The Impact of Supply Chain Management Practices in Total · PDF fileQuality Management...

ORIGINAL ARTICLE

The Impact of Supply Chain Management Practices in TotalQuality Management Practices and Flexible System PracticesContext: An Empirical Study in Oil and Gas Industry

Fauzia Siddiqui • Abid Haleem • Chitra Sharma

Received: 2 August 2011 / Accepted: 1 February 2012 / Published online: 17 May 2012

� Global Institute of Flexible Systems Management 2012

Abstract A supply chain management (SCM) is an

ongoing process and needs continuous efforts to get the

desired results. SCM practices has become a potentially

valuable way of securing total quality management (TQM)

practices and flexible system (FS) practices since compe-

tition is no longer between organizations, but among sup-

ply chains. Poor SCM erodes profitability, delays projects,

and limits production. This research conceptualizes and

develops two dimensions of SCM practices (strategic

relationship and customer’s relationship) and tests the

relationship of SCM practice in terms of SCM program,

TQM practices, and FS practices. Structured questionnaire

has been developed on the basis of extensive literature

survey. Data for the study were collected from major

players of oil and gas industries and the relationships

proposed in the framework were tested using SPSS-16

software. The hypotheses testing for selected variables

have been done by using stepwise regression analysis.

Further correlation was done among the selected vari-

ables, reveals that SCM practices is positively correlated

with TQM Practices and FS Practices. TQM practice and

FS practices are vital and play crucial role in SCM

practice. The validated model so developed shows the

relationship among the selected variables. SCM program

has been observed to be directly linked with FS practices

and not by any other variable. This observation has

emerged from the statistical analysis of the data collected

from questionnaire based survey. India today remains one

of the least explored regions with well density per thousand

sq. kms. Being among the lowest, it is also evident that vast

amount of capital investments are necessary if exploration

efforts are to be substantially augmented. Therefore, there

is need of FS practices and SCM practices to attract both

the national oil companies, as well as, private sector oil

companies to invest in this critical area.

Keywords Customer relationship �Flexible system practices � Indian oil and gas industry �Supply chain management practices � Flexibility �Strategic management � Total quality management

Introduction

Supply chain management (SCM) can be defined as the

configuration, coordination and continuous improvement of

an organized set of operations. Its goal is to provide max-

imum customer service at the lowest cost possible, where a

customer is anyone who uses the output of a Process. Since

the goal of a company is to maximize profits, it must weigh

the benefits versus the costs of its decisions along the supply

chain. Very few industries can benefit more from maxi-

mizing supply chain efficiencies than the oil and gas com-

panies (Chima and Hills 2007). The understanding and

practicing of SCM has become an essential prerequisite for

staying in the global race as well market for enhancing

profitability (Moberg et al. 2002). The concept of SCM has

F. Siddiqui (&)

Department of Manufacturing Technology, JSS Academy

of Technical Education, Noida 201301, U.P., India

e-mail: [email protected]

A. Haleem

Department of Mechanical Engineering, Faculty of Engineering

and Technology, Jamia Millia Islamia, New Delhi 110 025, India


C. Sharma

Department of Mechanical and Automation Engineering,

IGIT, GGSIPU, New Delhi 110 025, India


123

Global Journal of Flexible Systems Management (March 2012) 13(1):11–23

DOI 10.1007/s40171-012-0002-9

been considered from different points of view as described

in the literature (Croom et al. 2000), such as purchasing and

supply management, logistics and transportation, operation

management, marketing, organizational theory, and man-

agement information systems.

The purpose of this work is to empirically develop and test

a framework by identifying the relationships among total

quality management (TQM) practices, flexible system (FS)

practices and SCM program and their impact on SCM

practices in oil and gas industry. The oil and gas sector is one

of the six core industries in India that has significant forward

linkages with the entire economy. India has been growing

annually and is committed to maintain the growth momen-

tum in the years to come. This would translate into India’s

energy needs growing many times in the years to come

(KPMG Report-2009). Hence, there is an emphasized need

for wider and more intensive exploration for new finding,

more efficient and effective recovery, a more rational and

optimally balanced global price regime—as against the

rather wide upward fluctuations of recent times, and a spirit

of equitable common benefit in global energy cooperation.

The framework developed has been tested empirically,

using data collected from 309 respondents to a survey

questionnaire in oil and gas industry. SPPS-16 is used to test

the hypothesized relationships. In the study three variables

define TQM Practices (top management, employee empow-

erment and team work). The FS Practices in terms of inter-

departmental task forces, standard operating procedures and

flexible approach towards process, routing, volume, product

and expansion has been considered. In SCM Program the

variables in terms of effective customer’s relations, co-

management activities and building trust, the variables are

selected by implementing the factor analysis.

The remainder of this paper is organized as follows:

second section gives a brief review of the Indian oil and gas

industry, the figure of energy basket and gross turn over in

industry for 2009 is also provided. Thew third section

presents a literature review underlying each dimension of

SCM practices; discuss the concepts of FS practices and

TQM practices. In fourth, fifth, sixth and seventh major

sections problem definition, research methodology, design

of questionnaire and data analysis are discussed. In later

sections correlation, stepwise regression analysis along

with discussion of hypothesis is then presented followed by

the implication of the study.

Oil and Gas Sector in India: An Overview

The oil and gas sector in India presents a significant oppor-

tunity for investors and is expected to demonstrate robust

growth with the Indian economy (Hussain et al. 2006). The

new exploration licensing policy (NELP), conceived to

address the increasing demand supply gap of energy in India,

has proved to be successful in attracting the interest of both

domestic and foreign players. Companies therefore have

recognized that improved supply chain efficiencies represent

a huge area for cost savings, specifically in the logistics area;

they are estimated to be an average between 10 and 20 per-

cent of revenues (Hamilton 2003). Also, companies believe

that the supply chain in which they participate as customers

and suppliers is what creates competition rather than indi-

vidual companies (Whitfield 2004; Lang 2004; Morton

2003; Collins 1999; Coia 1999).

India is the fifth largest energy consumer in the world

with primary commercial energy consumption in 2004 of

375.8 million metric tonnes of equivalent (MMTOE)

(Source: KMPG-statistical survey 2009). In 2004, the

consumption of oil and gas formed a major percentage in

the world energy consumption basket. In India, however,

coal dominated the consumption basket. The national oil

companies (NOCs), Oil and Natural Gas Corporation Ltd.

(ONGC) and Oil India Ltd. OIL dominate upstream seg-

ment with 80 % contribution of oil and natural gas pro-

duction of India. The present energy basket of India looks

somewhat like this and is presented in Fig. 1.

GAIL (India) Limited, is India’s flagship natural gas

company, integrating all aspects of the natural gas value

chain (including exploration & production, processing,

transmission, distribution and marketing) and its related

services. GAIL has a market share of 78 % of the gas

transmission business and 70 % of the gas marketing busi-

ness in India. India now ranks amongst the most preferred

destinations for many of the major oil and gas players. The

prominent oil and gas players in the Indian Market in terms of

their turnover are: ONGC, IOCL, BPCL, HPCL, GAIL, OIL,

RIL, MRPL, GSPC, Essar, Cairn Energy etc.

Figure 2 shows the TQM practice and FS practice are

vital and important for SCM practices in effective and

efficient manner. In this paper efforts have been made to

find the exact relationship between TQM practice, SCM

and FS practice in terms of SCM practice in the Indian oil

and gas sector. It examines six research hypotheses and for

Fig. 1 Present Energy basket of India.

Source: (British Gas-Report, 2009)

12 Global Journal of Flexible Systems Management (March 2012) 13(1):11–23

123

the purpose of investigating these issues. The consequences

section deals with the literature review for assessing SCM

practices was developed.

Literature Review

A literature review has been done to identify the key

research issues of SCM practices, TQM practices, and their

role in FS practices. The research paper and articles were

reviewed in the areas of Customer’s relationship, strategic

relationship, top management, team work, effective cus-

tomer’s relation, standard operating procedure and inter-

departmental tasks, employee empowerment, building trust

and marketing. A brief review of SCM program, TQM

practice FS practices, SCM Practices and its impact on oil

and gas industry has also been covered.

Supply Chain Management Practices

The challenge for firms today is not just to take up a SCM

initiative but also to implement it successfully as the future

shall see a competition among supply chains. (Ellaram and

Cooper 1990) defined that SCM is an integrative philoso-

phy to manage the total flow of distribution channel from

supplier to ultimate user. (Mohanty and Deshmukh 2005)

stated that SCM is a loop that starts with customers and

ends with customer; through the loop flow all materials,

finished goods, information, and transaction’s. Today’s

businesses have become extremely complex. SCM has

received ever-growing interest both in the literature as well

as from industrial practice (Oliver & Weber 1992).

Customers are demanding more variety, better quality and

service, including both reliability and faster delivery.

Technological developments are occurring at a faster pace,

resulting in new product innovations and improvement in

manufacturing processes (Tarofder and Ashiquzzaman

2008). The latest evolution of SCM practices, which includes

supplier partnership, outsourcing, continuous flow, and

information technology sharing (Donlon 1996). SCM prac-

tices represent use of purchasing, quality, and customer

relations (Tan et al. 1998). The concept of SCM practices

include agreed vision and goal, information sharing, coop-

eration, long term relationship and agreed supply chain

leadership (Min and Mentzer 2004), The three main strategic

imperatives that emerged in this century are low cost, high

quality and improved responsiveness (both delivery time and

flexibility of product delivery) (Aquilano et al. 1995).

Flexible System Practices

Flexibility in supply chain execution means that the appli-

cations must change and adapt as quickly as businesses

around them (Gupta and Nehra 2002). With this increased

flexibility, manufacturing systems are able to accommodate

different routing and have the choice to choose the best, are

suggested (Fawzan 2005). Four flexible conditions are

associated with the manufacturing of a part, namely

sequencing flexibility, machine flexibility, routing flexibil-

ity, and processing flexibility (Sethi and Sethi 1990).

Sequencing flexibility refers to the possibility of altering the

sequence of manufacturing operations for a given part, tak-

ing into account the restrictions of the design specification.

There are machine flexibility, process flexibility, product

flexibility, routing flexibility, volume flexibility, expansion

flexibility, operation flexibility and production flexibility

(Ozmutlu and Harmonosky 2005) justify a flexible manu-

facturing systems relatively high investment, it is of utmost

important to make full use of the flexibilities that the FMS

offer is routing flexibility, which is the capability of pro-

cessing a part type using alternate routing through machines

(Ghosh and Gaimon 1992). Pankaj (1991) reflects the view

that the flexibility of a system is a function of the technology

as well as how well the system is managed with the global-

ization of manufacturing sector. Sushil (1997) carried a

survey that the main aim of Flexible Systems Management

is to facilitate the actor in liberation from ignorance by

understanding the dynamic interplay of forces. Mandelbaum

and Buzacott (1990) deemed flexibility as required in a

‘‘system or process so that it is able to respond change in the

system’s environment or a change in the decision maker’s

perception of reality’’. The changes in the environment could

be in the form of demand fluctuations, machine breakdowns

absenteeism of the skilled labour (Wadhwa and Rao 2002).

Total Quality Management Practices

Total quality management (TQM) is both a philosophy and

a set of principles that represents the foundation of a

continuously improving organization (Calingo 1995). It

involves everyone in the organization and extends to sup-

pliers as well as customers. In a TQM environment the

customer is the focal point and customer satisfaction is the

driving force (Stevenson 1993). TQM is a management

strategy aimed at embedding awareness of quality in all

Fig. 2 TQM practice & FS practices in terms of SCM practices.

(Fauzia and Haleem 2009)

Global Journal of Flexible Systems Management (March 2012) 13(1):11–23 13

123

organizational processes. Customer focus, process

improvement and total involvement are the three funda-

mental principles of TQM (Tenner and Toro 1992). At

organisation level, however (House1998) suggests that

empowerment could be achieved through employee selec-

tion and training programs designed to provide required

technical skills together with a culture that encourage self-

determination and collaboration instead of competition.

Schlesinger et al. (1991a, b) found that employee’s per-

ception of service quality positively relates to job satis-

faction, job commitment, and pride of workmanship.

Related finding reported by (Tornow and Wiley 1991) are

employee attitudes-measured by feelings about reward for

performance, work itself, management practices, satisfac-

tion with the company, work group climate, and a culture

for success are related to customer satisfaction.

After TQM has been in use, it’s very common for parts

to be redesigned so that critical measurements either cease

to exist, or become much wider. The last decade has wit-

nessed the increased acceptance and use of TQM in the

service sector (Milakovich 1995), with service quality

being an important factor for growth, survival and success

(Quinn and Humble 1993; Donaldson 1995; Rust et al.

1995). Hosein Fallah (1993) reviews quality system mod-

els, introduces AT&T’s Total Quality Approach (TQA),

and describes the TQA implementation strategy.

The Table 1 lists the factors of TQM practices and FS

practices which are considered as a part of micro variables

in the present study and these micro variables are supported

by the authors as to how these factors are important to

TQM practices and FS practices. Among these micro

variables the FS practices variables are highly affecting the

performance in terms of SCM practices in terms of cus-

tomer’s relationship and strategic relationship in oil and

gas industry. Among the above six factors role of flexible

approach and interdepartmental tasks are strongly related

to SCM practices.

Oil and Gas Scenario

Very few industries can benefit more from maximizing

supply chain efficiencies than the oil and gas companies

(Chima and Hills 2007). In this sector, there is a need to

ensure that each entity along the supply chain can respond

quickly to the exact needs of its customers. On the other

hand, one of its weaknesses is that each entity is likely to act

in its best interests to optimize its own profit. Oil SCM is

intrinsically associated with integrated planning. First, it is

concerned with functional integration of acquisition of raw

material (crude oil), manufacturing (refining), transporta-

tion, and warehousing activities (Shapiro 2006). The steadily

increasing global demand for oil and its derivatives such as

petrochemicals has enabled companies providing these

products to reach more customers and increase their market

share and profitability. This boom in global demand along

with the ease of international trade and the inflexibility

involved in the petroleum industry’s supply chain has made

its management more complex and more challenging (Coia

1999; Morton 2003). Despite the importance of SCM and its

growing complexity, the petroleum industry is still in the

development stage of efficiently managing their supply

chains. The oil and petrochemical industry’s insight into the

supply chain is still in its infancy (Schwartz 2000). However,

even with the inflexibility and complexity involved in the

industry’s supply chain, there is a lot of room for improve-

ment and cost reduction, specifically in its logistics area.

A large number of articles using surveys-based empiri-

cal methods have also been published in the area of FS,

Table 1 List of major factors constituting TQM practice and FS practice

Sub constructs Definition Literature

Employee

empowerment

Employee empowerment means turning ‘‘front line’’ loose and encouraging and

rewarding Employees to exercise initiative and imaginative

Zemke and Schaaf (1989)

Top Management Top Management in quality, to act on suggestions, to reach common goals and avoid

conflict, to work with internal and external customers

Taveira et al. (2003)

Teamwork Team work is defined as the extent to which the people work for a specific purpose is

used in the intended. For example in TQM training, successful team work occurs if

the trainee can apply the knowledge and skills learned in the formal training

sessions to working on the problem faced by the TQM team

Tesluk et al. (1995)

Standard operating

Procedures

Logically flexible production technologies are needed to support continuous

improvement as top management strategy is intended to produce continuous

improvement

McLaughlin and Clark (1994)

Interdepartmental tasks Interdepartmental task firm performance is contingent upon how well the technology

fits the organization of work and the firm’s HR systems

Ichniowski et al. (1996)

Flexible approach Flexible approach that consist of skill variety achieved through job rotation and job

autonomy is defined in terms of taking responsibility for quality and continuous

improvement

MacDuffie and Krafcik (1992)


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TQM and SCM. The integration of these three factors was

shown in the review paper ‘‘role of SCM in context of

TQM in FS: A state of the art literature review’’ (Fauzia

and Haleem 2009).

Problem Definition

The aim of the present work is to understand and analyze

SCM strategy, TQM practices and FS approach and their

impact on SCM practices on oil and gas industry, in

national capital region. Following are the major research

objectives:

The scope of this study relates SCM, in terms of SCM

program and SCM practices of final product, to TQM

practice and FS practice in oil and gas industry. The study

is concentrated only on the above mentioned factors and

their relationships. The area covered in the study is only

national capital region (NCR).

Research Hypothesis Formulation

The questionnaire was developed on the basis of the model

which shows the integration between the three factors SCM,

TQM and FS systems (Fauzia and Haleem 2009), based on

these factors a pilot survey and the industry expert opinion

were taken to identify the critical factors on that basis we

formulate the following three sets of hypotheses to express

the relationship between the SCM practices, TQM practices,

SCM program and FS practices. In total, six hypotheses are

formulated for testing and validation of the model.

Predictors of Organization’s SCM Practices

A1: Organization’s SCM practices are affected by FS

Practices in oil and gas industry.

A2: Organization’s SCM practices are affected by TQM

practices in oil and gas industry.

A3: Organization’s SCM practices are affected by SCM

program in oil and gas industry.

Predictors of Organization’s TQM Practices

B1: Organization’s TQM practices are affected by FS

practices in oil and gas industry.

B2: Organization’s TQM practices are affected by SCM


Predictors of Organization’s FS Practices

C1: Organization’s FS practices are affected by SCM


Research Methodology

The study is carried out for testing the above hypothesis

requires a data on selected variables of FS practices, TQM

practices and SCM practices and SCM program in Indian oil

and gas industry. The method of study is collecting informa-

tion from primary source through a questionnaire. The qual-

itative data has been collected using interviewing and

observing techniques, and quantitative data has been collected

using questionnaire. statistical software for social sciences

(SPSS-16) software is used for mean, correlation and stepwise

regression analysis. The analysis shows that SCM practices

are highly correlated with FS practices although it is also

showing the correlation with TQM practices also but if we

compare the two variables then the effect of FS is more in

SCM practices as compared to TQM practices.

Following are the steps used in conducting the study.

Literature review and experts opinions have been com-

pleted. Identification of variables has been done. On the

bases of identified variables a conceptual model has been

developed and Research Hypothesis Formulated. Ques-

tionnaire was developed and data was collected from the

target audience. Data has been analyzed by the software

package for social science (SPSS-16). Regression, corre-

lation and various statistical analyses have been done to

validate the model. Conceptual model was validated on the

basis of data analysis Learning and discussion has been

done to summarize the study findings (Figs. 3, 4).

Design of the Questionnaire

The research objectives were translated into hypotheses,

which were then defined as relationships of guiding vari-

ables. The guiding variables were further divided into

micro variables and translated into specific questions or

statements. Rensis Likert has developed Likert type scale

where the respondents are asked to express their position

on a scale, which has two extremes. Here 5 point Likert

scale (1–5) is used starting from ‘‘very low to very high’’ as

two extremes of continua, which have been divided in five

intervals for measurement, respondents were to indicate the

level of their agreement and disagreement to these state-

ments. In addition, the approximations were used in terms

of numbers and/or percentages, obtained for measurement.

To convey the intent quickly, question description has been

kept short and precise.

Data Analysis

The univariate analysis for variables has been carried out

and the statistical description of data on mean values is


123

presented in Table 8 in Appendix. The standard deviation

of all the variables being low show that there is least spread

around the mean. The analysis is helpful in implementing

the SCM practices in terms of TQM practices and FS

practices in the oil and gas sector.

Flexible System Practice (FSPRT)

The FS practices has mean value 3.99 (on the 1–5 Scale) in

the overall sample’s practices are found to be an important

component of SCM practices with a mean value of 3.99.

The development of SCM practices in terms of customers

relationship and strategic relationship enables to FS prac-

tices easily, thereby, providing the standard operating

procedures and inter departmental task forces and flexible

approach. Since the SCM practices are successful in oil and

gas organizations continuously build SCM practices to FS

practices rapidly to sustain and lead the industry. 79.8 %

(3.99 out of 5) respondents are of the view that FS practices

in an important aspect of overall TQM practice and SCM

practices.

Total Quality Management Practice (TQMPRT)

TQM practices has mean of 4.21 (on the 1–5 Scale) which

indicate that customer’s top management and employee

empowerment and team work are the very important assets

enabling to generate TQM practices and translating

Fig. 3 Research methodology

of the study


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innovative ideas into actions. SCM practices in terms of

customer’s relationship and strategic relationship allow an

organization to deliver superior performance to achieve

employee empowerment. It is evident from the mean value

that 84.2 % (4.21 out of 5) of the respondents feel positive

relationship between customer’s relationship and Strategic

relationship in terms of TQM Practices.

SCM Program (SCMPRG)

Enhancement of SCM program results in better SCM

practices of an organization. If an organization builds

effective customer’s relation and building trust in market-

ing leads to effective SCM practices in terms of customer

relationship and Strategic relationship, it ultimately adds

profit resulting in improved performance. The mean value

of SCM program is found to be 3.486 (on the 1–5 scale),

which tells us that 69.72 % of the responses are in favour

of the view that SCM Program are positively linked with

the SCM practices.

SCM Practice (SCMPRT)

The SCM practices have mean value of 3.561. It means

71.22 % (3.561 out of 5) respondents feel that SCM

practices is affected by the TQM practice, SCM program

and strongly affects the FS practices.

Among the different micro variables the study of mean

and standard deviations clearly signifies that how posi-

tively the FS practices are affecting the SCM practices in

the oil and gas sectors.

Correlation Among Variables

Correlation technique is used to measure the degree of

association between two sets of quantitative data and it also

help to understand strength of linear relationship between

the two quantitative variables. In the present study, corre-

lation analysis has been carried out on all four variables,

viz TQM practice, SCM program, FS practices and SCM

practices. After calculating the values of all four variables;

these are presented in Table 2. The results show the degree

of association among variables. Pearson correlation test is

used for the full sample of 309 responses.

It is found that SCM PRT has significant correlation

with TQM PRT (0.273**), FS PRT (0.595**) and SCM

PRG (0.455**) at 99 % of confidence level.

SCM Program has significant relationship with TQM

practice (0.455**) and FS practice (0.595**) at 99 % of

confidence level. It shows that the SCM program is

strongly dependent on the TQM practice and FS practice of

an organization but more towards FS practice (0.645**).

TQM practices leads to FS practices enhancement in terms

of interdepartmental task, standard operating procedures

and flexible approach towards volume, expansion and

product. The above data show that SCM practices

enhancement is significantly linked with TQM practices,

FS practices and SCM program at 99 % of confidence

level.

There is strong relationship exists between TQM prac-

tices and FS practices (0.556**) at 99 % level of

confidence.

Regression Analysis for Selected Variables

Step wise regression of multivariate technique has been

used to test the hypotheses is the step-wise regression

analysis. It presents the large amount of complex data in a

more simplified and meaningful form. The analysis enabled

to predict the variability in dependent variable based on its

covariance with all the independent variables. The purpose

of performing the stepwise regression analysis is to

examine the statistical significance of model showing

Fig. 4 Conceptual model (Fauzia and Haleem 2009)

Table 2 Correlation among selected variables

TQMPRT FSPRT SCMPRG SCMPRT

TQMPRT 1

FSPRT 0.556** 1

SCMPRG 0.498** 0.645** 1

SCMPRT 0.273** 0.595** 0.455** 1

** Correlation is significant at the 0.01 level (2-tailed)

* Correlation is significant at the 0.05 level (2-tailed)


123

relationships of variables presented in the Conceptual

Model (Fig. 5).

SCM Practice as Dependent Variable in TQM

Practices

The coefficient of determination (R2) indicates that 52 %

variation in SCM practices is explained by ‘TQM prac-

tices’. Beta Value which indicates regression coefficient

shows the degree of association between SCM practices

and TQM practices is 0.193 (b value). The ‘t’ statistics

(3.302) tests the significance of the slope, which is equiv-

alent to testing the significance of the correlation between

dependent and independent variable given in Table 4 in

Appendix.

The sum of the squared error is 19.737; it means that this

could be the amount of error if mean of the dependent

variable is predictor. But using FS practices as the pre-

dictor, this error is reduced by 38.0 %, which is the value

for adjusted R Square. The standard error of the estimate is

the square root of the residual mean square in ANOVA

given in Table 5 in Appendix. In this case, standard error is

equal to 0.771 and measures the spread of the residuals or

errors. The F-value 5.526 (square of t value) being small,

(5.526 with 1, 100 degree of freedom) shows that inde-

pendent variable helps to explain the less variation in the

dependent variable; here F value is statistically significant.

SCM Practice as Dependent Variable in FS Practice

The model summary, ANOVA, and coefficient summary,

in terms of SCM practices as dependent variable, are

shown in in Table 6 in Appendix, respectively. Two steps

have been taken to compute stepwise regression analysis

for SCM as dependent variable. The change in FS practices

due to standard operating procedures and flexible approach

in expansion,volume and routing can be explained by the

R2 (0.227). Higher will be the value of R2 better will be the

prediction. Standard coefficient b shows that the flexible

system practices (0.520) have more impact as compared to

TQM practice (0.269). The F-value (30.330) is statistically

significant where TQM practice and SCM practice are

independent variables.

SCM Practices as Dependent Variable

SCM practices are affected by TQM practices. 23.6 % (R2

value) variation in SCM practices is explained by TQM

practices. The degree of association (b value) with

dependent variable of flexible system practices is 0.556.

The independent variable reduces the sum of squared errors

by 22.8 %. The F-value 30.843 (with 1,100 degrees of

freedom) shows the highly significant relation of SCM

practice with ‘FS approach and explains the variation in

TQM practice.

The model summary, ANOVA, and coefficient summary,

in terms of SCM practices as dependent variable, are shown

in Tables 4, 5, 6, 7, 8 in Appendix, respectively (Fig. 6).

Discussion on Hypothesis Testing

The summary of the three regression models is shown in

the Table 3 below in terms of the independent variables

acting as predictors, cumulative R2 and the hypothesis

codes for the hypotheses accepted and the hypotheses

rejected. Though all the R2 values are significant indicating

a reasonable explanation of the respective dependent

Fig. 5 Validated model for

relationship of selected

variables


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variables, the highest one is for SCM practices (0.520) in

FS practices. The variable comparatively less explained is

TQM practices with R2 value of 0.227 and for SCM pro-

gram the value of R2 is less 0.269 but higher than the TQM

practices.

Total six (6) hypotheses of association were formulated

at macro level; only four have been accepted as shown in

Table 3 above.

Two hypotheses have been rejected. The rejected

hypotheses are linked with TQM practices (A2, A3). The

SCM practices are in terms of customer’s relationship and

strategic relationship and TQM practices in terms of top

management, employee empowerment and team work. The

above results imply that SCM practices is not strongly

dependent on TQM practice and its factors. It is dependent

on FS practices which here are taken as interdepartmental

task forces, standard operating procedure and flexible

approach.

The results from this study show that SCM practices is

predominantly affected by the TQM practices and linked

with FS practices. According to Sutcliffe et al. (2000), the

literature distinguishes two types of research trends

regarding change and efficiency in organizations. The SCM

practices and its positive impact on the SCM program can

Fig. 6 Validated model for micro variable SCM practices as dependent variables

Table 3 Model summary table for variables analysis

Dependent

variable

Independent

variables

R2 Hypotheses

accepted

Hypotheses

rejected

SCM Practices TQM Practice 0.227 A1 A2, A3

FS practices 0.520 B1, B2 –

SCM Program 0.269 C1 –


123

be achieved by focusing more on the variables of TQM

practices and FS practices in oil and gas industry. The

study is only a modest attempt to bring out the significant

variables and factors affecting the SCM practices. More

efficient and cost effective supply chain practices in the

petroleum industry represent important factors for main-

taining continuous supplies of crude oil, the reduction of

lead times, and lowering of production and distribution

costs (Raed 2006). Due to the FS practices are involved in

the petroleum industry’s supply chain network, logistics

represent a great challenge. However, it is only one of

several challenging factors. Interdepartmental task forces,

standard operating procedures and flexible approach are

equally important. Despite the great challenges in the gas

and petroleum industry’s supply chain, opportunities for

improvements and cost savings do exist along the supply

chain. One major area for improvement and cost savings

lies in the logistics function. Companies in the petroleum

industry have become increasingly reliant on the services

of third-party logistics companies to manage their supply

chains. Companies in the petroleum industry took the

outsourcing idea a step further to collaborate with com-

petitors and found shared solutions to their supply chain

challenges.An example in the real world is present in the

Indian Gas Industry. GAIL the leading gas distribution and

marketing company has flexible gas sourcing options (in-

fraline 2009). In 2004 when the domestic gas supply option

was exhausted GAIL took the initiative and formed petr-

onet LNG (PLL) for importing regassified liquefied natural

gas (RLNG) from the Gulf region through ships or tankers.

The enablers in the SCM practice in the Indian Oil &

Gas Industry have been the new oil and gas discoveries in

India. Traditionally India has been a gas deficit company

but things are going to change. The Government of India

(GoI) is considering all options available to increase the

supply of natural gas in the country. India is heavily

dependent on imports to meet the rapidly growing demand

for petroleum products and change in SCM practices and

implementation of more SCM practices and FS practices

will increase the Current demand and supply projections

indicate that the level of self-sufficiency to about 30% over

the next few years. Substantial efforts are therefore, nec-

essary to boost the level of exploration activity in the

country, so that, new finds can be made and the level of

crude oil and gas production significantly increases in the

years to come.

Conclusion

TQM practice and FS practices are vital and play crucial

role in SCM practice. The validated model so developed

shows the relationships among the selected variables. A

relationship between SCM program, FS practices, TQM

practice and SCM practices has been observed (Fig. 5).

From this framework we have not observed any significant

direct relationship between SCM program and SCM prac-

tices and TQM practices. SCM program has been observed

to be directly linked with FS practices and not by any other

variable. This observation has emerged from the statistical

analysis of the data collected from questionnaire based

survey. The results shows that if the FS practices in terms

of interdepartmental tasks, standard operating procedures

and flexible approach towards product, volume, routing and

expansion positively relates to SCM practices in terms of

customers relationship and strategic relationship as the

final product in oil and gas industry.

Best-in-class SCM in oil and gas supply chains results in

steadier and more profitable capital expansion, which means

a higher return on assets (ROA). Steadier prices would

translate to higher operating profits and lower operating

costs. Perhaps most importantly, more stable investment in

new technology results in greater oilfield productivity.

Appendix

See Tables 4, 5, 6, 7, 8.

Table 4 Model summary/

ANOVA/coefficients for SCM

practice as dependent variable

in TQM practices

a Dependent variable:

SCMPRT

Model R R2 Adjusted R2 Std. Error of the estimate

1 0.227a 0.052 0.042 0.771

1

Regression 9.863 3 3.288 5.526 0.001a

Residual 18.874 304 0.595

Total 19.737 307

B Std. Error b Std. Error of the estimate

1

(Constant) 2.680 0.365 7.335 0.000

TQMPRT 0.216 0.068 0.193 3.203 0.002


123

Table 6 Coefficients for TQM

practice as dependent variable

in FS practices & SCM

practices


TQMPRTb Predictors: (Constant),

FSPRTc Predictors: (Constant),

SCMPRG

Model Unstandardized coefficients Standardized coefficients t Sig.

B Std. Error Beta

1

(Constant) 3.641 0.380 9.583 0.000

FSPRT 0.020 0.061 0.021 0.333 0.740

Model Sum of squares df Mean square F Sig.

1

Regression 8.578 1 8.578 14.409 0.000b

Residual 18.159 306 0.595

Total 19.737 307

2

Regression 9.781 4 2.445 4.095 .003c

Residual 18.956 303 0.597

Total 19.737 307

Table 5 Model summary/

ANOVA/coefficients for SCM

as dependent variable in FS

practices


SCMPRTb Predictors: (constant), FSPRT

Model R R2 Adjusted R2 Std. error of the estimate

1 0.085a 0.007 -0.003 0.789

Model Sum of squares df Mean square F value Sig.

1

Regression 1.372 3 0.457 0.734 0.532a

Residual 189.365 304 0.623

Total 190.737 307


B Std. Error b

1

(Constant) 3.641 0.380 9.583 0.000

FSPRT 0.082 0.067 0.075 1.218 0.224

Table 7 Coefficients for

SCMPRT as dependent variable

in FS practices and TQM

practices

s Dependent variable:

SCMPRT


B Std. Error Beta

1

(Constant) 3.055 0.260 11.728 0.000

TQMPRT 0.238 0.063 0.212 3.796 0.000

2

(Constant) 2.776 0.438 6.344 0.000

FSPRT 0.071 0.066 0.065 1.082 0.280


123

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Key Questions

What is the impact of SCM practices in terms of TQM and FS

practices in oil and gas industry?

What are the benefits of using SCM practices in oil and gas

industry?

What are the key factors affecting the SCM practices?

Author Biographies

Fauzia Siddiqui is a research scholar at USIT,

GGSIPU, Delhi pursuing PhD in the area of

Industrial and Production Engineering. She is

currently the Assistant Professor at the Department

of Manufacturing Technology, JSS Academy of

Technical Education, Noida U. P. India. She has

an experience of 9 years in the field of education.

Dr. Abid Haleem is Professor and Head of

Mechanical Engineering Department at Faculty of

Engineering and Technology, and is also Honorary

Director, IQAC, Jamia Millia Islamia (A Central

University by an Act of Parliament), New Delhi,

India. Dr. Haleem obtained his PhD from IIT

(Delhi) in the area of ‘Strategic Management’ and

completed his graduation and post graduation

degrees in ‘Mechanical Engineering’ and ‘Industrial Engineering’

respectively. Professor Haleem has more than hundred research

papers to his credit, published in international and national journals

like National Social Science Journal (USA), Production Planning and

Control, Journal of Architectural Engineering, International Journal

on Electronic Governance, Global Journal of Flexible Systems

Management,), Journal of Human Ergology, Industrial Engineering

Journal, IJMMR (Malaysia), International Review of Mechanical

Engineering (Italy), Indian Journal of Business and Economics, Pro-

ductivity, Pranjana etc. He has authored a book titled ‘‘Innovation,

Flexibility and Technology Transfer’’, published by Tata McGraw

Hill, India. He was on the Board of TCIL as an Independent Director

during 2008–2011.

Chitra Sharma is Associate Professor and Head

of the Mechanical and Automation Engineering,

Indira Gandhi Institute of Technology, GGSIP

University, Delhi. She had earned the PhD in

Industrial Engineering and Management from the

Indian Institute of Technology, Delhi, INDIA in

the year 1999. She has over 12 years’ experience

in the education sector. She has supervised PhD

work of students in diverse areas which include flexible manufac-

turing systems, total quality management, electronic discharge

machining, and metrology. Her research interests include application

of qualitative and quantitative techniques to evaluate and rank issues

related to technology forecasting planning and implementation at the

macro level.


123

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