 35 cm + 25 cm. Cabin baggage is
not allowed in flights connecting the Indian state of Jammu and Kashmir. SpiceJet
allows customers to earn reward points and cash back offers as they book using their
SpiceJet State Bank of India Master Card which was recently introduced by SpiceJet
in collaboration with the State Bank of India and Mastercard. They also provide
Insurances Air Accident Insurance, Delayed Flight Insurance, and Lost Baggage
Insurance. Despite no in-flight entertainment, SpiceJet provides an in-flight magazine
named SpiceRoute. Since August 2009, Maxposure Media Group has been printing
and publishing the magazine. (en.wikipedia.org/wiki/SpiceJet)
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2.8.7 JAGSON AIRLINES
Jagson Airlines is an airline based in Delhi, founded in 1991. It operates scheduled
and charter services within India and to Bhutan and Nepal.
History
The airline was established and started operations in November 1991. It began charter
operations with two 18-seat Dornier 228-201 aircraft and later operated regular
services from Delhi. It is wholly owned by Jagson International. In 2006 they
announced plans to expand their services to 9 cities, using leased Airbus A321-200
aircraft. Jagson have withdrawn plans to launch a nationwide scheduled low-cost
airline by mid-2006 and plan to continue as a regional airline.
Jagson has recently taken deliveries of RJ 80s / BAe 146-200s Avro Regional Jets.
They will be starting operations to all their previous routes shortly. Efforts are on to
merge the erstwhile MDLR, which operated the same type of aircraft, and form a 5
aircraft airline.
Besides a seat to travel, the above mentioned airlines offering service products to
domestic air travellers. There are equal chances that a traveller gets satisfied or
dissatisfied after consuming these services. But there are some other airline
performance areas with which the traveller is encountered and which also determines
the air traveller’s satisfaction or dissatisfaction like on-time arrival and departure,
baggage handling, handling of complaints, right and timely information to the
customers, security services, interaction with the crew and ground staff members etc.
(en.wikipedia.org/wiki/Jagson_Airline)
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2.8.8 PARAMOUNT AIRWAYS
Paramount Airways was an airline based in Chennai, India. It was a national licensed
airline. It operated scheduled services, mainly targeting business travellers. Its hub
was Chennai International Airport. It was the first airline in India to launch the New
Generation Embraer 170/190 Family series aircraft.
History- The airline started operations in October 2005 and the company was
originally headquartered in Madurai, where they also operate Paramount Textiles.
Destinations- Since the withdrawal of its license, the operations of the airline are
currently suspended. The airline has stated that it intends to resume operations in
December 2010 following their successful case in the Madras High Court. As of
January 2010 the average age of the Paramount Airways fleet was 8 years. On 20th
June, 2009, Paramount Airways signed a MoU to buy ten Airbus A321-200 aircrafts
with an option for an additional ten. The agreement was concluded at the 48th Paris
Air Show. The deal is being funded by the European Central Bank.
The airline evaluated two turboprop aircraft, the ATR 72-600 and the Bombardier
Dash 8 Q400 at the 2009 Dubai Air show. It had plans to buy up to eight turboprop
aircrafts which would be deployed to connect smaller Indian cities. It however settled
for 6 Bombardier Dash 8 Q400s.
Legal issue and cancellation of licence- In early 2010, legal issues between
Paramount Airways and the lessors of their Embraer aircraft led to the de-registration
of their fleet. This caused a gradual termination of all services as their fleet was
grounded and then, subsequently, seized by the leasing companies.
Court victory and resumption of services - In November, 2010, it was announced
that Paramount Airways have won their legal battle and are all set to resume services
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with a fleet based on Airbus and Bombardier aircraft. Normalisation of the route
network should be successful by December, 2010.
(en.wikipedia.org/wiki/Paramount_Airways)
2.9 AIR TRAFFIC TRENDS
Table 2.3 Air traffic trends: World vs India 2000-2010
E-Estimated
F –Forecast
Source: ICAO data to 2008, IATA 2009 estimates and 2010 forecasts and Airport Authority of India traffic forecasts
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Fig 2.5 Worldwide Passenger Traffic: % Growth Total 2000 to 2010F
Fig 2.6 India Passenger Traffic: % Growth Total 2000 to 2010F
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Fig 2.7 Strong Domestic Passenger Traffic Growth
Fig 2.8 Load Factor at the Highest Level in a Decade
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Table 2.4 Monthly Traffic and Operating Statistics of All Indian Carriers on
Scheduled Domestic Services During 2009-2010
Source: DGCA
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Table 2.5 Comparative Statement of Domestic Traffic on Scheduled Services of
All Indian Carriers During 2009-10
Source: ICAO Form-A Furnished by Scheduled Indian Carriers
103
Table 2.6 Comparative Statement of Total Traffic on Scheduled Services of All
Indian Carriers During 2009-2010
Source: ICAO Form-A Furnished by Scheduled Indian Carriers
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REFERENCES
Airline. (2010). Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/Airline.
Air India. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/Air_India.
Anjali. (2011). Find cheap domestic flights in India with a click of mouse. Retrieved
June 18, 2011 from http://www.articlesalley.com/article.detail.php.
Aviation. (March, 2011). Retrieved June 23, 2011 from
http://www.ibef.org/sector/Aviation.
Civil Aviation Policy. (2011). Retrieved June 23, 2011 from
http://www.businessmapsofindia.com/indiapolicy.
Civil Aviation Policy (Draft). (April, 2000).Retrieved June 25, 2011 from
http://www.gidb.org.
Domestic airports in India. Retrieved June 23, 2011 from http://mapsofindia.com/air-
network/domestic-airport-map.htm.
Go Air. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/GoAir.
Gupta, Sanjana. (2008). Service Quality in Airlines. A Dissertation submitted to The
University of Jammu.
IndiGo. Retrieved Feb 10, 2012 from http://en.wikipedia.org/wiki/IndiGo.
International airports in India. Retrieved June 23, 2011 from
http://mapsofindia.com/air-network/international-airport-map.htm.
Jagson Airline. Retrieved June 25, 2011 from
http://en.wikipedia.org/wiki/Jagson_Airline.
Jet Airways. Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/Jet_Airways.
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Kingfisher Airline. Retrieved Feb 10, 2012 from
http://en.wikipedia.org/wiki/Kingfisher_Airlines.
Latest developments and policy initiatives in Civil Aviation in India (March, 2007),
Retrieved June 23, 2011 from
http://www.inrnews.com/realestateproperty/india/infrastructure.
Overview. (2008). Retrieved June 22, 2011 from http://www.info.shine.com/Industry-
Information/Aviation.
Paramount Airways. Retrieved June 23, 2011 from
http://en.wikipedia.org/wiki/Paramount_Airways.
Passenger data. (2012). Retrieved Feb. 10, 2012 from
http://www.dgca.nic.in/reports/pass_data.pdf.
Pasari Nitika. (2005-06). Low Cost Airlines in a Developing Economy- The Case of
India. A Dissertation submitted to The University of Nottingham.
Role of Aviation Industry in India GDP. (2008). Retrieved June 23, 2011 from
http://www.businessmapsofindia.com/indiagdp/industries.
SpiceJet. Retrieved June 23, 2011 from http://en.wikipedia.org/wiki/SpiceJet.
Vivek. (2011). Travelling between the cities with the cheapest flights in India.
Retrieved June 18, 2011 from
http://www.articlesalley.com/article.detail.php.
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–
During the past three decades, a growing number of researchers and marketing
practitioners have undertaken systematic efforts to understand the effect of
consumption of services on the customer’s satisfaction. The increasing attention given
to the subject has been manifested in various ways. In the service consumption
process, service encounter stage and post encounter stage is very critical to build the
relationship between a service provider and a customer. A negative evaluation of
service encounter by a customer leads to service failure which effects the satisfaction
of a customer. After a service failure occurs, the service provider has the opportunity
to take a variety of recovery actions to re-establish the customer satisfaction. A lot of
research work has been done in the areas of effect of service encounter, service
failures and recovery strategies on customer satisfaction. In this context, it becomes
imperative to undertake a synoptic view of research conducted on effect of service
encounter, service failures and recovery strategies on customer satisfaction in various
service sectors (like restaurant, hotels, airlines, medical, self-service technologies,
online environment etc.). This will indicate the areas in which researcher could
concentrate more, though, it may be necessary but not possible to give a detailed
review of existing literature, yet an attempt has been made to provide a
comprehensive account of the findings of various studies and identify research gaps
there in. Further with the help of review of literature, an outline of the research design
to be adopted by the researcher in the present study has been developed.
CHAPTER-3
REVIEW OF LITERATURE
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The review of literature has been divided into two sections; separately dealing with
the topics of service encounters and service failure and recovery strategies. The
literature review includes findings of studies in the related subject done in the recent
past. However, research by Bitner, Booms and Tetreault (1990) form the basis of
present research. Since the time of Bitner et al’s work, several studies have been
published that attempt to study the effect of service failures and recovery strategies on
customer satisfaction.
3.1 SERVICE ENCOUNTER
For the success of marketing efforts, there is increased recognition of the significance
of the person to person encounter i.e. between the service provider and the customer
and the effect of this encounter on the customer. The concept of Service Encounter
i.e. a period of time during which a customer interact directly with service provider
(Shostack, 1985). The concept of service encounter and its effect on the person
involved has attracted the attention of researchers in the last few years.
Surprenant and Solomon (1987) in the paper “Predictability and Personalization in
the Service Encounter” investigate the soundness of the conventional wisdom that
personalized service is better service. The findings of the study confirm that service
personalization is a multidimensional construct and all forms of personalization do
not necessarily result in more positive evaluations of the service offering by
consumers. Personalized service is not without cost to the service establishment or to
consumers, and its degree of “value added” should be assessed carefully.
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Bitner (1990) in her research paper “Evaluating Service Encounters: The Effects of
Physical Surroundings and Employee Responses” presents a model for understanding
service encounter evaluation that synthesizes consumer satisfaction, services
marketing and attribution theories and provides a framework for programmatic
research on service encounter evaluations. A controlled experiment was conducted to
test a portion of the model focusing on the relationships between attributions and
satisfaction and between selected elements of the services marketing mix and
attributions. The results of the study showed that when customers perceive the cause
of service failure to be with in the control of the firm and likely to occur again, they
will be more dissatisfied than when opposite conditions hold. The controllable
variables such as employee explanations, offers to compensate and the appearance of
the physical environment can influence how customers perceive the causes of service
failure. The framework and study results reinforce the idea that elements of the
expanded marketing mix should be included in strategies for improving service
encounter satisfaction.
Bitner, Booms and Tetreault (1990) in their study “The Service Encounter:
Diagnosing Favorable and Unfavorable Incidents” applied the Critical Incident
Method, collected 700 incidents from customers of airlines, hotels and restaurants,
resulted in three major groups of employee behaviours that could account for all
satisfactory and dissatisfactory incidents. The three major groups are – Group 1:
Employee response to service delivery system failures: When the service delivery
system fails, contact employees are required to respond to consumer complaints or
disappointments. The content or form of the employee response determines
customer’s perceived satisfaction or dissatisfaction. Group 2: Employee Response to
Customer Needs and Requests: When a customer requires the contact employee to
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adapt the service delivery system to suit his or her unique needs, the contact
employee’s response determines customer’s dis/satisfaction. In this group incidents
are required to contain either an explicit or inferred request for customized service
and Group 3: Unprompted and Unsolicited Employee Actions: Events and
employee behaviours that are truly unexpected from the customer’s point of view are
included in this group. Satisfactory incidents represent very pleasant surprises (special
attention, being treated like royalty, something nice but not requested) where as
dissatisfactory incidents comprise negative and unacceptable employee behaviours
(rudeness, stealing, discrimination, ignoring the customer).
With in three major groups, there are 12 categories under which various incident
outcomes were defined. Group1 includes three categories –
G1A: Response to Unavailable Service: Services normally available are lacking or
absent like the airplane is overbooked or the reserved table is occupied. The way in
which non availability is handled influences the customer’s perception of the service.
G1B: Response to Unreasonably Slow Service: This category reflects incidents in
which services or employee performances are perceived as inordinately slow.
Employee reaction to such delays determines the customer’s satisfaction level.
G1C: Response to other Core Service Failures: It includes incidents in which other
aspects of the core service do not meet basic performance standards for the industry
(e.g. the hotel room is not clean, the baggage arrives damaged). How the employee
responds to these failures determines the customer’s perceptions of the encounter.
Group2 includes four categories – G2A: Response to Special Needs Customers:
This category involves customers who have special medical, dietary, psychological,
language or sociological difficulties. Failure to recognize the seriousness of the
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customer’s need and/or inappropriate or inadequate treatment of the problem can
result in a very dissatisfactory incident.
G2B: Response to Customer Preferences: This category includes incidents when
from the customer’s perspective, special requests are made. These requests reflect
personal preferences unrelated to the customer’s sociological, physical or
demographic characteristics. However, customers can be very dissatisfied when their
preferences are not accommodated, especially if the employee shows no interest and
exerts no effort to be responsive, is unwilling to consider ‘bending the rules’, or
promises to do something and then fails to follow through.
G2C: Response to Admitted Customer Error: In this category the triggering event
is a customer error that strains the service encounter (e.g. lost tickets, missed
reservations). Dissatisfactory employee responses include laughing at and
embarrassing the customer for his or her mistake, avoiding any responsibility and
demonstrating an unwillingness to assist the customer in solving the problem.
G2D: Response to Potentially Disruptive Others: With in the environment of the
service encounter, other customers’ behaviours can strain the encounter (e.g.
intoxication, rudeness, social deviance). The contact employee either does or does not
cope with the disruptive person(s) to the satisfaction of other customers present.
Group3 includes five categories – G3A: Attention paid to Customers: This category
includes incidents in which the level of attention paid to the customer is viewed very
favourably or negatively. Dissatisfactory encounters occur when contact employees
demonstrate poor attitudes toward the customer, ignore the customer or treat the
customer impersonally.
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G3B: Truly out-of-ordinary employee behaviour: In this category are incidents in
which the employee does some small thing that for the customer translates into a
highly satisfactory or dissatisfactory encounter. In case of dissatisfactory encounters,
extraordinary employee behaviour may consist of profanity, yelling, inappropriate
touching or rudeness.
G3C: Employee behaviours in the context of Cultural norms: Incidents in this
category reflect employee behaviours relating to cultural norms such as equality,
honesty and fairness. Dissatisfactory encounters are associated with employee
behaviours that clearly violate cultural norms (discrimination against female/young
customers, employee theft, bribery or lying).
G3D: Gestalt evaluation: For dissatisfactory incidents in this category, customers
are unable to attribute dis/satisfaction to any single feature of the service encounter.
Instead the service encounter is evaluated holistically, either ‘everything went right’
or ‘everything went wrong’.
G3E: Performance under adverse circumstances: This category includes incidents
in which the customer is particularly impressed / displeased with the way a contact
employee handles a stressful situation.
The incidents were categorized to isolate the particular events and related behaviours
of contact employees that cause customers to distinguish very satisfactory service
encounters from very dissatisfactory ones. The study has various implications like the
Critical Incident Method is a useful tool for assessing customer dis/satisfaction in
service encounters and the classification system that emerged from the data can be
used to other high-contact transaction-based service industries as well. The CIT
enables managers to identify what knowledge is needed and what control is required
112
as well as providing a basis for determining which is more important for a given type
of encounter. The results of this study suggest that the CIT is also an appropriate and
useful method for studying marketing questions and for assessing customer
perceptions.
Table 3.1 Bitner et al’s (1990) Group and Category Classification by Type of
Incident Outcome
Group & Category Type of Incident Outcome
Group 1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service
G1B Response to unreasonably slow service
G1C Response to other core service failures
Group 2 Employee Response to Customer Needs and Requests
G2A Response to special needs customers
G2B Response to customer preferences
G2C Response to admitted customer error
G2D Response to potentially disruptive others
Group 3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customers
G3B Truly out-of-the ordinary employee behaviour
G3C Employee behaviours in the context of cultural norms
G3D Gestalt evaluation
G3E Performance under adverse circumstances
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Bitner, Booms and Mohr (1994) in their study “Critical Service Encounters: The
Employee’s Viewpoint” collected critical service encounters reported by employees
of the hotel, restaurant and airline industries. The purpose of the study is to evaluate
the soundness of the classification scheme developed by Bitner et al, 1990 in a
distinctive context. Drawing on insights from role, script and attribution theories
critical service encounters were analyzed and compared with previous research. The
results indicated that all the categories found in the original customer-perspective
study (Bitner et al, 1990) were also found when employees were asked to report
and also identify an additional source of customer dissatisfaction i.e. their own
misbehaviour. The addition of this new group 4, problematic customer behaviour
provides a more complete classification system that can be further examined in other
contexts. It is suggested that many frontline employees do have a true customer
orientation and do identify with and understand customer needs in service encounter
situations. It is also derived that customers can be the source of their own
dissatisfaction through inappropriate behaviour or being unreasonably demanding.
Mohr and Bitner (1995) in their empirical study “The Role of Employee Effort in
Satisfaction with Service Transactions” examined how one aspect of service
encounter i.e. perceived employee effort affects customer satisfaction with service
transactions. The results of the study indicated that perceived effort has a strong
positive impact on transaction satisfaction, and this effect is not eliminated when the
perceived success of the service outcome is statistically controlled. They also
concluded that effort is perceived by consumers through a variety of behavioural and
attitudinal cues. The study results suggest implications for motivation, attribution, and
customer satisfaction theories, as well as for managing the service encounter.
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Price, Arnould and Tierney (1995) in the paper “Going to Extremes: Managing
Service Encounters and Assessing Provider Performance” provided a framework for
analysis and comparison of service encounters using three dimensions- duration,
affective content and spatial proximity. They also develop measures of service
provider performance and test a structural model of the relationships among service
provider performance, affective response and service satisfaction for EAI encounters.
The results supported that EAI encounters provider performance strongly influences
positive affect, and affect both negative and positive, in turn influences encounter
satisfaction. It is found that emotional fatigue, role stress, role conflict and the
problem of negotiating relationship boundaries pose important managerial challenges
for EAI services.
Bejou, Edvardsson and Rakowski (1996) in their empirical study “A Critical
Incident Approach to Examining the Effects of Service Failures on Customer
Relationships: The Case of Swedish and U.S. Airlines” analyze negative critical
incidents from the customers’ point of view and thus create a basis for crisis
management and quality improvement. The study describe and analyze negative
critical incidents from 320 customers and 80 airline employees in Sweden and 241
customers and 100 employees in the United States. The results indicate how important
it is to collect data about lapses in quality directly from the customer in order to gain
an understanding of quality defects and to develop quality in the right areas. It is
drawn from the study that the airline should train its staff in the techniques of
communication and how to relate to customers when critical incidents occur. The
study showed that the critical incident technique is a useful tool and that it provides
interesting and meaningful information about customers.
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Grove and Fisk (1997) conducted a study “The Impact of Other Customers on
Service Experiences : A Critical Incident Examination of ‘Getting Along” using the
critical incident technique, data were gathered from 486 customers regarding
satisfying or dissatisfying episodes with service organizations that were the result of
other customer’s presence. The findings of this study are (a) Extended waits that often
accompany many service encounters can put people in a bad mood, tempers can flare
and disruptive behavior can result, (b) apparently satisfying all customers with the
same service delivery is virtually impossible, (c) tendency of people to be less
inhibited when they are “out-of-town” or among strangers has long been observed, (d)
methods for improving customer-to-customer relationships are apparently needed.
The study suggested that before means of enhancing customer-to-customer
relationships or controlling against negative incidents can occur, organizations need to
develop an appreciation for the importance of managing other customers.
Callan (1998) in the paper “The critical incident technique in hospitality research: an
illustration from the UK lodge sector” studied the strengths and weaknesses of the cri
tical incident technique to compare the criteria used in the grading of UK budget
hotel lodges with the needs of customers and the hotel managers’ view of customers’
perceived needs. As the study was concerned with the adequacy of the grading
scheme for lodges, the incidents were first subdivided into three major categories.
Under each of these categories, ten sub categories were developed. In turn, a number
of attributes were identified under each of the sub categories. This broader application
of CIT allows not only comparisons between sub categories, but also judgements to
be made about the relative importance of a range of tangible and intangible attributes.
It is suggested that CIT is an appropriate and useful technique for studying service
quality questions and assessing customers’ perceptions.
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Chell and Pittaway (1998) in their research paper “A study of entrepreneurship in
the restaurant and café industry: exploratory work using the critical incident technique
as a methodology” study the Critical Incident Technique as a methodology and show
the technique can be used to research development in the hospitality industry. This
technique has been used in the paper to analyse the behaviors associated with
entrepreneurship in the restaurant and café industry. The CIT has been shown to be a
versatile and useful tool for gathering primary data of a subjective nature from
participants. It can, through careful coding, reveal both quantifiable data, and
descriptions of a qualitative kind. In the study concluded that CIT is a powerful tool
which is theoretically sound, capable of facilitating considerable depth of analysis and
can help produce important insights into the nature of entrepreneurship in the
hospitality industry.
Smith, Bolton and Wagner (1999) executed the research in the context of two
different service settings, restaurants and hotels in their study “A Model of Customer
Satisfaction with Service Encounters Involving Failure and Recovery” They
developed a model of customer satisfaction with service failure/recovery encounters
based on an exchange framework that integrates concepts from both the consumer
satisfaction and social justice literature, using principles of resource exchange, mental
accounting and prospect theory. The results show that customers prefer to receive
recovery resources that ‘match’ the type of failure they experience in ‘amounts’ that
are commensurate with the magnitude of the failure that occurs. The study also
provided organizations with guidelines for developing service recovery procedures
that improve customer service and enhance customer relationships. These guidelines
can be used to implement service delivery systems that include provisions for
appropriate recovery efforts, allocate recovery resources to maximize returns in terms
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of satisfaction, and train employees to recognize failures and reduce their effects on
customers.
Bitner, Brown and Meuter (2000) in their research paper “Technology Infusion in
Service Encounters” examined the ability of technology to effectively-customize
service offerings, recover from service failure, and spontaneously delight customers.
The infusion of technology is examined as an enabler of both employees and
customers in efforts to achieve these three goals. The challenges of successfully
incorporating technology must be recognized. Firms that consider the implementation
of technology should closely involve customers in the design process. Satisfying
specific customers’ needs and creating an open dialogue to address concerns are
important ways of overcoming some of the negative repercussions of technology
infusion. They suggested that management must carefully address the impact of
technology on encounter costs and customer satisfaction and loyalty. In moving
toward enabling technology use in service encounters, it is important to retain the
traditional low-tech, high-touch approach as a viable option for customers.
Meuter, Ostron, Roundtre and Bitner (2000) described in their study “Self-Service
Technologies: Understanding Customer Satisfaction with Technology –Based Service
Encounters” the CIT involving self-service technologies (SSTs) solicited from
customers through a web-based survey. The incidents are categorized to discern the
sources of satisfaction and dissatisfaction with SSTs. They categorized the incidents
into seven groups (solved intensified need, better than the alternative, did its job,
technology failure, process failure, poor design and customer driven failure) to
discern the sources of satisfaction and dissatisfaction with SSTs. By including a series
of quantitative measures to elicit additional information related to the incident, the
study linked the qualitative categories to other consumer evaluations and behaviors. In
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the study, the researchers related the critical incident categories with customer
attributions, complaining behavior, word of mouth and repeat purchase intentions.
They also studied the sources of customer satisfaction with SST encounters similar to
or different from the sources of customer satisfaction and dissatisfaction with
interpersonal encounters.
Dolen, Lemmink, Mattsson and Rhoen, (2001) in their research paper “Affective
consumer responses in service encounters: The emotional content in narratives of
critical incidents” explores the effect of emotion on satisfaction with after sales
services. It is concluded that critical incidents evoke emotional responses in a
customer. The emotional content is classified according to three levels of
inclusiveness: the super ordinate, the basic and the subordinate level. It is found that
the subordinate level is responsible for explaining most of the service satisfaction.
Positive emotions like positive surprise, pleasure and contentment contribute
positively to satisfaction, while negative emotions, such as irritation and
disappointment have a negative influence. Also, more intense emotions have a greater
impact on customer satisfaction than less intense emotions. By analyzing and
classifying content from respondents’ written answers to the critical incident question,
seem to be a valid way to isolate the particular emotions that cause customers to
distinguish satisfactory service encounters from less satisfactory ones. It is suggested
that training, motivating and rewarding service employees to evoke positive emotions
in the customers raise the potential for imposing a significant positive impact on the
overall customer satisfaction.
Friman, Edvardsson, Garling (2001) in their study “Frequency of negative critical
incidents and satisfaction with public transport services I” investigated whether
cumulative overall and attribute-specific satisfaction with public transport services are
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related to the remembered frequency of negative critical incidents. A model of these
relationships was proposed and estimated for survey data obtained from public
transport users. In this model overall cumulative satisfaction is positively related to
attribute-specific cumulative satisfaction which in turn is negatively related to the
remembered frequency of negative critical incidents. In addition, measurement
models indicated that both attribute-specific satisfaction and the frequency of negative
critical incidents are related to treatment by employee, reliability of service, simplicity
of information and design.
Kivela and Chu (2001) in their empirical study “Delivering Quality Service:
Diagnosing Favorable and Unfavorable Service Encounters in Restaurants” found
linkages between customer feedback and employee performance and the possible
integration of feedback into the overall management of service delivery in restaurants.
By using CIT 1294 favorable and unfavorable responses were collected from the
customers of restaurants. The results of this study concur with and confirm Bitner
et al’s 1990 findings and suggest that classifications and sub classifications are
more critical contributory factors of favorable and unfavorable service
encounters in restaurants. It is suggested that the CIT has the potential to provide
appropriate qualitative data as a foundation for restaurants’ service quality assurance
strategies to their customers. The findings of this study is that service encounters in
restaurants appeared to moderate the relationship between employees and customers
as well as customers’ overall dining experiences. This study also suggested that the
quality of customer-service provider encounters might have a greater impact on how
customers feel about restaurants than the quality of food and the ambience.
Ofir and Simonson (2001) in their experimental study “In Search of Negative
Customer Feedback: The Effect of Expecting to Evaluate on Satisfaction Evaluations”
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demonstrated that expecting to evaluate leads to less favorable quality and satisfaction
evaluations and reduces customers’ willingness to purchase and recommend the
evaluated services. Systematic bias can be possible through three ways referred as
negativity enhancement, role expectation, and vigilant processing. The findings of the
study are most consistent with the negativity enhancement account indicating that
unless buyers begin the evaluation task with low expectations, they tend to focus
during consumption primarily on negative aspects of product /service quality.
Turley and Hoffman (2001) in their paper “The Role of the Environment in Self-
service Encounters” explores a type of encounter that occurs between customers and
inanimate service environment. Also find strategic differences that differentiate
environmentally-based service encounters from those that are primarily based on
interactions between providers and customers. The level of technology needed for
delivering self-service need not be extremely high, low level technology is used in
some cases.
Dolen, Lemmink, Ruyter and Jong (2002) in their research paper “Customer-sales
employee encounters: a dyadic perspective” found that the perceptions of employee
performance and satisfaction do not only reflect the unique interaction between the
customer and the employee, but also relatively stable characteristics of the employee.
It is the unique experience of the customer and the employee during the interaction
that is important in creating satisfaction for both parties. It is suggested that hiring and
training policies for employees focusing on task and social competence profiles could
be valuable for the sake of customer and employee satisfaction, contributing thereby
to sales and employee success.
Hoffman and Turley (2002) examined in their study “Atmospherics, service
encounters and consumer decision-making: An integrative perspective” the impact of
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the environment on the consumer’s service experience and the potential role of
atmospherics throughout the service consumer decision process. It is found that
creating an atmosphere that enhances the delivery of a product can have a tremendous
effect on how consumers perceive that product. Managers should review the
atmosphere in which these encounters occur to make sure that information sought out
during the prepurchase stage is present, that the atmosphere supports and encourages
consumers to interact with service personnel during the consumption stage, and that
the environment will contribute to meeting consumer expectations and leading to
satisfaction.
Aksoy, Atilgan and Akinci (2003) found in their paper “Airline services marketing
by domestic and foreign firms: difference from the customers’ view point” that
significant differences exist between the foreign and domestic airline passenger
groups on the same flight destinations with respect to their demographic profiles,
behavioral characteristics, and understanding of airline service dimensions. They also
suggested that a firm’s competitive advantage is established by its ability to satisfy
customers’ present and future needs. The primary purpose of this paper is to look at
the profiles and service expectations of airline customers of domestic and foreign
carriers, and to provide valuable clues to improve services.
Hoffman, Kelly, and Chung (2003) in their research paper “A CIT investigation of
servicescape failures and associated recovery strategies” investigated service failures
relating to problems with the management of the servicescape with the help of CIT.
Of the 1370 failure critical incidents collected, 123 were identified as servicescape
failures. The three primary types of servicescape failure identified are - cleanliness
issues, mechanical problems and facility design issues. The study also identifies eight
servicescape sub failure type categories and discusses failure ratings, recovery
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strategies, recovery ratings and customer retention rates. They suggested that the
design of facilities is important; their impact on customers is only as good as how
well these facilities are maintained over time.
Chung-Herrera, Goldschmidt and Hoffman (2004) examined perceptual
similarities and differences between customers and employees in terms of critical
service incidents in the research paper “Customer and employee views of critical
service incidents”. The Critical Incident Technique was used to collect 1512
customer-reported incidents and 390 employee-reported incidents. Each critical
incident through a deductive sorting process systematically categorized into three
major failure groups developed by Bitner et al (1990). The results showed that
overall customers and employees were fairly similar in their perceptions regarding
failures that ultimately resulted in a good recovery effort. They concluded that
employee perceptions tended to be more aligned with customer perceptions when the
overall outcome was good. Conversely, employees tended to diverge from customer
views when the overall outcome was poor. During the service encounter, it is
important that employees have a better understanding of exactly how customers
perceive failure events.
Friman (2004) in the paper “The structure of affective reactions to critical incidents”
examines affective reactions to positive and negative scenarios describing critical
incidents in public transport and their impact on satisfaction. It is concluded that
satisfaction depended on the nature and type of the critical incidents. The mood
people experience when using public transport services may be influenced by
critical incidents, as the difference between positive critical incident, negative
critical incident and neutral incidents gives witness to. Also, unpleasantness -
pleasantness rather than deactivation – activation appeared to determine satisfaction.
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The results of the study indicated that respondents rated satisfaction lower after
having encountered a negative critical incident and higher after having encountered a
positive critical incident.
Poon, Hui and Au (2004) in their study “Attributions on dissatisfying service
encounters : A cross-cultural comparison between Canadian and PRC consumers”
explores the variations in the stage of economic development and the cultural
dimension of long-term versus short-term orientation affect consumers’ perceived
level of control in and attributions of dissatisfying service encounters, and the relative
effects of various attribution dimensions (including locus, controllable-by-
organization, and stability) on consumers’ switching intentions. The results indicated
that compared to PRC consumers, Canadian consumers experience more deprivation
of control in dissatisfying service encounters and exhibit stronger self-serving biases
in forming attributions about their dissatisfying service experiences. Also, the
controllable-by-organization dimension is found to have a stronger effect on the
switching intentions of Canadian consumers than that of PRC consumers, while the
opposite is found for the stability dimension. The results suggested that switching
intentions are affected by the three casual attributions (locus, controllable-by-
organization, stability). The service companies or employees should understand that
service failure is inevitable and it is important to carry out appropriate service
recovery (such as apology, explanation and offer to compensate) so as to alleviate the
negative effect of the casual attributions on post consumption behavioral intentions.
Petrick, Tonner and Quinn (2006) in their study “The Utilization of Critical
Incident Technique to Examine Cruise Passengers’ Repurchase Intentions” use CIT to
identify both positive and negative incidents and examine the differences among the
established CIT categories (both positive and negative) and their overall satisfaction,
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perceived value, WOM and repurchase intentions. The results of the CIT analysis
revealed eight themes related to moments of truth that are positively related to cruise
passengers’ cruise experiences and ten themes related to negative cruise experiences.
These identified themes can be used by cruise management to examine areas in which
critical incidents are assisting and/or hindering their interactive marketing efforts.
Results imply that analyzing critical incidents can be an effective management tool
for cruise line management and that these “moments of truth” are relevant to visitor
retention. Also, found that negative incidents have a much greater effect on cruise
passengers’ post hoc cruise evaluations than positive incidents.
Holloway and Beatty (2008) in their study “Satisfiers and Dissatisfiers in the Online
Environment A Critical Incident Assessment” examines the factors driving customer
dis (satisfaction) in the online service environment using critical incident technique
and content analysis. They identify the critical drivers reported by consumers to
produce particularly satisfactory or dissatisfactory online service encounters in three
industry groups (hard goods, soft goods and services). The results found how
satisfiers and dissatisfiers vary both overall and across industry classifications,
providing an assessment of the differences between the factors producing online
success versus those preventing failure.
Lundberg (2011) in the research paper “Critical Service Encounters in Hotel
Restaurants: The Personnel’s Perspective” explores the frontline hotel restaurant
workers’ experiences of satisfactory and dissatisfactory face to face critical service
encounters. A critical incident technique was employed to collect experiences of
critical service encounters together with projective techniques. The findings of the
study showed that a large proportion of the dissatisfactory incidents are related to
problematic customer behaviour.
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3.2 SERVICE FAILURE AND SERVICE RECOVERY
Service failures, recovery strategies and their effect on customer have attracted a lot
of attention from researchers. Various research studies have been conducted on
various issues related to this area of service marketing. A brief account of the
researchers carried out in the area has been discussed.
Singh (1988) in the study “Consumer Complaint Intentions and Behavior:
Definitional and Taxonomical Issues” assesses the validity of the three current
operationalizations and taxonomies of consumer complaint behavior (CCB) using
intentions data from four different and independent CCB situations. The findings
indicate that the currently available taxonomies and operational definitions cannot be
accepted as satisfactory representations of observed CCB responses. It is showed that
CCB is a three-faceted phenomenon consisting of voice, third party and private
actions; are distinct, have discriminant validity and warrant additional research
attention. The findings suggest that researchers may find it advantageous to
operationalize the CCB construct at the level of its individual dimensions.
Hart, Heskett and Sasser (1990) explained in their article “The Profitable Art of
Service Recovery” that service recovery is a significant management philosophy, one
that embraces customer satisfaction as a primary goal of business. Service companies
shift the emphasis from the cost of pleasing a customer to the value of doing so and it
entrusts front line employees with using their judgment. In the article it is emphasized
that a good service recovery can turn angry, frustrated customers into loyal ones and it
can create more goodwill than if things had gone smoothly in the first place. They
suggested that companies that want to build the capability of recovering from service
problems should do these things: measure the costs of effective service recovery,
break customer silence and listen closely for complaints, anticipate needs for
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recovery, act fast, train employees, empower the front line and close the customer
feedback loop.
Bitner (1992) in the paper “Servicescape: The Impact of Physical Surroundings on
Customers and Employees” provide a theoretical framework that describes how the
built environment (i.e. the manmade, physical surroundings) or what is referred to as
the servicescape affects both consumers and employees in service organizations. The
overall conclusion is that through careful and creative management of the
servicescape, firms may be able to contribute to the achievement of both external
marketing goals and internal organizational goals. Decisions about the physical
facility can have an impact on human resource goals (e.g. worker retention, worker
productivity), operations goals (e.g. efficiency, cost reduction) and marketing goals
(e.g. consumer attraction, consumer satisfaction). The typology of service
organizations combined with the theoretical framework suggests that the physical
environment assume a variety of strategic roles in services marketing and
management.
Kelly, Hoffman and Davis (1993) in their research work “A Typology of Retail
Failures and Recoveries” provides an initial investigation of the failures and
subsequent recoveries experienced by retail customers using the CIT methodology.
The work of Bitner and her colleagues (Bitner, Booms, Tetreault, 1990; Gremler
and Bitner, 1992) served as a starting point for the content analysis of the critical
incidents collected for this research. They identified nine categories of service
failures in group1- employee response in service delivery system failures, two
categories of service failures in group2- employee response to customer needs and
requests and four categories of service failures in group 3- unprompted and
unsolicited employee actions. Total fifteen types of retail failures and twelve types
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of recovery strategies were identified in this study. The study demonstrates the
importance of recovery in the retail industry whenever a retail customer experiences a
failure.
Kelly and Davis (1994) proposed model in the paper “Antecedents to Customer
Expectations for Service Recovery” in which customer perceptions of service quality ,
customer satisfaction and customer organizational commitment function as
antecedents to service recovery expectations. The proposed model was tested with
covariance structure analysis. The results of the study indicated that perceived service
quality and customer satisfaction are directly related to customer organizational
commitment. Committed customers are also likely to hold elevated expectations for
recovery. The results suggested that service quality and customer organizational
commitment have direct effects on customer service recovery expectations and that
customer satisfaction has an indirect effect on service recovery expectations.
Taylor (1994) in the paper “Waiting for Service: The Relationship Between Delays
and Evaluations of Service” concluded that delays can affect service evaluations in a
negative fashion. An empirical test of the model with delayed airline passengers
reveals that delays do affect service evaluations; however this impact is mediated
negative affective reactions to the delay. Service providers should attempt to either
shorten or eliminate delays for service (by operations management), or change the
consumer’s wait service (by perceptions management) so that it results in less
uncertainty and anger. The affective reactions of anger and uncertainty play a key role
in mediating the delay’s effects on service evaluations.
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Blodgett, Wakefield and Barnes (1995) conducted a study “The effects of customer
service on consumer complaining behavior” to determine why some dissatisfied
consumers seek redress while others do not approach the seller with their complaint.
The study also presents a dynamic model of the complaining behavior process. The
results indicated that the pay-off gained from retaining a dissatisfied customer is many
times greater than the cost of remedying the complaint. It is also implied that
dissatisfied customers expect not only to receive a fair settlement but, more
importantly, they also to be expect treated with courtesy and respect. It is suggested
that retailers and other service providers can view the complaining behavior process
as an opportunity to solidify and strengthen their relationships with their customers.
Sellers can implement complaint-handling policies and procedures that are designed
to maximize customer satisfaction and can train their employees to implement these
policies and procedures effectively.
Hoffman, Kelly and Rotalsky (1995) in their research article “Tracking service
failures and employee recovery efforts” identify and classify failures with in the
restaurant industry, assess customer perceptions regarding the magnitude of each
failure, identify and classify recovery strategies utilized by restaurants to correct
failures, assess customer perceptions of the effectiveness of each recovery strategy
and assess subsequent patronage behaviors. The CIT is applied to describe a
typology of service failures and recoveries and three main categories previously
identified by Bitner et al (1990) was used to classify the service failures. The
results of the study suggest the importance of employee training as these failures were
difficult to effectively recover. Also, suggest service managers to effectively design
their service delivery systems and procedures.
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Spreng, Harrell and Mackoy (1995) in their paper “Service Recovery: impact on
satisfaction and intentions” using data from 410 customers who reported damage
following a move of their household goods examined the relative importance of
service recovery activities in determining overall satisfaction and consequent
behavioral intentions. The results indicate that the service recovery process variables
have a relatively greater effect on overall satisfaction and behavioral intentions than
does the customer’s satisfaction with original service outcomes. It is suggested that
the companies should develop an excellent service recovery program then companies
should actively encourage complaining behavior and it should reevaluate their relative
budget allocations to these two activities. Also provides evidence of the importance of
service recovery in producing satisfied customers who intend to use the firm’s
services in the future and would provide positive word of mouth.
Brown, Cowles and Tuten (1996) in their study “Service recovery: its value and
limitations as a retail strategy” examines the impact of service recovery as a
relationship tool; in addition to its well accepted role as a means to enhance customer
satisfaction at the transaction-specific level. A comparison of the concept of service
consistency and reliability with the concept of service recovery leads to a statement of
hypothesis tested in an experimental setting. The implications of service recovery as a
means to create and retain satisfied customers as well as its potential role in the
continual improvement of a service delivery system by providing employees both the
resources and the authority to recovery and inspiring them to participate in the process
of continual improvement.
Boshoff and Leong (1998) in their study “Empowerment, attribution and apologizing
as dimensions of service recovery – An experimental study” addresses the question of
relative importance of service recovery dimensions from a customer’s point-of-view
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by considering three dimensions- taking ownership of the problem; apologizing for
the inconvenience and empowering employees to solve customer complaints- that
could influence customer satisfaction. It is implied from the results that once a service
failure has occurred, customers expect the service firm to accept responsibility for the
problem; they prefer to deal with staff that are fully empowered to solve their problem
relatively quickly. An apology in person or, alternatively, by telephone is preferable.
Hocut and Stone (1998) in their experimental study “The Impact of Employee
Empowerment on the Quality of a Service Recovery Effort” investigate the effects of
frontline employee empowerment in a service recovery situation. The study1 showed
that giving employees’ autonomy to handle a service recovery situation would
significantly enhance their levels of satisfaction on the job. Additionally, providing
training in how to handle service recovery problems further improved employee
satisfaction. In study 2, an interaction effect was found between empathy/courtesy and
responsiveness. The effect revealed that satisfaction was maximized when high levels
of both empathy/courtesy and responsiveness occurred. It is indicated that employee
empowerment components (autonomy and training) influence employee job facet
satisfaction which in turn influences the perceived fairness of the service recovery
effort, thus leading to higher customer satisfaction. The study suggested that a service
recovery policy to empower frontline employees to “do whatever it takes to satisfy a
customer” must be combined with training on a set of guidelines to help employees
determine what would be reasonable to do under different service failure situations.
Tax and Brown (1998) in their article “Recovering and Learning from Service
Failure” used a survey designed to assess customers’ evaluations of their most recent
service complaint. More than 30 different types of services were the subjects of
respondent complaints, the most frequently identified were restaurants, automobile
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repair, banks, doctors and dentists, airlines, hotels and motels. The results of the
research shows that the majority of customers are dissatisfied with the way companies
resolve there complaints and there are vast majority of customers who do not take
advantage of the learning opportunities afforded by service failures. To guide
managers in designing an effective strategy, the researchers provide a four-stage
approach to service recovery- identifying service failures, resolving customer
problems, communicating and classifying service failures and integrating data and
improving overall service. The results of the study indicates that the successful
service recovery strategy has a strong effect on customer loyalty, employee
satisfaction and, ultimately, firm performance and profitability.
Webster and Sundaram (1998) in their research work “Service Consumption
Criticality in Failure Recovery” examined the effects of various service failure
recovery efforts – an apology, different levels of monetary compensations and an
offer to reperform the service- on customer satisfaction and loyalty across varying
levels of criticality for different service industries. An experimental design was used
to determine the effects of level of criticality, type of recovery effort and type of
service on customer satisfaction and loyalty. The findings of this study indicate that
both type of service failure recovery effort and criticality of service consumption have
a significant effect on customers’ perceived level of satisfaction and extent of loyalty
toward the firm. Also, there is a negative relationship between perceived criticality of
service consumption and customers’ attitudes once service failure occurs. It is
suggested that when service firm managers are deciding how to recover once service
failure occurs, they should consider the level of criticality the customer places on
successful delivery of that particular service. It means a recovery effort strategy must
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be based on the specifics of the situation; a firm cannot assume that standardized
recovery measures will be appropriate across all service failure situations.
Boshoff (1999) conducted a study “Recovsat : An instrument to Measure Satisfaction
with Transaction-Specific Service Recovery” to identify the dimensions of
transaction-specific service recovery satisfaction by analyzing consumer expectations
and to develop a validated measuring instrument to measure satisfaction with
transaction-specific service recovery based on those dimensions. It led to the
conclusion that the use of RECOVSAT instrument to evaluate how effectively service
recovery is performed from a customer’s point of view but it will also permit an
investigation of the organizational antecedents of satisfactory service recovery. This
tool can be adapted to be used as a service recovery performance evaluation measure
of frontline staff.
Johnston and Fern (1999) in their exploratory study “Service Recovery Strategies
for Single and Double Deviation Scenarios” contribute to the growing body of
knowledge on service recovery by identifying effective recovery strategies from a
customer’s point of view. It was found that customers have clear expectations of
service recovery for different levels of failure. Furthermore, service recovery can
restore the customer to a satisfied state or to a delighted state. Getting the customer
‘back to neutral’ appears to require one set of ingredients, where as an enhanced set is
required to delight the customer. The study also distinguishes between the actions
required in dealing with service failures (single deviation) and the situations where
there was an inappropriate or inadequate response to the failure (double deviation).
Mc Dougall and Levesque (1999) in their experimental study “Waiting for service:
the effectiveness of service recovery strategies” examined the effectiveness of service
recovery strategies in situations where the service firm made customers wait even
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though they had made a reservation. The recovery strategies –apology only,
assistance, compensation, assistance plus compensation- which reflected industry
practices, did not lead to positive future intentions towards the service firm. The
results of the study are customers held negative future intentions towards the service
provider regardless of the recovery strategy offered including assistance plus
compensation. Customers do not like pre-process, post-schedule waits. The best
strategy a service firm can pursue is to eliminate these waits, which they can do.
Levesque and Mc Dougall (2000) in their experimental study “Service Problems and
Recovery Strategies: An Experiment” examines the effectiveness of recovery
strategies after a service failure on customer complaint and complaint intentions. The
results of the study suggest that effectiveness of service recovery strategies (assistance
and/or compensation) varied depending on the type of service, problem severity, and
criticality levels. Also to improve the probability of retaining new customers, the firm
needs to reduce core failure rates. “Getting it right the first time” optimizes value for
both the customer and the firm.
Mack, Mueller, Crotts and Broderick (2000) examined in their study “Perceptions,
corrections and defections: implications for service recovery in the restaurant
industry” customer perceptions of their personal service failures experienced in the
restaurant industry. This study found customers to be very specific about, and
involved in, failures they experienced in the restaurant industry. Identifying failures
points in the service delivery process and identifying methods to prevent these failures
help to prevent negative customer perceptions. The effectiveness of simpler recovery
strategies such as discount, partial free food or replacement or a coupon as compared
to “overkill” recovery methods can be used in structuring appropriate recovery
strategies.
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Miller, Craighead and Karwan (2000) in their empirical research “Service
recovery: a framework and empirical investigation” provides a framework for
examining the service recovery process. In the service recovery framework, the
various elements include- outcome measures related to customer satisfaction and
retention, antecedents to successful/unsuccessful recovery, the phases of recovery,
types of recovery activities and the delivery of service recovery. The study used the
Critical Incident Technology for research methodology. It is concluded from
empirical analysis that (a) successful and unsuccessful service recoveries are
characterized by very different customer outcome measures, mixes of psychological
and tangible recovery efforts and attention to operational details, and (b) the factors
that seem to matter the most (fair restitution and value-added) are very much
operational in nature.
Lewis and Clacher (2001) in their study “Service failure and recovery in UK theme
parks: the employees’ perspective” focused on the perspective of customer contact-
employees on service failure and service recovery. It is concluded that formal
understanding of service failure and recovery varied amongst the managers, but all
referred to exceptional communication and “people” skills, and they had a desire to
investigate service failures and recovery and take positive actions in the parks.
Critical incident technique was used to describe service failures and subsequent
service recoveries, both satisfactory and dissatisfactory, which were categorized in
relation to employee response to service delivery system failures, employee response
to customer needs and requests, unprompted employee actions and problem
customers. The critical incidents that were collected were subjected to the method
of sorting and analysis developed by Bitner et al (1990). It is suggested the
applicability of the critical incident method to identify service failures and associated
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recovery strategies in other service industries that involve substantive customer-
employee interaction and subjective judgement.
Lewis and Spyrakopoulos (2001) in their empirical study “Service failures and
recovery in retail banking: the customers’ perspective” assess the significance of
service failures and recovery strategies in financial services from the customers’ point
of view. The researchers identified various types of service failure and recovery
strategies with the help of critical incident technique. These were investigated further
through a survey questionnaire, to discover customer perceptions of the importance of
particular failures and the effectiveness of the service recovery strategies. The results
of the study indicated that service failures were found to be of varying importance and
different service recovery strategies more effective for particular failures. Further,
customers with long relationships with their banks were more demanding with respect
to service recovery.
Maxham III (2001) in the research paper “Service recovery‘s influence on customer
satisfaction, positive word-of –mouth, and purchase intentions” examined the effects
of service recovery on key purchase perception variables in both experimental and
field study analyses. The results of the study suggest that effective service recoveries
can enhance consumer perceptions of satisfaction, purchase intent and positive word
of mouth. Also there is not a significant difference in satisfaction and purchase intent
between groups receiving high and moderate service recoveries. The results do not
support a recovery paradox, where by post recovery satisfaction is greater that that
satisfaction prior to the service failure. It is suggested that poor service recovery
efforts may influence consumers to discontinue service with such organizations and it
may also increase a firm’s sales and administration costs associated with recruiting
new customers.
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Matillaa (2001) in the study “The effectiveness in service recovery in a multi-industry
setting” examined how two situational factors, the service type and magnitude of
failure, moderate customer responses to service failures. A 3(service type) X
2(compensation) X 2(magnitude of failure) between subjects design was used to test
the hypothesis. Subjects were exposed to a written scenario describing a service
failure with in the context of one of three service types (restaurant, hair stylist or dry-
cleaning). The findings indicated that the relative importance of the fairness
dimensions in driving service recovery satisfaction might depend on the type of
service or the failure context. It is suggested that service managers should tailor their
recovery efforts to match the customer’s perceptions of the seriousness of failure.
Customer perceptions of the magnitude of failure should then guide employee actions
in resolving the problem to the customer’s satisfaction.
Mattilab (2001) in the experimental study “The Impact of Relationship Type on
Customer Loyalty in a Context of Service Failures” examines the impact of
relationship type (true service relationship, pseudorelationship, and service encounter)
on customers’ behavioral intentions in a context of service failures. It is concluded
that customers might feel equally dissatisfied about poorly handled service recovery
regardless of the relationship type, yet their behavioral intentions might differ
depending on the closeness of the customer-provider bond. The results from the two
experiments suggest that building and maintaining close relationships with customers
are critical in case of a failed service recovery.
Michel (2001) in his research study “Analyzing service failures and recoveries: a
process approach” suggested a process approach by which not only dissatisfied or
complaining customers are surveyed but due attention is paid to a representative
sample of both satisfied and dissatisfied customers. A service blueprint approach was
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used to track the path of the customer’s service experience before asked for specific
negative incidents. A large proportion of the failure incidents reported by the
respondents did not meet the restrictive criteria of ‘critical incidents’ suggested
by Bitner et al (1990). However, the reported failure incidents were critical regarding
their impact on satisfaction, an open coding procedure was applied. He found that
process-by-process analysis reveals specific service problems and therefore helps
to manage service recoveries accordingly. An analysis of the effect of good
recoveries resulted in the recovery paradox being found in all but one process type. It
is suggested that service recovery not only involves the costs of redressing failures but
is also a powerful tool for increasing customer satisfaction.
Maxhama III and Netemeyer (2002) examined in their study “A Longitudinal Study
of Complaining Customers’ Evaluations of Multiple Service Failures and Recovery
Efforts” complaining customers’ perceptions of two service failures and recovery
efforts. The findings indicate customers reporting an unsatisfactory recovery followed
by a satisfactory recovery reported significantly higher ratings at the second post
recovery period than did customers reporting the opposite recovery sequence. The
outcome of the second recovery also demonstrated a significant influence on customer
ratings (positively if the recovery was satisfactory, negatively if the recovery was
unsatisfactory), regardless of whether the customer found the first recovery
satisfactory or unsatisfactory.
De Witt and Brady (2003) in their empirical study “Rethinking Service Recovery
Strategies-The Effect of Rapport on Consumer Responses to Service Failure”
examines the recovery benefits of fostering rapport between the service provider and
customer by conducting four independent studies test. The first study employed a
scenario based experimental design and a student sample. The second study was
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intended to assess the external validity of the Study1. The third and fourth studies
were designed to further explore some of the results found in studies 1 and 2. The
third study was intended to uncover strategies that can be used to encourage
complaint behavior under conditions of high rapport, where as the fourth study tested
whether the strategies uncovered in study 3 were viable. The findings indicate that in
addition to enhancing perceptions of service quality and customer satisfaction, rapport
can have a positive effect on the negative outcomes often associated with service
failures. For managers focused on rapport, the findings indicate that in addition to
enhancing perceptions of service quality and customer satisfaction, rapport can have a
positive effect on the negative outcomes often associated with service failures. Also,
the results suggest that consumers who have developed rapport with the service
provider are less likely to complain because they are empathic toward the situations
these individuals work under and are unwilling to possibly damage their relationship
by complaining.
Hessa Jr., Ganesan and Klein (2003) in their empirical study “Service Failure and
Recovery: The Impact of Relationship Factors on Customer Satisfaction” examined
how customer relationships either buffer or magnify the impact of service failures on
customer satisfaction. Also, how the quality of past service performance, number of
past encounters with the organization, and the customers’ expectations of relationship
continuity affect consumers’ responses to failures and recoveries. It is concluded that
customers with higher expectations of relationship continuity had lower service
recovery expectations after a service failure to a less stable cause. Both the lower
recovery expectations and the lower stability attributions were associated with greater
satisfaction with the service performance after the recovery. It is also showed that
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customer-organization relationships can help to shield a service organization from the
negative effects of failures on customer satisfaction.
Holloway and Beatty (2003) in their two research studies “Service Failure in Online
Retailing-A Recovery Opportunity” employing both qualitative and quantitative
methods with samples of online shoppers to provide an initial examination of the
service recovery management of online retailers. The results provide a typology of
online service failures and demonstrate a number of areas in which online retailers are
failing to effectively manage their service recoveries. The typology of service
failures share some consistency with Bitner et al’s classification but they mostly
differ due to the lack of human interaction, the influence of technology and other
factors unique to the online environment. It is concluded that the online retailers
are largely failing in their service recovery efforts. These ineffective service
recoveries are negatively affecting important consumer behaviors, particularly
retention.
Leal and Pereira (2003) in their empirical research “Service recovery at financial
institution” focusing the main aspects of the service recovery process after a
complaint has occurred. A specific methodology is proposed to analyse the failures
and corresponding complaints in service delivery, with the ultimate goal of
articulating internal and external measures of performance. The methodology
provides a better knowledge of the impact caused by operational factors (internal
measures) on customer perceptions (external measures), so that management
decisions can be objectively taken.
Lidén and Skålén (2003) in their research paper “The effect of service guarantees on
service recovery” focused on the risk-reducing effect of service guarantees and how
guarantees influence employee service recovery behavior. Critical incident data were
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collected using the critical incident interview technique with customers of hotels. It is
proved that the implicit guarantee may serve as a risk reducer, which contradicts and
adds to previous research because the previous research states that only the explicit
guarantee has these benefits. The results of the study suggested that service
guarantees can impact the behavior of front-line employees in the service recovery
process. Also it is indicated that the service guarantee may actually lower customer
satisfaction after an incident if the employee relies too heavily on the possibility of
compensating the customer with economic means.
Mueller, Palmer, Mack and Mc Mullan (2003) in their research paper “Service in
the restaurant industry: an American and Irish comparison of service failures and
recovery strategies” determine the most prevalent service failures and recovery
strategies used in each country. This study compares the effects of failure and
recovery strategies in the restaurant sector of two countries with very different dining
traditions- the United States and Ireland. Analysis of over 700 personal interviews
with restaurant customers shows that there is much commonality with regard to
service failures but significant differences in recovery efforts. This study also used
the same classification system of service failures as given by Bitner et al (1990)
and also used by Hoffman et al (1995). It is found that twice as many service
failures were attributed to service delivery system failures than in the studies of
Bitner et al and Hoffman et al (1995). In both countries, overcompensation methods
do not appear to influence customer repeat patronage intentions, nor do they have
significant influence on the rating of recovery effort. This study supported that simple
apologies are not enough, successful recovery strategies should be used in conjunction
with some sort of compensation- regardless of nationality and some recovery action is
much more likely to result in repeat business than no action.
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Warden, Liu, Huang and Lee (2003) extended in the Stauss and Mang model in
their study “Service failures away from home: benefits in intercultural service
encounters” by including the importance of recovery strategies, and the benefit gained
by any recovery attempt with in an intercultural service setting. A pretest, employing
the CIT, established descriptions of common service failures and recovery strategies
for the sample frame. A total of thirteen service failure incident categories and nine
categories of recovery strategies were found. They suggested to service providers that
often have contact with customers of foreign cultures need to build into their
corporate cultures not only an atmosphere of tolerance, but also a proactive behavior
towards solving service problems. When a service failure does occur, a positive
attempt at recovery will trigger a positive reaction from the consumer that has
increased benefit, surpassing intra-culture recoveries.
Craighead, Karwan and Miller (2004) in the paper “The Effects of Severity of
Failure and Customer Loyalty on Service Recovery Strategies” creates and analyzes
empirical types of service failures by using the hierarchical and non-hierarchical
cluster analysis and to gain some insight into how the failure types may require
differential treatment. The CIT was used to generate the service failures. The results
found the differences among the failures which fit together to form common
encounters and indeed the service recovery techniques varied in their effectiveness
relative to the failure types. The creation of meaningful failure types from pre-
encounter factors serves as another way to verify the importance of other studies
which have identified and studied the antecedents to service recovery but, more
importantly, offers a mechanism which then allows for a theory of “strategic fit” in
the determination of service recovery strategies.
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Cranage (2004) in the paper “Plan to do it right: and plan for recovery” presents
research results and implications in the literature for the last 15 years, and suggests
guidelines on how to make the best use of the information to develop strategies that
‘fit’ a service operation. There are numerous benefits of customer satisfaction, loyalty
and increased profits from developing strategies to prevent service failures and
strategies to successfully implement service recovery. The researcher suggested three
steps to prevent service failure are- talk to the customer; truly analyze the operation
and analyze the staff. All of this is to try to get it right the first time. If the service
failure still occurs then management should consider some pre-emptive strategies to
mitigate the negative effects of service failure.
Lewis and Mc Cann (2004) in their study “Service failure and recovery: evidence
from the hotel industry” focused on service failure and recovery in the hotel industry
in the UK. They assess the quality attributes which are important to guests when
staying in three-or-four- star hotels; the types and magnitude of service failures
experienced; the different recovery strategies used to satisfy the guests; and the
effectiveness of these strategies.
Magnini and Ford (2004) in their research paper “Service failure recovery in China”
found that in the hotel industry, exceptional service failure recovery is a key
determinant of customer satisfaction and loyalty; even across cultures. Excellent
recovery requires employees to decode emotional cues and to be empowered to offer
a customized recovery effort; these skills should be taught through service training.
Teaching these skills to Chinese hotel associates is different than teaching these skills
to associates in other countries. Service recovery training has been shown to be
effective and is a strategic necessity for guest retention and hotel profitability, but
western training programs do not take into consideration cultural differences and
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sensitivities. Hoteliers with properties in China must consider adapting their programs
to reflect Chinese cultural issues and requirements.
Mattila (2004) in the research paper “The impact of service failures on customer
loyalty: The moderating role of affective commitment” examined the moderating role
of affective commitment on post failure attitudes and loyalty intentions under two
service failure conditions: a successful and poor service recovery. The findings
indicate that emotionally – bonded customers might feel betrayed when a service
failure occurs, thus resulting in sharp decrease in post-recovery attitudes. The results
suggest that affective commitment might produce the spill-over effects of service
failures to future loyalty behaviours.
Robbins and Miller (2004) in the research paper “Considering Customer Loyalty In
Developing Service Recovery Strategies” analyze the potential for customer loyalty to
play an antecedent role in service recovery by interacting with perceptions of
unfairness to influence post-failure reactions. The Critical Incident Technique was
used to collect the data for this study. The respondents were asked about the two
service failure incidents; for the first failure they described a successful resolution and
for the second an unsuccessful resolution. They described the company, the service
failure, provided their evaluations of service recovery management and perceptions of
the fairness of interactions and outcomes for both incidents. Pre-failure variables (i.e.
customer loyalty) as well as post-failure reactions (e.g. loyalty, repatronage intentions
etc.) were also assessed. The results of the study suggested that both procedural and
distributive fairness in recovery had stronger influences on subsequent reactions of
customers with higher levels of loyalty prior to the service failure. It is found that the
effectiveness of service recovery had the strongest influence on loyal customers. It is
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also suggested that business strategies and training programs should stress the
importance of managing the fairness perceptions of loyal customers in particular.
Weber and Sparks (2004) in their study “Consumer attributions and behavioral
responses to service failures in strategic airline alliance settings” suggested that
potential problems for airlines in an alliance where their image can be negatively
affected by a service failure of a partner airline in terms of negative evaluations
leading to customer dissatisfaction, negative word-of-mouth and reduced loyalty. This
suggests that airlines involved in alliance structures need to take cognizance of the
service quality being offered by their partners. Interviews were used to determine
airline passengers’ attributions and behavior towards the various alliance entities
following a service failure and recovery.
Weun, Beatty and Jones, (2004) in their research paper “The impact of service
failure severity on service recovery evaluations and post-recovery relationships” focus
on customer reaction to a service organization’s service recovery efforts under
varying levels of service failure severity. The present paper investigated the main and
interactive effects of the severity of the service failure, along with perceptions of
interactive and distributive justice, on satisfaction with the service recovery with the
help of experimental design and stimuli. The results indicate that service failure
severity has a significant influence on satisfaction, trust, commitment and negative
word-of-mouth. In terms of interactional justice, the severity of the service failure did
not moderate the interactional justice/satisfaction relationship. In terms of the key
outcome relationship variables, the severity of the service failure moderated the
satisfaction/commitment relationship.
Bamford and Xystouri (2005) in their research paper “A case study of service failure
and recovery with in an international airline” concluded that service quality
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excellence can only be achieved through employee satisfaction, commitment and
loyalty as a result of senior management commitment, focus and drive. Also, found
that for service recovery to be effective, it must be external (to the customer) as well
as (to the organization) so that internal improvement can be ensured. Periodic review
of performances and reward schemes are considered of vital importance, to aid the co-
evolution of mutual understanding between managers and employees, and hence the
development of superior service quality.
Forbes, Kelly and Hoffman (2005) in their research paper “Typologies of e-
commerce retail failures and recovery strategies” applied CIT using 377 customer
responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-
commerce service firms. The present study took the guidance from the Bitner et al,
1990 (favorable and unfavorable service encounters) and Kelly et al, 1993 (retail
failures and recoveries) for analyzing and sorting the content of the critical
incidents. It is derived that major group 3, unprompted and unsolicited action
failures did not occur in the data collected may be because of the non-human
element of the service encounter. It is concluded that the analysis of failures and
recovery strategies is beneficial to organizations as it allows management to identify
the areas of improvement valued by customers. This information can in turn be used
to minimize future mistakes, and improve the recovery efforts of the organization
through improved technology, revised policies and employee training programs
focusing on these issues.
Reynolds and Harris (2005) in their study “When service failure is not service
failure: an exploration of the forms and motives of “illegitimate” customer
complaining” explore the service encounters where in customers knowingly, and
incorrectly report service failures and their motives behind it. The qualitative method
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i.e. critical incident technique was applied in the study. It was found that (a) coding
procedures revealed four distinct forms of customer complainants –one-off
complainants, opportunistic complainants, conditioned complainants and professional
complainants. (b) six main motives for articulating fraudulent complaints –
freeloaders, fraudulent returners, fault transferors, solitary ego gains, peer-induced
esteem seekers and disruptive gains. The results of the study suggested that managers
should enforce mechanisms wherein customer complaints are monitored and tracked
in a manner that assists in the identification and challenging of re-offending
fraudulent complainers.
Youjae and Lee (2005) in their empirical research work “An Empirical Study on the
Customer Responses to Service Recovery in the context of Service Failure” examined
how customers respond to various service recoveries by investigating the moderate
role of service failure severity. The results show that under the core service failure,
high recoveries are more effective than low recoveries, where as low recoveries are as
effective as high recoveries under the peripheral service failure. The effects were
assessed in terms of customers’ intentions such as repurchase intention and word-of-
mouth communication.
Harris, Grewal, Mohr and Bernhardt (2006) in their empirical study “Consumer
responses to service recovery strategies: The moderating role of online versus offline
environment” examine the affects of on/offline medium on customer satisfaction with
service failure recovery and post purchase intentions in two different service contexts.
The data were gathered using a scenario-based experiment, constructed the scenarios
to manipulate the service medium (online versus offline) and the remedy for the
service failure (high versus low level) across the two service industries i.e. airlines
and banks. The results indicated that recovery levels have positive effects on
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satisfaction and intentions in both online and offline settings and that the on-/offline
medium moderates the relationship between the recovery level and both satisfaction
and post purchase intentions. In low recovery situations, online customers are more
satisfied and have more positive intentions than do their offline counterparts. Airline
customers were more satisfied and had more positive post purchase intentions than
did bank customers. Also, in low recovery situations, airline customers were more
satisfied and more inclined towards repurchase and positive word-of-mouth behaviors
than were bank customers.
Gupta Anil (2006) explained in his article “Regaining Customer Confidence” about
different incidents of service delivery failures, how customers react to service failure,
and regaining customer share through service recovery and how service providing
firms can build customer-driven service recovery competencies. The researcher
emphasized if firms plan service recovery mechanism, it could lead to even higher
customer satisfaction levels and have a positive influence on customer commitment,
trust, word-of-mouth and repurchase intentions.
Patterson, Cowley and Prasongsukarn (2006) in their research article “Service
failure recovery: The moderating impact of individual-level cultural value orientation
on perceptions of justice” examined the influence of customers’ cultural value
orientation (i.e. cultural values measured at the individual level, not national level)
and service recovery processes on the perception of fairness (justice) and post
recovery satisfaction in a medium contact service. To test the hypothesis three single
factor experimental designs was used. The results reveal that cultural values of
individual power distance, uncertainity avoidance and collectivism do indeed interact
with a firm’s recovery tactics to influence perceptions of fairness (justice). Finally, all
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three forms of justice (distributive, procedural, interactional) impact on overall service
recovery satisfaction.
Gountas, Ewing and Gountas (2007) conducted a study “Testing airline passengers’
responses to flight attendants’ expressive displays: The effects of positive affect”
collected 1160 useable questionnaires from the national airline passengers. They
measure the influence of service providers’ positive expressive displays on life
satisfaction, overall consumption satisfaction and intention to purchase. The findings
indicate a strong positive relationship between and with in affective displays, overall
service satisfaction and life satisfaction. The results of the study found a strong
relationship between ‘sincere or authentic’ smiles and the perception of genuine care
for the consumer. There is no significant direct, relationship between life satisfaction
and service satisfaction.
Lin, Lin and Lin (2007) investigated in their study “The Relationship between
Service Failures, Service Recovery Strategies and Behavioral Intentions in Hotel
Industry” the impact of hotel guests’ sociodemographic characteristics and their
perceptions of service recovery strategies, in explaining behavioral intentions of hotel
guests in Orlando, Florida. The results of the study showed that three dimensions of
service failure-facilities, procedure, and provider’s behaviour- were significant
explanatory variables of behavioral intentions. Also all dimensions of service
recovery strategies- correction, exceptional treatment, explanation, apologies,
redirection, and compensation and did nothing- were significant explanatory variables
of behavioral intention.
Ringberg, Odekerken – Schroder, and Christensen (2007) in their paper “A
Cultural Models Approach to Service Recovery” empirically identify three embodied
cultural models – relational, oppositional and utilitarian –that consumers apply to
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goods or service failures. They suggested that the more successful the provider is at
creating a self – relevant connection between the service and the consumer,
paradoxically, the less flexibility and control the firm has in managing consumers
during failures.
Choi and Matilla (2008) in the research paper “Perceived controllability and service
expectations: Influences on customer reactions following service failure” examines
the impact of perceived controllability over service failures and service quality
expectations on customer reactions to those failures. The experimental design method
was used to test the hypothesis. The study’s findings show that customers’ perception
of a service firm’s controllability over a service failure influences their reaction after
the incident. Customers holding higher service expectations are more likely to be
more tolerant with the service failure and that their overall satisfaction, return intent
and positive word-of-mouth are significantly higher than their counterparts with low
expectations. The findings of the study implied that when a failure is outside a firm’s
control, it is crucial to let customers know what circumstances led to the failure;
letting the customer know that the firm has taken actions to prevent a failure can
mitigate the negative effects of poor service and to reduce the potential negative
impact of inevitable service failures on business outcomes, service firms need to
enhance customer expectations.
Luria, Gal and Yagil (2009) in their research article “Employees’ Willingness to
Report Service Complaints” conducted two qualitative and a quantitative study to
examine frontline workers’ discretion about reporting customer complaints. The
qualitative studies based on critical incident technique and interviews with service
providers and reveal that service providers practice much discretion in their decision
to report formal and informal complaints and also conceptualize willingness to report
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service complaints (WRC). The quantitative study examines a preliminary WRC scale
and shows that WRC levels are associated with measures of organizational citizenship
behaviour, service climate and empowerment.
Mc Collough (2009) in the paper “The Recovery Paradox: The effect of Recovery
Performance and Service Failure severity on post-recovery customer satisfaction”
investigates the recovery paradox, the proposition that superior recovery can leave the
customer as satisfied, if not more satisfied, than if nothing had gone wrong by
examining the impact of service failure severity and the recovery performance on
post-recovery satisfaction. The findings of the study showed that for a recovery
paradox to emerge the service failure severity must be very modest and the recovery
effort superior. The relative low level of harm caused by the failure and the relatively
high recovery performance necessary is surprising and indicates that the recovery
paradox may be rather limited phenomenon.
Mostert, Meyer and Rensburg (2009) in their study “The influence of service
failure and service recovery on airline passengers’ relationships with domestic
airlines: an exploratory study” investigates the effect of service failures and an
airline’s service recovery efforts on their customer relationships and future patronage
of the airline. A non-probability convenience sampling method was used to survey
passengers of domestic airlines in South Africa. A self-administered questionnaire
was randomly distributed by trained fieldworkers to passengers at the check-in
counters of the various domestic airlines at airport. The findings indicate that
customer satisfaction with an airline’s service recovery efforts significantly influences
their relationship with the airline as well as their future patronage of the airline.
Dissatisfied respondents indicated that their relationship with the airline was
weakened or broken and that they would fly less frequently or never again with the
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airline following the service failure. Satisfied respondents’ relationships with the
airline were unchanged or strengthened, and they flew with the airline all the time or
as frequently as before the service failure.
Malhotra and Malhotra (2011) attempts to study in their paper “Evaluating
Customer Information Breaches as Service Failures: An Event Study Approach”
associated breach reports with the decline in market value of firms using an event
study. Due to the greater potential of customer backlash, negative publicity and
liability risk, managers must view customer information breaches as service failures
rather than as information system failures. Employing established service failure
recovery strategies may allow firms to quickly and proactively address customer
privacy concerns and thereby mitigate negative market reaction to information
breaches.
3.2.1 PERCEIVED JUSTICE
Spreng and Mackoy (1996) in their exploratory study “An Empirical Examination of
a Model of Perceived Service Quality and Satisfaction” assess the distinction between
perceived service quality and satisfaction and examine the impact of different
standards of comparison. The results of the study indicated that service quality and
satisfaction, in a confirmatory factor analysis, are distinct and structural equations
modeling showed that they have different antecedents. They also noted that
expectations have a negative effect on satisfaction, through disconfirmation, but a
positive effect on both satisfaction and perceived service quality, through perceived
performance. A key determinant of both satisfaction and service quality is meeting
customers’ desires.
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Blodgett, Hill and Tax (1997) in their experimental study “The Effects of
Distributive, Procedural, and Interactional Justice on Post complaint Behavior”
examined the effects of distributive, interactional and procedural justice on
complainants’ subsequent repatronage and negative word of mouth intentions. The
results indicated that complainants who experience higher levels of distributive and
interactional justice are more likely to repatronize the retailer and are less likely to
engage in negative word-of-mouth behavior (and vice-versa). On the other hand,
procedural justice or timeliness had no effect on subjects’ repatronage intentions
or on their negative word-of-mouth intentions. Also, the higher levels of
interactional justice can compensate for lower levels of distributive justice. The
findings of the study points to the importance of training retail employees how to
respond to customer complaints and retailers that focus on interactional issues will
have the greatest chances of building long-term relationships with their customers.
Maxhamb III and Netemeyer (2002) in their paper “Modeling customer perceptions
of complaint handling overtime: the effects of perceived justice on satisfaction and
intent” suggested that procedural and interactional justice are more influential in
forming overall firm satisfaction than distributive justice. Retailers offering refunds
and discounts (i.e. distributive justice) following product or service failures can likely
increase satisfaction with recoveries and indirectly affect WOM intent. Also, retailers
offering procedural and interactional justice following failures may increase overall
firm satisfaction and indirectly affect purchase intent. It is also suggested that
distributive justice is more pronounced in forming satisfaction with recovery
perceptions among durable good complainants than service complainants, and
interactional justice is more influential in forming satisfaction with recovery
perceptions among service complainants than durable good complainants.
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Mc Coll-Kennedy and Sparks (2003) in their study “Application of Fairness Theory
to Service Failures and Service Recovery” to understand customer responses to
service failures and recovery presented a theoretical framework for studying and
managing service recovery and provided demonstrated support for the conceptual
framework through the results of the five focus groups. It is concluded that service
failures can be triggered by events from a range of sources, including the following
four major areas: (a) problems with the service itself, (b) problems associated with the
service provider, (c) problems outside the service provider’s control, and (d) problems
related to the customer. Also it is clear from the focus groups that when customers
experience a negative event (service failure), they commence an assessment of the
situation, making attributions as to whether the service provider could (in terms of
conduct) and should (in terms of moral principles) have done something more to
remedy the situation. The key managerial implication is that to manage service failure
situations, service organizations need to have knowledge of the range of solutions that
(a) possible, (b) practical, (c) fair, and (d) understood by customers to be all three of
these things.
Maxham III and Netemeyer (2003) in the research paper “Firms Reap What They
Sow: The Effects of Shared Values and Perceived Organizational Justice on
Customers’ Evaluations of Complaint Handling” examined how employees’
perceptions of shared values and organizational justice can stimulate customer-
directed extra-role behaviors when handling complaints and also investigated how
these extra-role behaviors affect customers’ perceptions of justice, satisfaction, word
of mouth and purchase intent. The results of the study are- customer-directed extra-
role behaviors had strong effects on customers’ perceptions of interactional
justice, procedural justice and distributive justice, customer ratings of
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distributive justice affected all outcome variables (i.e. satisfaction with recovery,
overall firm satisfaction, purchase intent and word of mouth), procedural justice
affected satisfaction with recovery, overall firm satisfaction and word of mouth
and interactional justice affected overall firm satisfaction and purchase intent.
Extra-role behaviors affected all dimensions of customer justice which shows that
extra-role behaviors indirectly and significantly affect customer outcomes.
Yim, Gu, Chan, and Tse (2003) in their empirical study “Justice-Based Service
Recovery Expectations: Measurement and Antecedents” examine the measurement
properties of an equity-based expectancy-disconfirmation framework in service
recovery evaluation and to test hypothesis regarding potential antecedents to
consumer normative recovery expectations. The results showed that customers form
justice-based normative recovery expectations and use them as reference standards in
evaluating recovery performance of the service provider. Also, recovery
expectations of distributive justice are more strongly related to the recovery
disconfirmation judgment than that of procedural/interactional justice. All three
tested antecedents-magnitude of service failure, switching cost, and length of the
customer-organization relationship- are found to have either a direct or an interactive
effect on expectations of distributive justice and procedural/interactional justice. The
results of the study confirm the important role of normative equity-based expectations
in service recovery evaluation. To institute effective programs of service recovery,
managers need to know what customers expect in order to be satisfied. They should
strive to offer high recovery performance that meets or exceeds customer
expectations.
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Mattila and Patterson (2004) in their experimental study “Service Recovery and
Fairness Perceptions in Collectivist and Individualistic Contexts” contrasts the impact
of two recovery attributes (compensation and exceptional) on customers’ post
recovery perceptions in a cross-cultural context (East-Asia versus United States).
They suggested that offering compensation is particularly effective in restoring the
sense of justice among American consumers. Offering an explanation for the failure
had a positive impact on the customer perceptions regardless of the customers’
cultural orientation. It is also found that perceived fairness is directly linked to post
recovery satisfaction. The results clearly showed that firms (domestic and
international) should consider ways to restore consumers’ sense of justice
considerations- distributive and interactional, as each affects post recovery
satisfaction, irrespective of culture.
Kau and Wan-Yiun Loh (2006) in the study “The effects of service recovery on
consumer satisfaction: a comparison between complainants and non-complainants”
examines the perception of “justice” in service recovery and how it affects the level of
satisfaction and behavioral outcomes. Also explores whether the “recovery paradox”
exists. The researchers proposed model in which customers in a service setting can be
broadly divide into two distinct classes: those who complain (complainants) and those
who do not complain (non-complainants). Of the non-complainants, they are either
satisfied with the service or dissatisfied with the service provider but did not lodge a
complaint. Of the complainants, they are either satisfied with the service recovery
provided or dissatisfied. These four types of consumers may experience different
service encounters and would be expected to display different levels of satisfaction
with the service provider. This satisfaction or dissatisfaction would lead to different
behavioral outcomes. The findings of the study indicated that distributive justice is
156
significantly related to satisfaction with service recovery. Similarly, procedural
justice also played a significant role in influencing the level of satisfaction with
service recovery. It is suggested that service recovery should not be neglected and
bad service recovery efforts might lead to more detrimental consequences such as loss
of trust and bad publicity through negative word-of-mouth communications. Finally,
the lack of support of the “recovery paradox” effect suggests that successful service
recovery alone could not bring customer satisfaction to pre-service failure types.
Thus, it is imperative for service providers to examine their service operations to
identify potential pitfalls with the objective of providing fail-proof service at the first
instant.
157
Fig 3.1 The Research Model
158
Shapiro and Nieman-Gonder (2006) in their scenario-based experimental study
“Effect of communication mode in justice-based service recovery” investigate the
effects of organizational justice-based recovery strategies and the mode of
communication used following a service failure on key organizational variables
including customer satisfaction, loyalty and complaining behavior. The scenario
manipulated the type of organizational justice-based recovery strategy (distributive,
interactional, both) and the mode of communication (in-person, toll-free number, e-
mail) used during the recovery process. The findings of the study suggest no
difference between the effect of justice-based strategies on overall customer
satisfaction or loyalty. Customers were more likely to engage in informal negative
word-of-mouth behaviour than formally complaining to the company. It is suggested
that employees close to the customer are vital to service recovery because they are
often the first to know about problems. These employees must be trained in
communication, creative thinking and decision-making skills that allow them to deal
with customer complaints.
Hessb Jr., Ganesan and Klein (2007) in their research paper “Interactional service
failures in a pseudorelationship: The role of organizational attributions” investigates
interactional service failures with in a pseudorelationship, a context in which
customers interact with different frontline employees in multiple settings across
service encounters. The study establishes the globality attributions after a service
failure in a pseudorelationship are a major element of dissatisfaction with the
organization. The results show a strong relationship between dissatisfaction with the
employee and organization, as expected, but that customers in a pseudorelationship
distinguish between the employee and the organization in their responses to
interactional failures. Managers might consider communications intended to reduce
159
those attributions following a failure. They should note the crossover effect, in which
a good record of core service helps to mitigate the effects of an interactional failure.
Excellent service on one dimension may contribute to the organization’s stereotype as
a high quality service provider, creating some synergy between the core and
interactional elements of service.
Kim, Kim and Kim (2009) in their study “ The effects of perceived justice on
recovery satisfaction, trust, word of mouth and revisit intention in upscale hotels”
assesses the relative influences of justices on customer satisfaction with service
recovery and to examine the relationship between recovery satisfaction and
subsequent customer relationships; trust, word of mouth and revisit intention. The
results showed that the effect of Distributive Justice (DJ) on satisfaction with
service recovery was stronger than those of Procedural Justice (PJ) and
Interactional Justice (IJ). Since DJ, PJ and IJ have significant effects on trust,
word of mouth and revisit intention through recovery satisfaction, recovery
satisfaction was found to be an important mediating variable.
Chang and Chang (2010) in their paper “Does service recovery affect satisfaction
and customer loyalty? An empirical study of airline services” investigates the
relationships among service recovery, recovery satisfaction, overall customer
satisfaction and customer loyalty in airline services using structural equation models.
It is found that both interactional and procedural justice have a significant effect
on recovery satisfaction. Overall satisfaction mediates the relationship between
recovery satisfaction and loyalty.
160
Nikbin, Ismail, Marimuthu and Jalalkamali (2010) in their research paper
“Perceived Justice in Service Recovery and Recovery Satisfaction: The Moderating
Role of Corporate Image” assess the influence of perceived justice on recovery
satisfaction and to examine the moderating role of corporate image in the relationship
between perceived justice and recovery satisfaction. Data was gathered by means of
survey from Iran Air customers who experienced a service failure with in last year. It
was found that distributive and interactional justices have significant effects on
recovery satisfaction. The effects of distributive justice on recovery satisfaction
were stronger than interactional justice. Also, corporate image plays a moderating
role between perceived justice and recovery satisfaction in the distributive and
interactional justice dimensions.
DISSERTATION
McCollough (1995) in his dissertation “The Recovery paradox: A conceptual model
and empirical investigation of customer satisfaction and service quality attitudes after
service failure and recovery” explores the nature of post-recovery customer
satisfaction and service quality evaluations (where recovery refers to the efforts of the
service provider to turn customer dissatisfaction into satisfaction by addressing the
customer’s service problem). The researcher develops a general model of customer
satisfaction after recovery which incorporates the disconfirmation, service quality,
attribution and the justice literatures. A scenario-based experimental approach was
used to test hypothesis and data was collected by surveying airline passengers in an
airport. This research also demonstrated that recovery can partially mitigate the
dissatisfaction which results from service failures. The results of this research provide
overall support for the general model of recovery, with a few notable exceptions. The
results indicated that given failure, satisfaction was very strongly related to the
161
superiority of the recovery effort. All three experiments in this study showed that the
higher the recovery, the higher the satisfaction evaluation and service quality
attitudes. The general model of recovery predicted that distribution justice would
have a greater effect on satisfaction, while procedural justice would have a
greater effect on service quality. The findings show that procedural justice was the
most important predictor of satisfaction might be due, in part, to the inability of
the service provider to fully recover in the situation depicted. It is suggested that
service providers will find that the most direct and least problematic way for them to
enhance satisfaction judgements, service quality attitudes and repurchase intentions is
through improving service reliability.
Ma, Jun (2007) in his study “Attribution, Expectation, and Recovery: An Integrated
Model of Service Failure and Recovery” integrated attribution theory, expectancy-
disconfirmation paradigm, and justice theory into a model of customer satisfaction
with failure and recovery encounters. Also, the relationship between attribution,
recovery expectations and perceived justice toward service encounters is empirically
tested. It provides answers for questions regarding how consumers make a causal
attribution, how their causal attributions influence their reactions to service failures,
and how their causal attributions affect the effect of recoveries on perceived justice
and service encounter satisfaction. The results of the study reveal that between the
two dimensions of perceived justice (distributive justice and procedural justice)
distributive justice plays a salient role in the formation of recovery expectations. It is
derived that when a procedural justice is violated, it leads to a low level of distributive
justice and further a high level of recovery expectations. Further, the results suggest
that the more attributes a recovery strategy contained, the higher the evaluation of
procedural justice and service encounter satisfaction will be. The significant
162
implication of this study is that offering consumers more than what they expect can
delight consumers and make them more satisfied. Matching consumer needs both
economically and psychologically elevates consumer perceived justice and service
encounter satisfaction.
Weng, Hua-Hung (Robin) (2009) in the dissertation “Service Recovery: Trend, Path
Model, and Cultural Comparison” studies the trends of service recovery practice over
the past decade, establishes a service recovery model, and compares the cultural
differences using it. Comparing the results from 2000 and 2008, the study finds
decreased impact on customer satisfaction and loyalty over time, suggesting that the
recovery practice has changed from order winner to order qualifier. Based on Justice
Theory, a new service recovery model is established in this study. This new model
suggests two insights on service recovery. First, process and outcome satisfactions are
considered separately. Second, Interactional Justice, regarded as service encounter,
has a direct impact on the other two justice measure and influences satisfaction
indirectly through them.
163
3.3 HIGHLIGHTS OF THE PRESENT STUDY
The main issues addressed in the present study are:-
1. It attempts to clarify the concept of service encounter, service failure and
service recovery by surveying the available literature.
2. It makes the use of CIT to identify the service failures that happened with
airline passengers while travelling in domestic sectors of India.
3. It also tries to identify the recovery actions taken by the airline companies
after service failure and their effect on satisfaction of passengers.
4. It makes use of survey technique to study the airline passenger’s complaint
intentions and perceived justice and their effect on satisfaction.
5. It also studies the level of seriousness of airline passenger’s towards service
failures, their frequency of encountering these failures and the effect of service
failures on their satisfaction.
6. It further, consolidates the research available in the field of service failures
and recoveries.
164
RESEARCH GAP
From the detailed review of literature it is found that researchers study the service
failures and recovery strategies from the customer’s perspective (Bitner et al, 1990;
Bejou et al, 1996; Smith et al, 1999; Lewis et al, 2001; Ofir et al, 2001; Mueller et al,
2003; Chung-Herrera, 2004; Bamford et al, 2005; Harris et al, 2006; Gountas et al,
2007; Choi et al, 2008) in various service sectors (airlines, hotels, restaurants, public
transport services, cruises, theme parks, retail banking), employees’ perspective
(Bitner, 1990; Bitner et al, 1994; Mohr et al, 1995; Hocutt et al, 1998; Lewis and
Clacher,2001; Chung-Herrera, 2004; Luria et al, 2009 ), other customers’ perspective
(Grove, 1997); servicescape failures (Bitner, 1992; Hoffman et al, 2003), self-service
technology failures (Meuter at al, 2000), e-commerce failures and online failures
(Tyrrell, 2004, Forbes et al, 2005, Holloway et al, 2003, 2008; Harris et al, 2006),
retail failures and recoveries (Kelly et al, 1993). It is derived from the literature that
till date their exists no study that attempts to study the customer’s perspective of
service failures and recovery actions undertaken by the airlines operating in domestic
sectors of India and their effect on customer satisfaction indicating the gap in existing
literature. The findings of the study shall fill the gap in the existing literature. Airline
companies shall be able to use the findings by knowing the passenger’s perspective of
service failure and recovery issues. The findings would help managers to improve the
quality of services to customers.
165
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4.1 RESEARCH PURPOSE
The primary focus of this research is to study the service failures and recovery
strategies made by the airlines, providing services in domestic sectors of India, to
overcome the various failures and their effect on the customer’s overall satisfaction.
The analysis of service failures and service recoveries is beneficial to service
organizations as it allows management to identify and rectify common failure
situations (Hoffman, Kelly and Rotalsky, 1995).
Previous research has also supported that when consumers are offered an apology or
are provided with the opportunity to express their concerns to a service representative
those perceptions of satisfaction and fairness are enhanced, particularly when
recovery outcomes are favourable. There has been consistently found a relationship
between satisfaction and repurchase intentions, satisfaction and word of mouth
(Spreng, Harrell and Mackoy, 1995).
4.2 RESEARCH OBJECTIVES
CHAPTER-4
RESEARCH DESIGN AND METHODOLOGY
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The main objectives of the study are:
O1: To study the various types of service failures and their effect on customer’s
satisfaction in aviation industry.
O2: To study the various coping strategies undertaken by the airlines to overcome
the service failures.
O3: To make an impact assessment of recovery efforts in enhancing the customer’s
satisfaction.
4.3 RESEARCH HYPOTHESIS
H1: Service failures have negative effect on customer’s overall satisfaction.
H2: Recovery efforts have a positive role in enhancing customer’s satisfaction
levels.
4.4 RESEARCH DESIGN
It specifies the methods and procedures for conducting a particular study. According
to Green and Tull (1970), a research design is the specification of methods and
procedures for acquiring the information needed. It is the overall operational pattern
or framework of the project that stipulates what information is to be collected, from
which sources and by what procedures.
In simple terms research design is the detailed blueprint used to guide a research study
towards its objectives (Aaker, Kumar and Day, 2001). One of the most significant
decision as a part of research design is the choice of research approach, because it
determines how the information will be obtained. In the present study personal
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interviews were conducted with the help of a questionnaire for Study I and Survey
Research Approach was used for Study II to meet the objectives of the research.
4.5 RESEARCH METHODS
The research uses primary data to address the research objectives. This study uses
both the qualitative and quantitative methods of primary data collection. Two pilot
studies were conducted for Study1 and Study2. The first pilot study was conducted to
collect satisfying or dissatisfying incidents that were encountered with the airline
passengers regarding the services provided by airlines in the domestic sectors in India.
A set of six questions was framed in the form of questionnaire to describe the whole
incident in case the respondent missed some information to narrate. A total of 20
respondents were approached and 28 incidents were collected using personal
interview method. Initially, a voice recorder was used to record the incident described
by the respondents for getting original data that saves time of the respondent and the
researcher, then the incident was written on the paper to derive the information from
the dissatisfying incidents. But this method of collecting incident is not convenient to
the respondents because of privacy issue, as such, only personal interviews were
conducted and the information shared by the respondent was written on the paper.
Finally, Study 1 was conducted and 338 dissatisfying incidents were collected using
critical incident technique.
After sorting these incidents, twenty-six service failures were identified that had
happened with airline customers (passengers). Second pilot study was conducted with
20 respondents using a questionnaire to insure that there were no errors in the
questionnaire and to prevent misinterpretation of questions and to find out time taken
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by the respondent to fill a questionnaire and whether filling up the questionnaire was
easy or not? It was found that the respondents were comfortable to fill up the
questionnaire and it took approximately fifteen minutes to fill the questionnaire.
4.5.1 SAMPLING
The process of sampling forms a very important part of the research process. The
basic idea behind sampling is that by selecting some of the elements in a population,
conclusions can be drawn about the entire population. In other words, the process of
sampling involves any procedure using a small number of items or parts of the whole
population to make conclusions regarding the whole population (Zikmund, 2007). The
sampling methods are broadly classified as either probability sampling or non-
probability sampling.
In the first part of the study where the objective was to identify the various types of
service failures encountered, random sampling method was used. Previous studies like
Bitner, Booms and Tetreault (1990) collected 700 incidents (satisfactory and
unsatisfactory) from customers of airlines (163), restaurant (356) and hotel (180);
Hoffman, Kelly and Rotalsky (1995) collected 373 incidents from customers of
restaurants; Kivela and Chu (2001) collected favourable and unfavourable service
encounters from 417 customers of restaurants; Chung-Herrera, Goldschmidt and
Hoffman (2004) collected customer-reported incidents and employee-reported
incidents; Forbes, Kelly and Hoffman (2005) applied CIT using 377 customer
responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-
commerce service firms. Keeping in view the previous studies, the present study
collected 338 dissatisfying incidents from 200 respondents and derived the twenty-six
service failures from these incidents and classified according to Bitner, Booms and
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Tetreault (1990) classification by type of incident outcome which became the base for
Study II.
In Study II, the stratified sampling method was employed. This data collection
method, a process of segregating a population into relevant mutually exclusive groups
followed by random selection of subjects from within each stratum, ensured a good
cross-section of the population with adequate representation for strata with fewer
members.
The population is stratified on the basis of type of carrier. Accordingly, in Apr-Jun,
2008, the market share (domestic) of full service carrier and low cost carrier was
36.5% and 63.5% and in the year 2010, it was 34.8% and 65.1% respectively. For
data collection, the market share of the airlines is considered (irrespective of the
airline) through survey method. A total of 305 (or 61%) of the 500 distributed
questionnaires were sufficiently completed and returned by respondents. Out of which
20.98% (64) of the respondents didn’t mention the name of the airline. The response
percentage of respondents is 26.89% (82) and 52.13% (159) of full service carrier and
low cost carrier respectively.
4.6 INSTRUMENT DEVELOPMENT
The whole study is divided into two- Study I and Study II. The study I became the
basis for study II.
STUDY I
The first questionnaire developed was used to identify the various types of service
failures encountered by the customers (passengers) of airlines operating in domestic
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sectors of India only by using Critical Incident Technique (CIT) (Flangan, 1954 and
Booms, Bitner and Tetreault, 1990).
The survey instrument is self-administered and consists of two sections. The questions
in the first section are about demographic profile of the respondents like gender, age,
income, occupation and belong to city & state. In the second section, respondents
were asked about an incident that stands out in their mind as either satisfying/positive
or dissatisfying/negative experience with the airline in domestic sectors of India
during the last five years of their travel in domestic sectors of India only. The
following questions were asked to all the respondents and answers were written down
on the paper attached with the questionnaire as:
• Was this a satisfying/dissatisfying experience?
• Please describe the circumstances leading up to this incident.
• Describe what happened during the incident. What specific details do you
recall that made this experience memorable for you?
• What was the outcome of the incident?
• How could this experience have been improved (if at all)?
• Did you complain to the organization about this incident? If yes, how did you
complain? If not, why not?
Critical Incident Technique (CIT) – Critical Incident Technique is a qualitative
interview procedure in which customers are asked to provide verbatim stories about
satisfying and dissatisfying service encounters they have experienced. The critical
incident technique (CIT) in its original conception consisted of “….a set of
procedures for collecting direct observations of human behaviour in such a way as to
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facilitate their potential usefulness in solving practical problems and developing broad
psychological principles” (Flanagan, 1954, pp. 327-358). The use of this technique in
various services like hotels, restaurants, airlines, amusement parks, automotive
repairs, retailing, banking, cable television, public transportation and education has
been reported. The primary research objectives of using this technique are-
1. To identify ‘best practices’ at transaction level.
2. To identify customer requirements as input for quantitative studies.
3. To identify common service failure points.
4. To identify systematic strengths and weaknesses in customer-contact services.
(Zeithaml, Gremler, Bitner and Pandit, 2008).
STUDY II
Study II consists of two parts. Part I of the study includes demographic profile of the
respondents like gender, age (in years), Income (in Rupees, approx. per year), Travel
frequency by air (in a year), Travel purpose and preference of the carrier. On the basis
of study I, 26 service failures were identified and also defined under the classification
by type of incident outcome given by Bitner, Booms and Tetreault (1990). Bitner et al
classified the incident outcomes into three major groups - Group1 is Employee
Response to Service Delivery System Failures, Group 2 is Employee Response to
Customer Needs and Requests and Group 3 is Unprompted and Unsolicited Employee
Actions. With in three major groups, a total of 12 categories were developed- three in
Group1, four in Group 2 and five in Group 3. The present study defined the twenty-
six identified service failures into sub- groups.
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Six service failures are included in sub group G1A, Response to unavailable service,
four service failures are included in sub group G1B, Response to unreasonably slow
service, six service failures are in sub group G1C Response to other core service
failures, one service failure in sub group G2A, Response to special need customers,
two service failures are included in sub group G2B, Response to customer
preferences, one service failure in sub group G2C, Response to admitted customer
error, one service failure in sub group G2D, Response to potentially disruptive others,
one service failure included in sub group G3A, Attention paid to customer, two
service failures are included in sub group G3B, Truly out-of-the-ordinary employee
behaviour, one service failure in sub group G3C, Employee behaviour in the context
of cultural norms and one service failure is included in sub group G3D Gestalt
Evaluation. There is no service failure incident outcome that falls in sub group G3E,
Performance under Adverse Circumstances.
Respondents were asked about the level of seriousness of these 26 service failures
(rated on 5-point Likert scale i.e. 1 being not at all serious and 5 being very serious),
how often they encountered with these failures in domestic sectors (after 2000) (rated
on 5- point Likert scale i.e. 1 being never and 5 being always) and whether these 26
service failures effect their satisfaction level (rated on 5- point Likert scale i.e. 1 being
strongly disagree and 5 being strongly agree).
The part II of the questionnaire consists of a precise description about the
respondents’ latest dissatisfying /negative domestic air travel experience. Then, 10-
items of consumer complaint behaviour intentions were measured on 6-point scale 1
being least likely to 6 being most likely taken from Singh, 1988. Respondent’s
opinion about the 10 recovery actions were taken, what recovery actions were taken
by the airline (Lewis and Mc Cann, 2004) and what they were expecting from the
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airline. 4-items of distributive justice, 4-items of procedural justice and 4-items of
interactional justice were asked to the respondents rated on 7-point Likert scale i.e. 1
being very strongly disagree and 7 being very strongly agree (Maxham III and
Netemeyer, 2003). 2-items of overall airline satisfaction and 3-items of satisfaction
with recovery were rated by the respondents on 7-point scale i.e. 1 being very strongly
disagree and 7 being very strongly agree (Maxham III and Netemeyer, 2002). Finally
the respondents were asked about the satisfaction with the overall quality of the
airline rated on 7-point Likert scale i.e. 1 being very dissatisfied and 7 being very
satisfied.
4.7 STATISTICAL TECHNIQUES USED
Research uses primary data to address the research objectives and test the hypothesis
developed. Study uses both the qualitative and quantitative methods for primary data
collection.
4.7.1 CRITICAL INCIDENT TECHNIQUE
A critical incident is defined as the confrontation of a group leader with one or more
members, in which an explicit or implicit opinion, decision or action is demanded of
him. The word critical incident probably communicates a common meaning to a great
many people. One would expect them to have occurred quite often in psychological
literature, particularly in those situations where selective observations were involved.
The only systematic use of the critical – incident technique was developed by John C.
Flanagan and first reported in the Psychological Bulletin (1954). The summary and
conclusions from his review article follow.
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This review has described the development of a method of studying activity
requirements called the critical incident technique. The technique grew out of studies
carried out in the Aviation Psychology Program of the Army Air Force in World War
II. The success of the method in analysing such activities as combat leadership and
disorientation in pilots resulted in its extension and further development after the war.
This developmental work has been carried out primarily at the American Institute for
Research and the University of Pittsburgh. The reports of this work are previewed
briefly.
The five steps included in the critical incident procedure that are most commonly used
at present are as under-
a.) Determination of the general aim of the activity. This general aim should be a
brief statement obtained from the authorities in the field which expresses in
simple terms those objectives to which most people would agree.
b.) Development of plans and specifications for collecting factual incidents
regarding the activity. The instructions to the persons are to report their
observations, need to be specific as possible with respect to the standards to be
used in evaluating and classifying the behaviour observed.
c.) Collection of the data. The incident may be reported in an interview or written
by the observer himself. In either case it is essential that the reporting be
objective and includes all relevant details.
d.) Analysis of the data. The purpose of this analysis is to summarize and describe
the data in an efficient manner so that it can be effectively used for various
practical purposes. It is not usually possible to obtain as much objectivity in
this step as in the preceding one.
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e.) Interpretation and reporting of the statement of the requirements of the
activity. The possible biases and implications of decisions and procedures
made in each of the four previous steps should be clearly reported. The
researcher is responsible for pointing out not only the limitations but also the
degree of credibility and the value of the final results obtained.
It should be noted that the critical incident technique is very flexible and the
principles underlying it have many types of applications. Its two basic principles may
be summarized as follows-
a.) reporting of facts regarding behaviour is preferable to the collection of
interpretations, ratings and opinions based on general impressions;
b.) reporting should be limited to those behaviours which, according to competent
observers, make a significant contribution to the activity.
It should be emphasized that critical incidents represent only raw data and do not
automatically provide solutions to problems. However, a procedure which assists in
collecting representative samples of data that are directly relevant to important
problems such as establishing standards, determining requirements, or evaluating
results should have wide applicability.
The applications of the critical incident technique which have been made to date are
discussed under the following headings: a.) measures of typical performance
(criteria); b.) measures of proficiency (standard samples); c.) training; d.) selection
and classification; e.) job design and purification; f.) operating procedures; g.)
equipment design; h.) motivation and leadership (attitudes); i.) counselling and
psychotherapy.
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In summary, the critical incident technique, rather than collecting opinions, and
estimates, obtains a record of specific behaviours from those in the best position to
make the necessary observations and evaluations. The collection and tabulation of
these observations make it possible to formulate the critical requirements of an
activity. A list of critical behaviours provides a sound basis for making inferences as
to requirements in terms of aptitudes, training, and other characteristics. It is believed
that progress has been made in the development of procedures for determining
activity requirements with objectivity and precision in terms of well defined and
general psychological categories. Much remains to be done. It is hoped that the
critical incident technique and related developments will provide a stable foundation
for procedures in many areas of psychology. (pp. 354-355).
Since 1954, no additional review has been made of the critical incident technique as
Flanagan developed it. Its use has been primarily in military-related studies.
Pigors and Pigors (1965) developed the Incident Process, a five step method for the
purpose of improving decision making and leadership skills in industrial relations.
The five steps or phases are : 1.) Studying an incident; 2.) Getting information about
facts; 3.) Stating the Immediate Issue- or hub of a problem; 4.) Deciding this issue;
and 5.) Thinking about the case as a whole, to answer the practical questions: What
Can We Learn From It? (pp. 2-3)
The data collected through the measurement instruments was subjected to a number of
statistical tools and techniques. In the first stage, a detailed descriptive analysis has
been done. Descriptive analysis refers to the transformation of raw data into a form
that will make them easy to understand and interpret. In addition to the descriptive
analysis, this research uses statistical techniques as suggested by Zikmund (2007)
keeping in view
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1. Type of question to be answered
2. Number of variables
3. Scale of Measurement
This research uses a combination of univariate, bivariate and multivariate data
analysis techniques. The following bivariate analysis technique has been used-
4.7.2 ANALYSIS OF VARIANCE (ANOVA)
Analysis of Variance is a statistical method used to compare two or more means. It is
used to test general rather than specific differences among means. This section shows
how ANOVA can be used to analyze a one-factor between subjects design. The null
hypothesis tested by ANOVA is that the population means for all conditions are the
same. This can be expressed as follows:
H0: µ1= µ2=….. µk
Where H0 is the null hypothesis and k is the number of conditions.
If the null hypothesis is rejected, then it can be concluded that at least one of the
population means is different from at least one other population means.
Analysis of Variance is a method for testing differences among means by analyzing
variance. The test is based on two estimates of the population variance (σ2). One
estimate is called the Mean Square Error (MSE) and is based on differences among
scores within the groups. MSE estimates σ2 regardless of whether the null hypothesis
is true (the population means are equal). The second estimate is called the Mean
Square Between (MSB) and is based on differences among the sample means. MSB
only estimates σ2 if the population means are equal. If the population means are not
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equal, then MSB estimates a quantity larger than σ2. Therefore, if the MSB is much
larger than the MSE, then the population means are unlikely to be equal. On the other
hand, if the MSB is about the same as MSE, then the data are consistent with the
hypothesis that the population means are equal.
Before proceeding with the calculation of MSE and MSB, it is important to consider
the assumptions made by ANOVA:
1. The populations have the same variance. This assumption is called the
assumption of homogeneity of variance.
2. The populations are normally distributed.
3. Each value is sampled independently from each other value. This
assumption requires that each subject provide only one value. If a
subject provides two scores, then the value are not independent.
These assumptions are the same as for a t test of differences between groups except
that it applies to two or more groups, not just to two groups.
Computing MSE
Recall that the assumption of homogeneity of variance states that the variance with in
each of the populations (σ2) is the same. This variance, σ2, is the quantity estimated by
MSE and is computed as the mean of the sample variances.
Computing MSB
The formula for MSB is based on the fact that the variance of the sampling
distribution of the mean is
σ2
σ2M = ―
n
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where n is the sample size. Rearranging this formula we have
σ2 = n σ2M
therefore, if we knew the variance of the sampling distribution of the mean, we could
compute σ2 by multiplying by n, although, we do not know the variance of the
sampling distribution of the mean, we can estimate it with the variance of the sample
means.
To sum up these steps:
1. Compute the means.
2. Compute the variance of the means.
3. Multiply by the variance of the means by n.
Comparing MSE and MSB
The critical step in an ANOVA is comparing MSE and MSB. Since MSB estimates a
larger quantity than MSE only when the population means are not equal, a finding of
a larger MSB than an MSE is a sign that the population means are not equal. But since
MSB could be larger than MSE by chance even if the population means are equal,
MSB must be much larger than MSE in order to justify the conclusion that the
population means differ. But how larger must MSB be? Is that difference big enough?
To answer, we would need to know the probability of getting this big a difference or a
bigger difference between if the population means were all equal. The mathematics
necessary to answer this question were worked out by the statistician R. Fisher.
Although Fisher’s original formulation took a slightly different form, the standard
method for determining the probability is based on the ratio of MSB to MSE. This
ratio is named after Fisher and is called the F ratio.
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The shape of the F distribution depends on the sample size. More precisely, it depends
on two degrees of freedom (df) parameters: one for the numerator (MSB) and one for
the denominator (MSE). Recall that the degree of freedom for an estimate of variance
is equal to the number of scores minus one. Since the MSB is the variance of k means,
it has k-1 df. The MSE is an average of k variances each with n-1 df. Therefore the df
for MSE is k(n-1)= N-k where N is the total number of scores, n is the number in each
group and k is the number of groups. To summarize:
dfnumerator = k-1
dfdenominator = N-k
Tukey Honestly Significant Difference (HSD) Test
Many experiments are designed to compare more than two conditions. An obvious
way to proceed would be to do a t-test of the difference between each group mean and
each other group mean. The problem with this approach is that the possibility of
making a Type I error increases. Therefore, if one were using the 0.05 significance
level, the probability that one would make a Type I error on at least one of these
comparisons is greater than 0.05. the more means that are compared, the more the
Type I error rate is inflated.
The type I error rate can be controlled using a test called the Tukey Honestly
Significant Difference test or Tukey HSD for short. The Tukey HSD is based on a
variation of the t distribution that takes into account the number of means being
compared. This distribution is called the studentized range distribution.
Tukey’s test calculates a new critical value that can be used to evaluate whether
differences between any two pairs of means are significant. The critical value is a
little different because it involves the mean difference that has to be exceeded to
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achieve significance. So, one simply calculates one critical value and then the
difference between all possible pairs of means. Each difference is then compared to
the Tukey critical value. If the difference is larger than the Tukey value, the
comparison is significant. The formula for the critical value is as follows:
‾dT = qT√MSs/A
‾‾‾‾‾‾
n
qT is the studentized range statistic (similar to the t-critical values, but different),
MSs/A is the mean square error from the overall F-test, and n is the sample size for
each group.
This the test usually recommend, because studies show it has greater power than the
other tests under most circumstances and it is readily available in computer packages.
It is important to note that the power advantage of the Tukey test depends on the
assumption that all possible pairwise comparisons are being made.
Tukey HSD is calculated as per the steps are outlined below:
1. Compute the means and variances of each group.
2. Compute MSE which is simply the mean of the variances.
3. Compute:
Mi – Mj
Q = ‾‾‾‾‾‾‾
√MSE/n
for each pair of means where Mi is one mean, Mj is the other mean and n is the
number of scores in each group.
The following multivariate analysis techniques have been used
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4.7.3 MULTIPLE REGRESSION
The general purpose of multiple regression (the term was first used by Pearson, 1908)
is to learn more about the relationship between several independent or predictor
variables and a dependent or criterion variable.
The Regression Equation- A line in a two dimensional or two-variable space is
defined by the equation Y= a + b*X; in full text: the Y variable can be expressed in
terms of a constant (a) and a slope (b) times the X variable. The constant is also
referred to as the intercept, and the slope as the regression coefficient or β coefficient.
In the multivariate case, when there is more than one independent variable, the
regression line cannot be visualized in the two dimensional space, but can be
computed just as easily. In general then, multiple regression procedures will estimate
a linear equation of the form:
Y = a + b1*X1 + b2*X2 + …..+ bp*Xp
Beta (standardised regression coefficients)
The beta value is a measure of how strongly each predictor variable influences the
criterion variable. The beta is measured in units of standard deviation. For example, a
beta value of 2.5 indicates that a change of one standard deviation in the predictor
variable will result in a change of 2.5 standard deviations in the criterion variable.
Thus, the higher the beta value the greater the impact of the predictor variable on the
criterion variable.
When we have only one predictor variable in the model, then beta is equivalent to the
correlation coefficient between the predictor and the criterion variable. This
equivalence makes sense, as this situation is a correlation between two variables.
When we have more than two predictor variable, we cannot compare the contribution
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of each predictor variable by simply comparing the correlation coefficients. The beta
regression coefficient is computed to allow you to make such comparisons and to
assess the strength of the relationship between each predictor variable to the criterion
variable.
Predicted and Residual Scores
The regression line expresses the best prediction of the dependent variable (Y), given
the independent variables (X). However, nature is rarely (if ever) perfectly
predictable, and usually there is substantial variation of the observed points around
the fitted regression line. The deviation of a particular point from the regression line
(its predicted value) is called the residual value.
Residual Variance and R-square
The smaller the variability of the residual values around the regression line relative to
the overall variability, the better is our prediction. For example, if there is no
relationship between the X and Y variables, then the ratio of the residual variability of
the Y variable to the original variance is equal to 1.0. If X and Y are perfectly related
then there is no residual variance and the ratio of variance would be 0.0. In most
cases, the ratio would fall somewhere between these extremes, that is, between 0.0
and 1.0. 1.0 minus this ratio is referred to as R-square or the coefficient of
determination. This value is immediately interpretable in the following manner. If we
have an R square of 0.4 then we know that the variability of the Y values around the
regression line is 1–0.4 times the original variance; in other words we have explained
40% of the original variability, and are left with 60% residual variability. Ideally, we
would like to explain most if not all of the original variability. The R-square value is
an indicator of how well the model fits the data (e.g. an R square close to 1.0 indicates
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that we have accounted for almost all of the variability with the variables specified in
the model).
Interpreting the Correlation Coefficient R
Customarily, the degree to which two or more predictors (independent or X variables)
are related to the dependent (Y) variable is expressed in the correlation coefficient R,
which is the square root of R-square. In multiple regression, R can assume values
between 0 and 1. To interpret the direction of relationship between variables, one
looks at the signs (plus or minus) of the regression or B coefficients. If a B coefficient
is positive, then the relationship of this variable with the dependent variable is
positive; if the B coefficient is negative then the relationship is negative. Of course, if
the B coefficient is equal to 0 then there is no relationship between the variables.
R, R Square, Adjusted R Square
R is a measure of the correlation between the observed value and the predicted value
of the criterion variable. R Square (R2) is the square of this measure of correlation and
indicates the proportion of the variance in the criterion variable which is accounted
for by our model. In essence, this is a measure of how good a prediction of the
criterion variable we can make by knowing the predictor variables. However, R
Square, tends to somewhat overestimate the success of the model when applied to the
real world, so an adjusted R Square value is calculated which takes into account the
number of variables in the model and the number of observations (participants) our
model is based on. This Adjusted R Square value gives the most useful measure of the
success of our model. If, for example, we have an adjusted R Square value of 0.75 we
can say that our model has accounted for 75% of the variance in the criterion.
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4.7.4 FACTOR ANALYSIS
Factor analysis is used to uncover the latent structure (dimensions) of a set of
variables. It reduces attribute space from a larger number of variables to a smaller
number of factors and as such is a “non-dependent” procedure (that is, it does not
assume a dependent variable is specified). Factor analysis could be used for any of the
following purposes:
• To reduce a large number of variables to a small number of factors for
modelling purposes, where the large number of variables precludes modelling
all the measures individually.
• To select a subset of variables from a larger set, based on which original
variables have the highest correlations with the principal component factors.
• To create a set of factors to be treated as uncorrelated variables as one
approach to handling multicollinearity in such procedures as multiple
regression.
• To validate a scale or index by demonstrating that its constituent items load on
the same factor, and to drop proposed scale items which cross load on more
than one factor.
Steps in Factor Analysis
Step 1: Compute a k by k intercorrelation matrix. Compute the factorability of the
matrix.
There are two ways to determine the Factorability of an intercorrelation matrix.
(1) Bartlett’s Test of Sphericity- Calculates the determinate of the matrix of the
sums of products and cross-products (S) from which the intercorrelation matrix is
200
derived. The determinant of the matrix S is converted to a chi-square statistic and
tested for significance. The null hypothesis is that the intercorrelation matrix comes
from a population in which the variables are noncollinear (i.e an identity matrix). And
that the non-zero correlations in the sample matrix are due to sampling error.
(2) Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO)- If two variables
share a common factor with other variables, their partial correlation will be small,
indicating a unique variance they share. Interpretation of the KMO as characterized
by Kaiser, Meyer and Olkin….
KMO Value Degree of Common Variance
0.90 to 1.00 Marvelous
0.80 to 0.89 Meritorious
0.70 to 0.79 Middling
0.60 to 0.69 Mediocre
0.50 to 0.59 Miserable
0.00 to 0.49 Don’t Factor
Step 2: Extract an initial solution
A variety of methods have been developed to extract factors from an intercorrelation
matrix. SPSS offers the following methods-
� Principal component method (probably the most commonly used method)
� Maximum likelihood method (a commonly used method)
� Principal axis method also known as common factor analysis
� Unweighted least squares method
201
� Generalized least squares method
� Alpha method
� Image factoring
There are several different types of factor analysis, with the most common being
principal component analysis (PCA). Principal Component Analysis seeks a linear
combination of variables such that the maximum variance is extracted from the
variables. It then removes this variance and seeks a second linear combination which
explains the maximum proportion of the remaining variance, and so on. This is called
the principal axis method and results in orthogonal (uncorrelated) factors. PCA
analyzes total (common and unique) variance.
Step 3: From the initial solution, determine the appropriate number of factors to be
extracted in the final solution
In the initial solution, each variable is standardized to have a mean of 0.0 and a
standard deviation of +_1.0. Thus the variance of each variable = 1.0. Since a single
variable can count for 1.0 unit of variance, a useful factor must account for more than
1.0 unit of variance, or have an eigen value λ > 1.0, otherwise the factor extracted
explains no more variance than a single variable.
Eigen Values: Also called Characteristic roots. The eigen value for a given factor
measures the variance in all the variables which is accounted for by that factor. The
ratio of eigen values is the ratio of explanatory importance of the factors with respect
to the variables. If a factor has a low eigen value, then it is contributing little to the
explanation of variances in the variables and may be ignored as redundant with more
important factors.
Interpretation. Eigen values measure the amount of variation in the total sample
202
REFERENCES
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and Sons, New York, NY.
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Encounter: Diagnosing Favorable and Unfavorable Incidents. Journal of
Marketing, 54 (January), 71-84.
Chung-Herrera, Beth G., Goldschimdt, Nadav & Hoffman, K. Doug. (2004).
Customer and employee views of critical service incidents. Journal of
Services Marketing, 18 (4), 241-254.
Cohen, Arthur M. & Smith, R. Douglas (1976), Chapter 4, The Critical-Incident
Model: Its Use and Application, The Critical Incident in Growth Groups:
Theory and Technique, University Associates Publishers and Consultants.
Flanagan, John C. (1954). The Critical Incident Technique. Psychological Bulletin. 51
(July), 327-57.
Forbes, Lukas P., Kelley, Scott W. & Hoffman, K. Douglas. (2005). Typologies of e-
commerce retail failures and recovery strategies. Journal of Services
Marketing, 19(5), 280-292.
George, Darren & Mallery, Paul. (2009). SPSS for Windows Step By Step- A Simple
Guide and Reference 15.0 Update. (8th ed.). Pearson Education, Inc.,
Dorling Kindersley (India) Pvt. Ltd.
Green, PE & Tull, DS. (1970). Research for Marketing Decisions, Englewood Cliffs,
NJ: Prentice –Hall, Inc.
203
Gupta, S.P. (2009). Statistical Methods. (37th revised ed.). Sultan Chand and Sons,
New Delhi.
Hoffman, Douglas K., Kelly, Scott, W. & Rotalsky, Holly, M. (1995). Tracking
Service Failures and Employee Recovery Efforts. Journal of Services
Marketing, 9 (2).
Kivela, Jaksa, J. & Chu, Carmen Yiu Ha. (2001). Delivering Quality Service:
Diagnosing Favorable And Unfavorable Service Encounters in
Restaurants. Journal of Hospitality and Tourism Research, 25 (3), August,
251-271.
Lewis, Barbara R. & Mc Cann, Pamela. (2004). Service failure and recovery:
evidence from the hotel industry. International Journal of Contemporary
Hospitality Management, 16 (1), 6-17.
Malhotra, Naresh, K. & Dash, Satyabhusan. (2009). Marketing Research An Applied
Orientation, (5th ed.). Dorling Kindersley (India) Pvt. Ltd.
Maxham III, James G. & Netemeyer, Richard G. (2002). A Longitudinal Study of
Complaining Customers’ Evaluations of Multiple Service Failures and
Recovery Efforts. Journal of Marketing, 66, (October). 57-71.
Maxham III, James G. & Netemeyer, Richard G. (2003). Firms Reap What They Sow:
The Effects of Shared Values and Perceived Organizational Justice on
Customers’ Evaluations of Complaint Handling. Journal of Marketing, 67,
(January), 46-62.
Pigors & Pigors. (1965). The Pigors Incident Process Case Studies for Management
Development. BNA Incorporated.
204
Singh, Jagdip. (1988). Consumer Complaint Intentions and Behavior: Definitional and
Taxonomical Issues. Journal of Marketing, 52, (January), 93-107.
Spreng, Richard A., Harrell, Gilbert D. & Mackoy, Robert, D. (1995). Service
Recovery: Impact on Satisfaction and Intentions. Journal of Services
Marketing, 9 (1), 15-23.
Zeithaml, Valarie A., Gremler, Dwayne D., Bitner, Mary Jo & Pandit, Ajay. (2008).
Services Marketing Integrating Customer Focus Across the Firm (4th ed.).
Tata McGraw Hill.
Zikmund, William G. (2007). Business Research Methods, Cincinnati, Ohio.
Thomson/South-Western.
205
STUDY I
5.1 IDENTIFICATION OF VARIOUS TYPES OF SERVICE FAILURES
To identify the various types of service failures that happened with passengers
travelling in domestic sectors of India, a technique called Critical Incident Technique
(CIT) is used. It is a qualitative interview procedure in which customers are asked to
provide verbatim stories about satisfying and dissatisfying service encounters they
have experienced. The CIT in its original conception consisted of “….a set of
procedures for collecting direct observations of human behaviour in such a way as to
facilitate their potential usefulness in solving practical problems and developing broad
psychological principles” (Flanagan, 1954, pp. 327-357). The use of this technique in
various services like hotels, restaurants, airlines, amusement parks, automotive
repairs, retailing, banking, cable television, public transportation, self-service
technologies and education has been reported. Bitner et al’s (1990) findings became
the foundation for the future studies in examining the service failure incidents with
the help of critical incident technique and the classification by type of incident
outcome provided guidelines to improve customer satisfaction. Each critical incident
through a deductive sorting process systematically categorized into three major failure
groups developed by Bitner et al (1990).
CHAPTER-5
DATA ANALYSIS AND INTERPRETATION
206
Table 5.1 Bitner et al’s (1990) Group and Category Classification by Type of
Incident Outcome
Group &
Category
Type of Incident Outcome
Group 1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service
G1B Response to unreasonably slow service
G1C Response to other core service failures
Group 2 Employee Response to Customer Needs and Requests
G2A Response to special needs customers
G2B Response to customer preferences
G2C Response to admitted customer error
G2D Response to potentially disruptive others
Group 3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customers
G3B Truly out-of-the ordinary employee behaviour
G3C Employee behaviours in the context of cultural norms
G3D Gestalt evaluation
G3E Performance under adverse circumstances
207
Group1, Employee response to service delivery system failures- When the service
delivery system fails, contact employees are required to respond to consumer
complaints or disappointments. The content or form of the employee response
determines the customer’s perceived satisfaction or dissatisfaction. All group1
incidents are related directly to failures in the core service (flight delay, overbooking
of passengers, and delay in refund of cancelled ticket) and inevitable system failures
that occur for even the best of firms.
G1A, Response to unavailable service- Services normally available are lacking or
absent: overbooking of passengers, no provision of any refreshment when there is
long delay in flight, non-availability of right information about flight delay. The way
in which unavailability is handled influences the customer’s perception of the service.
Failure to apologize, offer to compensate or give an explanation can result in an
unavailability incident being remembered as very dissatisfactory.
G1B, Response to unreasonably slow service- This category reflects incidents in
which services or employee performances are perceived as inordinately slow. Delay
in refund of cancelled ticket, delay of baggage delivery, rescheduling without prior
notice, employee reactions to such delays determines the customer’s satisfaction
levels. Acting as though nothing is wrong, not explaining the delay and leaving
customers to figure out what to do their own are ways to aggravate the customer.
G1C, Response to other core service failures- Since unavailability (1A) and slow
service (1B) were dominating causes of core service failure, separate categories were
established for each category 1C encompasses incidents in which other aspects of the
core service do not meet basic performance standards for the industry e.g. missing of
baggage, exchange of baggage, inconvenience due to non working of air condition in
208
an aircraft, food and beverage not of high quality. How the employee responds to
these failures determines the customer’s perceptions of the encounter.
G2, Employee response to customer needs and requests- When a customer requires
the contact employee to adapt the service delivery system to suit his or her unique
needs, the contact employee’s response determines the customer’s dis/satisfaction. To
be classified in group2, incidents were required to contain either an explicit or
inferred request for customized service. ‘Customized’ was interpreted from the
customer’s point of view because much of what customers perceive as special
needs/requests may actually be routine from the firm or contact employee’s point of
view. What is important whether or not the customer perceives that his or her special
requests or needs have been accommodated?
G2A, Response to special needs customers- This category involves customers who
have special medical, dietary, psychological difficulties. Failure to recognize the
seriousness of the customer’s need and/or inappropriate or inadequate treatment of the
problem can result in a very dissatisfactory incident.
G2B, Response to customer preferences- This category includes incidents when,
from the customer’s perspective, ‘special’ requests are made. These requests reflect
personal preferences unrelated to the customer’s sociological, physical or
demographic characteristics (2A). This category also includes incidents in which the
customer requests a level of service customization clearly beyond the scope of or in
violation of firm/industry policies or norms. Customers can be very dissatisfied when
their preferences are not accommodated, especially if the employee shows no interest
and exerts no effort to be responsive, is unwilling to consider the ‘bending the rules’,
or promises to do something and then fails to follow through.
209
G2C, Response to admitted customer error- In this category the triggering event is
a customer error that strains the service encounter (e.g. lost ticket, reached late at
check in counter). Dissatisfactory employee responses include laughing at and
embarrassing the customer for his or her mistake, avoiding any responsibility, and
demonstrating unwillingness to assist the customer in solving the problem.
G2D, Response to potentially disruptive others- Within the environment of the
service encounter, other customers’ behaviours can strain the encounter (e.g.
intoxication, rudeness, creating noise). The contact employee or firm either does or
does not cope with the disruptive person to the satisfaction of other customers present.
G3, Unprompted and unsolicited employee actions- Events and employee
behaviours that are truly unexpected from the customer’s point of view are included
in group 3.
G3A, Attention paid to customer- This category includes incidents in which the
level of attention paid the customer is viewed very favourably or very negatively.
Dissatisfactory encounters occur when contact employees demonstrate poor attitudes
toward the customer, ignore the customer, not caring about the customer’s comfort,
and failing to provide information.
G3B, Truly out-of-ordinary employee behaviour- In this category are incidents in
which the employee does some small thing that for the customer translates into a
highly satisfactory or dissatisfactory encounter. In the case of dissatisfactory
encounters, extraordinary employee behaviour may consist of yelling, inappropriate
touching or rudeness.
G3C, Employee behaviours in the context of cultural norms- Incidents in this
category reflect employee behaviours relating to cultural norms such as equality,
210
honesty and fairness. Dissatisfactory encounters are associated with employee
behaviours that clearly violate cultural norms (discrimination against female/young
customers, employee theft, lying)
G3D, Gestalt evaluation- In this category, customers are unable to attribute
dissatisfaction to any single feature of the service encounter. Instead, the service
encounter is evaluated holistically, either everything went right or everything went
wrong.
G3E, Exemplary performance under adverse circumstances- This category
include incidents in which the customer is particularly displeased/ impressed with the
way a contact employee handles a stressful situation. This category emerged only for
satisfactory encounters.
211
Table 5.2 Demographic Profile of Respondents (N=200)
S.No. Variable No. of respondents Percentage
1. Gender
(a.) Male 139 69.5
(b.) Female 61 30.5
2. Age (in years)
(a.) below 20 8 4
(b.) 20-40 117 58.5
(c.) 40-60 61 30.5
(d.) above 60 14 7
3. Income (in Rs.)
(a.) below 10,000 21 10.5
(b.) 10,000-30,000 69 34.5
(c.) 30,000-50,000 69 34.5
(d.) above 50,000 41 20.5
4. Occupation
(a.) service 123 61.5
(b.) business 38 19
(c.) student 8 4
(d.) others 31 15.5
212
Table 5.2 presents the distribution of sample respondents with respect to the
demographics used in the study. From this distribution, it is seen that there are 139
(69.5%) male and 61 (30.5%) female amongst the respondents. The main age group is
20 – 40 years representing 58.5 % of the respondents (below 20 with 4%, 40-60 with
30.5% and above 60 with 7%). Equal percentages of the respondents’ i.e 34.5% have
income between Rs. 10,000 to Rs. 30,000 and Rs. 30,000 to Rs. 50,000 and 61.5% of
the respondents belong to occupation service, 19% belongs to business and 4% of the
respondents are students.
The critical incidents collected were categorized as per the classification given by
Bitner et al, 1990. For the classification of incidents, the procedures used by Bitner et
al, 1990; Kivela and Chu, 2001; Forbes et al, 2005 were considered. The analytic
induction process was used which consists of repeated, careful readings and sorting of
the incidents into groups and categories according to similarities in the reported
experience. Bitner et al classified the incident outcomes into three major groups -
Group1 is Employee Response to Service Delivery System Failures, Group 2 is
Employee Response to Customer Needs and Requests and Group 3 is Unprompted
and Unsolicited Employee Actions. Within three major groups, a total of 12
categories were developed- three in Group1, four in Group 2 and five in Group 3.
There is no service failure incident outcome that falls in category G3E, Performance
under Adverse Circumstances.
213
Table 5.3 Group and Category Classification by Type of Incident Outcome
Group &
Category
Type of Incident Outcome Count Percentage
Group 1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service 53 31.5
G1B Response to unreasonably slow service 48 24
G1C Response to other core service failures 67 33.5
Total (1) 168 49.7
Group 2 Employee Response to Customer Needs and Requests
G2A Response to special needs customers 16 8
G2B Response to customer preferences 21 10.5
G2C Response to admitted customer error 5 2.5
G2D Response to potentially disruptive others 6 3
Total (2) 48 14.2
Group 3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customers 23 11.5
G3B Truly out-of-the ordinary employee behaviour
36 18
G3C Employee behaviours in the context of cultural norms
29 14.5
G3D Gestalt evaluation 34 17
Total (3) 122 36.1
Total (1+2+3) 338 100
214
Table 5.3 indicated that 49.7% of incidents reported by passengers in domestic sectors
of India occurred due to service delivery system failures i.e. the incidents are related
directly to failures in the core service and inevitable system failures that occur for
even the best of firms, 14.2% of incidents occurred due to employee response to
customer needs and requests i.e. when a customer requires the contact employee to
adapt the service delivery system to suit his or her unique needs, the contact
employee’s response determines the customer’s dis/satisfaction and 36.1% of
incidents reported due to unprompted and unsolicited employee actions i.e. events and
employee behaviours that are truly unexpected from the customer’s point of view.
Examination of Table 5.3 reveals that a large proportion of dissatisfactory encounters
were related to employees’ inability or unwillingness to respond in core service
failure situations (33.5%). These core service failures are related with missing,
exchange and mishandling of baggage, quality of food provided by the airlines and
technology failures like non-working of air condition in the aircraft. After careful and
repeated readings of the incidents indicate that it is not the initial failure to deliver the
core service alone that causes dissatisfaction but rather the employees’ response to the
failure.
Category ‘unavailable service’ accounted for 31.5% of the total failures. It includes
non-availability of seat at departure terminal, no information is provided about flight
delay, after long delay flight cancelled, flight cancelled without any prior notice to the
passengers, no provision of any refreshment when there is long delay in flight and
some passengers suffered due to overbooking.
Incidents classified under category of ‘unreasonably slow service’ made up of 24% of
total incidents collected. These dissatisfactory encounters are delay in baggage
215
delivery and delay in refund of cancelled ticket. Also, food provided in the aircraft is
not on time and rescheduling is not intimated to the passengers.
In all group 1 dissatisfactory incidents, the employee failed to handle the situations in
a way that could have satisfied the passenger.
Group 2 failures involved employee response to customer needs and requests and
accounted for 14.2% of total failures. Incidents classified under category of response
to special needs customers made up of 8% of total incidents. It is mishandling of
carry-on/delicate items by the airlines’ personnel after special request is made by the
passengers. Response to customer preferences accounted for 10.5% of total failures.
Respondents considered inconvenience caused due to less leg space in aircraft and
allow to carry- on items at one sector by the airline personnel and deny the same item
by the same airline personnel at another sector considered dissatisfactory encounters.
Five incidents were reported that fall in the category response to admitted customer
error (2.5%) i.e. airline staff shows unwillingness to assist the customer in solving the
problem arises due to customer error. And failure incidents were identified in the
category response to potentially disruptive others (3%) i.e. co-passengers in the
aircraft caused inconvenience to the other passengers. Thus, failures to accommodate
the need for customized service are relatively infrequent in comparison with other
sources of dissatisfaction.
36.1% of dissatisfactory service encounters in Group 3 are related to passenger’s
negative reactions to unprompted and unsolicited employee behaviours. Twenty-three
service failure incidents were identified that belong to the category attention paid to
customers (11.5%) i.e. inefficiency shown by the staff of the airlines while solving the
problems of the passengers. Thirty-six incidents were identified in category truly out-
of-ordinary employee behaviour (18%), twenty-nine incidents in the category
216
employee behaviour in the context of cultural norms (14.5%) and thirty-four failure
incidents in category gestalt evaluation (17%). In this group of incidents, the assessed
character or attitude of the airline personnel as inferred from particular behaviours
both verbal and non verbal caused dissatisfaction to passengers.
Table 5.4 Group 1 – Sample Incidents: Employee Response to Service Delivery
Failures
Category Dissatisfactory Incident
A. Response to Unavailable
Service
Boarding 5.30 pm, flight departed at 2.30 am
finally flight reached at 4 am. There is no way to
contact my son who is waiting for me at Chennai
airport. There is no place to sit at Delhi airport. If
flight is delayed due to unavoidable circumstances
at least they provide a place to sit comfortably.
(2006)
B. Response to Unreasonably
Slow Service
Scheduled to depart at 12 noon, planned to reach
Delhi around 1 pm and had lunch by 2.30 pm, but
the flight get delayed by 1hr, informed me via
phone. I reached airport after check in wait 1 and a
half hour at airport, boarded flight wait for another
half an hour, finally flight departed at 3 pm. They
don’t ask for water or any refreshment to the
passengers. I didn’t complain for that, especially
Spice Jet provide paid and costly snacks in the
flight. (2008)
C. Response to Other Core
Service Failures
My luggage was lost. I complained to the staff
members at Jammu airport and I also sent mail to
CC, later. But I didn’t get any reply. Till date,
neither had I got my luggage nor did I get any
compensation. (2006)
217
Table 5.5 Group 2– Sample Incidents: Employee Response to Customer Needs
and Requests
Category Dissatisfactory Incident
A. Response
“Special
Needs”
Customers
During flight landing and departing faced problems in ears/ear
pressure, ask for ear buds. They didn’t provide me and they don’t have
such facility. But they should provide some earphone or buds so that
passengers don’t feel pressure. (2008)
B. Response
to Customer
Preferences
Morning flight at 4.20am, reached airport at 4am did not get three
seats together because they already accommodated the passengers
who already check in, uncomfortable atmosphere, huge rush in the
flight, even air hostess didn’t give the breakfast properly or on time,
complained them that I am a frequent flyer, arrange three seats
together when we returned after three days, they noted down my
frequent flyer no. and when we came back after three days to board
the fight, huge rush was their but they upgraded in executive class,
cabin crew staff didn’t provide efficient service. (2007)
C. Response
to Admitted
Customer
Error
I reached at airline counter thirty minutes before the departure of
flight; 3-4 passengers were also late. I got late because of traffic
chaos. But the customer service manager denied us to check in,
without listening any reason of ours. He was least cooperative and
didn’t help at all. He didn’t even try to speak to the captain and wasted
another 10-15 minutes in arguing with us. Ultimately, I purchased
another ticket of next flight. (2009)
D. Response
to Potentially
Disruptive
others
The passenger sitting next to me was drunkard, he showed a very
wrong behaviour towards the passengers, after every ten minutes went
to toilet and came back. His movement caused inconvenience to me
and others and kids were also sitting with me. Asked the crew staff to
change my seat or tell that passenger to sit properly. But no response
from the staff and through out the journey I was uncomfortable and
remained alert for any adverse circumstances. (2008)
218
Table 5.6 Group 3 – Sample Incidents: Unprompted and Unsolicited Employee
Actions
Category Dissatisfactory Incident
A. Attention
Paid to
Customer
Scheduled time 4.15 pm but departed at 9.30 pm, during the whole
period stranded at Delhi airport, time wastage, none of my fault,
boring period, after this period I never travelled with Air Deccan. It
doesn’t look good to ask for tea/coffee, they should give themselves,
like coupons to check-in passengers. There should be tight scheduling
of time. (2004)
B. Truly Out-
of-the-
Ordinary
Employee
Behaviour
I have delicate items and informed the security personnel, they took it
lightly, paste the sticker on the packed items. After taking boarding
pass, I again informed that there are delicate items, handle them
carefully. When I reached Jammu, locked was broken of my suitcase,
flower vase was broken when I saw at home. Go Air staff members
have very careless attitude. Not possible to complain at Srinagar
airport. (2008)
C. Employee
Behaviours in
the context of
Cultural
Norms
I have to go to Mumbai for the cremation of my relative, I booked the
flight through the agent when I reached the airport what I found that
the airline was overbooked, the airline member denied check-in and
offered me to board the next flight of Indian Airline. I told them the
reason that this flight is urgent for me and gave the reason that you
booked the flight on the same day. I don’t understand if it is fully
booked then why they issued the ticket. Finally, I boarded the next
flight and the purpose of my visit was not fulfilled. (2001)
D. Gestalt
Evaluation
The airline issued boarding pass to four passengers as connecting
flight from Mumbai to Delhi, the Rajkot-Mumbai flight landed at 9.05
pm but the airline staff misguided us that our next fight is already left
and contact duty manager at the airport. Actually, our next flight was
delayed by 40 minutes but due to staff negligence they pushed us into
a mess just to avoid a little effort at their part. Finally, they boarded us
in Jet Konnect flight which left Mumbai at 12.20 am, very
inconvenient journey, moreover no food was provided by the staff. It
was a full fledged mess created by the airline staff. (2009)
219
Comparison of Failure Frequency in Percentage
45.5
27.3 27.3
49.7
14.2
36.1
0102030405060
Employee Response toService Delivery System
Failures
Employee Response toCustomer Needs and
Requests
Unprompted andUnsolicited Employee
Actions
G1 G2 G3
Bitner et al (1990) Failure Frequency (Airlines) (%)
Present Study Failure Frequency (%)
Fig 5.1 Shows the Comparison of Failure Frequency in Percentage (Study I)
220
Table 5.7 Comparison of Failure Frequency in Percentage
Bitner et al (1990)
Failure Frequency
(Airlines)
Present Study
Failure Frequency
Group Statements
No. % No. %
Group1 Employee Response to
Service Delivery System
Failures
35 45.5 168 49.7
Group2 Employee Response to
Customer Needs and
Requests
21 27.3 48 14.2
Group3 Unprompted and
Unsolicited Employee
Actions
21 27.3 122 36.1
Total 77 100 338 100
Table 5.7 shows the comparison of failure frequency of incidents in airline sector of
Bitner et al’s (1990) study and present study.
221
STUDY-II
After initial sorting process and classification, twenty-six service failure
categories were identified. All twenty-six service failures classified in to sub
categories of three major groups as per the classification given by Bitner et al (1990).
The present study defined the twenty-six identified service failures into categories.
Table 5.8 Classification of Service Failures in Bitner et al’s (1990) Group and
Category Classification by Type of Incident Outcome
Group &
Category
Type of Incident Outcome Number of
Service
Failures
Group 1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service Six
G1B Response to unreasonably slow service Four
G1C Response to other core service failures Six
Group 2 Employee Response to Customer Needs and Requests
G2A Response to special needs customers One
G2B Response to customer preferences Two
G2C Response to admitted customer error One
G2D Response to potentially disruptive others One
Group 3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customers One
G3B Truly out-of-the ordinary employee behaviour Two
G3C Employee behaviours in the context of cultural norms One
G3D Gestalt evaluation One
G3E Performance under adverse circumstances Nil
222
Six service failures are included in category G1A Response to unavailable service -
cancelled flight without prior notice, non-availability of seat at departure terminal,
overbooking of passengers, no provision of any refreshment when there is long delay
in flight, flight delay and non-availability of right information about flight delay; four
service failures are included in category G1B Response to unreasonably slow
service- delay in refund of cancelled ticket, rescheduling without prior notice,
provision of food not on time and delay of baggage delivery; six service failures are in
category G1C Response to other core service failures- mishandling of baggage,
food and beverage not of high quality, missing of baggage, exchange of baggage,
inconvenience due to non working of air condition in aircraft and printing mistake on
ticket; one service failure in category G2A Response to special need customers-
mishandling of carry-on items/delicate items; two service failures are included in
category G2B Response to customer preferences- less leg space and allow to carry-
on items at one sector and deny the same at another; one service failure is in category
G2C Response to admitted customer error- staff shows unwillingness to assist the
customer in solving the problem arises due to customer error, one service failure in
category G2D Response to potentially disruptive others- co-passengers show
interrupted behaviour; one service failure included in category G3A Attention paid
to customer- inefficient staff; two service failures are included in category G3B
Truly out-of-the-ordinary employee behaviour- unfriendly and unhelpful attitude
of ground staff members and unfriendly and unhelpful attitude of crew members; one
service failure in category G3C Employee behaviour in the context of cultural
norms- theft of items which are under the scrutiny of airline staff members and one
service failure is included in category G3D Gestalt Evaluation- unfriendly and
223
uncomfortable ambience for the travellers. There is no service failure incident
outcome that falls in category G3E, Performance under Adverse Circumstances.
Table 5.9 Classification of Twenty-six Identified Service Failures into Groups
and Categories
Group and
Category
Statements
G1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service
1 Cancelled flight without prior notice
2 Non-availability of seat at departure terminal
3 Overbooking of passengers
4 No provision of any refreshment when there is long delay in flight
5 Flight delay
6 Non-availability of right information about flight delay
G1B Response to unreasonably slow service
7 Delay in refund of cancelled ticket
8 Rescheduling without prior notice
9 Provision of food not on time
10 Delay of baggage delivery
G1C Response to other core service failures
11 Mishandling of baggage
12 Food & beverage not of high quality
13 Missing of baggage
14 Exchange of baggage
15 Inconvenience due to non working of air condition in aircraft
16 Printing mistake on ticket
G2 Employee Response to Customer Needs and Requests
G2A Response to special needs customers
17 Mishandling of carry-on items/delicate items
G2B Response to customer preferences
18 Less leg space
19 Allow to carry-on items at one sector & deny the same at another
224
G2C Response to admitted customer error
20 Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
G2D Response to potentially disruptive others
21 Co-passengers show interrupted behaviour
G3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customer
22 Inefficient staff
G3B Truly out-of-the-ordinary employee behaviour
23 Unfriendly & unhelpful attitude of ground staff members
24 Unfriendly & unhelpful attitude of crew members
G3C Employee behaviours in the context of cultural norms
25 Theft of items which are under the scrutiny of airline staff members
G3D Gestalt evaluation
26 Unfriendly & uncomfortable ambience for the travellers
5.2 SECTION I- DEMOGRAPHIC PROFILE OF THE RESPONDENTS
The demographic profile of the respondents is reflected in Table 5.10. It is clear from
the table that out of the 305 total respondents, 201 (65.90 %) are male and 104 (34.10
%) are female.
Majority of the respondents are in the age group 20-40 i.e. 203 constituting 66.56%
followed by 40-60 i.e. 64 (20.98%).
As far as the income of the respondents is concerned, maximum respondents i.e. 98
(32.13%) belong to Rs.20,000 - Rs.40,000, followed by less than Rs.20,000 i.e. 77
(25.25%).
Table 5.10 shows that the travel frequency of respondents by air in a year is 120
(39.34%) who travelled less than 5 times in a year followed by 110 (36.07%)
225
respondents travelled by 5-10 times, 51 (16.72%) respondents travelled by 10-15
times and only 24 (7.87%) respondents travelled above 15 times in a year.
For travel purpose and preference given to full service carrier and low cost carrier,
respondents selected more than two options. 76 and 74 respondents travelled for
vacation and business purpose respectively. 170 respondents preferred low cost
carrier for travel and only 60 respondents preferred full service carrier.
226
Table 5.10 Demographic Profile of the Respondents
N=305
S.No. Variable No. of Respondents Percentage
(%)
1. Gender
(a) Male 201 65.90
(b) Female 104 34.10
2. Age (in years)
(a) less than 20 20 6.56
(b) 20-40 203 66.56
(c) 40-60 64 20.98
(d) above 60 18 5.90
3. Income (in Rs.) (approx. per year)
(a) less than 20,000 77 25.25
(b) 20,000-40,000 98 32.13
(c) 40,000-60,000 68 22.30
(d) above 60,000 62 20.33
4. Travel frequency (by air) ( in a year)
(a) less than 5 120 39.34
(b) 5-10 110 36.07
(c) 10-15 51 16.72
(d) above 15 24 7.87
5.* Travel purpose
(a) Business 74
(b) Visit 47
(c) Vacation 76
(d) Education 23
(e) Others 14
6.* Preference given to
(a) Full Service Carrier 60
(b) Low Cost Carrier 170
• Respondents selected more than one option.
227
5.3 SECTION II- DESCRIPTIVE STATISTICS (MEAN AND STANDARD
DEVIATION) OF LEVEL OF SERIOUSNESS, FREQUENCY OF SERVICE
FAILURES ENCOUNTERED AND EFFECT ON SATISFACTION
The mean and standard deviation were computed to illustrate the central tendency and
dispersion of variables.
The mean is simply the average of each variable. From the mean we can determine
the standard deviation, is a measure of how widely values are dispersed from the
average value (the mean).
Table 5.11 describes the mean scores and standard deviation values of all twenty-six
service failures classified in three major groups as per the classification given by
Bitner et al (1990).
228
Table 5.11 Statement Wise Response (Mean and Standard Deviation) to Level of
Seriousness, Frequency of Failures Encountered and effect on Satisfaction
N=305
A. Level of Seriousness
B. Frequency of failures encountered
C. Effect on Satisfaction
Statements
Mean SD Mean SD Mean SD
G1 Employee Response to Service
Delivery System Failures
G1A Response to unavailable
service
1 Cancelled flight without prior notice
4.35 0.85 1.70 0.76 4.37 0.74
2 Non-availability of seat at departure terminal
3.86 1.03 1.54 0.82 4.15 0.83
3 Overbooking of passengers 4.17 0.84 1.51 0.73 4.29 0.72 4 No provision of any
refreshment when there is long delay in flight
4.15 0.86 1.93 0.99 4.41 0.65
5 Flight delay 4.38 0.77 2.40 1.04 4.51 0.67 6 Non-availability of right
information about flight delay 4.22 0.84 2.21 1.09 4.50 0.67
Grand Mean 4.18 0.54 1.88 0.64 4.37 0.48
G1B Response to unreasonably slow service
7 Delay in refund of cancelled ticket
4.37 0.79 1.69 0.89 4.47 0.71
8 Rescheduling without prior notice
4.50 0.69 1.63 0.84 4.51 0.67
9 Provision of food not on time 4.03 0.91 1.65 0.88 4.36 0.78 10 Delay of baggage delivery 4.30 0.80 1.86 1.07 4.50 0.66 Grand Mean 4.3 0.58 1.71 0.73 4.46 0.52
G1C Response to other core service
failures
11 Mishandling of baggage 4.59 0.69 1.59 0.85 4.54 0.69 12 Food & beverage not of high
quality 4.36 0.74 1.6 0.86 4.50
0.72 13 Missing of baggage 4.68 0.59 1.35 0.67 4.59 0.64 14 Exchange of baggage 4.64 0.70 1.35 0.65 4.6 0.69 15 Inconvenience due to non
working of air condition in aircraft
4.24 0.88 1.36 0.66 4.50 0.72
16 Printing mistake on ticket 4.35 0.72 1.27 0.62 4.49 0.69 Grand Mean 4.48 0.47 1.42 0.50 4.54 0.51
G2 Employee Response to
Customer Needs and Requests
G2A Response to special needs
customers
17 Mishandling of carry-on items/delicate items
4.45 0.67 1.36 0.66 4.47 0.66
229
G2B Response to customer preferences
18 Less leg space 3.71 0.95 1.68 1.04 4.09 0.78 19 Allow to carry-on items at one
sector & deny the same at another
4.35 0.75 1.43 0.76 4.51 0.71
Grand Mean 4.03 0.69 1.56 0.79 4.3 0.62
G2C Response to admitted customer error
20 Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
4.00 0.99 1.43 0.68 4.28 0.85
G2D Response to potentially
disruptive others
21 Co-passengers show interrupted behaviour
3.96 0.83 1.44 0.69 4.2 0.78
G3 Unprompted and Unsolicited
Employee Actions
G3A Attention paid to customer
22 Inefficient staff 4.08 0.88 1.69 0.84 4.38 0.71 G3B Truly out-of-the-ordinary
employee behaviour
23 Unfriendly & unhelpful attitude of ground staff members
4.36 0.76 1.73 0.79 4.48 0.71
24 Unfriendly & unhelpful attitude of crew members
4.42 0.75 1.65 0.81 4.54 0.68
Grand Mean 4.39 0.69 1.69 0.73 4.51 0.63 G3C Employee behaviour in the
context of cultural norms
25 Theft of items which are under the scrutiny of airline staff members
4.61 0.64 1.36 0.59 4.62 0.73
G3D Gestalt evaluation 26 Unfriendly & uncomfortable
ambience for the travellers 4.27 0.88 1.73 0.89 4.57 0.69
It is concluded from the Table 5.11 that the respondents (N= 305) show the highest
level of seriousness towards the service failures that are included in category G3C,
employee behaviour in the context of cultural norms (Mean= 4.61, SD= 0.64) and
also the satisfaction (Mean= 4.62, SD= 0.73) is highly affected by this category of
failures. The most frequently encountered (Mean= 1.88 and SD= 0.64) failures are
included in category G1A, response to unavailable service.
230
Within a group1, employee response to service delivery system failures, the
respondents are considered the other core service failures (Mean= 4.48, SD= 0.47)
highly serious and these failures are highly affected the satisfaction of respondents.
But the failures that are most frequently encountered by respondents are included in
category response to unavailable service (Mean= 1.88, SD= 0.64).
In group2, employee response to customer needs and requests, failures regarding
employee response to special needs customers are considered most serious (Mean=
4.45, SD= 0.67) and these failures highly affected the satisfaction (Mean= 4.47, SD=
0.66) of respondents but the failures regarding customer preferences are more
frequently encountered (Mean= 1.56, SD= 0.79) by respondents.
In group3, unprompted and unsolicited employee actions, the respondents are
considered the failures regarding the employee behaviour in the context of cultural
norms (Mean= 4.61, SD= 0.64) most serious and these failures highly affected the
satisfaction (Mean= 4.62, SD= 0.73). The failures that are most frequently
encountered (Mean= 1.73, SD= 0.89) by respondents are gestalt evaluations.
231
Table 5.12- Statement Wise Response (Mean and Standard Deviation) to Level of
Seriousness, Frequency of Failure Encountered and Effect on Satisfaction on the
basis of gender
Males, N=201, Females, N=104
A-Level of Seriousness B-Frequency of Failures
Encountered
C- Effect on
Satisfaction
S.No
.
Type of Service
Failure
Male
(Mean, SD)
Female
(Mean, SD)
Male
(Mean, SD)
Female
(Mean, SD)
Male
(Mean, SD)
Female
(Mean, SD)
G1 Employee Response to Service Delivery
System Failures
G1A Response to
unavailable service
1. Cancelled flight without prior notice
4.4 (0.90) 4.34 (0.76) 1.72 (0.78) 1.68 (0.71) 4.39 (0.71) 4.33 (0.78)
2. Non-availability of seat at departure terminal
3.86 (1.02) 3.85 (1.02) 1.57 (0.87) 1.47 (0.71) 4.20 (0.83) 4.05 (0.84)
3. Overbooking of passengers
4.18 (0.84) 4.14 (0.83) 1.50 (0.72) 1.55 (0.76) 4.34 (0.71) 4.17 (0.72)
4. No provision of any refreshment when there is long delay in flight
4.10 (0.88) 4.24 (0.81) 1.95 (1.04) 1.88 (0.88) 4.40 (0.65) 4.42 (0.66)
5. Flight delay 4.34 (0.81) 4.45 (0.70) 2.47 (1.01) 2.27 (1.08) 4.47 (0.71) 4.61 (0.60) 6. Non-availability of
right information about flight delay
4.15 (0.90) 4.36 (0.71) 2.21 (1.08) 2.21 (1.12) 4.51 (0.66) 4.49 (0.70)
Grand Mean 4.17 (0.55) 4.23 (0.53) 1.90 (0.67) 1.84 (0.58) 4.39 (0.47) 4.34 (0.50)
G1B Response to
unreasonably slow
service
7. Delay in refund of cancelled ticket
4.38 (0.77) 4.35 (0.84) 1.70 (0.83) 1.69 (1.00) 4.44 (0.73) 4.51 (0.67)
8. Rescheduling without prior notice
4.47 (0.72) 4.56 (0.64) 1.70 (0.87) 1.5 (0.75) 4.52 (0.72) 4.5 (0.57)
9. Provision of food not on time
4.01 (0.95) 4.08 (0.81) 1.66 (0.89) 1.63 (0.86) 4.33 (0.83) 4.42 (0.66)
10. Delay of baggage delivery
4.31 (0.85) 4.28 (0.69) 1.94 (1.13) 1.70 (0.91) 4.50 (0.70) 4.48 (0.59)
Grand Mean 4.29 (0.60) 4.31 (0.55) 1.75 (0.76) 1.63 (0.66) 4.45 (0.54) 4.48 (0.46)
G1C Response to other
core service failures
11. Mishandling of baggage
4.59 (0.70) 4.60 (0.69) 1.62 (0.86) 1.53 (0.82) 4.51 (0.73) 4.60 (0.62)
12. Food & Beverage not of high quality
4.36 (0.76) 4.37 (0.70) 1.69 (0.93) 1.43 (0.71) 4.49 (0.72) 4.51 (0.74)
13. Missing of baggage 4.69 (0.62) 4.65 (0.53) 1.40 (0.71) 1.26 (0.56) 4.58 (0.62) 4.61 (0.69) 14. Exchange of baggage 4.63 (0.72) 4.64 (0.67) 1.38 (0.70) 1.30 (0.56) 4.60 (0.70) 4.60 (0.68) 15. Inconvenience due to
non working of air condition in aircraft
4.22 (0.89) 4.28 (0.85) 1.44 (0.73) 1.21 (0.48) 4.54 (0.67) 4.42 (0.81)
16. Printing mistake in ticket
4.36 (0.71) 4.35 (0.75) 1.31 (0.68) 1.20 (0.49) 4.47 (0.71) 4.54 (0.64)
Grand Mean 4.48 (0.48) 4.48 (0.47) 1.47 (0.55) 1.32 (0.37) 4.53 (0.50) 4.54 (0.53)
232
G2 Employee Response
to Customer Needs
and Requests
G2A Response to special needs customers
17. Mishandling of carry-on items/delicate items
4.42 (0.68) 4.49 (0.64) 1.40 (0.69) 1.29 (0.62) 4.48 (0.68) 4.45 (0.64)
G2B Response to
customer preferences
18. Less leg space 3.71 (0.94) 3.73 (0.99) 1.71 (1.05) 1.62 (1.02) 4.11 (0.79) 4.05 (0.76) 19. Allow to carry-on
items at one sector & deny the same at another
4.37 (0.67) 4.31 (0.89) 1.49 (0.78) 1.32 (0.71) 4.51 (0.71) 4.51 (0.71)
Grand Mean 4.04 (0.66) 4.02 (0.75) 1.60 (0.80) 1.47 (0.76) 4.31 (0.62) 4.28 (0.63)
G2C Response to admitted customer error
20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
4.01 (1.00) 3.98 (0.98) 1.46 (0.73) 1.38 (0.56) 4.28 (0.88) 4.27 (0.79)
G2D Response to
potentially disruptive
others
21. Co-passengers show interrupted behaviour
3.93 (0.85) 4.01 (0.79) 1.46 (0.70) 1.40 (0.66) 4.17 (0.78) 4.25 (0.76)
G3 Unprompted and Unsolicited Employee Actions
G3A Attention paid to customer
22. Inefficient staff 4.04 (0.94) 4.16 (0.74) 1.73 (0.86) 1.62 (0.78) 4.36 (0.73) 4.43 (0.68) G3B Truly out-of-the-
ordinary employee
behaviour
23. Unfriendly & unhelpful attitude of ground staff members
4.29 (0.79) 4.51 (0.70) 1.77 (0.82) 1.67 (0.74) 4.48 (0.70) 4.49 (0.73)
24. Unfriendly & unhelpful attitude of crew members
4.39 (0.79) 4.48 (0.68) 1.69 (0.85) 1.57 (0.72) 4.49 (0.70) 4.63 (0.63)
Grand Mean 4.34 (0.72) 4.50 (0.63) 1.73 (0.78) 1.62 (0.64) 4.49 (0.63) 4.56 (0.62)
G3C Employee behaviour
in the context of
cultural norms
25. Theft of items which are under the scrutiny of airline staff members
4.62 (0.65) 4.61 (0.63) 1.36 (0.60) 1.35 (0.57) 4.60 (0.76) 4.66 (0.66)
G3D Gestalt evaluation 26. Unfriendly &
uncomfortable ambience for the travellers
4.25 (0.89) 4.31 (0.85) 1.08 (0.89) 1.69 (0.89) 4.56 (0.68) 4.60 (0.70)
233
Table 5.13- Statement Wise Response (Mean and Standard Deviation) to Level of
Seriousness on the Basis of Travel Frequency
A. Level of Seriousness S. No. Type of Service Failure
a.) less than 5
(Mean & SD)
N= 120
b. ) 5-10
(Mean & SD)
N= 110
c.) 10-15
( Mean & SD)
N= 51
d.) above 15
(Mean & SD)
N= 24
G1 Employee Response to Service Delivery System Failures
G1A Response to unavailable
service
1. Cancelled flight without prior notice
4.29 (0.95) 4.37 (0.80) 4.35 (0.87) 4.58 (0.50)
2. Non-availability of seat at departure terminal
3.85 (0.98) 3.87 (1.04) 3.76 (1.12) 4 (0.98)
3. Overbooking of passengers 4.16 (0.86) 4.21 (0.74) 4.22 (0.86) 3.92 (1.06) 4. No provision of any
refreshment when there is long delay in flight
4.18 (0.82) 4.07 (0.87) 4.16 (1.01) 4.29 (0.62)
5. Flight delay 4.32 (0.73) 4.42 (0.79) 4.43 (0.88) 4.42 (0.65) 6. Non-availability of right
information about flight delay 4.23 (0.85) 4.17 (0.76) 4.25 (0.98) 4.38 (0.88)
Grand Mean 4.17 (0.54) 4.19 (0.54) 4.20 (0.64) 4.26 (0.34)
G1B Response to unreasonably
slow service
7. Delay in refund of cancelled ticket
4.34 (0.84) 4.39 (0.65) 4.29 (0.99) 4.54 (0.72)
8. Rescheduling without prior notice
4.48 (0.73) 4.5 (0.69) 4.51 (0.70) 4.63 (0.49)
9. Provision of food not on time 4.02 (0.86) 4.1 (0.86) 4.06 (0.99) 3.75 (1.15) 10. Delay of baggage delivery 4.28 (0.81) 4.3 (0.77) 4.39 (0.80) 4.25 (0.85)
Grand Mean 4.28 (0.63) 4.32 (0.50) 4.31 (0.65) 4.29 (0.63)
G1C Response to other core service failures
11. Mishandling of baggage 4.53 (0.80) 4.67 (0.53) 4.59 (0.75) 4.5 (0.66) 12. Food & Beverage not of high
quality 4.37 (0.73) 4.41 (0.67) 4.29 (0.90) 4.29 (0.75)
13. Missing of baggage 4.68 (0.63) 4.7 (0.52) 4.63 (0.66) 4.67 (0.56) 14. Exchange of baggage 4.58 (0.80) 4.7 (0.61) 4.65 (0.66) 4.63 (0.65) 15. Inconvenience due to non
working of air condition in aircraft
4.19 (0.95) 4.26 (0.80) 4.22 (0.94) 4.42 (0.72)
16. Printing mistake in ticket 4.35 (0.72) 4.4 (0.72) 4.35 (0.69) 4.29 (0.86) Grand Mean 4.45 (0.53) 4.52 (0.40) 4.45 (0.51) 4.47 (0.41)
G2 Employee Response to
Customer Needs and
Requests
G2A Response to special needs
customers
17. Mishandling of carry-on items/delicate items
4.4 (0.69) 4.43 (0.66) 4.55 (0.64) 4.54 (0.66)
G2B Response to customer
preferences
18. Less leg space 3.7 (0.94) 3.74 (0.90) 3.67 (1.16) 3.79 (0.83) 19. Allow to carry-on items at one 4.26 (0.82) 4.44 (0.70) 4.27 (0.75) 4.54 (0.59)
234
sector & deny the same at another
Grand Mean 4.0 (0.71) 4.09 (0.66) 3.97 (0.78) 4.17 (0.48)
G2C Response to admitted
customer error
20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
3.85 (1.00) 4.15 (0.91) 4.08 (1.02) 3.96 (1.16)
G2D Response to potentially
disruptive others
21. Co-passengers show interrupted behaviour
3.86 (0.84) 4.06 (0.77) 4 (0.82) 3.88 (1.03)
G3 Unprompted and Unsolicited
Employee Actions
G3A Attention paid to customer
22. Inefficient staff 3.96 (0.93) 4.29 (0.76) 4.02 (0.86) 3.88 (0.99) G3B Truly out-of-the-ordinary
employee behaviour
23. Unfriendly & unhelpful attitude of ground staff members
4.31 (0.79) 4.47 (0.74) 4.31 (0.76) 4.25 (0.74)
24. Unfriendly & unhelpful attitude of crew members
4.33 (0.77) 4.54 (0.67) 4.49 (0.70) 4.17 (1.01)
Grand Mean 4.32 (0.71) 4.5 (0.65) 4.40 (0.65) 4.21 (0.85)
G3C Employee behaviour in the
context of cultural norms
25. Theft of items which are under the scrutiny of airline staff members
4.62 (0.68) 4.65 (0.61) 4.57 (0.64) 4.5 (0.66)
G3D Gestalt evaluation 26. Unfriendly & uncomfortable
ambience for the travellers 4.09 (0.95) 4.45 (0.81) 4.35 (0.77) 4.17 (0.87)
235
Table 5.14- Statement Wise Response (Mean and Standard Deviation) to
Frequency of Failure Encountered on the Basis of Travel Frequency
B. Frequency of Failures Encountered S.
No.
Type of Service Failure
a.) less than 5
(Mean & SD)
N=120
b. ) 5-10
(Mean & SD)
N= 110
c.) 10-15
(Mean & SD)
N= 51
d.) above 15
(Mean & SD)
N= 24
G1 Employee Response to Service Delivery System Failures
G1A Response to unavailable service 1. Cancelled flight without prior notice 1.51 (0.69) 1.73 (0.68) 1.96 (0.87) 2.04 (0.95) 2. Non-availability of seat at departure
terminal 1.41 (0.76) 1.65 (0.89) 1.55 (0.73) 1.63 (0.88)
3. Overbooking of passengers 1.47 (0.77) 1.57 (0.76) 1.57 (0.67) 1.38 (0.49) 4. No provision of any refreshment
when there is long delay in flight 1.7 (0.88) 1.94 (1.00) 2.29 (0.99) 2.25 (1.15)
5. Flight delay 2.18 (0.95) 2.51 (1.08) 2.61 (1.10) 2.58 (0.97) 6. Non-availability of right
information about flight delay 1.98 (1.02) 2.35 (1.12) 2.37 (1.11) 2.42 (1.14)
Grand Mean 1.71 (0.59) 1.96 (0.65) 2.06 (0.65) 2.05 (0.62)
G1B Response to unreasonably slow
service
7. Delay in refund of cancelled ticket 1.56 (0.88) 1.71 (0.85) 1.86 (0.93) 1.96 (1.00) 8. Rescheduling without prior notice 1.44 (0.81) 1.68 (0.79) 1.76 (0.97) 2.04 (0.69) 9. Provision of food not on time 1.52 (0.83) 1.77 (0.98) 1.61 (0.78) 1.88 (0.74) 10. Delay of baggage delivery 1.56 (0.88) 1.96 (1.03) 2.10 (1.20) 2.33 (1.37) Grand Mean 1.52 (0.66) 1.78 (0.73) 1.82 (0.78) 2.05 (0.73)
G1C Response to other core service failures
11. Mishandling of baggage 1.44 (0.79) 1.63 (0.81) 1.75 (1.02) 1.79 (0.83) 12. Food & Beverage not of high
quality 1.44 (0.81) 1.75 (0.99) 1.59 (0.75) 1.75 (0.61)
13. Missing of baggage 1.31 (0.67) 1.37 (0.65) 1.35 (0.69) 1.46 (0.72) 14. Exchange of baggage 1.36 (0.66) 1.39 (0.66) 1.27 (0.70) 1.29 (0.46) 15. Inconvenience due to non working
of air condition in aircraft 1.31 (0.62) 1.39 (0.72) 1.31 (0.58) 1.63 (0.77)
16. Printing mistake in ticket 1.23 (0.63) 1.3 (0.66) 1.31 (0.62) 1.29 (0.46) Grand Mean 1.35 (0.49) 1.47 (0.53) 1.43 (0.49) 1.53 (0.40)
G2 Employee Response to Customer
Needs and Requests
G2A Response to special needs
customers
17. Mishandling of carry-on items/delicate items
1.24 (0.53) 1.41 (0.68) 1.43 (0.85) 1.58 (0.65)
G2B Response to customer preferences 18. Less leg space 1.56 (0.94) 1.78 (1.17) 1.63 (0.85) 1.92 (1.18) 19. Allow to carry-on items at one
sector & deny the same at another 1.37 (0.73) 1.43 (0.76) 1.45 (0.73) 1.75 (0.90)
Grand Mean 1.46 (0.75) 1.60 (0.83) 1.54 (0.68) 1.83 (0.95)
G2C Response to admitted customer
error
20. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
1.34 (0.64) 1.45 (0.61) 1.43 (0.67) 1.83 (0.96)
G2D Response to potentially disruptive
others
21. Co-passengers show interrupted 1.4 (0.68) 1.45 (0.67) 1.39 (0.67) 1.67 (0.82)
236
behaviour G3 Unprompted and Unsolicited
Employee Actions
G3A Attention paid to customer
22. Inefficient staff 1.54 (0.81) 1.72 (0.83) 1.86 (0.85) 1.96 (0.91) G3B Truly out-of-the-ordinary
employee behaviour
23. Unfriendly & unhelpful attitude of ground staff members
1.55 (0.73) 1.82 (0.85) 1.90 (0.73) 1.92 (0.83)
24. Unfriendly & unhelpful attitude of crew members
1.46 (0.71) 1.68 (0.81) 1.90 (0.92) 1.88 (0.85)
Grand Mean 1.50 (0.63) 1.75 (0.77) 1.90 (0.76) 1.90 (0.81)
G3C Employee behaviour in the
context of cultural norms
25. Theft of items which are under the scrutiny of airline staff members
1.27 (0.58) 1.45 (0.61) 1.35 (0.56) 1.42 (0.58)
G3D Gestalt evaluation 26. Unfriendly & uncomfortable
ambience for the travellers 1.51 (0.84) 1.8 (0.84) 2.10 ( 0.96) 1.79 (0.88)
237
Table 5.15 Statement Wise Response (Mean and Standard Deviation) to Effect
on Satisfaction on the Basis of Travel Frequency
C. Effect on Satisfaction S.
No.
Type of Service Failure
a.) less than 5
(Mean & SD)
N= 120
b. ) 5-10
(Mean & SD)
N= 110
c.) 10-15
(Mean & SD)
N= 51
d.) above 15
(Mean & SD)
N= 24
G1 Employee Response to Service
Delivery System Failures
G1A Response to unavailable service
1. Cancelled flight without prior notice
4.27 (0.87) 4.55 (0.60) 4.31 (0.81) 4.17 (0.64)
2. Non-availability of seat at departure terminal
4.11 (0.76) 4.25 (0.83) 4.20 (0.85) 3.79 (1.10)
3. Overbooking of passengers 4.21 (0.68) 4.42 (0.63) 4.29 (0.70) 4.04 (1.12) 4. No provision of any refreshment
when there is long delay in flight 4.38 (0.66) 4.47 (0.62) 4.43 (0.64) 4.21 (0.78)
5. Flight delay 4.53 (0.70) 4.51 (0.59) 4.59 (0.67) 4.29 (0.91) 6. Non-availability of right
information about flight delay 4.47 (0.69) 4.5 (0.63) 4.57 (0.70) 4.54 (0.72)
Grand Mean 4.33 (0.47) 4.45 (0.40) 4.40 (0.53) 4.17 (0.66)
G1B Response to unreasonably slow
service
7. Delay in refund of cancelled ticket
4.47 (0.69) 4.51 (0.57) 4.47 (0.78) 4.25 (1.11)
8. Rescheduling without prior notice 4.45 (0.72) 4.61 (0.58) 4.43 (0.76) 4.58 (0.65) 9. Provision of food not on time 4.39 (0.75) 4.49 (0.65) 4.20 (0.89) 3.96 (1.04) 10. Delay of baggage delivery 4.47 (0.67) 4.58 (0.61) 4.43 (0.64) 4.38 (0.88) Grand Mean 4.44 (0.56) 4.55 (0.39) 4.38 (0.57) 4.29 (0.65)
G1C Response to other core service failures
11. Mishandling of baggage 4.53 (0.72) 4.62 (0.54) 4.39 (0.78) 4.54 (0.93) 12. Food & Beverage not of high
quality 4.39 (0.78) 4.72 (0.45) 4.37 (0.80) 4.29 (1.04)
13. Missing of baggage 4.5 (0.73) 4.74 (0.48) 4.47 (0.67) 4.63 (0.65) 14. Exchange of baggage 4.56 (0.71) 4.76 (0.47) 4.37 (0.85) 4.54 (0.93) 15. Inconvenience due to non
working of air condition in aircraft
4.38 (0.79) 4.67 (0.53) 4.41 (0.73) 4.5 (0.98)
16. Printing mistake in ticket 4.43 (0.68) 4.58 (0.56) 4.55 (0.81) 4.29 (0.91) Grand Mean 4.46 (0.53) 4.68 (0.31) 4.43 (0.61) 4.47 (0.76)
G2 Employee Response to
Customer Needs and Requests
G2A Response to special needs customers
17. Mishandling of carry-on items/delicate items
4.38 (0.67) 4.6 (0.55) 4.45 (0.70) 4.38 (0.92)
G2B Response to customer
preferences
18. Less leg space 4 (0.80) 4.17 (0.76) 4.14 (0.75) 4.08 (0.83) 19. Allow to carry-on items at one
sector & deny the same at another 4.41 (0.70) 4.71 (0.51) 4.41 (0.88) 4.29 (0.95)
Grand Mean 4.20 (0.64) 4.44 (0.50) 4.27 (0.70) 4.19 (0.79)
G2C Response to admitted customer
error
20. Staff shows unwillingness to assist the customer in solving the
4.2 (0.82) 4.4 (0.77) 4.18 (1.01) 4.33 (0.96)
238
problem arises due to customer error
G2D Response to potentially
disruptive others
21. Co-passengers show interrupted behaviour
4.12 (0.78) 4.29 (0.71) 4.22 (0.83) 4.17 (0.92)
G3 Unprompted and Unsolicited
Employee Actions
G3A Attention paid to customer
22. Inefficient staff 4.34 (0.70) 4.48 (0.63) 4.29 (0.73) 4.33 (1.01) G3B Truly out-of-the-ordinary
employee behaviour
23. Unfriendly & unhelpful attitude of ground staff members
4.41 (0.80) 4.62 (0.54) 4.43 (0.70) 4.33 (0.87)
24. Unfriendly & unhelpful attitude of crew members
4.45 (0.77) 4.65 (0.52) 4.55 (0.64) 4.46 (0.88)
Grand Mean 4.43 (0.72) 4.63 (0.42) 4.49 (0.60) 4.40 (0.86)
G3C Employee behaviour in the
context of cultural norms
25. Theft of items which are under the scrutiny of airline staff members
4.53 (0.87) 4.76 (0.45) 4.57 (0.70) 4.54 (0.98)
G3D Gestalt evaluation 26. Unfriendly & uncomfortable
ambience for the travellers 4.45 (0.78) 4.74 (0.46) 4.57 (0.76) 4.42 (0.83)
The Tables 5.12 and 5.13, 5.14 and 5.15 provides information about the level of
seriousness, frequency of failures encountered and effect on satisfaction of
respondents on the basis of gender and travel frequency respectively
In category G1A, response to unavailable service, the service failure flight delay is
considered to be highly serious by female (Mean= 4.45, SD= 0.70) as shown in Table
5.12 and to the respondents travelled by air 10 to 15 times in a year (Mean= 4.43,
SD= 0.88) as shown in Table 5.13. But the service failure cancelled flight without
prior notice is considered to be serious by male (Mean= 4.40, SD= 0.90) as shown in
Table 5.12 and to the respondents travelled by air more than 15 times in a year
(Mean= 4.58, SD= 0.50) as shown in Table 5.13.
The highest value of mean score of flight delay indicates that this failure is most
frequently encountered by male (Mean= 2.47, SD= 1.01), female (Mean= 2.27, SD=
1.08) as presented in Table 5.12 and the respondents travelled by air less than 5 times
239
in a year (Mean= 2.18, SD= 0.95), 5 to 10 times in a year (Mean= 2.51, SD= 1.08), 10
to 15 times in a year (Mean= 2.61, SD= 1.10) above 15 times in a year (Mean= 2.58,
SD=0.97) as shown in the Table 5.14.
Non availability of right information about flight delay highly affected the satisfaction
of male (Mean= 4.51, SD= 0.66) as shown in Table 5.12 and to the respondents
travelled by air more than 15 times in a year (Mean= 4.54, SD= 0.72) as presented in
Table 5.15; flight delay highly effected the satisfaction of female (Mean= 4.61, SD=
0.60) as presented in Table 5.12 and the respondents travelled by air less than 5 times
in a year (Mean= 4.53, SD= 0.70) and 10 to 15 times in a year (Mean=4.59, SD=
0.67). The satisfaction of respondents travelled by air 5 to 10 times in a year (Mean=
4.55, SD= 0.60) highly affected by the service failure cancelled flight without prior
notice as shown in Table 5.15.
In category G1B, response to unreasonably slow service, the service failure
rescheduling without prior notice is considered to be highly serious by female (Mean=
4.56, SD= 0.64), male (Mean= 4.47, SD= 0.72) as shown in Table 5.12 and the
respondents travelled by air less than 5 times in a year (Mean= 4.48, SD= 0.73), 5 to
10 times in a year (Mean= 4.5, SD= 4.48), 10 to 15 times in a year (Mean= 4.51, SD=
0.70) and above 15 times in a year (Mean= 4.63, SD= 0.49) as shown in Table 5.13.
The delay of baggage delivery is more frequently encountered by male (Mean= 1.94,
SD= 1.13), female (Mean= 1.70, SD= 0.91) as presented in Table 5.12 and by the
respondents travelled by air less than 5 times in a year (Mean= 1.56, SD= 0.88), 5 to
10 times in a year (Mean= 1.96, SD= 1.03), 10 to 15 times in a year (Mean= 2.10,
SD= 1.20) and above 15 times in a year (Mean= 2.33, SD= 1.37) as presented in
Table 5.14.
240
The satisfaction of male (Mean= 4.52. SD= 0.72) as shown in Table 5.12 and the
respondents travelled by air 5 to 10 times in a year (Mean= 4.61, SD= 0.58) and
above 15 times in a year (Mean= 4.58, SD= 0.65) as shown in Table 5.15 is highly
affected by the service failure rescheduling without prior notice. The delay in refund
of cancelled ticket highly effected the satisfaction of female (Mean= 4.51, SD= 0.67)
as presented in Table 5.12 and the respondents travelled by air less than 5 times in a
year (Mean= 4.47, SD= 0.69) and 10 to 15 times in a year (Mean= 4.47, SD= 0.78) as
shown in Table 5.15.
In category G1C, response to other core service failures, the service failure missing of
baggage (Mean= 4.68, SD= 0.59) is considered to be most serious by male (Mean=
4.69, SD= 0.62), female (Mean= 4.65, SD= 0.53) as shown by Table 5.12,
respondents travelled by air less than 5 times in a year (Mean= 4.68, SD= 0.63), 5 to
10 times in a year (Mean= 4.70, SD= 0.52) and above 15 times in a year (Mean= 4.67,
SD= 0.56). Respondents travelled by air 5 to 10 times in year (Mean= 4.70, SD=
0.60) and 10 to 15 times in a year (Mean= 4.65, SD= 0.66) as presented in Table 5.13
are considered the service failure exchange of goods as most serious.
Mishandling of baggage is most frequently encountered by female (Mean= 1.53, SD=
0.82) as presented by Table 5.12 and the respondents travelled by air less than 5 times
in a year (Mean= 1.44, SD= 0.79), 10 to 15 times in a year (Mean= 1.75, SD= 1.02)
above 15 times in a year (Mean= 1.79, SD= 0.83) as shown in Table 5.14. Male
(Mean= 1.69, SD= 0.93) as shown in Table 5.12 and the respondents travelled by air
less than 5 times in a year (Mean= 1.44, SD= 0.81) and 5 to 10 times in year (Mean=
1.75, SD= 0.99) as shown in Table 5.14 are most frequently encountered the service
failure food and beverage not of high quality.
241
Missing of baggage highly affected the satisfaction of female (Mean= 4.61, SD= 0.69)
as shown in Table 5.12 and the respondents travelled by air above 15 time in a year
(Mean= 4.63, SD= 0.65) as presented in Table 5.15. But the exchange of baggage
highly effected the satisfaction of male (Mean= 4.60, SD= 0.70) as presented in Table
5.12 and the respondents travelled by air less than 5 times in a year (Mean= 4.56, SD=
0.71) and 5 to 10 times in a year (Mean= 4.76, SD= 0.47) as shown in Table 5.15. The
service failure printing mistake on ticket highly effected the satisfaction of
respondents travelled by air 10 to 15 times in a year (Mean= 4.55, SD= 0.81) as
shown in Table 5.15.
In category G2A, response to special needs customers, the female (Mean= 4.49, SD=
0.64) considered the service failure mishandling the carry on items is more serious
than male (Mean= 4.42, SD= 0.68) as presented in Table 5.12. And the respondents
travelled by air 10 to 15 times in a year (Mean= 4.55, SD= 0.64) considered it more
serious than other respondents as presented in Table 5.13.
Male (Mean= 1.40, SD= 0.69) are more frequently encountered and their satisfaction
(Mean= 4.48, SD= 0.68) is highly effected by the service failure mishandling of carry
on items than female as shown in Table 5.12. Respondents travelled by air above 15
times in a year (Mean= 1.58, SD= 0.65), as shown in Table 5.14, are more frequently
encountered the service failure mishandling of carry on items and the failure is highly
effected the satisfaction of the respondents travelled by air 5 to 10 times in a year
(Mean=4.60, SD= 0.55) as shown in Table 5.15.
In category G2B, response to customer preferences, male (Mean= 4.37, SD= 0.67) as
presented in Table 5.12 and the respondents travelled by air above 15 times in a year
(Mean= 4.54, SD= 0.59), as shown in Table 5.13, are considered the service failure
allow to carry-on items at one sector and deny the same at another is very serious.
242
The service failure less leg space in the aircraft is most frequently encountered by
male (Mean= 1.71, SD= 1.05) as shown in Table 5.12 and the respondents travelled
by air above 15 times in a year (Mean= 1.92, SD= 1.18) as shown in Table 5.14.
The equal mean score value of male (Mean= 4.51, SD= 0.71) and female (Mean=
4.51, SD= 0.71) as presented in Table 5.12 indicates that the service failure allow to
carry-on items at one sector and deny the same at another equally effected the
satisfaction of both. And the satisfaction is highly effected by the service failure allow
to carry-on items at one sector and deny the same at another of respondents travelled
by air 5 to 10 times in year (Mean= 4.71, SD= 0.51) as shown in Table 5.15.
In category G2C, response to admitted customer error, male (Mean= 4.01, SD= 3.98)
as shown in table 5.12 and respondents travelled by air 5 to 10 times in a year (Mean=
4.15, SD= 0.91) as shown in Table 5.13 considered the service failure staff shows
unwillingness to assist the customer in solving the problem arises due to customer
error is highly serious. This service failure is more frequently encountered by males
(Mean= 1.46, SD= 0.70) as presented in Table 5.12 and the respondents travelled by
air above 15 times in a year (Mean= 1.83, SD= 0.96) as shown in Table 5.14. The
satisfaction is highly effected by the above mentioned failure of male (Mean= 4.28,
SD= 0.78) as shown in Table 5.12 and the respondents travelled by air 5 to 10 times
in a year (Mean= 4.29, SD= 0.71) as presented in Table 5.15.
In the category G2D, response to potentially disruptive others, for female (Mean=
4.01, SD= 0.79) as shown in Table 5.12 and the respondents travelled by air 5 to 10
times in a year (Mean= 4.06, SD= 0.91) as shown in Table 5.13 considered the service
failure co-passengers show interrupted behaviour to be very serious than other
respondents. Male (Mean= 1.46, SD= 0.70) as presented in Table 5.12 and the
respondents travelled by air above 15 times in a year (Mean= 1.67, SD= 0.82) as
243
shown in Table 5.14 most frequently encountered by this service failures. This failure
is highly effected the satisfaction of female (Mean= 4.25, SD= 0.76) as shown in
Table 5.12 and the respondents travelled by air 5 to 10 times in a year (Mean= 4.29,
SD= 0.71) as presented in Table 5.15 than other respondents.
In the category G3A, attention paid to customer, the service failure inefficient staff is
considered most serious by the male (Mean= 4.04, SD= 0.94) as presented in Table
5.12 and the respondents travelled by air 5 to 10 times in a year (Mean=4.29, SD=
0.76) as shown in Table 5.13. It is more frequently encountered by male (Mean= 1.73,
SD= 0.86) as shown in Table 5.12 and the respondents travelled by air above 15 times
in a year (Mean= 1.96, SD= 0.91) as presented in Table 5.14. This failure is highly
effected the satisfaction of female (Mean= 4.43, SD= 0.68) as presented in Table 5.12
and the respondents travelled by air 5 to 10 times in a year (Mean= 4.48, SD= 0.63) as
shown in Table 5.15.
In the category G3B, truly out-of-ordinary employee behaviour, the highest mean
value of female (Mean= 4.51, SD= 0.70) as shown in Table 5.12 and the respondents
travelled by air above 15 times in a year (Mean=4.25, SD= 0.74) as shown in Table
5.13 of service failure unfriendly and unhelpful attitude of ground staff members
showed that they are very serious towards this failure. And male (Mean= 4.39, SD=
0.79) as presented in Table 5.12 and respondents travelled by air less than 5 times in a
year (Mean= 4.33, SD= 0.77), 5 to 10 times in a year (Mean= 4.54, SD= 0.67) and 10
to 15 times in a year (Mean= 4.49, SD= 0.70) are considered the service failure
unfriendly and unhelpful attitude of crew members very serious as presented in Table
5.13.
Male (Mean= 1.77, SD=0.82) as shown in Table 5.12 and the respondents travelled by
air less than 5 times in a year (Mean= 1.55, SD= 0.73), 5 to 10 times in a year (Mean=
244
1.82, SD= 0.85) and above 15 times in a year (Mean= 1.92, SD=0.83) are frequently
encountered the service failure unfriendly and unhelpful attitude of ground staff
members as shown in Table 5.14. Equal value of mean scores of both failures
included in category G3B indicated that respondents travelled by air 10 to 15 times in
a year (Mean=1.90, SD= 0.73 and Mean= 1.90, SD= 0.92) equally encountered by
these failures as shown in Table 5.14.
Unfriendly and unhelpful attitude of crew members highly effected the satisfaction of
male (Mean= 4.49, SD= 0.70), female (Mean= 4.63, SD= 0.63) as presented in Table
5.12 and the respondents travelled by air less than 5 times in a year (Mean= 4.45, SD=
0.77), 5 to 10 times in a year (Mean= 4.65, SD= 0.52), 10 to 15 times in a year
(Mean= 4.55, SD= 0.64) and above 15 times in a year (Mean=4.46, SD= 0.88) as
shown in Table 5.14. The satisfaction of female (Mean= 4.60, SD= 0.70) as shown in
Table 5.12 and the respondents travelled by air 5 to 10 times in a year (Mean= 4.74,
SD= 0.46) is highly effected by the above mentioned failure as shown in Table 5.15.
In the category G3C, employee behaviour in the context of cultural norms, male
(Mean= 4.62, SD= 0.65) as shown in Table 5.12 and the respondents travelled by air 5
to 10 times in a year (Mean= 4.65, SD= 0.61) as shown in Table 5.13 are considered
the failure theft of items which are under the scrutiny of airline staff members very
serious. Male (Mean= 1.36, SD= 0.60) as shown in Table 5.12 and the respondents
travelled by air 5 to 10 times in a year (Mean= 1.45, SD= 0.61) are more frequently
encountered this failure as shown in Table 5.14. This failure is highly effected the
satisfaction of female (Mean= 4.66, SD= 0.66) as shown in Table 5.12 and the
respondents travelled by air 5 to 10 times in a year (Mean=4.74, SD= 0.46) as shown
in Table 5.15.
245
In the category G3D, Gestalt evaluation, female (Mean=4.31, SD= 0.85) as shown in
Table 5.12 and the respondents travelled by air 5 to 10 times in a year as shown in
Table 5.13 (Mean=4.45, SD= 0.81) are considered the failure unfriendly and
uncomfortable ambience for traveller is very serious. The highest mean score of
female (Mean= 1.69, SD= 0.89) as shown in Table 5.12 and the respondents travelled
by air 10 to 15 times in a year (Mean=2.10, SD= 0.96) are more frequently
encountered by this failure as shown in Table 5.14. The satisfaction of female (Mean=
4.60, SD= 0.70) as shown in Table 5.12 and the respondents travelled by 5 to 10 times
in a year as presented in Table 5.15 is highly effected by the failure unfriendly and
uncomfortable ambience for the travellers.
Table 5.16- Descriptive Statistics (Mean and Standard Deviation) of Three
Groups N=305
Group Statements A- Level of
Seriousness
Mean (SD)
B- Failure
Frequency
Mean(SD)
C- Effect on
Satisfaction
Mean (SD)
G1 Employee Response to Service Delivery System Failures
4.32 (0.44) 1.67 (0.54) 4.46 (0.43)
G2 Employee Response to Customer Needs and Requests
4.09 (0.52) 1.47 (0.58) 4.31 (0.53)
G3 Unprompted and Unsolicited Employee Actions
4.35 (0.58) 1.63 (0.59) 4.52 (0.56)
Table 5.16 indicated that respondents are more serious towards the unprompted and
unsolicited employee actions and this also highly effected the satisfaction where as
the service delivery system failures are most frequently encountered by respondents.
246
Comparison of Failure Frequency in Percentage
45.5
27.3 27.3
61.54
19.23 19.23
010203040506070
Employee Response toService Delivery System
Failures
Employee Response toCustomer Needs and
Requests
Unprompted andUnsolicited Employee
Actions
G1 G2 G3
Bitner et al (1990) Failure Frequency (Airlines) (%)
Present Study Failure Frequency (%)
Fig 5.2 Shows the Comparison of Failure Frequency in Percentage (Study II)
247
Table 5.17 Comparison of Failure Frequency in Percentage
Group Statements Bitner et al (1990)
Failure Frequency
(Airlines) (%)
Present Study
Failure Frequency
(%)
G1 Employee Response to
Service Delivery System
Failures
45.5 61.54
G2 Employee Response to
Customer Needs and
Requests
27.3 19.23
G3 Unprompted and
Unsolicited Employee
Actions
27.3 19.23
5.4 DESCRIPTIVE STATISTICS (MEAN AND STANDARD DEVIATION) OF
CONSUMER COMPLAINT BEHAVIOUR (CCB) INTENTIONS OF AIRLINE
PASSENGERS
The demographic composition of complainants (N=201) and non-complainants
(N=104) is show in Table 5.18. It is clear from the table that out of 201 complainants,
134 (66.67%) are male and 67 (33.33%) are female. Majority of the respondents fall
in the age group 20 to 40 i.e 144 constituting 71.64% followed by 40 to 60 i.e. 37
(18.41%), 14 (6.96%) respondents fall in age group less than 20 years and 6
respondents (2.99%) belongs to above 60 years of age group. 68 respondents i.e.
33.83% belongs to the income group Rs. 20,000 to Rs. 40,000, 56 respondents i.e.
27.86% belongs to the income group less than Rs. 20,000, 43 (21.39%) falls in
income group Rs. 40,000 to Rs. 60,000 and 34 respondents (16.92%) have the income
248
above Rs. 60,000. The table presents 79 respondents i.e. 39.30% travelled by air 5 to
10 times in a year, 74 (36.82%) travelled less than 5 times in a year, 34 respondents
(16.92%) travelled by 10 to 15 times in a year and 14 respondents (6.96%) travelled
above 15 times in a year by air.
Table 5.18 Demographic Composition of Complainants and Non-Complainants
S.No. Variable Complainants,
N= 201
Non-Complainants,
N=104
No. of
respondents
Percentage No. of
respondents
Percentage
1. Gender (a.) Male 134 66.67 67 64.42 (b.) Female 67 33.33 37 35.58 2. Age (in years) (a.) less than 20 14 6.96 06 5.77 (b.) 20-40 144 71.64 59 56.73 (c.) 40-60 37 18.41 27 25.96 (d.) above 60 06 2.99 12 11.54 3. Income (in Rs.) (a.) less than
20,000 56 27.86 21 20.19
(b.) 20,000-40,000
68 33.83 30 28.85
(c.) 40,000-60,000 43 21.39 25 24.04 (d.) above 60,000 34 16.92 28 26.92 4. Travel
Frequency
(a.) less than 5 74 36.82 46 44.23 (b.) 5-10 79 39.30 31 29.80 (c.) 10-15 34 16.92 17 16.35 (d.) above 15 14 6.96 10 9.62
To study the airline passenger’s complaint behaviour intentions, a 10-items scale
developed by Singh (1988) to measure CCB intentions categorized into three
dimensions: voice, private and third party is used. The intentions data were obtained
on a most likely/least likely scale (coded 1 through 6).
249
Table 5.19- Statement wise response to Consumer Complaint Behaviour (CCB)
Intentions
N=305
CCB
Intentions
Statements Mean SD
1. Forget about the incident and do nothing 4.12 1.33
2. Definitely complain to the airline staff members
3.85 1.16
VOICE
4. Complain to the airline staff members and ask them to take care of your problem
3.90 1.09
Grand Mean 3.96 0.80
3. Decide not to travel by that airline 3.62 1.16
5. Speak to your friends and relatives about your bad experience
4.02 1.23
PRIVATE
6. Convince your friends and relatives not to travel by that airline
3.54 1.29
Grand Mean 3.73 0.97
7. Complain to a consumer agency and ask them to make the airline take care of your problem
3.07 1.10
8. Write a letter to the local newspaper about your bad experience
2.72 1.06
9. Report to the consumer agency so that they can warn other consumers
2.78 1.09
THIRD
PARTY
10. Take some legal action against the airline
2.55 1.08
Grand Mean 2.78 0.85
250
Table 5.20- Descriptive Statistics (Mean and Standard Deviation) of CCB
Intentions of Complainants and Non-Complainants
CCB
Intentions
Complainants, N=201
Mean (SD)
Non-Complainants, N=104
Mean (SD)
VOICE 4.18 (0.74) 3.54 (0.74)
PRIVATE 3.94 (0.93) 3.31 (0.90)
THIRD
PARTY
2.92 (0.87) 2.51 (0.73)
Table 5.21 Independent t-test Between Complainants and Non Complainants
Complainants N=201 Non-complainants N=104 CCB
Intentions t-value Sig. (2-tailed) t-value Sig. (2-tailed)
VOICE 7.214 .000 7.198 .000
PRIVATE 5.644 .000 5.705 .000
THIRD
PARTY
4.073 .000 4.304 .000
* at 5% level of significance
Table 5.19 describes the descriptive statistics of airline passenger’s complaint
behaviour intentions. The results show that mean value for voice intentions (Mean=
3.96, SD= 0.80) is highest than private (Mean= 3.93, SD= 0.97) and third party
(Mean= 2.78, SD= 0.85) intentions. It means that the respondents are actually
engaged in voice actions.
There are 66% of the respondents complaint to the airline about the service failure and
34% of the respondents did not complaint. The highest mean score of voice intention
251
(Mean=4.18, SD= 0.74) of complainants with respect to other two intentions i.e.
private and third party (Table 5.20) show that complainants preferred voice actions.
Table 5.21 reveals that there is no significant difference between the voice, private
and third party intentions of complainants and non-complainants at 5% level of
significance.
Table 5.22 Comparison of Descriptive Statistics (Mean and Standard Deviation)
of CCB intentions of Complainants on the Basis of Gender Complainants
N=201
Males, N=134 Females, N= 67 Consumer Complaint Behaviour Intentions
Mean SD Mean SD
1. Forget about the incident and do nothing
2.63 1.28 2.66 1.21
2.Definitely complain to the airline staff members
4.10 1.17 4.25 0.89
VOICE
4. Complain to the airline staff members and ask them to take care of your problem
4.18 1.08 4.18 0.82
Grand Mean 3.64 0.75 3.70 0.66
3. Decide not to travel by that airline 3.61 1.18 4.01 0.95
5. Speak to your friends and relatives about your bad experience
4.22 1.19 4.30 1.09
PRIVA
TE
6. Convince your friends and relatives not to travel by that airline
3.75 1.34 3.99 1.13
Grand Mean 3.86 0.97 4.10 0.83
7. Complain to a consumer agency and ask them to make the airline take care of your problem
3.16 1.16 3.27 1.10
8. Write a letter to the local newspaper about your bad experience
2.87 1.16 2.90 0.97
9. Report to the consumer agency so that they can warn other consumers
2.96 1.14 2.96 0.93
10. Take some legal action against the airline
2.62 1.16 2.72 1.08
Grand Mean 2.90 0.92 2.96 0.77
252
Table 5.23 Comparison of Descriptive Statistics (Mean and Standard Deviation)
of CCB Intentions of Complainants On the Basis of Age Complainants, N=201
Age less than 20,
N=14
Age 20 to 40,
N=144
Age 40 to 60,
N=37
Age above 60,
N=6
CCB INTENTIONS
Mean SD Mean SD Mean SD Mean SD
1. Forget about the incident and do nothing
2.43 0.85 2.69 1.31 2.46 1.07 3 1.67
2.Definitely complain to the airline staff members
4.14 0.53 4.12 1.16 4.32 1.00 4 1.10
VOICE
4. Complain to the airline staff members and ask them to take care of your problem
4.21 0.58 4.12 1.04 4.38 0.95 4.33 0.82
Grand Mean 3.60 0.47 3.64 0.78 3.72 0.55 3.78 0.78
3. Decide not to travel by that airline
3.93 0.62 3.76 1.13 3.46 1.19 4.67 0.82
5. Speak to your friends and relatives about your bad experience
4.14 0.86 4.24 1.18 4.24 1.23 4.83 0.75
PRIVATE
6. Convince your friends and relatives not to travel by that airline
3.79 0.97 3.78 1.29 3.95 1.41 4.33 0.82
Grand Mean 3.95 0.61 3.93 0.95 3.88 0.99 4.61 0.49
7. Complain to a consumer agency and ask them to make the airline take care of your problem
3.21 0.80 3.18 1.20 3.16 1.04 3.83 0.98
8. Write a letter to the local newspaper about your bad experience
3.14 0.66 2.77 1.11 3.03 1.14 3.83 0.75
9. Report to the consumer agency so that they can warn other consumers
3 0.88 2.94 1.08 2.92 1.14 3.5 1.05
THIRD
PARTY
10. Take some legal action against the airline
2.93 0.83 2.59 1.11 2.76 1.28 2.83 1.33
Grand Mean 3.07 0.68 2.87 0.88 2.97 0.89 3.5 0.82
253
The Tables 5.22 and 5.23 provides information about the complaint behaviour
intentions of male, female and the respondents divided in four age groups i.e. less
than 20 years, 20 to 40 years and 40 to 60 years and above 60 years among
complainants. It has been seen that female in comparison with male and the
respondents fall in the age group above 60 years got the highest mean score of voice,
private and third party intentions which indicated that these respondents are preferred
to complaint with the specified intentions.
In ‘voice’ behaviour intentions, male (Mean=4.18, SD= 1.08) and the respondents
belongs to the age group 40 to 60 years (Mean=4.38, SD= 0.95) are highly intended to
complain to the airline staff members and ask them to take care of the problem where
as female (Mean= 4.25, SD= 0.89) are highly intended to definitely complaint to the
airline staff members about the service failure.
In ‘private’ behaviour intentions, the highest mean value of male (Mean= 4.22, SD=
1.190), female (Mean= 4.30, SD= 1.09) and the respondents belong to the age group
above 60 years (Mean= 4.83, SD= 0.75) show that they are highly intended to speak
to friends and relatives about their bad experience.
In ‘third party’ behaviour intentions, the highest average values of male (Mean= 3.16,
SD= 1.16), female (Mean= 3.27, SD= 1.10) and the respondents belongs to the age
group above 60 years (Mean= 3.83, SD= 0.98) reveals that they are highly intended to
complain to a consumer agency and ask them to make the airline take care of their
problem.
254
5.5 DESCRIPTIVE STATISTICS (MEAN AND STANDARD DEVIATION)
FOR AIRLINE PASSENGER’S PERCEIVED JUSTICE
To study the airline passenger’s perceived justice after experiencing the service
failure, a 12-item scale taken from Maxham III and Netemeyer, 2003 further divided
into three i.e distributive, procedural and interactional justice. Four-items are included
in each construct. For each item, the respondents used a 7-point Likert scale to
respond to the statements with 1 being “Very Strongly Disagree” to 7 being “Very
Strongly Agree”.
Table 5.24 Statement wise response to Perceived Justice of Complainants
Complainants,
N=201
Customer Perceived Justice
Mean SD a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome
2.59 1.14
b. The final outcome I received from airline was fair, given the time and hassle
2.86 1.02
c. Inconvenience caused by the problem, the outcome I received from airline was fair
2.99 0.96
Distribution
Justice
d. The service recovery outcome that I received in response to the problem was more than fair
3.00 0.94
Grand Mean 2.86 0.82 a. Despite the hassle caused by the problem, the airline responded fairly and quickly
3.05 1.00
b. I feel airline responded in a timely fashion to the problem
3.10 1.01
c. I believe airline has fair policies & practices to handle problems
3.25 1.00
Procedural
Justice
d. With respect to its policies & procedures, the airline handled the problem in a fair manner
3.11 1.00
Grand Mean 3.13 0.78 a. In dealing with my problem, the airline personnel treated me in a courteous manner
3.40 1.19
b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair
3.29 1.14
c. The airline employees worked as hard as possible for me during the recovery effort
3.24 0.98
Interactional
Justice
d. The airline employees were honest and ethical in dealing with me during their fixing of my problem
3.28 1.02
Grand Mean 3.30 0.90
It has been seen from the Table 5.24 that there are 65% of the respondents who made
complaint to the airline. The highest mean score value of interactional justice (Mean=
255
3.30, SD= 0.90) reveals that the complainants are strongly agree with the interactional
justice of the airline.
Table 5.25 Statement wise response to Perceived Justice of Complainants on the
Basis of Gender
N= 201
Males, N= 134 Females, N= 67 Customer Perceived Justice
Mean SD Mean SD a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome
2.70 1.21 2.37 0.95
b. The final outcome I received from airline was fair, given the time and hassle
3.00 1.05 2.57 0.91
c. Inconvenience caused by the problem, the outcome I received from airline was fair
3.04 0.92 2.88 1.04
Distribution
Justice
d. The service recovery outcome that I received in response to the problem was more than fair
3.04 0.96 2.93 0.89
Grand Mean 2.95 0.85 2.69 0.72 a. Despite the hassle caused by the problem, the airline responded fairly and quickly
3.08 1.00 2.99 1.01
b. I feel airline responded in a timely fashion to the problem
3.18 1.03 2.96 0.96
c. I believe airline has fair policies & practices to handle problems
3.28 1.01 3.21 0.99
Procedural
Justice
d. With respect to its policies & procedures, the airline handled the problem in a fair manner
3.16 1.05 3.04 0.91
Grand Mean 3.17 0.81 3.05 0.71 a. In dealing with my problem, the airline personnel treated me in a courteous manner
3.45 1.19 3.31 1.18
b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair
3.31 1.13 3.27 1.16
c. The airline employees worked as hard as possible for me during the recovery effort
3.29 1.01 3.13 0.92
Interactional
Justice
d. The airline employees were honest and ethical in dealing with me during their fixing of my problem
3.34 1.08 3.18 0.89
Grand Mean 3.35 0.91 3.13 0.66
256
Table 5.26 Statement wise response to Perceived Justice of Complainants on the
Basis of Age
N=201
Age less than 20,
N=14
Age 20 to 40,
N=144
Age 40 to 60,
N=37
Age above 60,
N=6
Consumer Justice
Mean SD Mean SD Mean SD Mean SD
a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome
2.21 0.89 2.70 1.21 2.35 0.92 2.33 0.52
b. The final outcome I received from airline was fair, given the time and hassle
2.36 1.08 2.92 1.02 2.78 1.00 2.83 0.75
c. Inconvenience caused by the problem, the outcome I received from airline was fair
2.64 1.15 3.03 0.96 2.81 0.81 3.67 1.21
Distributive
Justice
d. The service recovery outcome that I received in response to the problem was more than fair
2.86 0.95 3.09 0.93 2.78 0.92 2.67 1.21
Grand Mean 2.52 0.87 2.94 0.84 2.68 0.68 2.88 0.72
a. Despite the hassle caused by the problem, the airline responded fairly and quickly
3.0 1.11 3.08 0.95 2.84 0.90 3.83 2.04
b. I feel airline responded in a timely fashion to the problem
2.86 1.17 3.16 0.99 3.0 1.03 3.00 1.26
c. I believe airline has fair policies & practices to handle problems
3.07 1.07 3.39 0.99 2.81 0.88 3.17 1.17
Procedural
Justice
d. With respect to its policies & procedures, the airline handled the problem in a fair manner
2.71 1.07 3.20 1.03 3.0 0.88 2.83 0.41
Grand Mean 2.91 0.82 3.21 0.78 2.91 0.71 3.21 0.93
Interactional
Justice
a. In dealing with my problem, the airline personnel treated me in a courteous manner
3.21 1.12 3.44 1.23 3.32 1.13 3.5 0.84
257
b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair
3.43 1.16 3.35 1.14 2.97 0.90 3.5 2.07
c. The airline employees worked as hard as possible for me during the recovery effort
3.21 0.97 3.33 1.0 2.92 0.89 3.17 0.98
d. The airline employees were honest and ethical in dealing with me during their fixing of my problem
3.21 0.97 3.35 1.0 3.11 1.10 3.00 1.10
Grand Mean 3.27 0.95 3.37. 0.91 3.08 0.78 3.29 1.16
Among the complainants, there are 66.67% of male and 33.33% of female. Both male
(Mean=3.35, SD= 0.91) and female (Mean= 3.13, SD= 0.66) and also respondents
belong to the age group 20 to 40 years are strongly agree with the interactional justice
of airlines (Table 5.25 and Table 5.26). But the equal mean values of procedural
justice of the respondents belong to age group 20 to 40 years (Mean=3.21, SD= 0.78)
and above 60 years (Mean=3.21, SD= 0.93) that they are satisfied with this justice.
258
Recovery Actions
93
25
3212
117
2615 9 8 2
Apology Corrected problem Explanation provided
Immediate Action Did nothing Took responsibility
Followed up Redirected the problem Compensation
Exceptional good treatment
Fig 5.3 Show the Recovery Actions taken by Airlines after Service Failure
259
5.6 DIMENSION RECOVERY STRATEGIES
Table 5.27 Recovery strategies used by airlines after service failure
Recovery Actions Frequency Frequency (%) Ranking of
frequency of use
Apology 93 27.4 2
Corrected problem 25 7.37 5
Explanation provided 32 9.4 3
Immediate Action 12 3.5 6
Did nothing 117 34.5 1
Took responsibility 26 7.7 4
Followed up 15 4.4 7
Redirected the problem 9 2.7 8
Compensation 8 2.4 9
Exceptional good treatment 2 0.6 10
Table 5.27 shows the list of ten recovery actions, the ones that the airline used to
rectify their particular problem, with each respondent (complainant N=201)
mentioning on an average two actions. 34.5% of respondents reported that the airline
did nothing to the problem faced by them, 27.4% of the respondents reported the
apology was made by the airline then explanation provided to the problem (9.4%),
7.7% of the respondents told that the airline took responsibility of the problem and
only 7.37% of the respondents told that the problem was corrected by the airline.
3.5% of the respondents reported that the airline took immediate action to solve the
problem. 2.7% of the respondents told that the airline redirected the problem and
260
2.4% of the respondents get compensation and only 0.6% of the respondents received
exceptional good treatment.
As far as the expectations of the respondents regarding recovery strategies should be
taken by the airline, when the service failure is encountered by them. Generally
respondents mark all the recovery strategies, it is concluded that they did not reply
rationally so the results of that section of the questionnaire is not reported.
5.7 DIMENSION OF PERCEIVED JUSTICE OF AIRLINE PASSENGERS
To study the perceived justice of airline passengers after experiencing service failure,
a 12-items scale of perceived justice of consumers (Maxham III and Netemeyer,
2003) divided into three- Distributive justice (4-items), Procedural justice (4-items)
and Interactional justice (4-items) is taken. For each item, the respondents used a 7-
point Likert scale to respond to the statements with 1 being “Very Strongly Disagree”
to 7 being “Very Strongly Agree”.
RELIABILITY
Reliability is a measure of consistency between multiple measurements of a variable.
The consistency of these measures indicates homogeneity of the variable measuring
the same construct. The items should be highly correlated to obtain a reliable measure
for the construct (Hair et al, 1998). Cronbach’s Alpha is a test designed to measure
this reliability. The correlation is indicated by a score greater than 0.70 (Hair et al,
1998). This research uses Cronbach’s Alpha to test for reliability.
All 12-items, four in each construct i.e. distributive, procedural and interactional
justice reported a high degree of consistency, homogeneity and reliability with
261
Cronbach’s Alpha in excess of 0.70 at 0.820, 0.781 and 0.850 respectively (Table
5.28).
Table 5.28 Reliability of Perceived Justice Construct of Airline Passengers
Construct Cronbach’s Alpha N
Distributive Justice 0.820 201
Procedural Justice 0.781 201
Interactional Justice 0.850 201
ADEQUACY AND SCALE PURIFICATION
The face and content validity of the instrument was duly attested. Kaiser-Meyer-Olkin
(KMO) is a measure of sampling adequacy to test if the distribution of values is
adequate for conducting Factor Analysis. Values between 0.50 and 1.0 indicate that
Factor Analysis is appropriate (Malhotra, 2005). Further, the Bartlett’s Test of
Sphericity also suggests that the intercorrelation matrix is factorable and therefore
factor analysis can be applied to the current data. The Kaiser-Meyer-Olkin values for
the aforesaid variables as depicted in Table 5.29 indicate the high degree of construct
validity.
Table 5.29 Kaiser-Meyer-Olkin and Bartlett's Test of Sphericity
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .869
Bartlett's Test of Sphericity Approx. Chi-Square 1123.056
df 66
Significance .000
262
FACTOR ANALYSIS
A factor analysis was performed to analyse the interrelationships of multiple variables
and to explain these variables in terms of their underlying commonalities as univariate
factors. The goal is to condense the variables into a set of variables for further
analysis with minimal data loss (Hair et al, 1998). Principal component matrix was
used to account for the full variance in the data set. Variables reporting factor
loadings above 0.50 are deemed to be significant (Hair et al, 1998).
Additionally, Eigen values are measured to determine the number of factors to be
retained. Only factors returning an Eigen value over 1 are deemed significant.
In the present study, factor analysis was performed on 12 statements. Table 5.29
summarises the twelve perceived justice variables into three factors that determines
the perceived justice of airline passengers which explains 65.684% of the total
variance. From the analysis of these results, it can be said that the factors returned
from this process have minimum factor loadings of 0.605, with a range between 0.605
and 0.829, demonstrating a high degree of reliability.
The first factor i.e. Distributive Justice, comprises of four statements. Statements ‘The
incident caused me problems, the airline effort to fix it resulted in a very positive
outcome’, ‘The final outcome I received from airline was fair, given the time and
hassle’, ‘Inconvenience caused by the problem, the outcome I received from airline
was fair’, ‘The service recovery outcome that I received in response to the problem
was more than fair’ are most important with factor loading values of 0.703, 0.812,
0.774 and 0.633 respectively. This factor explained 46.298% of variance.
The second factor i.e. Procedural Justice consist of four statements. Statements
‘Despite the hassle caused by the problem, the airline responded fairly and quickly’, ‘I
263
feel airline responded in a timely fashion to the problem’, ‘I believe airline has fair
policies & practices to handle problems’ and ‘With respect to its policies &
procedures, the airline handled the problem in a fair manner’ with factor loading
values of 0.605, 0.713, 0.775 and 0.692 respectively. The factor identified 11.191% of
variance.
The third factor i.e. Interactional Justice comprises of four statements. Statements ‘In
dealing with my problem, the airline personnel treated me in a courteous manner’,
‘During their effort to fix my problem, the airline employees showed a real interest in
trying to be fair’, ‘The airline employees worked as hard as possible for me during the
recovery effort’, ‘The airline employees were honest and ethical in dealing with me
during their fixing of my problem’ with factor loading values of 0.829, 0.814, 0.736
and 0.733 respectively. The factor identified 8.194% of variance.
These results show strong support for perceived justice of airline passengers as a
multidimensional construct consisting of distributive, procedural and interactional
justice.
264
Table 5.30 Summary of Results from Scale Purification
Name of the
Factor
Factor Wise Dimensions Factor
Loading
Values
Communalities Eigen
Values
% of
Variance
a. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome
0.703 0.600
b. The final outcome I received from airline was fair, given the time and hassle
0.812 0.733
c. Inconvenience caused by the problem, the outcome I received from airline was fair
0.774 0.702
1. Distributive Justice
d. The service recovery outcome that I received in response to the problem was more than fair
0.633 0.464
5.556 46.298%
a. Despite the hassle caused by the problem, the airline responded fairly and quickly
0.605 0.566
b. I feel airline responded in a timely fashion to the problem
0.713 0.674
c. I believe airline has fair policies & practices to handle problems
0.775 0.636
2. Procedural
Justice
d. With respect to its policies & procedures, the airline handled the problem in a fair manner
0.692 0.576
1.343 11.191 %
a. In dealing with my problem, the airline personnel treated me in a courteous manner
0.829 0.732
b. During their effort to fix my problem, the airline employees showed a real interest in trying to be fair
0.814 0.732
c. The airline employees worked as hard as possible for me during the recovery effort
0.736 0.701
3. Interactional
Justice
d. The airline employees were honest and ethical in dealing with me during their fixing of my problem
0.733 0.657
0.983 8.194 %
Cumulative percentage of
Variance
65.684%
Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalisation N=201
265
Fig.5.4 Scree Plot Rep
resenting the Factors of Perce
ived
Justice
266
After the systematic evaluation of the contents of data, SPSS was used to simplify the
data through the Scree test/plot under factor analysis (Sharma et al, 2001). Therefore,
the factors finally emerged were put under scree test so as to know which of them are
contributing significantly to the total variance in the results obtained. This test
examines the graph of Eigen values which stop factoring at the point where these
values begin to form a straight line with an almost horizontal slope (Fig. 5.4). The
findings are on the basis of the data gathered with in the domain of perceived justice.
5.8 REGRESSION ANALYSIS
In order to predict the changes on a dependent variable caused by the changes in an
independent variable, the regression analysis is applied. The basic information of the
regression equation is:
Y=a + bX
Where
Y = dependent variable and
X= independent variable
I. Regression output for customer satisfaction and seriousness of the service
failure
Customer Satisfaction = f (Seriousness of the service failure)
267
Table 5.31 Regression Coefficient of Seriousness of the Service Failure
Variable Beta t-value Sig.
Seriousness of the service failure .637 14.39 .000
Table 5.32 Regression Model for Seriousness of the Service Failure (Summary)
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .637(a) .406 .404 .33086
a Predictors: (Constant), Seriousness
The values shown in the Table 5.31 and Table 5.32 suggest that the customer
satisfaction is a function of seriousness of service failure. The dependent variable is
customer satisfaction and independent variable is seriousness of service failure. The
findings are presented by regression model (R Square = 0.406) and the β value
(0.637) of seriousness of service failure is significant as suggested by the t-value.
Thus, higher the seriousness of the service failure, higher is the satisfaction level of
customer affected.
II. Regression output for satisfaction with recovery and perceived justice
In order to predict the difference in the satisfaction with recovery of the complainants
due to distributive justice, procedural justice and interactional justice, the regression
analysis is used. The basic information of the regression equation is:
Y=a + bX
268
Where
Y = dependent variable i.e. satisfaction with recovery of complainants.
X= independent variable i.e. distributive justice, procedural justice and interactional
justice.
This research explores the effect of distributive, procedural and interactional justice
provided by airlines to complainants’ satisfaction. Thus, the dependent variable is
satisfaction with recovery and the independent variable is the justice of airlines.
Satisfaction with recovery = f (Distributive Justice, Procedural Justice and
Interactional Justice)
Table 5.33 Regression Coefficient of Perceived Justice
Variable Beta Value t-value Sig.
Distributive Justice 0.269 3.385 .001
Procedural Justice 0.245 3.042 .003
Interactional Justice 0.128 1.736 .084
Table 5.34 Regression Model for Perceived Justice (Summary)
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .549(a) .302 .291 .45202
a Predictors: (Constant), CIJ, CDJ, CPJ
The values shown in the Table 5.33 and Table 5.34 suggest that the satisfaction with
recovery is a function of distributive justice, procedural justice and interactional
269
justice. The β values of distributive and procedural justice are significant as suggested
by the t-values. The justice construct together explain 30.2% of the total variance in
the satisfaction with recovery as suggested by the R-square value.
III. Regression output for overall airline satisfaction and satisfaction with
recovery
Overall Airline Satisfaction = f (Satisfaction with Recovery)
Table 5.35 Regression Coefficient of Satisfaction with Recovery
Table 5.36 Regression Model for Satisfaction with Recovery (Summary)
Model R R Square
Adjusted R
Square Std. Error of the Estimate
1 .303(a) .092 .087 .53206
a Predictors: (Constant), SR
The values shown in the Table 5.35 and Table 5.36 suggest that the satisfaction with
recovery is a function of overall airline satisfaction. The β value of satisfaction with
recovery is significant as suggested by the t-value.
Variable Beta t-value Sig.
Satisfaction with
recovery
0.303 4.477 .000
270
5.9 DESCRIPTIVE STATISTICS OF DIMENSION OVERALL AIRLINE
SATISFACTION W.R.T. EACH AIRLINE
The mean scores and standard deviation values of dimension overall airline
satisfaction are mentioned in the Table 5.37. Out of 305 respondents, only 241
respondents mentioned the name of the airline with which service failure was
encountered during travel in domestic sectors of India. There are ten airlines
identified- Air Deccan (now its Kingfisher Red), Air India, Air Sahara (the name
changed is JetLite), Go Air, Indian Airline, Indigo, Jet airways, Spice jet, JetLite and
Kingfisher Airline.
Table 5.37 Descriptive Statistics (Mean and Standard Deviation) of Overall
Airline Satisfaction w.r.t Each Airline
N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Airline
Lower
Bound
Upper
Bound
Air Deccan 26 4.00 .40 .08 3.84 4.16
Air India 37 3.87 .40 .07 3.73 3.99
Air Sahara 6 4.00 .00 .00 4.00 4.00
Go Air 16 3.75 .89 .22 3.27 4.23
Indian Airline
14 3.96 .50 .13 3.68 4.25
Indigo Airline
15 3.93 .26 .07 3.79 4.08
Jet Airways 25 3.92 .62 .12 3.66 4.18
JetLite
27 4.07 .27 .05 3.97 4.18
Spice Jet 45 3.87 .60 .09 3.69 4.04
Kingfisher Airline
30 3.98 .36 .07 3.85 4.12
Total 241 3.93 .49 .03 3.87 3.99
271
Comparison of mean values as shown in Table 5.37 establishes that the satisfaction
with the overall quality of airlines JetLite, Air Deccan, Air Sahara and Kingfisher
Airline are higher than the rest of the airlines.
Table 5.38 Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig.
3.798 9 231 .000
5.9.1 COMPARISON OF AIRLINES ON THE BASIS OF OVERALL AIRLINE
SATISFACTION
This section was conducted with the null hypotheses that there is no significant
difference between the airlines as far as overall airline satisfaction is concerned.
Using the Analysis of Variance (ANOVA) test the hypotheses were tested, the results
are shown in the Table 5.39. Since the calculated value of F0.05 (0.760) is greater than
the table value (For v1= 9, v2=231, F0.05=0.653), the null hypothesis i.e. there is no
significant difference between the airlines as far as overall airline satisfaction is
concerned, is rejected in this case. It means that there is difference between the
airlines regarding overall airline satisfaction. It is implied that at least one of the
airlines is perceived by the passengers to be significantly different from the rest of the
lot.
Table 5.39 One Way ANOVA Results for Overall Airline Satisfaction
Sum of Squares Df Mean Square F Sig.
Between Groups 1.68 00009 .186 .760 .653
Within Groups 56.62 231 .245
Total 58.30 240
272
Tukey’s Honestly Significant Difference Test for Multiple Comparisons:
This test identifies the airlines that are significantly different from the rest of the lot.
The results of Tukey’s Honestly Significant Difference Test as shown in Table 5.40
for multiple comparisons suggest that all the airlines are significantly different from
the rest of the lot as far as overall airline satisfaction is concerned.
Table 5.40 Tukey HSD Multiple Comparisons Test for Overall Airline
Satisfaction
95% Confidence Interval Airline
Airline (In comparison
with)
Mean Difference
Std. Error
Sig.
Lower Bound
Upper Bound
Air Deccan
Air India .14 .13 .987 -.2697 .5399
Air Sahara .00 .22 1.000 -.7164 .7164 Go Air .25 .16 .852 -.2526 .7526 Indian Airline .04 .16 1.000 -.4887 .5601 Indigo .07 .16 1.000 -.4462 .5795 Jet Airways .08 .14 1.000 -.3631 .5231 JetLite -.07 .14 1.000 -.5087 .3606 Spice jet .13 .12 .985 -.2563 .5230 Kingfisher Airline .02 .13 1.000 -.4072 .4405 Air India Air Deccan -.14 .13 .987 -.5399 .2697 Air Sahara -.14 .22 1.000 -.8313 .5610 Go Air .11 .15 .999 -.3584 .5882 Indian Airline -.10 .16 1.000 -.5958 .3969 Indigo -.07 .15 1.000 -.5527 .4157 Jet Airways -.06 .13 1.000 -.4647 .3544 JetLite -.21 .13 .811 -.6096 .1912 Spice jet -.001 .11 1.000 -.3528 .3492 Kingfisher Airline -.12 .12 .993 -.5071 .2702 Air
Sahara
Air Deccan .00 .22 1.000 -.7164 .7164
Air India .14 .22 1.000 -.5610 .8313 Go Air .25 .24 .988 -.5072 1.0072 Indian Airline .04 .24 1.000 -.7361 .8076 Indigo .07 .24 1.000 -.6974 .8308 Jet Airways .08 .23 1.000 -.6391 .7991 JetLite -.07 .22 1.000 -.7880 .6399 Spice jet .13 .21 1.000 -.5541 .8208 Kingfisher Airline .02 .22 1.000 -.6907 .7241 Go Air Air Deccan -.25 .16 .852 -.7526 .2526
273
Air India -.11 .15 .999 -.5882 .3584 Air Sahara -.25 .24 .988 -1.0072 .5072 Indian Airline -.21 .18 .974 -.7932 .3646 Indigo -.18 .18 .990 -.7518 .3852 Jet Airways -.17 .16 .987 -.6764 .3364 Jetlite -.32 .16 .547 -.8231 .1750 Spice jet -.12 .14 .998 -.5771 .3438 Kingfisher Airline -.23 .15 .882 -.7230 .2563 Indian Airline
Air Deccan -.04 .16 1.000 -.5601 .4887
Air India .09 .16 1.000 -.3969 .5958 Air Sahara -.04 .24 1.000 -.8076 .7361 Go Air .21 .18 .974 -.3646 .7932 Indigo .03 .18 1.000 -.5569 .6188 Jet Airways .04 .17 1.000 -.4837 .5723 JetLite -.11 .16 1.000 -.6307 .4112 Spice jet .10 .15 1.000 -.3865 .5817 Kingfisher Airline -.02 .16 1.000 -.5310 .4929 Indigo Air Deccan -.07 .16 1.000 -.5795 .4462 Air India .07 .15 1.000 -.4157 .5527 Air Sahara -.07 .24 1.000 -.8308 .6974 Go Air .18 .18 .990 -.3852 .7518 Indian Airline -.03 .18 1.000 -.6188 .5569 Jet Airways .01 .16 1.000 -.5033 .5300 JetLite -.14 .16 .997 -.6501 .3687 Spice jet .07 .15 1.000 -.4049 .5383 Kingfisher Airline -.05 .16 1.000 -.5502 .4502 Jet
Airways
Air Deccan -.08 .14 1.000 -.5231 .3631
Air India .06 .13 1.000 -.3544 .4647 Air Sahara -.08 .23 1.000 -.7991 .6391 Go Air .17 .16 .987 -.3364 .6764 Indian Airline -.04 .17 1.000 -.5723 .4837 Indigo -.01 .16 1.000 -.5300 .5033 JetLite -.15 .14 .982 -.5931 .2850 Spice jet .05 .12 1.000 -.3412 .4479 Kingfisher Airline -.06 .13 1.000 -.4917 .3650 Jetlite Air Deccan .07 .14 1.000 -.3606 .5087 Air India .21 .13 .811 -.1912 .6096 Air Sahara .07 .22 1.000 -.6399 .7880 Go Air .32 .16 .547 -.1750 .8231 Indian Airline .11 .16 1.000 -.4112 .6307 Indigo .14 .16 .997 -.3687 .6501 Jet Airways .15 .14 .982 -.2850 .5931 Spice jet .21 .12 .783 -.1777 .5925 Kingfisher Airline .09 .13 1.000 -.3289 .5104 Spice jet Air Deccan -.13 .12 .985 -.5230 .2563 Air India .001 .11 1.000 -.3492 .3528 Air Sahara -.13 .22 1.000 -.8208 .5541
274
Go Air .12 .14 .998 -.3438 .5771 Indian Airline -.10 .15 1.000 -.5817 .3865 Indigo -.07 .15 1.000 -.5383 .4049 Jet Airways -.05 .12 1.000 -.4479 .3412 JetLite -.21 .12 .783 -.5925 .1777 Kingfisher Airline -.12 .12 .992 -.4895 .2562 Kingfishe
r Airline
Air Deccan -.02 .13 1.000 -.4405 .4072
Air India .12 .12 .993 -.2702 .5071 Air Sahara -.02 .22 1.000 -.7241 .6907 Go Air .23 .15 .882 -.2563 .7230 Indian Airline .02 .16 1.000 -.4929 .5310 Indigo .05 .16 1.000 -.4502 .5502 Jet Airways .06 .13 1.000 -.3650 .4917 JetLite -.09 .13 1.000 -.5104 .3289 Spice jet .12 .12 .992 -.2562 .4895
5.10 DESCRIPTIVE STATISTICS OF DIMENSION SATISFACTION WITH
OVERALL QUALITY OF AIRLINE
The mean scores and standard deviation values of dimension satisfaction with overall
quality of airline are mentioned in the Table 5.41. Out of 305 respondents, only 241
respondents mentioned the name of the airline with which service failure was
encountered during travel in domestic sectors of India. There are ten airlines
identified- Air Deccan (now its Kingfisher Red), Air India, Air Sahara (the name
changed is JetLite), Go Air, Indian Airline, Indigo, Jet airways, Spice jet, JetLite and
Kingfisher Airline.
275
Table 5.41 Descriptive Statistics (Mean and Standard Deviation) of Satisfaction
with the Overall Quality of Each Airline
95% Confidence
Interval for Mean
Airline N
Mean
Std.
Deviation
Std.
Error
Lower
Bound
Upper
Bound
Air Deccan 26 2.85 .92 .18138 2.4726 3.2197
Air India 37 3.05 .99 .16415 2.7211 3.3870
Air Sahara 6 3.17 .41 .16667 2.7382 3.5951
Go Air 16 3.75 1.18 .29580 3.1195 4.3805
Indian Airline 14 3.79 1.53 .40841 2.9034 4.6680
Indigo Airline 15 3.07 1.10 .28396 2.4576 3.6757
Jet Airways 25 3.56 1.33 .26508 3.0129 4.1071
JetLite 27 3.37 1.15 .22103 2.9160 3.8247
Spice Jet 45 3.33 1.07 .15891 3.0131 3.6536
Kingfisher
Airline
30 3.87 1.28 .23358 3.3889 4.3444
Total 241 3.37 1.16 .07506 3.2173 3.5130
Comparison of mean values as shown in Table 5.41 establishes that the satisfaction
with the overall quality of Kingfisher Airline, Indian Airline and Go Air are higher
than the Air Deccan, Air India, Air Sahara, Indigo Airline, Jet Airways, JetLite and
Spice Jet.
Table 5.42 - Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig.
2.668 9 231 .006
276
5.10.1 COMPARISON OF AIRLINES ON THE BASIS OF SATISFACTION
WITH THE OVERALL QUALITY OF AIRLINE
This section was conducted with the null hypotheses that there is no significant
difference between the airlines as far as satisfaction with overall quality of airline is
concerned. Using the Analysis of Variance (ANOVA) test the hypotheses were tested,
the results are shown in the Table 5.43. Since the calculated value of F0.05 (2.183) is
greater than the table value (For v1= 9, v2=231, F0.05=0.024), the null hypothesis i.e.
there is no significant difference between the airlines as far as satisfaction with overall
quality of airline is concerned, is rejected in this case. It means that there is difference
between the airlines regarding satisfaction with overall quality of airline. It is implied
that at least one of the airlines is perceived by the passengers to be significantly
different from the rest of the lot.
Table 5.43- One Way ANOVA results for Satisfaction with Overall Quality of
Airline
Sum of
Squares
df Mean
Square
F Sig.
Between Groups 25.54 9 2.84 2.183 .024
Within Groups 300.32 231 1.30
Total 325.87 240
Tukey’s Honestly Significant Difference Test for Multiple Comparisons:
This test identifies the airlines that are significantly different from the rest of the lot.
Since the null hypotheses got rejected, it is necessary to find out as to which airline (s)
is/are significantly different from the rest. The results of Tukey’s HSD Test as shown
in Table 5.44 for multiple comparisons suggest that Kingfisher Airline is significantly
different from Air Deccan as far as satisfaction with overall quality of airline is
concerned.
277
Table 5.44- Tukey HSD Multiple Comparisons Test for Satisfaction with Overall
Quality of Airline
95% Confidence Interval
Airline
Airline (In Comparison with)
Mean Difference
Std. Error
Sig.
Lower Bound
Upper Bound
Air Deccan Air India -.21 .29 .999 -1.1402 .7244 Air Sahara -.32 .52 1.000 -1.9704 1.3294 Go Air -.90 .36 .277 -2.0614 .2537 Indian Airline -.94 .38 .282 -2.1472 .2681 Indigo -.22 .37 1.000 -1.4017 .9607 Jet Airways -.71 .32 .436 -1.7343 .3066 JetLite -.52 .31 .809 -1.5252 .4768 Spice jet -.49 .28 .775 -1.3846 .4102 Kingfisher Airline -1.02(*) .31 .032 -1.9966 -.0444 Air India Air Deccan .21 .29 .999 -.7244 1.1402 Air Sahara -.11 .50 1.000 -1.7159 1.4907 Go Air -.70 .34 .572 -1.7859 .3941 Indian Airline -.73 .36 .568 -1.8747 .4114 Indigo -.01 .35 1.000 -1.1277 1.1025 Jet Airways -.51 .30 .787 -1.4491 .4372 JetLite -.32 .29 .985 -1.2384 .6057 Spice jet -.28 .25 .984 -1.0877 .5292 Kingfisher Airline -.81 .28 .111 -1.7076 .0824 Air Sahara Air Deccan .32 .52 1.000 -1.3294 1.9704 Air India .11 .50 1.000 -1.4907 1.7159 Go Air -.58 .55 .987 -2.3273 1.1606 Indian Airline -.62 .56 .983 -2.3966 1.1585 Indigo .10 .55 1.000 -1.6597 1.8597 Jet Airways -.39 .52 .999 -2.0494 1.2628 JetLite -.20 .51 1.000 -1.8479 1.4405 Spice jet -.17 .50 1.000 -1.7499 1.4166 Kingfisher Airline -.70 .51 .934 -2.3292 .9292 Go Air Air Deccan .90 .36 .277 -.2537 2.0614 Air India .70 .34 .572 -.3941 1.7859 Air Sahara .58 .55 .987 -1.1606 2.3273 Indian Airline -.03 .42 1.000 -1.3689 1.2975 Indigo .68 .41 .812 -.6259 1.9926 Jet Airways .19 .37 1.000 -.9763 1.3563 JetLite .38 .36 .988 -.7697 1.5290 Spice jet .42 .33 .962 -.6437 1.4770 Kingfisher Airline -.12 .35 1.000 -1.2444 1.0111 Indian Airline Air Deccan .94 .38 .282 -.2681 2.1472 Air India .73 .36 .568 -.4114 1.8747 Air Sahara .62 .56 .983 -1.1585 2.3966 Go Air .04 .42 1.000 -1.2975 1.3689 Indigo .72 .42 .796 -.6347 2.0728 Jet Airways .23 .38 1.000 -.9903 1.4418 JetLite .42 .38 .984 -.7844 1.6151
278
Spice jet .45 .35 .954 -.6624 1.5672 Kingfisher Airline -.08 .37 1.000 -1.2601 1.0982 Indigo Air Deccan .22 .37 1.000 -.9607 1.4017 Air India .01 .35 1.000 -1.1025 1.1277 Air Sahara -.10 .55 1.000 -1.8597 1.6597 Go Air -.68 .41 .812 -1.9926 .6259 Indian Airline -.72 .42 .796 -2.0728 .6347 Jet Airways -.49 .37 .947 -1.6831 .6964 JetLite -.30 .37 .998 -1.4768 .8694 Spice jet -.27 .34 .999 -1.3528 .8194 Kingfisher Airline -.80 .36 .447 -1.9520 .3520 Jet Airways Air Deccan .71 .32 .436 -.3066 1.7343 Air India .51 .30 .787 -.4372 1.4491 Air Sahara .39 .52 .999 -1.2628 2.0494 Go Air -.19 .37 1.000 -1.3563 .9763 Indian Airline -.23 .38 1.000 -1.4418 .9903 Indigo .49 .37 .947 -.6964 1.6831 JetLite .19 .32 1.000 -.8215 1.2007 Spice jet .23 .28 .999 -.6820 1.1354 Kingfisher Airline -.31 .31 .992 -1.2932 .6798 JetLite Air Deccan .52 .31 .809 -.4768 1.5252 Air India .32 .29 .985 -.6057 1.2384 Air Sahara .20 .51 1.000 -1.4405 1.8479 Go Air -.38 .36 .988 -1.5290 .7697 Indian Airline -.42 .38 .984 -1.6151 .7844 Indigo .30 .37 .998 -.8694 1.4768 Jet Airways -.19 .32 1.000 -1.2007 .8215 Spice jet .04 .28 1.000 -.8498 .9238 Kingfisher Airline -.50 .30 .827 -1.4627 .4701 Spice Jet Air Deccan .49 .28 .775 -.4102 1.3846 Air India .28 .25 .984 -.5292 1.0877 Air Sahara .17 .50 1.000 -1.4166 1.7499 Go Air -.42 .33 .962 -1.4770 .6437 Indian Airline -.45 .35 .954 -1.5672 .6624 Indigo .27 .34 .999 -.8194 1.3528 Jet Airways -.23 .28 .999 -1.1354 .6820 JetLite -.04 .28 1.000 -.9238 .8498 Kingfisher Airline -.53 .27 .611 -1.3920 .3253 Kingfisher
Airline
Air Deccan 1.02(*) .31 .032 .0444 1.9966
Air India .81 .28 .111 -.0824 1.7076 Air Sahara .70 .51 .934 -.9292 2.3292 Go Air .12 .35 1.000 -1.0111 1.2444 Indian Airline .08 .37 1.000 -1.0982 1.2601 Indigo .80 .36 .447 -.3520 1.9520 Jet Airways .31 .31 .992 -.6798 1.2932 JetLite .50 .30 .827 -.4701 1.4627 Spice jet .53 .27 .611 -.3253 1.3920
* The mean difference is significant at the .05 level.
279
Comparison of Number of Service Failures in Each
Group w.r.t. Airline
32
13
19
29
39
1512
21
4
24
2 1 30
6
1 2 40 1
23
68 8
14
6 69
3
10
0
5
10
15
20
25
30
35
40
45
Air India
Indian A
irline
Jet A
irways
Kingfis
her A
irline
Spice
Jet
Go Air
Indigo
Airline
JetLite
Air Sa
hara
Air Dec
can
Group-1 Service Delivery System Failures Group-2 Customer Needs and Requests
Group-3 Unprompted and Unsolicited Actions
Fig 5.5 Comparison of Number of Service Failures in Each Group w.r.t. Airline
280
Table 5.45- Comparison of Number of Service Failures in Each Group w.r.t.
Airline
Airlines Group-1 Service
Delivery System
Failures
Group-2
Customer
Needs and
Requests
Group-3
Unprompted and
Unsolicited
Actions
Total
Air India 32 02 23 57
Indian Airline 13 01 06 20
Jet Airways 19 03 08 30
Kingfisher
Airline
29 00 08 37
Spice Jet 39 06 14 59
Go Air 15 01 06 22
Indigo Airline 12 02 06 20
JetLite 21 04 09 34
Air Sahara 04 00 03 7
Air Deccan 24 01 10 35
281
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Flanagan, John C. (1954). The Critical Incident Technique. Psychological Bulletin. 51
(July), 327-57.
Forbes, Lukas P., Kelley, Scott W. & Hoffman, K. Douglas. (2005). Typologies of e-
commerce retail failures and recovery strategies. Journal of Services
Marketing, 19(5), 280-292.
Hair, J.F. Jr., Anderson, R.E., Taltan, R.L. & Black W.C. (1988). Multivariate Data
Analysis. Prentice-Hall Inc., Englewood Cliffs, NJ.
Kivela, Jaksa, J. & Chu, Carmen Yiu Ha. (2001). Delivering Quality Service:
Diagnosing Favorable And Unfavorable Service Encounters in
Restaurants. Journal of Hospitality and Tourism Research, 25 (3), August,
251-271.
Malhotra, Naresh K. (2005). Marketing Research: An Applied Orientation, Prentice
Hall of India Private Ltd: New Delhi.
Maxham III, James G. & Netemeyer, Richard G. (2003). Firms Reap What They Sow:
The Effects of Shared Values and Perceived Organizational Justice on
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Sharma, R. D., Gurjeet Kaur & Mahesh C. Gupta. (2001). Measurement of Marketing
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282
Singh, Jagdip. (1988). Consumer Complaint Intentions and Behavior: Definitional and
Taxonomical Issues. Journal of Marketing, January, 93-107.
283
In this chapter, all the key findings supplemented by the conclusions and the
suggestions are discussed, that can provide useful inputs for companies that are
providing services especially airline companies. The conclusions drawn are based on
the data analysis conducted and presented in the previous chapter.
6.1 OBJECTIVES OF THE STUDY AND THEIR ACHIEVEMENT
The following three objectives were set forth for the present research work. In the
section below, we discuss how the objectives set forth were achieved
Objective 1: To study the various types of service failures and their effect on
customer’s satisfaction in aviation industry.
The first objective was to study the various types of service failures encountered by
the customers (passengers) while using services of airlines, travelling by air in
domestic sectors of India and the effect of these failures on their satisfaction. This
objective was achieved in Study I using the Critical Incident Technique. A total of
338 dissatisfying incidents were collected from the customers (passengers) of airlines.
After initial sorting process and classification, twenty-six service failure categories
were identified and classified into three major groups as per Bitner et al’s (1990)
Group and Category Classification by Type of Incident Outcome discussed in detail in
Chapter 5.
CHAPTER-6
CONCLUSION AND SUGGESTIONS
284
It is evident from the literature that Bitner et al’s (1990) classification by Type of
Incident Outcome is applied by researchers in their studies in various service sectors
like Hoffman, Kelly and Rotalsky (1995) collected 373 incidents from customers of
restaurants; Kivela and Chu (2001) collected favourable and unfavourable service
encounters from 417 customers of restaurants; Chung-Herrera, Goldschmidt and
Hoffman (2004) collected customer-reported incidents and 390 employee-reported
incidents; Forbes, Kelly and Hoffman (2005) applied CIT using 377 customer
responses to present ten e-tail failures and eleven e-tail recovery strategies used by e-
commerce service firms.
The effect of service failures on customer satisfaction is analysed in Study II with the
help of mean and standard deviation as presented in Table 5.11. Among all service
failures, the failures that fall under category of employee behaviour in the context of
cultural norms (Mean= 4.62, SD= 0.73) highly effected the satisfaction of customers
i.e. if employee behaved negatively to cultural norms such as equality, honesty and
fairness it definitely effected the satisfaction of customers.
It is the first study in India which identifies the failures in the airline services from
passenger’s perspective.
Objective 2: To study the various coping strategies undertaken by the airlines
to overcome the service failures.
The objective was to study the various recovery actions taken by the airlines to
overcome the service failures encountered by customers. It is derived from Study I
that, generally, customers did not complain regarding the failure they encountered; the
reason may be- lack of time, doubt on the ability of the airline to rectify the situation,
lengthy procedures to follow etc. Only 3% of the respondents are satisfied with the
285
service failure recovery and the recovery strategies used by the airline are
compensation, timely action and fulfil the needs of customers.
This objective was achieved in Study II using the survey method. It is found that,
despite some recovery efforts by airlines, the majority of respondents who
experienced a service failure with a domestic airline (34.5%) indicated that the airline
did nothing to recover from the failure. This finding is similar to that of a study in the
hotel industry, where only 40% of guests reported that the hotel had not offered them
service recovery, suggesting that hotels are not doing enough to resolve service
failures (Lewis & McCann 2004) and in the South African airline industry where
57.7% of the service failure experienced respondents also agreed that domestic airline
did nothing to recover from the failure (Mostert, Meyer and Rensburg, 2009).
If the customer complained to the airline about the service failure, the most common
recovery action taken by airline is apology. And, only 7% of the respondents told that
the problem was corrected by the airline.
Objective 3: To make an impact assessment of recovery efforts in enhancing the
customer’s satisfaction.
The objective was to find out if recovery actions taken by the airlines enhanced the
satisfaction of customers? This objective was achieved by applying regression
analysis on the perceived justice as independent variable and satisfaction with
recovery of complainants as dependent variable. The findings suggest that distributive
and procedural justice have strong influence on customer’s satisfaction with recovery.
It is indicated that customers are satisfied with the outcome of the service recovery
process adopted by airlines and the fairness of the service recovery to rectify the
problem. But the effect of distributive justice on satisfaction with recovery of
286
respondents is stronger than procedural justice. This finding is consistent with results
of previous studies where distributive justice was found to have the greatest impact on
customer satisfaction (Kim et al, 2009; Kau and Loh, 2006; Mattila, 2001). The
interactional dimension of perceived justice is not significantly affecting the
satisfaction with recovery of respondents. It means that how the airline personnel
treated the customers’ through-out the service recovery process is not affecting the
satisfaction of customers.
It is also measured that satisfaction with recovery significantly effected the overall
airline satisfaction.
6.2 VALIDITY OF HYPOTHESIS TESTED
Two separate hypotheses were set up to be tested. The data generated from the present
research has been used to test the hypotheses and check whether they have been
accepted or not.
H1: Service failures have negative effect on customer’s overall satisfaction.
Twenty-six service failures were derived from StudyI and the mean values of service
failures fall in the category employee behaviour in the context of cultural norms (theft
of items which are under the scrutiny of airline staff members, Mean=4.62, SD=0.73),
gestalt evaluation (unfriendly and uncomfortable ambience for travellers, Mean=4.57,
SD=0.69) and response to core service failures (mishandling, missing and exchange
of baggage, printing mistake on ticket, inconvenience due to non-working of air
condition in aircraft, food and beverage not of high quality, Mean=4.54, SD=0.51)
suggests that service failures have negative effect on customer’s overall satisfaction in
287
the context of airline services provided to its customers (passengers). Hence,
hypothesis 1 is accepted.
In addition, effect of seriousness of service failure on customer satisfaction is also
measured with the help of regression analysis. The dependent variable is customer
satisfaction and independent variable is seriousness of service failure. The findings
are presented by regression model (R Square = 0.406) and the β value (0.637) of
seriousness of service failure is significant as suggested by the t-value. Thus, higher
the seriousness of the service failure, higher is the satisfaction level of customer
affected.
H2: Recovery efforts have a positive role in enhancing customer’s satisfaction
levels.
This hypothesis was tested using regression analysis, the dependent variable is
satisfaction with recovery and the independent variable is perceived justice and the
findings are presented by regression models (R Square=0.302) suggests that recovery
efforts in terms of perceived justice have a positive relationship in customer
satisfaction. It is indicated that customers are satisfied with the outcome of the service
recovery process adopted by airlines and the fairness of the service recovery to rectify
the problem. But the effect of distributive justice on satisfaction with recovery of
respondents is stronger than procedural justice. Hence, hypothesis 2, recovery efforts
have a positive role in enhancing customer’s satisfaction is accepted.
288
6.3 CONCLUSION
The demographic profile of the respondents of Study I point out that out of 200
respondents, 69.5% are male and 58.5% belong to the age group 20-40 years. Equal
percentage of respondents i.e. 34.5% belong to the 10,000 to 30,000 and 30,000 to
50,000 income group. Also, majority of the respondents 61.5% belong to occupation
service.
A total of 338 incidents were collected from 200 respondents, the analytic induction
process was used to classify these incidents into Bitner et al’s (1990) group and
category classification by type of incident outcome. 49.7% of the incidents collected
come under the group1, employee response to service delivery system failures; 14.2%
of the incidents come under the group2, employee response to customer needs and
requests and 36.1% of the incidents collected belong to the group3, unprompted and
unsolicited employee actions.
After initial sorting process and classification, twenty-six service failure categories
were identified in second part of the study. All twenty-six service failures classified
into sub categories of three major groups as per the classification given by Bitner et al
(1990).
The demographic profile of the respondents of Study II points out that out of 305
respondents, 65.90% are male, 66.56% belong to the age group 20-40, and 32.13%
belong to income group 20,000 to 40,000. Majority of the respondents (39.34%)
travelled by air less than 5 times in a year. 76 respondents travelled for vacation
purpose and 170 respondents’ preferred low cost carrier for travel.
It is found that the respondents are most serious towards the service failure like ‘theft
of items which are under the scrutiny of airline staff members (Mean=4.61,
289
SD=0.64)’ and it also effected their satisfaction (Mean=4.62, SD=0.73). The most
frequently encountered failures are ‘delay in flight (Mean=2.40, SD=1.04)’, ‘non
availability of right information about flight delay (Mean=2.21, SD=1.09)’, ‘no
provision of any refreshment when there is long delay in flight (Mean=1.93,
SD=0.99)’, ‘cancelled flight without prior notice (Mean=1.70, SD=0.76)’, ‘non-
availability of seat at departure terminal (Mean=1.54, 0.82)’ and ‘overbooking of
passengers (Mean=1.51, SD=0.73)’.
Both male (Mean=4.69, SD=0.62) and female (Mean=4.65, SD=0.53) considered the
service failure ‘missing of baggage’, most serious. The most frequently encountered
service failure is ‘delay in flight (male, Mean=2.47, SD=1.01 and female, Mean=2.27,
SD=1.08)’ and the service failure ‘theft of items which are under the scrutiny of
airline staff members (male, Mean=4.60, SD=0.76 and female, Mean=4.66,
SD=0.66)’ highly effected the satisfaction.
Respondents who travelled by air less than 5 times in a year (Mean=4.68, SD=0.63),
5 to 10 times in a year (Mean=4.7, SD=0.52) and above 15 times in a year
(Mean=4.67, 0.56) considered ‘missing of baggage’ as the most serious service failure
where as the passengers who travelled 5 to 10 times in a year (Mean=4.7, SD=0.61)
and 10 to 15 times in a year (Mean=4.65, SD=0.66) considered ‘exchange of
baggage’ as most serious service failure.
‘Flight delay’ is most frequently encountered by respondents who travelled less than 5
times in a year (Mean=2.18, SD=0.95), 5 to 10 times in a year (Mean=2.51,
SD=1.08), 10 to 15 times in a year (Mean=2.61, SD=1.10) and above 15 times in a
year (Mean=2.58, SD=0.97) by air.
290
‘Theft of items which are under the scrutiny of airline staff members’ is highly
effected the satisfaction of respondents travelled by air less than 5 times in a year
(Mean=4.53, SD=0.87), 5 to 10 times in a year (Mean=4.76, 0.45), 10 to 15 times in a
year (Mean=4.57, SD=0.70) and above 15 times (Mean=4.54, SD=0.98) in a year.
The demographic composition of complainants (N=201) exhibits that there are
66.67% of male, 71.64% belong to age group 20 to 40 and 33.83% belong to income
group 20,000 to 40,000. Also, 39.30% of respondents (complainants) travelled by air
5 to 10 times in a year.
It is found that the complainants preferred voice action (Mean=4.18, SD=0.74) in
comparison to private (Mean=3.94, SD=0.93) and third party (Mean=2.92, SD=0.87)
actions. The result of the independent t-test shows that there is no significant
difference between the voice, private and third party intentions of complainants and
non-complainants.
In ‘Voice’ behaviour intentions, male (Mean=4.18, SD=1.08) are highly intended to
complain to the airline staff members and ask them to take care of the problem where
as female (Mean=4.25, SD=0.89) are highly intended to complain to the airline staff
members about the service failure.
In ‘Private’ behaviour intentions, both male (Mean=4.22, SD=1.19) and female
(Mean=4.30, SD=1.09) are highly intended to speak to friends and relatives about
their bad experience. In ‘Third Party’ behaviour intentions, both male (Mean=3.16,
SD=1.16) and female (Mean=3.27, SD=1.10) are highly intended to complain to a
consumer agency and ask them to make the airline take care of their problem.
It is supported from the factor analysis that the perceived justice of airline passengers
as a multidimensional construct consisting of distributive, procedural and interactional
291
justice. The highest mean score value of interactional justice (Mean=3.30, SD=0.90)
reveals that the complainants strongly agree with the interactional justice of the
airline.
The result of regression analysis was applied on customer satisfaction and seriousness
of the service failure; perceived justice and satisfaction with recovery; overall airline
satisfaction and satisfaction with recovery.
The findings are presented by regression model (R2 = 0.406) and the β value (0.637)
of seriousness of service failure is significant as suggested by the t-value. Thus,
higher the seriousness of the service failure, highly effected is the satisfaction of
customers.
It is also derived that the perceived justice effected the satisfaction of customers after
recovery. The value of R2=0.302 shows that when perceived justice is increased by
one unit, the satisfaction with recovery increases by 30%. It is also evident from the
value of R2=0.302, that 30% of variation (increase) in satisfaction with recovery is
accounted for by distributive, procedural and interactional justice.
On the other hand, the regression analysis shows that when satisfaction with recovery
is increased by one unit, the overall airline satisfaction increases by 6%. The value of
R2=0.068 shows that only 6% of variation in overall airline satisfaction is accounted
for by satisfaction with recovery. Though the overall airline satisfaction has increased
after satisfaction with recovery, yet the results of regression reflect that satisfaction
with recovery contribute very little (6%) to bring about this change. There might be
other factors which also influenced the customers’ overall airline satisfaction like fare,
past experience etc. Therefore, although satisfaction with recovery leads to an
increase in the overall airline satisfaction, yet it is not the only variable.
292
As far as recovery strategies is concerned, it was established from the literature
review that organisation can use a number of strategies to recover from service
failures, including communicating with customers to provide feedback and offer an
explanation for the failure (Boshoff & Staude, 2003; La & Kandampully 2004) and
that the organisation should apologise for the failure (Boshoff & Leong, 1998; Mattila
& Cranage, 2005; Smith et al, 1999). The findings of this study support these service
recovery strategies in that the majority of the respondents (34.5%) reported that the
airline did nothing to the problem faced by them. The most often recovery action
taken by the airlines is apology (27.4%).
After comparison of mean values of overall airline satisfaction of all the airlines, the
overall airline satisfaction of JetLite (Mean=4.07, SD=0.27), Air Deccan (now it as
Kingfisher Red, Mean=4.00, SD=0.40), Air Sahara (the name changed to JetLite,
Mean=4.00, SD=0.00) and Kingfisher Airline (Mean=3.98, SD=0.36) are higher than
the Indian Airline (X=3.96, SD=0.50), Indigo Airline (Mean=3.93, SD=0.26), Jet
Airways (Mean=3.92, SD=0.62), Spice jet (Mean=3.87, SD=0.60), Air India
(Mean=3.87, SD=0.40), Go Air (Mean=3.75, SD=0.89).
The results of ANOVA (F0.05=0.760) rejected the null hypothesis that there is no
significant difference between the airlines as far as overall airline satisfaction is
concerned. It means that there is difference between the airlines regarding overall
airline satisfaction. It is implied that at least one of the airlines is perceived by the
respondents to be significantly different from the rest of the lot. And the results of
Tukey’s HSD Test for multiple comparisons suggest that all the airlines are
significantly different from the rest of the lot as far as overall airline satisfaction is
concerned.
293
The comparison of the mean score values of satisfaction from the overall quality of
airline showed that satisfaction from Kingfisher Airline (Mean=3.87, SD=1.28),
Indian Airline (Mean=3.79, SD=1.53) and Go Air (Mean=3.75, 1.18) are higher than
the Jet Airways (Mean=3.56, SD=1.33), JetLite (Mean=3.37, SD=1.15), Spice jet
(Mean=3.33, SD=1.07), Air Sahara (Mean=3.17, SD=0.41), Indigo Airline
(Mean=3.07, SD=1.10), Air India (Mean=3.05, SD=0.99), Air Deccan (Mean=2.85,
SD=0.92).
The results of ANOVA (F0.05=2.183) rejected the null hypothesis that there is no
significant difference between the airlines as far as satisfaction with overall quality of
airline is concerned. It means that there is difference between the airlines regarding
satisfaction with overall quality of airline. The results of Tukey’s HSD Test for
multiple comparisons suggest that Kingfisher airline is significantly different from Air
Deccan as far as satisfaction with overall quality of airline is concerned.
6.4 RECOMMENDATIONS
The Critical Incident Technique is a useful tool for gathering primary data of
subjective nature from respondents. It can, through careful coding, reveal both
quantifiable data and bountiful descriptions of a qualitative kind. Analytical
categories derived from such sources increase validity and explanation. Reliability is
also enhanced by defining the service failure categories in the classification given by
Bitner et al (1990).
The results of this study may prove useful to airline companies in a number of
different ways. First, it is revealed from the results that the service failures are
inevitable whether the services are provided by full service airlines like Air India, Jet
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Airways, Kingfisher Airline or low cost carriers like Kingfisher Red, Spice Jet, Go
Air, Indigo, JetLite. The prime motive of a person to travel by air is to save time and
expect efficient services when he spends more on by deciding travel by the costliest
mode of transportation. The results of this study revealed that the service delivery
system failures are the most encountered by passengers. The reason may be a core
service failure (mishandling of baggage, missing and exchange of baggage), a
particular service which is expected by the customers but is unavailable (cancelled
flight without prior notice, no provision of any refreshment when there is long delay
in flight) and unreasonably slow services (delay in refund of cancelled ticket, delay of
baggage delivery).
It is found that all customers didn’t complain (Goodman and Ward, 1993); customer
complaints serve as the main indicator of service failure because complaints provide
an organisation with the opportunity to recover from service failure and prevent
negative behaviours on the part of customers. So, the airline companies should
encourage the customers to complain. Make it easy for them to complain and give
them outlets to complain. A well-implemented recovery has the potential to make a
customer more satisfied than if no service failure had occurred. Make the recovery fit
the failure.
Examining how company policies are perceived is important, previous research has
shown that customers are sensitive to violations of distributive, procedural and
interactional justice (Tax et al, 1998). The results of the study showed that the airline
customers are more sensitive towards distributive and procedural justice as compared
to interactional justice. Invariably, the problem is not in the company policy itself but
in the perception and interpretation of the policy. It may be the case that some
company policies may inhibit the provision of high service quality and good recovery.
295
The importance of service staff in the success of the service encounter and in the
service recovery effort has constantly been cited in the literature. The airline industry
needs satisfied customers to survive in the fierce competition of today. Employees
should be trained to prevent failures in the first place and if failures do occur, to
recover from failures in an appropriate and satisfying manner. Staff training is
essential to be able to reach the above, and training with focus on service recovery is a
special area which could act as a competitive advantage.
Airline management should consider some pre-defined strategies to mitigate the
negative effects of service failure. When analyzing the services offered, management
should identify those areas with in the service encounters where the customer can be
empowered. Customers can be empowered by giving them choices and information to
make good choices, which will improve their service experience. This will reduce the
chance of service failures and if failure occurs, it will reduce customers’ negative
feelings toward the service provider through self-attribution and respect for
disclosure.
The lack of service recovery (or inadequate service recovery) will, therefore, have a
direct influence on the airline’s profitability, since customers will not be retained,
despite the airline’s marketing efforts. Airlines’ service recovery efforts do not
necessarily need to incur considerable costs, as customers may be satisfied by simply
keeping them informed and explaining the reason for the failure or offering an
apology for the failure. Airlines could, through effective service recovery, possibly
retain their customers in their competitive industry.
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6.5 RESEARCH CONTRIBUTIONS
Very limited work has been done on the Indian aviation industry and no research
work has been found in India to study the service failures and recovery actions taken
by the domestic airlines from customer’s perspective and their effect on satisfaction.
This study is an attempt in this direction. The major implications of this study are-
The results obtained in this study have important implications for airline managers
and suggests that they should consider the service failures seriously and take prompt
actions to retain customers and survive in this competitive industry.
The current study has made a meaningful contribution to the service failure and
recovery literature since it deals with the measurement of the influence of service
failure and recovery on customer satisfaction, using critical incident technique and
survey method.
The methodology followed in the present research in identifying the service failures
and recovery actions taken by airline companies strongly supports the classification of
Incident Outcome given by Bitner et al (1990).
6.6 LIMITATIONS/FUTURE RESEARCH DIRECTIONS
Several limitations of this study must be recognised, first owing to the airline-oriented
focus of this study, these results cannot be generalized for other service industries.
Future work should consider the other service providing sectors like restaurant, hotels,
banks etc. Secondly, the incidents collected were from the customer’s perspective i.e
the outcome of the interaction between the customer and services provided by
airlines. Future research should consider the non-human elements (e.g. equipment,
297
facilitating goods) in service encounter-dis/satisfaction. Also, study the incidents from
service provider’s perspective in the same industry or other service industries.
Third, this study classified only dissatisfactory incidents in the classification of
Incident Outcome given by Bitner et al (1990) and it becomes the base for other
studies like Kelly, Hoffman and Davis (1993), Bitner, Booms and Mohr (1994),
Hoffman, Kelly and Rotalsky (1995), Kivela and Chu (2001), Lewis and Clacher
(2001), Hoffman, Kelly and Chung (2003), Mueller, Palmer, Mack and Mc Mullan
(2003), Holloway and Beatty (2003), Chung-Herrera, Goldschmidt and Hoffman
(2004), Forbes, Kelly and Hoffman (2005). Future research can make its own
classification system based on type of incidents.
Fourth, another limitation of this study is that it is limited to study the effect of service
failure on customer satisfaction only but future research can contribute to study the
effect of service failure recovery on repurchase intentions, loyalty, value and word of
mouth publicity. Fifth, the study was further limited by identifying only
dissatisfactory incidents that happened with the passengers from the services provided
by the airlines. Future research can examine not only both satisfying and dissatisfying
incidents that occurred between passengers and airline services but also of the airport
services or of the peer passengers in particular in Indian aviation industry or other
service industries.
It is the limitation of the study to consider the service failures encountered by
passengers due to congestion and crowd in the airports that put pressure on the service
supplier to provide effective service.
Sixth, researchers should also study failures and recoveries using different
methodologies. The CIT method provides an informative starting point for research in
298
this area; future studies might investigate this phenomenon through survey research
methods and experimental methods (e.g. Goodwin and Ross, 1992).
299
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Encounter: Diagnosing Favorable and Unfavorable Incidents. Journal of
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Encounters: The Employee’s Viewpoint. Journal of Marketing, 58
(October), 95-106.
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dimensions of service recovery: an experimental study. International
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and its outcomes. South African Journal of Business Management, 34 (3),
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Questionnaire (Study I)
Dear Respondent
This research is being conducted as a part of PhD work titled “Service Failures and
Recovery Strategies- A Study of Indian Aviation Industry Since 2000”. The
data/information collected is purely for academic work and shall be kept confidential.
Demographic Profile of Respondents:
Belongs to: City:……………………….. State:……………………………
1. Gender: (a) Male (b) Female
2. Age: (a) below 20 (b) 20-40 (c) 40-60 (d) above 60
3. Income: (a) below Rs.10,000 (b) Rs.10,000-30,000
(monthly) (c) Rs. 30,000-50,000 (d) above Rs.50,000
4. Occupation: (a) service (b) business (c) student (d) others (…………….)
Think of the time when, as a passenger, you came across an incident that stands out in
your mind as either a particularly satisfying/positive or dissatisfying/negative
experience with the airline in domestic sectors of India during the last five years.
1. Demographic Profile
2. Was this a satisfying/dissatisfying experience?
3. Please describe the circumstances leading up to this incident.
4. Describe what happened during the incident. What specific details do you
recall that made this experience memorable for you?
5. What was the outcome of the incident?
6. How could this experience have been improved (if at all)?
7. Did you complain to the organization about this incident? If yes, how did
you complain? If no, why not?
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Questionnaire (Study II)
Dear Respondent
This research is being conducted as a part of PhD work titled “Service Failures and
Recovery Strategies-A Study of Indian Aviation Industry since 2000”. The
data/information collected is purely for academic work and shall be kept confidential.
Demographic profile of the Respondent:
� Gender: Male Female
� Age (in years): (a) less than 20 (b) 20-40 (c) 40-60 (d) above 60
� Income (in Rupees): (a) less than 20,000 (b) 20,000-40,000
(per month) (c) 40,000-60,000 (d) above 60,000
� Travel Frequency by air: (a) less than 5 (b) 5-10 (c) 10-15 (d) above 15
(in a year)
� Travel purpose: (a) Business (b) Visit (c) Vacation
(d) Education (e) Other
� Do you prefer: (a) Low Cost Airline (b) Full Cost Airline
� Which is your most preferred airline?
(a) Air India (b) Jet Airways (c) Kingfisher Airlines
(d) Go Air (e) Indigo (f) Spice Jet
(g) Jetlite (h) Any other……………..
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A: Indicate your level of seriousness w.r.t. each service failure by encircling at appropriate column. 1= Not at All Serious (NAS) , 2= Not
Very Serious (NVS), 3= Neutral (N), 4= Serious (S), 5= Very Serious (VS)
B: Indicate how frequently you had encountered the following service failure by encircling at appropriate column. 1= Never (N), 2=
Occasionally (Oc), 3= Sometimes (S), 4= Often (Of), 5= Always (A)
C: Do you think that the following service failure effected your satisfaction, indicate by encircling at appropriate column. 1= Strongly
Disagree (SD), 2= Disagree (D), 3= Neutral (N), 4= Agree (A), 5= Strongly Agree (SA)
A B C 1= Not at All Serious (NAS) , 2= Not Very Serious (NVS), 3= Neutral (N), 4= Serious (S), 5= Very Serious (VS)
1= Never (N), 2= Occasionally (Oc), 3= Sometimes (S), 4= Often (Of), 5= Always (A)
1= Strongly Disagree (SD), 2= Disagree (D), 3= Neutral (N), 4= Agree (A), 5= Strongly Agree (SA)
Type of Service Failure
NAS NVS N S VS N Oc S Of A SD D N A SA 1. Flight Delay 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 2. Non-availability of right information about flight delay
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
3. Mishandling of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 4. Delay of baggage delivery 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 5. Missing of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 6. Exchange of baggage 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 7. Unfriendly & unhelpful attitude of ground staff members
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
8. Unfriendly & unhelpful attitude of crew members
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
9. Mishandling of carry-on items/delicate items
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
10. Food & beverage not of high quality 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 11.Provision of food not on time 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 12. Non-availability of seat at departure terminal
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
13. Overbooking of passengers 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 14. Unfriendly & Uncomfortable ambience 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
305
for the travelers 15. Inconvenience due to non working of air condition in aircraft
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
16. No provision of any refreshment when there is long delay in flight
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
17. Less leg space 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 18. Inefficient staff 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 19. Delay in refund of cancelled ticket 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 20. Cancelled flight without prior notice 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 21. Rescheduling without prior notice 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 22. Printing mistake on ticket 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 23. Allow to carry-on items at one sector & deny the same at another sector by the same airline
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
24. Staff shows unwillingness to assist the customer in solving the problem arises due to customer error
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
25. Co-passengers show interrupted behavior
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
26. Theft of items which are under the scrutiny of staff members
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
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Section II
Think back about the latest dissatisfying/negative air travel experience that you came across, please describe it:
………………………………………………………………………………………………………………………………………………………………………
………………………………………………………………………………………………………………………………………………………………………
……………………………………………………………………………………………………………………………….
How likely is it that you would: -
Least Less Not More Most
Likely Likely Likely Likely Likely Likely (1) (2) (3) (4) (5) (6)
1. Forget about the incident and do nothing 1 2 3 4 5 6 2. Definitely complain to the airline staff members 1 2 3 4 5 6 3. Decide not to travel by that airline 1 2 3 4 5 6 4. Complain to the airline staff members and ask them to take care of your problem 1 2 3 4 5 6 5. Speak to your friends and relatives about your bad experience 1 2 3 4 5 6 6. Convince your friends and relatives not to travel by that airline 1 2 3 4 5 6 7. Complain to a consumer agency and ask them to make the airline take care of your problem 1 2 3 4 5 6 8. Write a letter to the local newspaper about your bad experience 1 2 3 4 5 6 9. Report to the consumer agency so that they can warn other consumers 1 2 3 4 5 6 10. Take some legal action against the airline 1 2 3 4 5 6
307
Did you complain to the airline about the service failure incident? YES NO
Please mark at the appropriate recovery strategy: S.No. Recovery Strategy Used by the airline against the
service failure experienced by you
That you think that
airline should do
1. Apologized 2. Corrected problem 3. Explanation provided 4. Immediate action 5. Did nothing 6. Airline took responsibility of the problem 7. Followed up 8. Redirected the problem 9. Compensation provided 10. Exceptional treatment
Indicate by encircling at appropriate column: 1= Very Strongly Disagree (VSD), 2= Strongly Disagree (SD), 3= Disagree (D), 4= Neutral (N), 5= Agree (A), 6= Strongly Agree (SA), 7= Very Strongly Agree (VSA) S.No. Items VSD
(1)
SD
(2)
D
(3)
N
(4)
A
(5)
SA
(6)
VSA
(7)
1. The incident caused me problems, the airline effort to fix it resulted in a very positive outcome for me
2. The final outcome I received from airline was fair, given the time & hassle 3. Inconvenience caused by the problem, the outcome I received from airline was fair 4. The service recovery outcome that I received in response to the problem was more than fair 5. Despite the hassle caused by the problem, the airline responded fairly and quickly 6. I feel airline responded in a timely fashion to the problem 7. I believe airline has fair policies & practices to handle problems 8. With respect to its policies & procedures, the airline handled the problem in a fair manner
308
9. In dealing with my problem, the airline personnel treated me in a courteous manner 10. During their effort to fix my problem, the airline employees showed a real interest in trying to
be fair
11. The airline employees worked as hard as possible for me during the recovery effort 12.
The airline employees were honest and ethical in dealing with me during their fixing of my problem
Indicate by encircling at appropriate column:
1= Very Strongly Disagree (VSD), 2= Strongly Disagree (SD), 3= Disagree (D), 4= Neutral (N), 5= Agree (A), 6= Strongly Agree (SA), 7= Very Strongly Agree (VSA) S.No. Items VSD
(1)
SD
(2)
D
(3)
N
(4)
A
(5)
SA
(6)
VSA
(7)
Overall Firm Satisfaction 1. I am satisfied with my overall experience with airline 2. As a whole, I am not satisfied with airline Satisfaction with Recovery 1. In my opinion, the airline provided a satisfactory resolution to my problem on this particular
incident
2. I am not satisfied with airline’s handling of the problem 3. Regarding the incident that I described above, I am satisfied with the airline
Indicate by encircling at appropriate column: 1= Very Dissatisfied(VD), 2= Somewhat Dissatisfied (SD), 3= Dissatisfied (D), 4= Neutral (N), 5= Satisfied (S), 6= Somewhat Satisfied ( SS), 7= Very Satisfied (VS)
S.No. Item VD (1)
SD (2)
D (3)
N (4)
S (5)
SS (6)
VS (7)
1. How satisfied are you overall with the quality of airline?
309
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