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ORISSA JOURNAL OF COMMERCEU.G.C. CARE listed, A peer Reviewed and Referred Journal

VOLUME - XXXX JULY-SEPTEMBER 2019 ISSUE No. - III

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ORISSA COMMERCE ASSOCIATION

President : Prof. P. K. Hota, Utkal UniversityVice President : Mr. Tekchand Doan, Sohela College

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Contents

1. Impact of Board of Directors'on NIFTY 50 Listed Companies in India 1H. K. Singh, Shantanu Saurabh & Veenita Singh

2. An Impact of Macroeconomic Variables on the Functioning ofIndian Stock Market 13

Brundaban Sahu & Rakesh Chandra Sahoo3. A Systematic Review of Literatures on Customer Churn Analysis in the

Telecommunication Industry 24Manoj Kumar Dash & Susmita Dash

4. Integrated Reporting for Corporate Sustainability: An Exploratory Study 42Tulika Bal & Sunil Kumar Dhal

5. Financial Literacy and Its Dimensions: An Empirical Study in Assam 51Sanjib Das & Santosh Kumar Mahapatra

6. Lifecycle Management Using Risk Estimation and Contingency Modelfor Indian Defence Sector 61

Mukesh Kumar Gupta & Gyanesh Kumar Sinha7. Recent Trends in Entrepreneurship (Start-Ups) Development with

Reference to North East-India 75K.C Biswal & Dhananjoy Narzary

8. Investment Pattern in Coastal Area of Odisha: A Special Referenceto Bhubaneswar-Cuttack Twin City 90

S.K Baral9. Opportunities and Challenges in Developing Inland Waterways

Transport in India 97Pradeepta Kumar Samanta

ORISSA JOURNAL OF COMMERCEU.G.C. CARE listed, A peer Reviewed and Referred Journal

ISSN-0974-8482

(iv)

EDITORIALIndia Skills Report which is a joint initiative of Wheebox, a Global TalentAssessment Company, PeopleStrong, a leading HR Tech Company andConfederation of Indian Industry (CII) and supported and backed byrenowned partners like United Nations Development Programme (UNDP),All India Council for Technical Education (AICTE) and Association ofIndian Universities (AIU), stated that Employability continues in India.Over the last 10 years, the Government of India (GOI) has undertakensignificant efforts in improving both the scale and quality of skilling,like setting up the National Skills Development Corporation (NSDC) in2009, launching the Skill India mission in 2015, and the flagship skillinginitiative, the Pradhan Mantri Kaushal Vikas Yojana (PMVKY) in 2016.This, in turn, is expected to drive economic gains and social mobility forindividuals as well as trigger a productivity dividend for enterprises. Asthe world moves towards demand-based economy, so should feederindustries, including India’s biggest offering its talent. India skills policieshave been plagued historically, unable to channel our demographicdividend towards this demand. In the 1980s and 1990s, private playerslike NIIT and Aptech built the pipeline for emerging tech jobs. In theAnnual Household Survey conducted by the Labour Bureau, it was foundthat the country’s unemployment rate had risen to a five-year high of 5per cent in 2015-16. Among those unemployed, female job seekers werethe worst hit as unemployment among them had sharply climbed to 8.7per cent in 2015-16 from 7.7 per cent in 2013-14, according to the FifthAnnual Unemployment Survey. While the Indian government is pressingthe accelerator to create more jobs with its Make in India, Skill India andStart up India campaigns. Unfortunately, many young people remainunemployed because their skills do not match the emerging industryrequirements in the country. Thus India is poised to provide fresh impetusto global growth. India’s economic growth will be significant in terms ofits absolute contribution to global economic activity. But India’sdevelopment model is uniquely innovative, frugal, and green. Todaythere is a strong institutional structure with the Skill Ministry at thehelm, supported by NSDC. According to the latest India Skill Report(2019), only 45.6% of the youth graduating from educational institutionsare employable. To address this mismatch, it is imperative to understandthe ‘return on skill’ (ROS) concept.

(Managing Editor)

Impact of Board of Directors’on NIFTY 50 ListedCompanies in India

Dr. H. K. Singh*, Dr Shantanu Saurabh & **Dr Veenita Singh***

ABSTRACTPurpose – applying a set of data Nifty 50 listed companies in India; this research paper is an attempt to

empirically evaluate the effects financial performance of board of director’s based on their characteristics.Design/ methodology/ approach – a sample size of 50 listed firms have been used, from the year 2008 to

2016. Time series and cross sectional are the basic features on which the entire study is based upon for panelestimation. Beside it, statistical measures like ordinary least squares (OLS) model of regression and robustregression is applied to mitigate the problems related to endogeneity.

Findings – The primary results shows that for financial performance measuring by ROA, ROE, ROCE,board of director’s features has positive and relevant effect on financial decision and performance of thefirms in our study on Indian Nifty 50 listed firms. The results also points out that in the perspective of nifty 50listed firms, the leverage and firm size are negatively related with the financial performance of the firms.

Limitations and implications of the Research –In accordance with the Indian corporate governancenorms and reforms, it is obligatory for the listed companies to appoint independent directors system, by faris successful still, the regulatory and governing authorities should efficiently implement the norms ofappointment of independent directors in listed companies to improve corporate governance system in India.

Originality/value- Initially, in not similar fashion with the prior studies based on the developing nations,this present study interrogates the impact of features of board of directors on financial performance of IndianNifty 50 listed firms. Thereafter, while a lot many studies applied a solitary indicator of firm financialperformance, this study examines ROA, ROE and ROCE. Using the OLS estimation the present studyemphasizes the endogeneity issue between firm performance and board of director’s characteristics, androbust regression for mitigating the exactness of using OLS estimation.

Keywords: Board of director’s characteristics, Firm performance, India, Nifty 50I

IntroductionThe corporate governance composition of boards in terms of structure and size have paid much

attention in the media and news in the corporate world in recent times, the failures of large companies

* Professor, Faculty of Commerce, Banaras Hindu University, Varanasi, Ex - Vice Chancellor (Managing Editor,The Indian Journal ofCommerce) Maharishi University of Information Technology,lucknow. E-mail ID: [email protected],

** Assistant Professor (Commerce), KIIT, Bhubaneshwar, Email: [email protected]*** Assistant Professor, School of Management Science, Varanasi

2 Orissa Journal of Commerce, Volume XXXX, July-September-2019, Issue No. - III

was felt and observed many scams such as Enron, WorldCom and Parma- lat. The basic and primaryidea is that, there is abundance of national and international guidelines for good corporate governancepractices that affect matters related to board of director’s characteristics (Bennedsen et al., 2008).Composition of company’s board of director is one of the most valuable and significant mechanism ofgood corporate governance. The focal point in academic section is the effectiveness and efficiencyof board of director’s characteristics. Firm financial performance has often been employed as a proxyfor deciding the governance potential efficiency of a company in many previous studies review suchas. Ghosh, (2006), revealed that firm’s performance either in terms of accounting concept or inmarketing measures, particularly large size firm is affected by size of board of director’s that tends tohave dampening impact.

The one of the most integral part of internal corporate governance mechanism is the board ofdirectors. According to(Akhtaruddin et al.,2009; Haji & Mubaraq, 2015) the vital institution in theinternal governance structure of a company includes board of directors, which facilitates a primarymonitoring function for agency problems. Definition of effectiveness means an extent to whichproblems are solved and objectives have been achieved (Wadhwa, 2014). Previous studies showedthat board of director’s effectiveness essentially depend on board of director’s attributes, as disclosureof more relevant information to external parties is an important characteristics that define theeffectiveness of boards. Following(Bennedsen et al., 2008; Green & Homroy, 2018; Merendino &Melville, 2019) studies, board of director’s effectiveness is defined in this study by its characteristics.In other way it can be said that, the improvement of the board of directors with reference to itsintegral elements such as independence, size, shareholding, nationality, multiple directorship, meetingand board committees can improve the effectiveness and capacity of the board to manage and monitormanagement and thus by increasing the scope and probability of providing more relevant informationto external investors relevantly.

All those financial shows that assess and fulfil the firm’s economic objective is a key matter ofinterest in management and other areas of researches. Firm financial performance concern with the avariety of subjective measures of how well a firm can apply its available assets from primary modeof operation to earn profit(Peters & Bagshaw, 2014). “The NIFTY 50 is the flagship index on theNational Stock Exchange of India Ltd. (NSE). The Index measures the behavior of a portfolioinvestment of blue chip companies through different domains, the largest and most liquid Indiansecurities. It includes 50 of the approximately 1600 companies listed on the NSE, capturesapproximately 65% of its float-adjusted market capitalization and is a true reflection of the Indianstock market”. NIFTY 50 includes major economic sectors of India. It issues declaration to offers aninvestment to managers’ publicity in one efficient portfolio in the Indian market. Indexing has beendone since April 1996 and is appropriate for establishing parameter, index funds and index-basedderivatives (NSI, 2019)1.

Figure 1 shows that there was an increase in Nifty market at a CAGR of 11.7% in last 20 years(since 1996) and 7.5% in last 10 years (since 2006). In terms of yearly returns, since 1996, NIFTY 50has given more than 50% return in (1999,2003,2007,2009,2018) 5 calendar years and more than 30%return in (1999,2003,2005,2006,2007,2009,2014,2017) 8 calendar years. NIFTY 50 has fallen by over20% only in (2008, 2011) 2 calendar years, giving positive returns in 16 out of 23 years.

3Impact of Board of Directors’on NIFTY 50 Listed Companies in India

Figure 1: Performance of NIFTY 50

Data for 2019 is as on March 29, 2019. Source: NSE

From the above context, research problem is clear and that objective is to study the impact of boardeffectiveness policy on the financial performance of the firm financial performance of NIFTY 50 tradedcompanies, therefore, necessary steps will be taken to provide a clear picture for indexing board ofdirectors. It is significant to enquire the relevant question the impact of composition of boards of directorson NIFTY 50 firm’s financial performance? Recent research work has answered this question by showingthe impact of board of directors in different countries. Further, with a shortage of empirical studies onthe impact of board of directors on many aspects of the Indian economy; academic research has not yetstudied the impact of composition of board effectiveness on the financial appraisal of NIFTY 50 listedfirms in India.

A lot was said about financial performance of NIFTY 50 traded firms based on the board of directorscharacteristics in different countries, through many pieces of writing. The present study aims to studythe effect of board of directors on the financial performance of NIFTY listed firms, and determinewhether it was affected positively or negatively. The rest part of this paper organized as follows. Secondsection deals with the formulation of hypotheses and review of different literatures. The next and thethird part constitute the research methodology section. Section four focuses on the descriptive statisticsand results of the empirical tests. Lat and the fifth section includes the concluding remarks of the study.Section six reveals the implications and drawback of the study.

Literature Review and Hypothesis DevelopmentThe important mechanism of internal corporate governance is constituent of board of directors.

Board of directors and business organizations occupies a unique position in corporate governance.Both big and small organisations are governed by corporate governance. It is mandatory for thecorporate entities to have board of directors by statue. Many studies have been done on variousaspects of characteristics of board of directors and their impact on the financial performance. Someof the previous studies argued that the board size provides board effectiveness to improve firmperformance. Guest(2008) argued the demerit that larger board size may face lack of coordinationand decrease the board’s ability to oppose and find loopholes the control of top managers due to


lack of opportunities of discussion of management problems. In the other hand, Guner et al., (2008)argued that constitution of large board size may facilitate firms in offering suitable advice thatcomes from directors’ external link and due to expertise knowledge and experience in their respectivefields.

Jermias & Gani(2014) interrogated the association between board of directors’ dependence,managerial ownership and firms performance based on board capital. The outcomes are consistentwith the view that firms advantage from board capital in terms of outside directors’ capability tocheck managers performance and provide advice and counsel to managers. Wang (2013) arguedand concluded that different firms have different requirements based on complicated and simplefirms performance-improvements board structure. Although large boards faces communicationdistortion and decision-making problems, they facilitates firms via making available more advisoryfunctions. Guest (2009) studied the impact of board size on firm performance for a large sample of2,746 UK listed firms over 1981-2002.They concluded that board size has a strong negative impacton financial performance.In addition, Ranasinghe (2010) found that board size had a negativeassociation with Return on Assets and market book value, which was applied as proxies for firmperformance.

Many prior studies have been done to know the relationship between board size and firmperformance has produced varied outcomes. It is discovered in most of the studies that the affiliationbetween board size and firm performance is negative (Bennedsen et al., 2008; Guest, 2009; Lin,2011).on the contrary, Conheady et al.,(2015) find a significant positive relationship between thefirm’s measure of board effectiveness and the firm’s contemporaneous and future market measureof performance. Furthermore, Bonn et al.,(2004) study and compared the sound effects of boardsize, proportion of female directors, proportion of outside directors and average age of directorson firm performance in Japanese and Australian firms. We found that board size and age of directorswere negatively associated with the performance of Japanese firms. For Australian firms, outsiderratio and female director ratio were positively related with performance.

Mohd Nor et al., (2014) analysed the trend of board characteristics and try to explore theassociation of board characteristics and Malaysian firm performance. The data were collected fromthe analysis of companies’ annual report for a sample size of 169 companies for period of 2009and 2010. Study shows that there is a significant relationship between board size and firmperformance. In addition, there are no association between proportions of independent non-executivedirectors to firm performance. Lin (2011) investigated the impact of duality and board structure oncorporate performance. The finding of small and medium-sized companies advocate that thesupervisory directors, outside independent and inside directors had positive impacts on financialperformance, ROA and ROE. Prior studies conducted in India have not yet studied and appraised theimpact of board characteristics on the financial performance. So, this study try to put in literature byintroducing the following conceptual framework as shown in the Figure 2 to examine the impact ofboard characteristics on the financial performance of the firms.


Figure 2: Conceptual Framework

Board Characteristics

Performance

ROA

ROE

ROCE Control variable

Firm size

Leverage Based on the above literatures review and objectives of the study demonstrated above, the hypotheses

of the present study are:H01: There is positive associated between board characteristics and return on assets of Nifty 50

listed firms.H02: There is positive associated between board characteristics and return on equity of Nifty 50

listed firms.H03: There is positive associated between board characteristics and return on capital employee of

Nifty 50 listed firms.

Research Methodology DateThe Research paper is based on pure secondary data which has been adopted from Prowess IQ a

database of Indian companies, Money control website2, books and journal. Whereas board of directorsand ownership structures, data were retrieved from the corporate governance reports section from theannual reports of the selected sample companies. Data which we need to justify objectives, collectedfor 8 years from 2008–2009 to 2015-2016. The purpose of the index is to compute the performance oflarge market capitalization companies. Sample SizeCompanies constituting the S&P CNX Nifty 50 firms which are registered on the National Stock

Exchange of India have been considered to fulfil the purpose of this study. (NSE), is a leading stock.The Nifty companies were classified into four eleven-samples classification as showing in the Table 1:

Table 1: Number and Percentage of sample firms by industry

S.no. Industry Number Proportion

1 Automobiles 8 16%

2 Cement 3 6%

3 Construction 1 2%

4 Consumer Goods 3 6%

5 Energy 8 16%


6 Financial Services 10 20%

7 IT 5 10%

8 Media and entertainment 1 2%

9 Metals 4 8%

10 pharma 5 10%

11 Telecom 2 4%

Total 50 100%

VariablesThere are three variables in this Research; the independent variable is board of director’s attributes

and the dependent variable and control variable are as follow:• Return on assets measures by net income over total assets at the end of the financial year.• Return on equity is measured by profit after tax divided by total equity shares in issue.• Return on capital employee is measured by net profit after tax /capital employed.• Firm size is measured by the natural logarithm of total assets.• Leverage measures by total debt percentage are divided by total assets. Statistical tools and MethodsThe study comprises descriptive statistics such as mean, median, mode, correlation and

multicollinearity diagnostic, ordinary least squares and robust regression eviews 10 using review ofliterature to study the impact of board of director’s characteristics on financial performance of Nifty 50listed firms.Therefore, the following model is developed:

ROAit = +1 BDCit +2LEVit + 3FSIZEit+åit

ROEit = +1 BDCit +2LEVit + 3FSIZEit+åit

ROCEit = +1 BDCit +2LEVit + 3FSIZEit+åit

Where, is the intercept in this study, å is defined as an error term for the model, i and t correspond to firm

and year, ROA is return on assets, ROE is return on equity, ROCE is return on capital employee, BDCis board of director’s characteristics, LEV is the short form of leverage, and FSIZE is the firm size.

Data Analysis and Findings:

Descriptive Statistics

Table 2 describes descriptive statistics for the variables applied in this research paper. It givesdetails information in the form of descriptive statistics, skewness, kurtosis and number of observationsfor the dependent variable and its causal and control variables. The output shows that skewness andkurtosis are in the range of ±1 and ±3 respectively. The results demonstrate the trend of financialperformance measurements; ROA, ROE, and ROCE over the period 2008–2016. Similarly, the resultsshow the descriptive statistics for board of director’s characteristics, leverage, firm size variables for


the same period. The results reveal that ROA, ROE, and ROCE each range between minimum values of-5.08,-18.18and -45.36and maximum values of 38.71, 86.91and 72.75with a mean of 11.98, 23.13 and17.09 respectively. Moreover, board of director’s characteristics ranges between a minimum of 0.44, amaximum of 0.94 with a mean value of 0.74, and standard deviation of 0.10.Controls variables have anaverage value of 11.95, 5.20, a minimum of.01,3.75 with standard deviation of 22.8,0,90 respectively.

Table 2: Descriptive Statistics

Stat. ROA ROE ROCE BDC LEV FSIZE

Mean 11.98 23.13 17.09 .74 11.95 5.20

Maximum 38.71 86.91 72.75 .94 87.61 10.14

Minimum -5.08 -18.18 -45.36 .44 .01 3.75

Std. Dev. 7.44 16.12 12.42 .10 22.8 .90

Skewness 0.65 1.61 0.72 -0.16 1.8 0.12

Kurtosis .247 1.73 2.47 -.61 2.27 2.09 observations 400 400 400 400 400 400

Correlation and Multicollinearity Diagnostic

Table 3 explains the Pearson correlation matrix and multicollinearity diagnostics for differentdependent and causal variables. The coefficients are based on the data from 50 Nifty Indian listed firmswith 400 observations for the period 2008/09–2015/16. Results reveal the positive relationship of boardof director’s characteristicswith financial performance. This indicates that if the companies follow therules of board of director’s characteristics, the financial performance of the companies are going toincrease. Similarly, the result also shows a positive relationship between firm leverage and financialperformance measured by ROA, ROE, and ROCE, which means that if there is increase in leverage itleads to an increase in profitability. The result also shows a positive relationship of board of director’scharacteristicswith leverage and firm size. This reveals that board of director’s characteristicsleads toincrease in leverage and firm size whereas board of director’s characteristicshas a negative associationswith financial performance measured by ROA, ROE, and ROCE.

Table 3: Correlation Matrix and Multicollinearity Diagnostics

Variables ROA ROE ROCE BDC LEV FSIZE

Correlation matrix (Panel A)

ROA 1

ROE .85** 1

ROCE .56** .52** 1

BDC .17** .06 .052 1

LEV .012 .04 .03 .02 1

FSIZE -.234** -.25** -.18** .04 -.15** 1

VIF 1.84 1.26 1.37

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


Results of Model EstimationTable 4 draws conclusion of regression estimation of firm financial performance on board

characteristics, and control variables. The regression results in Columns 1, 2 and 3 depend uponaccounting measures for ROA, ROE and ROCE, respectively. The board characteristics variables, thecoefficient of BDC is positively and statistically significant at the 1% significance level for ROA, ROEand ROCE. The conclusion favors the hypotheses of the study (H01, H02, H03) and are similar withthose of (Kao et al., 2019; Mohd Nor et al., 2014; Wang, 2013), suggesting that board characteristicsvariables does enhance firm financial and overall performance. The hypotheses have been accepted asthe coefficient of TIER is associated positively and significantly with ROA, ROE and ROCE at the 1 %level. Table 4 depicts that the coefficient value of leverage is negative and insignificant for all ROA,ROE and RCOE. The result is consistent with (Doan & Nguyen, 2018). Moreover, the coefficient ofFirm size is also negative and significant at the 1% level for both ROE and ROCE, These results areconsistent with those of (Guest, 2009; Wang, 2013).

Table 4: Regression Results Estimation

Models ROA ROE ROCE Variable / Type Coeff. Prob. Coeff. Prob. Coeff. Prob.

C 16.07 0.0 -42.53 0.0 29.32384 0.0003 BDC 14.64 0.0 20.86 0.006 31.46188 0.0001 LEV -0.02 0.16 -0.057 0.13 -0.01536 0.6963

FSIZE 0.004 0.017 -6.39 0.0 -6.07634 0.0000 R-squared 0.13 0.11 0.11 F-statistic 20.29 17.15 17.70

Prob. 0.0 0.0 0.0

Robust RegressionThe panel regression outcome may face the issues related to endogeneity. In this research study,

endogeneity of board of director’s characteristics through firm financial performance would entail thatthe panel regression estimates, are significantly biased and incoherent, and so it cannot applied to drawconclusions about the causality of the association. So, we go for applying the robust regression totackle the endogeneity issue. The equation is applied to carry out the robust regression is the same asequation (1). However, robust regression estimation may not convey better estimates in comparison topanel estimation.

Table 5 demonstrates the results of the robust regression model. The results show that there is aslight change in the values of coefficients, standard errors and t-statistic from the values of OLS regressionmodel in table 4. The coefficient estimates in case of robust regression are not inflated, deflated orhighly deviated from the coefficient estimates of OLS regression. Further, the standard error of both;robust regression and OLS regression are about similar which indicates a proper estimating of the results.

With view to the outcome of robust regression model, the second-stage firm performance equationsare presented in Columns 1-3 of Table 4. The coefficients signs on the causal and control variables ineach and every equation are g enerally as predicted. In general terms, the robust estimates are largerthan those of panel regression estimation in Table 4.


Table 5: Robust Regression

Models ROA ROE ROCE Variable / Type Coeff. Prob. Coeff. Prob. Coeff. Prob.

C 29.8911 0.0000 48.0912 0.0 34.2806 0.000 BDC 12.3953 0.0001 7.10256 0.1697 13.3755 0.0091 LEV -0.0337 0.0345 -0.0677 0.0084 -0.01432 0.5745

FSIZE -5.2475 0.0000 -6.1913 0.0 -5.19885 0.0000 R-squared 0.16 0.07 0.07

Prob. 0.0 0.0 0.0

ConclusionThis Research paper investigates the impact of board of director’s features on firm performance. In

compare to previous evidence for developing nations that reveals no connection between independentdirectors composition and firm performance, our results shows that for financial performance measuringby ROA, ROE, ROCE, board of director’s characteristics has a statistical significant and positive impacton firm performance in our work study on Indian Nifty 50 listed firms. It also points out that firm sizeand the leverage are negatively associated with firm performance in the context of nifty 50 listed firms.These findings can be concluded in association to the several institutional theory that portrays thesemechanisms are resultant of practices or regulations emerge from coercion by legislators who imposecertain good practices in order to improve organizational effectiveness, or as a result of imitation. Inother words, the findings may be referred to this theory which suggests that companies might adoptpractices or regulations as a result of coercion from a legislator who imposes some practices in order toimprove organizational effectiveness. However, there is no prediction that the adoption of theseregulations will improve organizational effectiveness and performance efficiency.

APPENDIX A

Table 5: Variables Definition

Variable Measurement References

Dependent variables

Return of Assets (ROA) ROA = Profit after Tax / Total Asset (Guest, 2009; Guner et al., 2008; Villanueva-Villar et al.,2016)

Return on Equity(ROE) ROE = Profit after Tax / Total Equity ( Hassan et al., 2017; Kao et al., 2019; Singh et al., 2018)

Return on capital employee (ROCE)

ROCE= Net profit after tax /capital employed (Vishwakarma & Kumar, 2015)

Independent variables 1. Size of board of directors is at least 5 but not more than 16 members. 2. The qualifications of the board members are revealed. 3. All members attended at least 75% of board meetings. 4. The number of board meetings held in

(Contd...)


Board of Director’s Characteristics

4. The number of board meetings held in the year and the attended physically, and/or attended via electronic media is disclosed for every board member. 5. The firms has implemented a procedure for a regular assessment of the board. 6. Public disclosure of offices held by any independent director in other companies 7. Separation of chairman and CEO 8. Firm has annual board meeting only for non-executives 9. Board performance is periodically evaluated 10. Company has a designated “lead” or senior non-executive board member Chairman of board independent director 11. The governance/nomination committee is composed of independent board members 12. No former CEO of the company serves on the board Time gap between the two meetings does not exceed 4 months 13. Governance/nomination committee has a written charter or terms of reference 14. Board is controlled by more than 50% of independent outside directors

(Abdallah & Ismail, 2017; Al-Malkawi et al., 2014; Ararat et al., 2017; Srairi,

2015; Wahab et al., 2007)

Control variable

Firm size Natural logarithm of total assets. (Arora & Sharma, 2016; Ullah, 2017)

Leverage It measured by total debt to total assets (Abdallah & Ismail, 2017; Hassan et al, 2016)

References1. Abdallah, A. A., & Ismail, A. K. (2017). Journal of International Financial Markets, Institutions & Money

Corporate governance practices, ownership structure, and corporate performance in the GCC countries. Journalof International Financial Markets, Institutions & Money, 46, 98–115. https://doi.org/10.1016/j.intfin.2016.08.004

2. Akhtaruddin, M., Hossain, M., & Yao, L. (2009). Corporate Governance and Voluntary Disclosure in CorporateAnnual Reports of Malaysian Listed Firms. Journal of Applied Management Accounting Research, 7(1), 1–20.

3. Al-Malkawi, H. A. N., Pillai, R., & Bhatti, M. I. (2014). Corporate governance practices in emergingmarkets: The case of GCC countries. Economic Modelling , 38 , 133–141. https://doi.org/10.1016/j.econmod.2013.12.019

4. Ararat, M., Black, B. S., & Yurtoglu, B. B. (2017). The effect of corporate governance on firm value andprofitability: Time-series evidence from Turkey. Emerging Markets Review, 30(November 2014), 113–132.https://doi.org/10.1016/j.ememar.2016.10.001

5. Arora, A., & Sharma, C. (2016). Corporate Governance and Firm Performance in Developing Countries:Evidence from India. Corporate Governance: The International Journal of Business in Society, 16(2). https://doi.org/doi.org/10.1108/CG-01-2016-0018

6. Bennedsen, M., Kongsted, H. C., & Nielsen, K. M. (2008). The causal effect of board size in the performanceof small and medium-sized firms. Journal of Banking and Finance, 32(6), 1098–1109. https://doi.org/10.1016/j.jbankfin.2007.09.016


7. Bonn, I., Yoshikawa, T., & Phan, P. H. (2004). Effects of Board Structure on Firm Performance: A ComparisonBetween Japan and Australia. Asian Business & Management, 3(1), 105–125. https://doi.org/10.1057/palgrave.abm.9200068

8. Conheady, B., McIlkenny, P., Opong, K. K., & Pignatel, I. (2015). Board effectiveness and firm performanceof Canadian listed firms. British Accounting Review, 47(3), 290–303. https://doi.org/10.1016/j.bar.2014.02.002

9. Doan, T., & Nguyen, N. Q. (2018). Boards of directors and firm leverage/: Evidence from real estateinvestment trusts &. Journal of Corporate Finance, 51(June), 109–124. https://doi.org/10.1016/j.jcorpfin.2018.05.007

10. Ghosh, S. (2006). Do board characteristics affect corporate performance? Firm-level evidence for India.Applied Economics Letters ISSN:, 13(7), 435–443. https://doi.org/10.1080/13504850500398617

11. Green, C. P., & Homroy, S. (2018). Female directors, board committees and firm performance. EuropeanEconomic Review, 102, 19–38. https://doi.org/10.1016/j.euroecorev.2017.12.003

12. Guest, P. M. (2008). The determinants of board size and composition/: Evidence from the UK &. Journal ofCorporate Finance, 14, 51–72. https://doi.org/10.1016/j.jcorpfin.2008.01.002

13. Guest, P. M. (2009). The impact of board size on firm performance/: evidence from the UK. The EuropeanJournal of Finance, 15(4), 385–404. https://doi.org/10.1080/13518470802466121

14. Guner, A. B., Malmendier, U., & Tate, G. (2008). Financial expertise of directors $. Journal of FinancialEconomics, 88, 323–354. https://doi.org/10.1016/j.jfineco.2007.05.009

15. Haji, A. A., & Mubaraq, S. (2015). Journal of Accounting in Emerging Economies Article information/:Journal of Accounting in Emerging Economies, 5(3), 350–380.

16. Hassan, A. F. S., Karbhari, Y., Isa, A. A. M., & Razak, N. H. A. (2017). Board Attributes and Performanceof Government-Linked Companies (Glcs): Evidence From an Emerging Economy. Corporate Ownership andControl, 14(3). https://doi.org/10.22495/cocv14i3art8

17. Hassan, Y. M., Naser, K., & Hijazi, R. H. (2016). The influence of corporate governance on corporateperformance: Evidence from Palestine. Afro-Asian Journal of Finance and Accounting, 6(3), 269–287. https://doi.org/10.1504/AAJFA.2016.79296

18. Jermias, J., & Gani, L. (2014). The impact of board capital and board characteristics on firm performance.British Accounting Review, 46(2), 135–153. https://doi.org/10.1016/j.bar.2013.12.001

19. Kao, M., Hodgkinson, L., & Jaafar, A. (2019). Ownership structure, board of directors and fi rm performance/: evidence from Taiwan. Corporate Governance: The International Journal of Business in Society Ownership,19(1), 189–216. https://doi.org/10.1108/CG-04-2018-0144

20. Lin, C. (2011). An examination of board and firm Performance: evidence from Taiwan. The InternationalJournal of Business and Finance Research, 5(4), 17–35.

21. Merendino, A., & Melville, R. (2019). The board of directors and firm performance: empirical evidence fromlisted companies. Corporate Governance: The International Journal of Business in Society. https://doi.org/10.1108/CG-06-2018-0211

22. Mohd Nor, M., Shafee, N. B., & Samsuddin, N. (2014). Board Characteristics and Malaysian Firm Performance.Global Journal of Business Research in Accounting, Auditing and Business Ethics, 1(3), 139–147.

23. Peters, G. T., & Bagshaw, K. (2014). Corporate Governance Mechanisms and Financial Performance of ListedFirms in Nigeria/: A Content Analysis. Global Journal of Contemporary Research in Accounting, Auditingand Business Ethics (GJCRA), 1(2), 103–128.

24. Singh, S., Tabassum, N., Darwish, T. K., & Batsakis, G. (2018). Corporate Governance and Tobin’s Q as aMeasure of Organizational Performance. British Journal of Management, 29(1), 171–190. https://doi.org/10.1111/1467-8551.12237

25. Srairi, S. (2015). Corporate governance disclosure practices and performance of Islamic banks in GCCcountries. Journal of Islamic Finance, 4(2), 1–17.

26. Ullah, W. (2017). Evolving corporate governance and firms performance: evidence from Japanese firms.Economics of Governance, 18(1), 1–33. https://doi.org/10.1007/s10101-016-0180-6

27. Villanueva-Villar, M., Rivo-López, E., & Lago-Peñas, S. (2016). On the relationship between corporategovernance and value creation in an economic crisis: Empirical evidence for the Spanish case. BRQ BusinessResearch Quarterly, 19(4), 233–245. https://doi.org/10.1016/j.brq.2016.06.002

28. Vishwakarma, R., & Kumar, A. (2015). Does Corporate Governance Increases Firm Performance of It Industry?an Empiricalanalysis. Journal of Management Research, 7(2), 82–90.

29. Wahab, E. A. A., How, J. C. Y., & Verhoeven, P. (2007). The Impact of the Malaysian Code on CorporateGovernance: Compliance, Institutional Investors and Stock Performance. Journal of Contemporary Accounting& Economics, 3(2), 106–129. https://doi.org/10.1016/S1815-5669(10)70025-4

30. Wang, Y.-C. (2013). The Influence of Board Structure on Firm Performance. The Journal of Global BusinessManagement, 9(2), 7–14. Retrieved from http://www.jgbm.org/page/2 Yang-Chao Wang-1.pdf

31. Wadhwa, M. (2014). Technology, Innovation, and Enterprise Transformation. IGI Global.

(Footnotes)1 NSE is the brief name of the National Stock Exchange of India. Available in https://www.nseindia.com

2 Moneycontrol is India’s leading financial information source. See https://www.moneyworks4me.com

An Impact of Macroeconomic Variables on theFunctioning of Indian Stock Market

Dr. Brundaban Sahu* & Rakesh Chandra Sahoo**

ABSTRACTPurpose: The purpose of this paper is to find out the impact of firm specific and macroeconomic variables

on Indian stock market return. The paper also aims at analysing the behavioural aspect of stock return.Design/Methodology/Approach: The paper uses hausman test and Breusch-Pagan Lagrange

multiplier(BPLM)testtofindouttheappropriatemodelforpaneldata.PooledOLSmethod is used to analyse theimpact of firm specific, macroeconomic variables and behavioural variable on stockreturn.

Findings: The results of the analysis indicate that price to book value ratio and firm sizes in terms of totalassets are two important firm specific determinants of Indian stock return. Macroeconomic variables- Grossdomestic products, money supply and 364 days U.S. Treasury bill rate have significant impact on stock return.India volatility index, a proxy for investors’ sentiment has significant negative impact on stock return.

Originality/ value: The paper considers both fundamental and behavioural aspects of Indian stock marketreturn.

Keywords: Stock market, macroeconomic variables, firm specific variables, India volatility index

IntroductionStock market, as an important component of financial system, plays a vital role in the economic

development of a country. It helps in transferring surplus fund from investors to the corporates, whichcan be used for productive purposes. The market exists only due to the fact that investors get sufficientreturn from their investment in various financial instruments. As per arbitrage pricing theory (APT) offinance stock return is affected by various macroeconomic (Gan et al., 2006) and firm specific variables(Shaikh et al., 2017). Other factors such as- legal, political environment, investors’ behaviour, riskreturn relationship in stock market can also affect stock return.

Over the years, a multitude of empirical studies have explored the relationship between stock marketreturn and macroeconomic and firm specific factors with most of the literature suggesting that basicmacroeconomic factors are influential in explaining stock return (Fama, 1981). Macroeconomic variables

* Assistant Professor, N.C Autonomous College, Jajpur, Odisha, Mobile- 9437315355, Email – [email protected]** Lecturer in Commerce, Model Degree College, Deogarh, Odisha. Mobile – 7873801335, Email- [email protected]


play an important role in deciding stock market return. Benjamin A. Abugri (2006) states that both domestic(exchange rates, interest rates, industrial production and money supply) as well as global variables (TheMorgan Stanley Capital International (MSCI) world index and the U.S. 3-month T-bill yield) have asignificant impact on Argentina, Brazil, Chile and Mexico stock market return. When the economic conditionof a country gets better, this impacts the stock market in a positive manner. Economic variables can affectthe amount of investment, demand supply factors, investors’ preference etc. A particular economic factorcan have impact on a particular stock market but may not affect other markets. Peiró (2015) Amadoproved that production and interest rate have significant impact on stock return in France, Germany andthe United Kingdom but United States stock market return is affected only by productionrate.

Stock return is also impacted by firm specific factors such as- size, price book value ratio, priceearnings ratio, dividend yield. Current market value of firm can changes due to change in discount rate/cost of capital, keeping future cash flow constant. Firm specific ratios- price book value, priceearningsratio; dividend yield can affect the discount rate, there by the future return on stock [Pontiffand Schall (1997)]. Size of firm in terms of total assets can affect the stock return. Stock market is alsoaffected by investors’ sentiment. If investors’ perception about the market trend is negative, it can affecttheir investment decision, thereby affecting stock return. Risk return relationship ofstocks can haveimpact on investment flow tostocks. Whether higher risk is being rewarded with higher return or notaffects the investment decision in a stock within a particular risk class (N. Pettengill et al.,1995).

As India is an emerging economy, stock market development can help the country a lot in thedirection of economic growth. Indian stock market is known for its high volatility. Excessive volatilityin the market discourages investment. One of the major challenges in the emerging markets is thepredictability of stock returns (Fama and French, 2004). So, research is to be done to understand theimpact of various factors on stock market return, which will help investors in taking confident investmentdecisions and policy makers in designing suitable policies for market and economic growth. Not manystudies have considered of both fundamentals and behavioural aspects of Indian stock market return.Our research objective in this direction is to find out the impact of both domestic, global macroeconomicfactors and company specific variables on Indian stock market return. Other objective of the study is toanalyse the behavioural aspect of Indian stock market return, which can motivate and help investors intaking investment decision. The novelty of the study is that it considers both fundamental and behaviouralaspects of stockreturn. Findings of the analysis indicates that price book value ratio, total assets affectstock return as two major firm specific variables. Domestic macroeconomic variables- Gross domesticproduct has a positive impact on stock return and money supply has negative impact on stock return.Global macroeconomic variable 364 days U.S. T bill rate positively affects Indian stock market return.The study reveals that behavioural factor can play a vital role in determination of stock return.

The paper is organised as follows. Section 2 gives a brief review of literature. Section 3 discussesthe data and methodology of the study. Section 4 is devoted to discussion of empirical results andsection 5 concludes the paper.

Literature ReviewThere exist a considerable amount of literature that supports the nexus between macroeconomic

variables and Stock market return, largely in the context of developed markets. However, Emerging

15An Impact of Macroeconomic Variables on the Functioning of Indian Stock Market

Stock markets stand out to that of developed markets owing to the huge amount of risk and a greaterreturn compared to the latter (Errunza, 1983; Claessens et al., 1993; Harvey, 1995a.). Both Global andLocal macroeconomic factors have an impact on the market return and Harvey (1995a) examined therelationship between the stock market return in emerging markets and a number of global factors likethat of world GDP, world oil prices, world inflation and trade weighted world exchange rate and founda limited impact of these factors on ESM return. Studies have also taken place considering the impactof local macroeconomic factors on stock return (Chen et al., 1986). Hence,the integration of the marketsdetermines the selection of global (perfectly integrated) or local macroeconomic variables (perfectlysegmented) or a combination of both (if the market is partiallyintegrated) (Bekaert and Harvey, 1995).As the assumption of perfect integration or perfect segmentation is not realistic, both global and localmacroeconomic variables may play a vital role in the stock market returns of the country.

Bilson et al., (2001) makes use of four domestic and one global factor to test the impact of thesevariables on ESM return. The four domestic variables are money supply, goods prices, real activity,exchange rate and value-weighted world market index proxying the global factor. In their study theyfind exchange rate and the world market index are the two influential macroeconomic variable on ESMreturn with other factors performing relatively poorly. Abugri, B. A. (2008) investigates the impact oflocal macroeconomic variables like exchange rate, interest rates, industrial productivity and moneysupply along with two global factors namely Morgan Stanley Capital International (MSCI) world indexand U.S 3-month T-bill yields on stock market return for four Latin American countries; Argentina,Brazil, Chile, Mexico. Abugri finds a consistent impact of Global macroeconomic factors on returnacross these four markets and impact of local factors vary across the countries.

Exploring these variables in particular, Appreciation of a country’s currency lowers the cost ofimporting goods including inputs, which makes up a major part of production in developing countries.This reduction in the cost of capital leads to an increase in local return. (Abugri, 2008; Pebbles andWilson, 1996; Bilson et al. (2001) finds a positive relationship between the appreciation of domesticcurrency and stockreturn.

In terms of money supply, the literature on the relationship of money supply with stock returngives mixed results, with several studies finding a positive impact of money supply on stock return(Bilson et al. 2001) and certain concluding a negative impact of money supply on stock return (Abugri,2008; Gan et al., 2006). The channel through which money supply impacts stock return varies. Changesin Money supply have an impact on the real activity of the economy thereby affecting the future cashflow and hence return (Rogalski and Vinso, 1977). However, changes in money supply have an effecton inflation, which may lead to a negative impact on stock return. (Abugri, 2008; Gan et al., 2006)

GDP represents the economic conditions of the market and the current stock level is positivelyrelated to GDP, as real economic activity has an impact on the future levels of cash flow therebyinfluencing stock market returns (Bilson et al. 2001; Fama, 1990; Ferson& Harvey, 1998; Peiró, 2016).

Bekaert, Harvey, and Lumsdaine (2002) expected U.S. interest rates to have a significant impacton that Latin American markets given the high U.S. equity ownership in the destination market. On thesame line, the Indian equity market have high share of U.S. equity ownership and hence one wouldexpect the U.S. interest rates to have a significant impact on the Indian stock marketreturn.


Firm specific variables such as dividend yield ratio, price to book value ratio, price earnings ratioalso affect stock return. Current market value of firm is calculated by discounting future cash flows atcost of capital. Keeping the cash flow constant, if the discount rate decreases, market value increases(over pricing of shares) (Pontiff and Schall, 1997). This can lead to lower future return. Discount ratechanges due to change in risk or liquidity. In this sense, firm specific ratios cause either increase ordecrease in discount rate affecting the stock return. They predict return because they capture informationabout risk (Lewellen, 2004). Literature provides evidence of impact of these ratios on stock return.Pontif and Schall (1997) showed aggregate measure of the book-to-market ratio of Dow index forecastsfuture market returns. Combination of these ratios can have impact that is more significant on stockreturn compared to individual variable impact (Shaikh et al., (2017); Jiang and Soo Lee, 2006). Duringcrisis period, higher risk stocks (lower price book value ratio) can generate lower return. Here theprice-book value ratio and return will have a positive relation (Serra and Martelanc, 2014). Cakici andTopyan (2013) proved price book value ratio as an important and consistent predictor of stock return.Size of firm in terms of total assets can also affect the stock return. Companies with more assets tend toinvolve in more risky business, which can lead to future loss. Assets of a company sometimes increasesbecause of acquisition of other firm, but this may not lead to higher future profit due to conflict ofinterest between managers and shareholders. Managers may go for such types of acquisitions, whichwill benefit them. This may not maximize shareholders wealth in long term. Stock prices falls due tothese acquisitions (Constantinouet al.,2017). Loughranand

Vijh(1997) proved disappointing return of acquiring firms in takeovers. Another reason for lowerreturn of large firms is overvaluation of stocks. If stock is currently overvalued due to investors’expectation that company will earn more profits in future, this may lead to lower future return on stocks(Constantinou et al., 2017). Jensen’s (1986) argued that excessive assets accumulation is a consequenceof agency cost of delegated management. Managers can go for such investment, which serves theirown interest. When shareholders realise this fact, stock price moves downward.

This study considers dividend yield, price to book value ratio, price earnings ratio, size in terms oftotal assets of Indian companies to understand their impact on stock return in manufacturing and servicessector. This also focuses on analysing global crisisimpact on stockreturn.

Stock market is also affected investors’ sentiment. If investors’ perception about the market trendis negative, it can affect their investment decision. Total investment flow to the stock market can getlower if the fluctuation in the stock prices (volatility) is high. Thus, volatility can negatively affectstock demand and price. Cakici and Topyan (2013) proved a negative correlation between total volatilityof stock and return. As per volatility feedback hypothesis, volatility leads to negative return (Pati et al.,2017). High volatility index indicates fear, anxiety, and pessimistic expectation of investors about thestock market, where as low volatility index reflect an optimistic attitude about the market. The sentimentof overall market can be judged with volatility index. The major source of stock market volatility isbehavioural finance, which states that investors are perfectly rational and their irrational and sentimentbased investment decisions can affect stock price movement (Daniel et al., 2002). Giot (2005a) reportedthat high volatility indicates an oversold market, which leads to lower return. Volatility index can alsobe used as risk management tool for deciding the investment in derivative products as a protectionagainst portfolio risk (Chandra and Thenmozhi,2015).


As investors’ behaviour or sentiment plays a vital role in determination of stock return, this studyfocuses on the behavioural aspect by considering the impact of volatility index on stock marketreturn.

Methodology

Data Source

The study considers S&P BSE (Bombay Stock Exchange) 200 index stocks for the period 1999-2017. BSE stocks are selected as BSE is the oldest stock exchange of India. The data for 100 companiesout of 200 listed companies at BSE is considered for the period of 1999-2017, due to inconsistency inthe availability of data. Only 100 companies reported values consistently for the period. To analyse thebehavioural aspect, data on India Volatility Index for 2009-2017. Annual Stock return (dependentvariable) data is taken from Prowess IQ maintained by Centre for Monitoring Indian Economy (CMIE).Price-earnings ratio, Price-book value ratio, dividend yield data is extracted from the same database.The missing values were replaced with an average value. Gross Domestic Products (GDP), narrowmoney supply data is collected from Reserve Bank of India database. 364 days US Treasury bill rate istaken from Federal Reserve Bank of St. Louis. India volatility index is taken from Prowess IQ databasefor the period 2009-2017. The general finance theory is the main input use in the process of selection ofvariables. The variables found to be having an influence on the stock return in the past studies and theavailability of data are other guiding factors in the variable selectionprocess.

Variables

Table 1: Definition and source ofvariables

Dependent Variable Definition

Annual Stock return (closing price-Opening price)/opening pricePrice-earnings ratio (P/E) Market price of share/ Earning of sharePrice-book value ratio (P/B) Market price of share/ book value of shareDividend yield ratio (yield) Dividend per share/ market price per shareSize Ln Total assetsGDP Gross Domestic ProductsM1 Narrow money supply364 US Treasury bill rate Coupon rateIndia Volatility Index Index valueIndustry D1 Dummy to distinguish the sectoral Impact on return

D = 1, If Manufacturing= 0, Otherwise (service)GFC D2 Dummy to incorporate the impact of Global financial crisis

D = 1, Post 2008 = 0,Otherwise

Descriptive StatisticsTable 2 reports the summary statistics for all the variables included in the model. The average

annual return is 0.82%. Standard deviation is 2.22, which indicates that there is a wide variation instock return of companies. Average of P/E, P/B, Yield ratios are 2.98, 1.06,.29 respectively. Indian


volatility index for average period is 17.13, which is very high. Size of the companies in terms of totalassets shows an average figure of 10.85 million rupees. The standard deviation of size indicates that allthe companies are quite similar insize.

Table 2: Descriptive Statistics

Variable Mean Std. Dev.

ReturnPrice-earnings ratio (P/E) 0.82323072.98255 2.2232150.8867693

Price-book value ratio (P/B) 1.065959 1.007783

Dividend yield ratio (yield) 0.2921827 0.9289635

Size 10.8517 1.76889

GDP 0.0679322 0.0187121

M1 0.120875 0.0498502

364 US Treasury bill rate -4755002 1.714372

India Volatility Index* 17.13444 4.53333

* - number of observation = 900

Model SpecificationTo investigate the relationship between macroeconomic, firm specific and behavioural aspects on

annual stock return in India, Panel data regression procedures are implied. Hausman test is applied toselect the appropriate model for panel data set. If the test failsto

reject the null hypothesis, Breusch-Pagan Lagrange multiplier test is used to select between randomeffect and pooled OLS. The results of the specification test are reported in table 3.

1 2 3 4 5 6 1 7Return lnP/ E B lnP/ B lnyield lnTA d lnGDP dlnM lnUSTbil

ThestudythenanalysesthebehaviouralaspectofstockreturnbyincorporatingIndiaVolatilityindexinthemodel

1 2 3 4 5 6 1 7 8Return lnP/ E B lnP/ B ln yield lnTA dlnGDP dlnM lnUSTbilate lndiaVIX

Results and DiscussionTo examine the impact of macroeconomic and firm specific factors on stock return and to evaluate

the impact of inclusion of VIX as a behavioural aspect, the study makes use of a 19 years micropanel data for the first objective and 9 years data for the second objective. Specification tests areemployed for selecting among Pooled OLS, Fixed Effect and Random Effect model. The results ofthe specification tests are reported in Table 3. The hausman test fails to reject the null Hypothesis ofno significant relationship between variable and unobserved heterogeneity, hence we proceed withthe BPLM test for the significance of unobserved heterogeneity. The BPLM test fails to reject thenull hypothesis of insignificance of unobserved heterogeneity. Therefore Pooled OLS is the preferredchoice.


Table 3: Specification tests

Model 1 – Firm Specific and Macroeconomic factors

Specification test Statistic P-Value Tested SelectionHausman -0.00 0.5807 Fixed/Random&pooled OLS* Random*Breusch-Pagan 0.09 0.3790 Pooled OLS/Random Pooled OLS

Model 2 – Firm Specific, Macroeconomic factors and behavioural Factor

Specification test Statistic P-Value Tested SelectionHausman 6.72 0.5670 Fixed/Random& Random*

pooled OLS*Breusch-Pagan 0.00 1.0000 Pooled OLS/Random Pooled OLS

*- Failing to reject the null of Hausman test, we accept Random effect model provisionally and test for thesignificance of unobserved heterogeneity

The result of the first regression model is reported in table 4.

Table 4: RegressionEstimates

Dependent Variable Return

Model Pooled OLSIndependent Variable CoefficientLn(pe) 0.0322

(0.0775)Ln(pb) -0.156**

(0.0691)Ln(yield) -0.0589

(0.0652)Dln(gdp) 0.1089***

(3.668)Dln(m1) -0.4123***

(1.491)Ln(ust) 0.233***

(0.0621)Ln(ta) -0.0760**

(0.0336)Industry dummy -0.0821

(0.114)Gfc dummy 0.195

(0.239)Constant 1.598***

(0.474)Observations 1,799R-squared 0.025

Standard errors inparentheses *** p<0.01, ** p<0.05, * p<0.1


The result of the first regression model indicates that price to book value ratio has a significantnegative impact on stock return, which means if P/B increases by 1%, return decreases by 15%.Increasein P/B indicates reduction in discount rate, which can lead to current overvaluation of stocks andultimately lower future return. This is similar to the study by Cakici and Topyan (2013), which provedbook to market ratio as a significant predictor of stock return. Size (ln total assets) indicates a significantnegative impact on return. This may be due to long-run underperformance by acquirer, over expansionby managers as a consequence of agency cost [Chan et al. (2008)]. If total assets of firm increases by 1unit, stock return of that company decreases by 7%. GDP has a significant positive impact on stockreturn. Growth in GDP, growth rate of money supply and U.S. T-bill perform verywell {Bilson et al.(2001); Abugri,(2008)} with a growth in GDP by 1% leading to increase in stock return by 11%. Moneysupply growth by 1% has a negative impact on stock return by 41%. Increase in US T bill rate can havea positive impact on S&P BSE stock return by 23%.

After getting the results of first regression model, the study considers 2008 crisis dummy, sectoraldummy to understand whether S&P BSE 200 index stock return is affected due to global financial crisisand whether there is a significant difference in stock return in manufacturing and services sector. PooledOLS again is applied after considering hausman and BPLM test results. As per the results of pooled OLSmodel, 2008 crisis has not brought any significant change in stock return of S&P BSE 200 index companies.There is also no significant difference in returns of manufacturing and services sector stocks.

Table 5: Regression Estimates

Dependent Variable ReturnModel Pooled OLSIndependent Variable CoefficientLn(pe) -0.0417

(0.0917)Ln(pb) -0.0249

(0.0829)Ln(yield) 0.00729

(0.0789)Dln(gdp) 0.09123**

(4.589)Dln(m1) -0.06905***

(2.424)Ln(ust) 0.0455

(0.0662)Ln(ta) -0.151***

(0.0424)Indiavix -0.0597***

(0.0165)Constant 0.03628***

(0.829)Observations 799R-squared 0.041

Standard errors inparentheses *** p<0.01, ** p<0.05, * p<0.1


Table 5 indicates the pooled OLS results of firm specific, macroeconomic, behavioural variableson stock return. When behavioural aspect is considered all firm specific financial variables are becominginsignificant. This shows that behavioural aspect plays a vital role in determination of stock return ofS&P BSE 200 index socks. Volatility index has a negative impact on stock return [Cakici and Topyan(2013)]. Kumar (2012) also proved a negative relation between India VIX and Indian stock marketreturn. When volatility index increase by 1 unit, return decreases by 6%. Total assets have a significantnegative impact on stock return. Macroeconomic variable, GDP growth indicates 9% increase in stockreturn. If money supply increases by 1%, return decease by6.9%.

ConclusionThis paper analysed the impact of various firm specific and macroeconomic variables on Indian

stock market return considering S&P BSE 200 index stocks. Making a departure from previous studies,this study considers both kinds of variables for analysing Indian stock market return. Hausman andBPLM tests are used to find out the appropriate model for panel data set consisting 100 companies for19 years. Pooled OLS results indicate that firm specific variables- price to book value ratio, total assetsand macroeconomic variables- GDP, money supply and U.S. T bill rate significantly affect S&P BSE200 index stocks.

In the second model, India volatility index is considered and the result shows that behaviouralaspect plays even more important role in determination of stock return compared to firm specificvariables. High volatility in the market can discourage investors from investing in stock market, whichcan affect stock return. Volatility index has a negative impact on stockreturn.

The study can help investors in taking investment decisions. Factors significantly affecting stockreturn have been discussed in the paper, which can be taken as one guideline for investment decision.Policy makers can consider impact of different firm specific and macroeconomic variables on stockmarket return, while designing policies for economic development of the country.

Future studies can consider stocks from other indices to generalise the findings of the paper. Otherfirm specific and macroeconomic variables can be studied to find out their impact on Indian stockmarket performance. Different behavioural indicators can be developed to proxy for investors’ sentiment,which can help in understanding the behavioural aspect of Indian stock market return in a bettermanner.

References1. Abugri, B.A., 2008. Empirical relationship between macroeconomic volatility and stock returns: Evidence

from Latin American markets. International Review of Financial Analysis, 17(2), pp.396-410.

2. Azeez, A.A. and Yonezawa, Y., 2006. Macroeconomic factors and the empirical content of the ArbitragePricing Theory in the Japanese stock market.Japan and the world economy, 18(4), pp.568- 591.

3. Bekaert, G., Harvey, C.R. and Lumsdaine, R.L., 2002. The dynamics of emerging market equity flows.

4. Journal of International money and Finance, 21(3), pp.295-350.

5. Bekaert, G. and Harvey, C.R., 1995. Time varying world market integration.The Journal of Finance, 50(2),pp.403-444.

6. Bhargava, A., 2014. Firms’ fundamentals, macroeconomic variables and quarterly stock prices in the US.Journalof Econometrics, 183(2), pp.241-250.


7. Bilson, C.M., Brailsford, T.J. and Hooper, V.J., 2001. Selecting macroeconomic variables as explanatoryfactors of emerging stock market returns. Pacific-Basin Finance Journal, 9(4), pp.401- 426.

8. Cakici, N. and Topyan, K., 2013. Return predictability of Turkish stocks: an empirical investigation.

9. Emerging Markets Finance and Trade, 49(5), pp.99-119.

10. Chan, L.K., Hamao, Y. and Lakonishok, J., 1991. Fundamentals and stock returns in Japan. the Journal ofFinance, 46(5), pp.1739-1764.

11. Chan, L.K., Karceski, J., Lakonishok, J. and Sougiannis, T., 2008.Balance sheet growth and the predictabilityof stock returns.University of Illinois at Urbana-Champaign working paper.

12. Chandra, A. and Thenmozhi, M., 2015. On asymmetric relationship of India volatility index (India VIX) withstock market return and risk management. Decision, 42(1), pp.33-55.

13. Chen, N.F., Roll, R. and Ross, S.A., 1986.Economic forces and the stock market.Journal of business,pp.383-403.

14. Claessens, S., Dasgupta, S. and Glen, J., 1995. Return behavior in emerging stock markets. The World BankEconomic Review, 9(1), pp.131-151.

15. Constantinou, G., Karali, A. and Papanastasopoulos, G., 2017. Asset growth and the cross-section of stockreturns: evidence from Greek listed firms. Management Decision, 55(5), pp.826-841.

16. Cooper, R.V., 1974. Efficient capital markets and the quantity theory of money.The Journal of Finance,29(3), pp.887-908.

17. Daniel, K., Hirshleifer, D. and Teoh, S.H., 2002. Investor psychology in capital markets: Evidence and policyimplications. Journal of monetary economics, 49(1), pp.139-209.

18. Errunza, V.R., 1983. Emerging markets: a new opportunity for improving global portfolio performance.

19. Financial Analysts Journal, 39(5), pp.51-58.

20. Fama, E.F., 1981. Stock returns, real activity, inflation, and money. The American economic review, 71(4),pp.545-565.

21. Fama, E.F., 1990. Stock returns, expected returns, and real activity. The Journal of Finance, 45(4), pp.1089-1108.

22. Fama, E.F. and MacBeth, J.D., 1973. Risk, return, and equilibrium: Empirical tests. Journal of politicaleconomy, 81(3), pp.607-636.

23. Ferson, W.E. and Harvey, C.R., 1997. Fundamental determinants of national equity market returns: A perspectiveon conditional asset pricing. Journal of Banking & Finance, 21(11-12), pp.1625-1665.

24. Gan, C., Lee, M., Yong, H.H.A. and Zhang, J., 2006. Macroeconomic variables and stock market interactions:New Zealand evidence. Investment Management and Financial Innovations, 3(4), pp.89- 101.

25. Giot, P., 2005. Implied volatility indexes and daily Value at Risk models.Journal of Derivatives, 12(4), p.54.

26. Hsing, Y., Phillips, A.S. and Phillips, C., 2013. Effects of Macroeconomic and Global Variables on StockMarket Performance in Mexico and Policy Implications.Research in Applied Economics, 5(4), p.107.

27. Jensen, M.C., 1986. Agency costs of free cash flow, corporate finance, and takeovers. The American economicreview, 76(2), pp.323-329.

28. Jiang, X. and Lee, B.S., 2007. Stock returns, dividend yield, and book-to-market ratio. Journal of Banking &Finance, 31(2), pp.455-475.

29. Kumar, S.S.S., 2012. A first look at the properties of India’s volatility index.International Journal of EmergingMarkets, 7(2), pp.160-176.

30. Lewellen, J., 2004. Predicting returns with financial ratios. Journal of Financial Economics, 74(2), pp.209-235.


31. Loughran, T. and Vijh, A.M., 1997. Do long term shareholders benefit from corporate acquisitions?.TheJournal of Finance, 52(5), pp.1765-1790.

32. Menike, L.M.C.S., Dunusinghe, P.M. and Ranasinghe, A., 2015. Macroeconomic and Firm Specific Determinantsof Stock Returns: A Comparative Analysis of Stock Markets in Sri Lanka and in the United Kingdom. Journalof Finance and Accounting, 3(4), pp.86-96.

33. Pati, P.C., Rajib, P. and Barai, P., 2017. A behavioural explanation to the asymmetric volatility phenomenon:Evidence from market volatility index. Review of Financial Economics, 35, pp.66-81.

34. Peiró, A., 2016. Stock prices and macroeconomic factors: some European evidence. International Review ofEconomics & Finance, 41, pp.287-294.

35. Pettengill, G.N., Sundaram, S. and Mathur, I., 1995. The conditional relation between beta and returns.Journalof Financial and quantitative Analysis, 30(1),pp.101-116.

36. Pontiff, J. and Schall, L.D., 1998. Book-to-market ratios as predictors of market returns 1. Journal ofFinancial Economics, 49(2),pp.141-160.

37. Rogalski, R.J. and Vinso, J.D., 1977. Stock returns, money supply and the direction of causality. The Journalof finance, 32(4),pp.1017-1030.

38. Samontaray, D.P., Nugali, S. and Sasidhar, B., 2014. A study of the effect of macroeconomic variables onstock market: Saudi Perspective. International Journal of Financial Research, 5(4), p.120.

39. Serra, R.G. and Martelanc, R., 2014. Hierarchical Determinants of Brazilian Stock Returns During the 2008Financial Crisis. Emerging Markets Finance and Trade, 50(sup5), pp.51-67.

40. Shaikh, A.S., Kashif, M. and Shaikh, S., 2017. Measuring Stock Market Predictability with Implications ofFinancial Ratios: An Empirical Investigation of Pakistan Stock Market. Journal of Business Strategies, 11(1),p.41.

41. Theriou, N.G., Aggelidis, V.P., Maditinos, D.I. and Ševiæ, Ž., 2010. Testing the relation between beta andreturns in the Athens stock exchange.Managerial Finance, 36(12), pp.1043-1056.

42. Verma, R., 2011. Testing forecasting power of the conditional relationship between beta and return.

43. The Journal of Risk Finance, 12(1), pp.69-77.


A Systematic Review of Literatures on CustomerChurn Analysis in the TelecommunicationIndustry

Dr. Manoj Kumar Dash* & Dr. Susmita Dash**

ABSTRACTPurpose - This paper aims to comprehensively and systematically review the existing literature on

customer churn analysis in a telecommunication industry context and critically analyze the research pattern,developments, and propose future research agenda and/or directions.

Design/Methodology/Approach- All relevant articles between 1985 and 2018 were systematicallycollected. The retrieved articles were then analyzed using bibliometric meta-analysis technique.

Findings- Customer Churn Analysis is the telecommunication industry is limited to mostly quantitativetechniques. Therefore, the advantage of qualitative research methods is not seen in the work. It is seen thatthere is a methodology bias in the telecom customer churn research. It is seen that the majority of theresearchers in the area of customer churn analysis are involved in theory verification than in theory generation.Further, the methodologies used in the research, developed and tested, are suitable for confirming propositionsor hypothesis rather than discovering new propositions or hypothesis. The existing literature reflects thedominance of a positivist view. The basic reflection from this study is that the researchers have too longignored the metatheoretical implications of reliance on a single logical positivism paradigm. Such dominanceof one theoretical philosophy in customer churn research is unfortunate and soon need to be addressed. It isalso seen that most of the research are from the USA, China,and some other countries. Customer churn inmany emerging economies like India needs to be more research. Even it is seen that most of the researcherssuggested a generalized set of reasons and model for the whole telecom industry of a particular country.

Originality/ValueThis study contributes to the existing research through its insights from the bibliometric analysis of

existing research and critical assessment of existing customer churn literature. This critical review providesboth academia and practicing world insights about the current developments and possible future directionsof research in customer churn analysis in the telecommunication industry.

Keywords: telecommunication, customer churn analysis, prediction, bibliometric analysis,Customerretention, Mobile phone services.

* Associate Professor, Khallikote University Berhampur (Odisha)** Lecturer, Khallikote Autonomous College, Berhampur

25A Systematic Review of Literatures on Customer Churn Analysis in the...

IntroductionToday, most of the markets face severe competition and are getting increasingly saturated. Therefore,

companies have recognized that they should focus on identifying possible churning customers anddevice their retention strategy or business strategy at large (Hadden et al., 2005). On the one hand,acquiring new customers is important for business growth and on the other hand retaining a customeris important for sustaining in the business and earn long term profitability. This is primarily becauseof the fact that the net return on investments from retention strategies is much higher than that foracquisitions as it’s relatively less costly to retain a customer than accruing new ones. Companiesacross the world leverage social insight and intelligence to prevent customer churn and particularlythose operating in the competitive sector like the Telecommunication sector. The situation is morealarming in emerging economies like India where 96% of mobile subscribers are constantly shiftingtheir service providers in search of a better offer (Kapoor, 2017)! Whereas in a developed economylike the USA, the average monthly churn rate for top wireless companies may vary in single digits.Verizon Wireless had 1.22 percent average monthly churn rate in the third quarter of 2018 and AT&T’sin the fourth quarter of 2016 had 1.71 percent churn rate. Sprint Nextel had the highest churn rate inthe U.S. in 2016 at 2.8 percent (FierceWireless). Though this percentage figures look small, whenwe see it in numbers it’s a huge customer base.But in the case of Germany, the churn rate of Vodafonein the mobile communications segment was in the second quarter of 2018/2019, the prepaid churn of38.3 percent! In 2018, there were roughly 18.62 million Germans aged 14 years, and older who werevery interested in telecommunications (IfdAllensbach) and consumer behaviour was different in theeconomy. In an emerging economy like India, Airtel said the percentage of users leaving the networkis 3.6% due to competitive pressures (Sengupta, 2017). In the same economy, Reliance Jio reportedthat they have a churn rate of 0.30 percent per month, which it claims to be the lowest churn rate inthe industry (Jain, 2018). Bersen et al. (2000) also estimated that the average churn rate at 2.2% permonth. Customers are not independent, and the behavior of a customer depends on the behavior ofthose who are around them (Zhang et al., 2012). Customer churn rate and reasons vary from economyto economy. Therefore, for any company to survive in the challenging environment oftelecommunication industry, the company must recognize and analyze customer attitudes and/orbehavior. As a result in the past two decades both academia and corporate world have devised multiplesolutions to make companies competitive by recognizing and forecasting customer preferences andbehaviors in order to minimize customer churn.This paper collects, filters, shortlist, and then analyzethe existing literature from the selected databases and demonstrates the development of customerchurn analysis area and various methods and models that are devised to predict customer churn in thetelecommunication industry.

Research MethodologyThe study follows a systematic approach in reviewing the relevant research papers in the area of

customer churn analysis in the telecommunication industry. Theliterature review followed the PRISMA


guidelines (Moher et al., 2009).The study was conducted in the year 2018 to identify 211 articles relatedto different approaches in dealing with customer churn issues in telecommunication industry worldwideand relevant other works of literature. The study includes the literature published between the years1985 and 2018. All the papers were searched, filtered, and collected from the databases (subscribed byABV IIITM Gwalior, India) like EBSCO Host, Emerald, Science Direct, Scopus, and Web of Science.

A comprehensive set of search terms were identified like a customer, churn, analysis, andtelecommunication based on the author’s judgment and experience on the subject matter. The use ofquestion marks symbol in the database during search ensured that both the British and American wayof spelling the selected words are identified and included in the preliminary analysis. In the study, onlythose papers were considered that are written in English and a full text is available for download. Thestudy includes only online publications. The search was matched for similarity in abstracts, paper titles,and keywords with the identified search terms. This resulted in a collection of 211 different articles.Allthe collected papers were managed using Mendeleysoftware,and the authors ensured no duplicate papersthough manual screening. The study might have missed a few papers that are not indexed in the chosendatabases and/or are available in offline mode only in the systematic approach of the literaturereview.Two researchers (authors) independently screened the selected literature and based on consensus thefinal list of papers were included. All form of disagreements related to the selection of papers wereresolved through detailed discussion and reasoning. The criteria of the sectionwerea citation, journalranking/indexing, relevance, and body of literature.

Table 4: Literature search and analysis

Type of Research Paper Conference papers, Journal Papers, Book Chapters

The medium of paper collection (Online/Offline) Online

Selection technique Systematic bibliometric analysis

Databases used Web of Science (Primarily for analysis) Scopus, EBSCO-Host, Emerald, Science Direct

Tools used for analysis VOS viewer and Web of Science online analysis facility

Duration of collection Between 1985 and 2018

Total Number of Papers Selected for Analysis 211

A literature review can be seen as a means to identify the conceptual content of a focused area and

may be used as a base for further research (Raghuram et al., 2010).The study further conducts abibliometric meta-analysis and generates new insights on the existing published research.The conceptof bibliometrics was first introduced by Allan Pritchard in 1969 in his popular work that was titled“Statistical Bibliography or Bibliometrics.” Bibliometric analysis helps us understand the existingliterature in a holistic way.The traditional literature reviews were limited by the capacity of manualdata processing and analysis of researchers. The result of such reviewis often limited to the priorknowledge, experience, opinions, and expertize of the researchers. In the bibliometric approach, thestudy uses quantitative methods to examine the research Metadata and comes up with new insights thatcreate new knowledge about the focused area of study.


Figure 5: a Literature search and shortlisting process

The bibliometric analysis uses some software/tools (in this study we have used VOSviewer1) toconduct a comprehensive search of relevant articles in the selected databases and quantitative methodsto present thescientific results(Pritchard, 1969).The bibliometric analysis approach may provide moreobjective and comprehensive results as compared with the traditional review approach (Ramos-Rodriguezet al., 2004).

Literatureand Analysis

A Working Definition

To Customer churn is defined as the movement of customers from one service provider to anotherservice provider in the telecom industry and churn management refers to the service provider’s processto retain itself profitable by retaining profitable customers (Berson et al., 2000).

Customer Churn in the Telecommunication Industry

To quote Professor Clayton Christensen, Harvard Business School, he says that disruptive innovationshave changed the way the businesses used to be run. These innovations are Social networks, cloudcomputing, and big data,etc. It seems that the telecommunication industry has witnessed these changesmore than many other industries. Unlike many industries, telecommunication industry hasa very minimumor negligible switching costs,and this is detrimental for the industry. Telecom customers who want toswitch their service provider for various reasons are free to do so.


Among many challenges that any telecom company face, the challenge of managing customer churnand maintain a healthy customer base is of utmost importance. Customer churn means the periodic lossof clients or customers for various reasons in a business organization. Customers are free to choosetheir service providers among the pool of similar or different service providers and thus exercise theirrights of choice and right to switch from one operator to another. When a customer churn, it is verycostly for a company. First, the company loses the prospect of future earnings from this churn customer.Secondly, the resources that were invested in acquiring this churn customer in terms of manpowerinvestment, the cost incurred in publicity, public relations, time invested, promotions and other operationscost. Churn customer is simply the one who joins another company (competing company) leaving theexisting service provider. Churn management, management that determinethe customer turnover orattrition. (Haddenet al, 2007). Churn rate measures the number of customer who decides to leave thecompany or join the company during a specific period and the term is used in business to present thenumber of customers leaving the company or staying in. The retention of the customer is possiblethrough improvement in the company’s services and offerings for the churn customers and this is possibleonly by knowing the reason for customer churn.

In the fiercely competitive telecommunication market like the Indian telecom market, customersdemand tailored products and expect better services but at a budget rate or fewer prices. The telecomcompanies extensively engage themselves and invest in various studies, campaigns, and almost everythingthat they may do in order to find the reasons of customers churn, measuring customer loyalty and waysto regain the lost customers. They focus on avoiding losing their customers because it is more costlyand difficult to acquire new ones. Attracting new customers’ costs multiple times more than retainingthe old customers,Therefore, the developments of new, effective, and efficient analysis methods anduse of proper tools have become necessary.

Bibliometric Analysis of Customer Churn Literature (in Telecommunication)

A detailed bibliometric analysis of the available literature on customer churn in thetelecommunication industry (in a web of science core collection between 1985 and 2018) reviled theimportance of the problem. Fig. 1 shows the increase in interest in customer churn related research inthe telecom industry, in terms of a number of publications and citations of the selected 211 documents,from 2000 to 2018 on the Web of Science database. It is seen that citations have been increasing overthe period of time and increasing significantly. It is seen that the publication citation reached a maximumnumber in 2017. In the year 2017, there was 317 publication citation related to customer churn in thetelecommunication industry (as on 4thMarch 2018; 15:00 pm). The first article appeared in an issue inthe year 2000. One of the early stage publications on customer churn is Mozer et al. (2000). The workof Mozer et al. (2000) have been cited for 137 times (as on 4thMarch 2018; 15:00 pm). Mozer et al.(2000) used various techniques like logit regression, neural network, decision trees, and boosting. Basedon this technique, the authors’ predicted churn and tried to find out answers to questions like whatincentives should be offered to the subscribed customers in order to increase retention rate in order tomaximize company’s profitability? Until 2008, there were not even 100 publication citation in the areaof study, annually. But, with time there is an increase in the annual citation count,and this signifies thatthere are an increasing research interest and importance in telecom churn. Telecom customer churnliterature has been cited for 2,275 times in total (Sum of times cited),and without self-citations, the


count stands at 1,754 (as on 4thMarch 2018; 15:00 pm). Fig. 1 reflects that customer churn in telecom iswell researched in recent years. The top 5 cited articles are listed in Table 2. It is seen that telecomchurn is more researched in countries like the USA, People Republic of China, Pakistan, and SouthKorea. It is seen that at large customer churn falls in the research areas of computer science, engineering,operation research management science, business economics, and telecommunication.

The highly contributing organizations are University College Dublin, Beijing University of PostsTelecommunications, and KU Leuven. One of the highest contributing authors is BingquanHuang. Some of his contributions are Huang et al. (2016), Huang et al. (2012), Huang et al.(2011), and Huang et al. (2010). Huang et al. (2016) discusses on rule-based learning algorithmsused in churn prediction. He discuss the concern that most of these algorithms are designedwith the assumption of having a well-balanced dataset. He suggests that this may result in anunacceptable prediction results. Thus, he introduces a Fuzzy Association Rule-basedClassification Learning Algorithm that may be used for churn prediction. The proposedapproach can achieve better and acceptable accuracy in customer churn prediction and maybe used for efficient customer churn prediction.

Fig.1: Citation report for 211 results on Customer Churn Literature (in telecommunication) from Web ofScience Core Collection between 1985 and 2018

A detailed co-authorship analysis of author, who have a minimum of 2 documents and a minimum50 citation, reflects that there is a high degree of collaborative work among authors like E. Johnson, R.Wolniewicz, H. Kaushansky, M. Mozer, and D. Grimes as seen in Fig. 2. Further, a more detailed co-authorship analysis of author, who have a minimum of 2 documents and irrespective of citation, reflectsthat there are two clusters of the author working collaboratively in the areas of telecom customer churnas seen in Fig. 3(red and green are two different clusters). It is seen that B. Baesens have more researchcontribution among all the authors. As seen in Fig. 4, the USA and China have more contribution toliterature among all countries. Authors from the USA have been working more collaboratively withauthors from countries like Pakistan, Sweden, Taiwan, China, South Korea, and Australia,etc. on telecomcustomer churn. Fig. 5 reflects that KatholiekeUniversiteit Leuven and the University of Southamptonhave more co-authorship in telecom churn literature, have been working collaboratively compared toother organizations, with significant literature contribution.


Table 3: Techniques used by various authors for churn prediction

Author/s

Rot

atio

n Fo

rest

Reg

ress

ion

CA

RT

Rou

gh S

et T

heor

y

Clu

ster

Ana

lysis

Mar

kov

Mod

el

Dec

isio

n T

ree

Gen

etic

A

lgor

ithm

s N

eura

l net

wor

k

Eth

nogr

aphy

/ N

etno

grap

hy

Rot

Boos

t

Hyb

rid

Mod

els

KN

N

Ran

dom

For

est

Rot

atio

n Fo

rest

Dis

crim

inan

t-an

alys

is

fuzz

y lo

gic

Bay

esia

n ne

twor

k

Supp

ort V

ecto

r M

achi

nes

Cla

ssifi

catio

n

Vot

ed P

erce

ptro

n

Ahmed et al. 2017

Sharma et

al. 2013

Kang 2008

Gursoy

2010

Verbeke

2012

Burez 2009

Brandusoiu

2013

Qureshi

2013

Hung 2006

Kirui 2013

Kamalraj

2013

Backiel

2015

Olle 2014

Idris 2013

Idris 2014

Yabas 2012

Amin 2014

Bose 2009

Ahn 2006


Table 4: Recent papers of telecom churn prediction, as on 4th March 2018K

eyw

ords

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me

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etw

orks

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ries

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adba

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2018

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Po

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, M.,

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., B

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ns, B

., Le

mah

ieu,

W.,

Van

thie

nen,

J. H

arta

ti, E

.P.,

Adi

wija

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Bija

ksan

a, M

.A.

Yeb

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Asia

mah

, E.,

Nar

teh,

B.,

Mah

mou

d, M

.A.

Ger

pott,

T.J.

, Mei

nert,

P.

Ósk

arsd

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, M.,

Bae

sens

, B

., V

anth

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n, J.

Title

Tim

e se

ries f

or e

arly

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tion:

Usin

g sim

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the

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obile

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unic

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s Mob

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oney

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Sl.

No.

1 2 3 4 5


ConclusionCustomer Churn Analysis is the telecommunication industry limited to data mining, machine

learning, and Statistical techniques, mostly quantitative techniques, and few researchuses social medianetworks to understand the reason for churn. There seems to be no research that tried to understand thereason of customer churn in telecommunication industry using the qualitative technique, eitherethnography or Netnography technique, and recommend solution accordingly in the form of Modelsand Strategies. Therefore, the advantage of qualitative research methods like Netnography/ Ethnographyis not seen in the works, thus missing naturalistic consumer insights and the advantage of the researcher’sparticipant observation. It is seen that there is a methodology bias in the telecom customer churn research.One of the established and followed psychologists, Charles Reichardt and Thomas Cookcommented inthe context of quantitative and qualitative research methods. It was suggested that the basic differencebetween the quantitative and qualitative paradigms is based on verifications versus discovery. Thequantitative methods are developed for the purpose of verification or confirmation of theories,and suchverifications are believed to lead towards the development of enduring theoretical structures that willerect “theoretical palaces” on the foundation being laid. Whereas, qualitative approacheswere developedfor the task of discovering or generating theories (Deshpande, 1983). It is seen that the majority of theresearchers in the area of customer churn analysis are involved in theory verification than in theorygeneration. Further, the methodologies used in the research, developed and tested, are suitable forconfirming propositions or hypothesis rather than discovering new propositions or hypothesis.Theexisting literature reflects the dominance of a positivist view asReichardt and Cook stated that wesometimes use methods of theory verification even in situations where theory discovery may be morerelevant. So, it is our intention to recommend that the qualitative paradigm has a strong hold in marketingdiscipline and sub areas like customer churn and we should also consider qualitative methods in ourproblem-solving approach and new theory building relevant to customer churn, as we believe that theoryverification is as important as theory generations. The basic reflection from this study is that theresearchers have long ignored the metatheoretical implications of reliance on a single logical positivismparadigm. Such dominance of one theoretical philosophy in customer churn research may not beencouraged and soon need to be addressed. Robert Chia in his article “The production of managementKnowledge: Philosophical Underpinnings of Research Design” says that legitimate and acceptableknowledge is determined by the philosophical attitude of a community of scholars and that it changesfrom time to time,i.e. knowledge creation and legitimation is never static and continues to renew itself.

It is also seen that most of the research are from the USA, China,and some other countries. Customerchurn (telecommunication context) in many emerging economies like India needs to be more research,as there are very few high-quality papers available in Indian context (Considering Web of Science CoreCollection database) and similar emerging economies. Even it is seen that most of the researcherssuggested a generalized set of reasons and model for the whole telecom industry of a particular country.Today, the reasonfor churn not only vary from economy to economy but also from company to company.So, we are required to consider the individual company in a particular economy for churn analysis.

Further, researchers may explore and consider new sources of data for the purpose of analysis. In thecan world, the relevant data doesn’t exist. Since the future hasn’t happened yet, we actually have no relevantdata to do the analysis on! (Martin and Golsby-Smith, 2017). We may try to find a new source of data that


may better help us in predicting churn behavior like say we may create data by prototyping (Say, we offercustomers with new services or offers and observe their reactions for insights and yield possible relationwith churn). What we want to bring out is that scientific analysis of data has helped in better decision makingand the world a better place,but it doesn’t mean that every business decision should follow the same path!Because things indeed can be different from what we see! But we need to remember that “variety of approachesto management theory has led to a kind of confusion and destructive jungle warfare” (Koontz, 1980) and weshould be cautious and justifiable in pursuing any approach leading to knowledge creation. The study by nomean tries to delegitimizing existing research approaches and only ask the researches to ensure that badmanagement theories don’t destroy good management practices (Ghosal, 2005).

Limitation of study and Future ResearchIn this piece of work, only mobile telecommunication related literaturewas taken into consideration.

In the whole work, only mobile telecommunication service is discussed exclusively. The research papersthat are listed in the Web of Science and Scopus database are widely used in this work. This has ensureda certain degree of quality. But, this has resulted in the exclusion of a number of works that are publishedin journals not indexed in Web of Science or Scopus databases. The insights from the study may not begeneralized and are particular to time, place (database), and keywords chosen in the study. There ishuge scope to extend the study to a larger scale and apply comprehensive meta-analysis.Thetelecommunications sector is known for its heavy marketing practice,and they apply various marketingstrategies toreduce churn and counteracts the negative effect related to various customer dissatisfaction.However, not all, service operators are successful in this respect and even all the discussed churn analysismethods and models are not equally promising. This begs the question of which of the discussed churnprediction methods and models are high performing solutions? In which situations are these methodsand models more suitable? Which of the above methods and models are more reliable and exhaustivein their insights? These questions may be seen as an important subarea for furtherresearch.

AcknowledgmentIt is our brilliant supposition to put on record my best admirations, most thoughtful feeling of

appreciation to Prof. (Dr.) Rajendra Sahu, Dr. Gourav Agarwal, and Prof. (Dr.) S.G Deshmukh of ABV-Indian Institute of Information Technology and Management, Gwalior (India) for their continuous supportand guidance in accomplishing this piece of work. We would like to take the opportunity to thank Prof.(Dr.) Russell W. Belk, Professor of Marketing; Kraft Foods Canada Chair in Marketing, from SchulichSchool of Business, Canada for his online support and advice.

References1. Ahmed, A. A., & Maheswari, D. (2017). Churn prediction on huge telecom data using hybrid firefly based

classification. Egyptian Informatics Journal, 18(3), 215-220.

2. Ahn, J. H., Han, S. P., & Lee, Y. S. (2006). Customer churn analysis: Churn determinants and mediationeffects of partial defection in the Korean mobile telecommunications service industry. Telecommunicationspolicy, 30(10-11), 552-568.

3. Ahn, J. H., Han, S. P., & Lee, Y. S. (2006). Customer churn analysis: Churn determinants and mediationeffects of partial defection in the Korean mobile telecommunications service industry. Telecommunicationspolicy, 30(10-11), 552-568.


4. Aircel files for bankruptcy at NCLT, facing Rs 15500 crore debt. (2018). Zee Business.

5. Amin, A., Khan, C., Ali, I., & Anwar, S. (2014, November). Customer churn prediction in the telecommunicationindustry: With and without counter-example. In Mexican International Conference on Artificial Intelligence(pp. 206-218). Springer, Cham.

6. Armstrong, W. E. (1950). A note on the theory of consumer’s behavior. Oxford Economic Papers, 2(1), 119-122. 10.1093/oxfordjournals.oep.a041384

7. Arno De Caigny, Kristof Coussement,and Koen W. De Bock. (2018) A New Hybrid Classification Algorithmfor Customer Churn Prediction Based on Logistic Regression and Decision Trees. European Journal ofOperational Research.

8. Ascarza, E., Iyengar, R., &Schleicher, M. (2015). The Wrong Way to Reduce Churn. Harvard BusinessReview. Retrieved 27 February 2018, from https://hbr.org/2015/10/the-wrong-way-to-reduce-churn

9. Belk, R. (2017). Netnography Query: Understanding better the relation between Netnography and SentimentAnalysis. Online.

10. Belk, R. W., Sherry Jr, J. F., &Wallendorf, M. (1988). A naturalistic inquiry into buyer and seller behaviorat a swap meet. Journal of Consumer Research, 14(4), 449-470.

11. Bersen et al (2000) BersenA Smith S Thearling K Building Data Mining Applications for CRM 2000 estimated that the average churn rate for mobile customers was 2.2% per month.

12. Chia, R. (2002). Philosophy and Research. Essential skills for management research, 1.

13. Denzin, N. K., & Lincoln, Y. S. (Eds.). (2011). The Sage handbook of qualitative research. Sage.

14. Deshpande, R. (1983). “Paradigms lost”: On theory and method in research in marketing. Journal of marketing,47(4), 101-110.

15. Duan, W., Gu, B., &Whinston, A. B. (2008). Do online reviews matter?—An empirical investigation of paneldata. Decision support systems, 45(4), 1007-1016.

16. Dwyer, F. R., Schurr, P. H., & Oh, S. (1987). Developing buyer-seller relationships. The Journal of marketing,11-27.

17. Escalas, J. E., &Bettman, J. R. (2017). Connecting with celebrities: How consumers appropriate celebritymeanings for a sense of belonging. Journal of Advertising, 46(2), 297-308. 10.1080/00913367.2016.1274925

18. FierceWireless. (n.d.). Average monthly churn rate for wireless carriers in the United States from 1st quarter2013 to 3rd quarter 2018. In Statista - The Statistics Portal. Retrieved February 28, 2019, from https://www.statista.com/statistics/283511/average-monthly-churn-rate-top-wireless-carriers-us/.

19. Fox, N., & Roberts, C. (1999). GPs in cyberspace: the sociology of a ‘virtual community’. The SociologicalReview, 47(4), 643-671.

20. Freiden, J., &Takacs, S. (1996). Consumer behavior and AIDS: Assessing the business impact. Journal ofConsumer Marketing, 13(6), 44-58. 10.1108/07363769610152590

21. Gensler, S., Völckner, F., Liu-Thompkins, Y., &Wiertz, C. (2013). Managing brands in the social mediaenvironment. Journal of interactive marketing, 27(4), 242-256.

22. Georgescu-Roegen, N. (1936). The pure theory of consumersbehavior. Quarterly Journal of Economics, 50(4),545-593. 10.2307/1891094

23. Gerpott, T. J., &Meinert, P. (2017). Termination notice of mobile network operator customers after a tariffswitch: An empirical study of postpaid subscribers in Germany. Telecommunications Policy.

24. Ghoshal, S. (2005). Bad management theories are destroying good management practices. Academy of Managementlearning & education, 4(1), 75-91.

25. Godes, D., &Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketingscience, 23(4), 545-560.


26. Gürsoy, U. T. ª. (2010). Customer churn analysis in telecommunication sector. Istanbul University Journal ofthe School of Business, 39(1), 35-49.

27. Hadden, J., Tiwari, A., Roy, R., &Ruta, D. (2007). Computer assisted customer churn management: State-of-the-art and future trends. Computers & Operations Research, 34(10), 2902-2917.

28. Hidalgo, F. (2009), “Netnografia”, available at: http://netnografia.blogspot.com.es (accessed 14 September2012).

29. Hirschman, E. C. (1986). Humanistic inquiry in marketing research: philosophy, method, and criteria. Journalof marketing Research, 237-249.

30. Hosseini, M., &Ghalamkari, A. (2018). Analysis social media based brand communities and consumer behavior:A netnographic approach. International Journal of e-Business Research, 14(1), 37-53. 10.4018/IJEBR.2018010103

31. Huang, B., Buckley, B., &Kechadi, T. M. (2010). Multi-objective feature selection by using NSGA-II forcustomer churn prediction in telecommunications. Expert Systems with Applications, 37(5), 3638-3646.

32. Huang, B., Huang, Y., Chen, C., &Kechadi, M. T. (2016, July). A Fuzzy Rule-Based Learning Algorithm forCustomer Churn Prediction. In Industrial Conference on Data Mining (pp. 183-196). Springer, Cham.

33. Huang, B., Kechadi, M. T., & Buckley, B. (2012). Customer churn prediction in telecommunications. ExpertSystems with Applications, 39(1), 1414-1425.

34. Huang, Y., Huang, B., &Kechadi, M. T. (2011, May). A rule-based method for customer churn prediction intelecommunication services. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 411-422). Springer, Berlin, Heidelberg.

35. Idris, A., Khan, A., & Lee, Y. S. (2013). Intelligent churn prediction in telecom: employing mRMR featureselection and RotBoost based ensemble classification. Applied intelligence, 39(3), 659-672.

36. IfdAllensbach. (n.d.). Number of persons interested in the telecommunications sector (e.g. mobile and smartphones,DSL) in Germany from 2014 to 2018, by level of interest (in millions). In Statista - The Statistics Portal.Retrieved February 28, 2019, from https://www.statista.com/statistics/483503/telecommunications-interest-germany/

37. Jain, R. (2018). Reliance Jio reports record subscription in Q2 with 28.7 million new users. Retrieved fromhttps://in.pcmag.com/reliance-jio/124501/reliance-jio-reports-record-subscription-in-q2-with-287-mill

38. Kapoor, S. (2017). Can Data Analytics Stop India’s Telecom Churn Crisis? | Absolutdata. Retrieved fromhttps://www.absolutdata.com/blog/can-data-analytics-stop-indias-telecom-churn-crisis/

39. Keramati, A., &Ardabili, S. M. (2011). Churn analysis for an Iranian mobile operator. TelecommunicationsPolicy, 35(4), 344-356.

40. Koontz, H. (1980). The management theory jungle revisited. Academy of management review, 5(2), 175-188.

41. Kozinets, R. V. (1998). On netnography: Initial reflections on consumer research investigations of cyberculture.ACR North American Advances.

42. Kozinets, R. V. (2002). The field behind the screen: Using netnography for marketing research in onlinecommunities. Journal of marketing research, 39(1), 61-72.

43. Kozinets, R. V. (2006). Netnography. Handbook of qualitative research methods in marketing, 129-142.

44. Kozinets, R. V., De Valck, K., Wojnicki, A. C., &Wilner, S. J. (2010). Networked narratives: Understandingword-of-mouth marketing in online communities. Journal of marketing, 74(2), 71-89.

45. Langer, R., & Beckman, S. C. (2005). Sensitive research topics: netnography revisited. Qualitative MarketResearch: An International Journal, 8(2), 189-203.

46. Liljedal, K. T., &Dahlén, M. (2018). Consumers’ response to other consumers’ participation in new productdevelopment. Journal of Marketing Communications, 24(3), 217-229. 10.1080/13527266.2014.995205

47. Lu, J. (2002). Predicting customer churn in the telecommunications industry––An application of survivalanalysis modeling using SAS. SAS User Group International (SUGI27) Online Proceedings, 114-27.


48. Mariampolski, H. (2006). Ethnography for marketers: A guide to consumer immersion. Sage.

49. Martin, R. and Golsby-Smith, T. (2017). Management Is Much More Than a Science.Retrieved from https://hbr.org/product/management-is-much-more-than-a-science/R1705L-PDF-ENG

50. Milley, D. J. (1987). Consumer demand by black americans. The Review of Black Political Economy, 15(3),87-99. 10.1007/BF02903994

51. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., &Prisma Group. (2009). Preferred reporting items forsystematic reviews and meta-analyses: the PRISMA statement. PLoS medicine, 6(7), e1000097.

52. Mowat, A., & Collins, R. (2000). Consumer behaviour and fruit quality: Supply chain management in anemerging industry. Supply Chain Management, 5(1), 45-54. 10.1108/13598540010312963

53. Neslin, S. A., Gupta, S., Kamakura, W., Lu, J., & Mason, C. H. (2006). Defection detection: Measuring andunderstanding the predictive accuracy of customer churn models. Journal of marketing research, 43(2), 204-211.

54. Ogilvy, D. (1983). Ogilvy on advertisement.

55. Óskarsdóttir, M., Van Calster, T., Baesens, B., Lemahieu, W., &Vanthienen, J. (2018). Time series for earlychurn detection: Using similarity based classification for dynamic networks. Expert Systems with Applications,106, 55-65.

56. Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of documentation, 25(4), 348-349.

57. Rageh, A., Melewar, T. C., & Woodside, A. G. (2013). Using netnography research method to reveal theunderlying dimensions of the customer/tourist experience. Qualitative Market Research: An InternationalJournal, 16(2), 126–149.

58. Raghuram, S., Tuertscher, P., &Garud, R. (2010). Research note—mapping the field of virtual work: Acocitation analysis. Information Systems Research, 21(4), 983-999.

59. Ramos Rodríguez, A. R., &Ruíz Navarro, J. (2004). Changes in the intellectual structure of strategic managementresearch: A bibliometric study of the Strategic Management Journal, 1980–2000. Strategic management journal,25(10), 981-1004.

60. Reeves, S., Kuper, A., & Hodges, B. D. (2008). Qualitative research methodologies: ethnography. BMJ:British Medical Journal (Online), 337.

61. Sengupta, D. (2017). Bharti Airtel responding well to Reliance Jio threat, say analysts - ET Telecom. Retrievedfrom https://telecom.economictimes.indiatimes.com/news/bharti-airtel-responding-well-to-reliance-jio-threat-say-analysts/58613566

62. Songa, G., & Russo, V. (2018). IAT, consumer behaviour and the moderating role of decision-making style:An empirical study on food products. Food Quality and Preference, 64, 205-220. 10.1016/j.foodqual.2017.09.006

63. Spandagos, C., & Ng, T. L. (2018). Fuzzy model of residential energy decision-making considering behavioraleconomic concepts. Applied Energy, 213, 611-625. 10.1016/j.apenergy.2017.10.112 Spandagos, C., & Ng, T.L. (2018

64. Tarasi, C. O., Bolton, R. N., Hutt, M. D., & Walker, B. A. (2011). Balancing risk and return in a customerportfolio. Journal of Marketing, 75(3), 1-17.

65. Thumin, F. J. (1968). Consumer behavior as related to personality, intelligence, age and education. PsychologicalReports, 23(3), 1185-1186.

66. Tynan, C. (1999). On metaphors, marketing and marriage. Irish Marketing Review, 12(1), 17.

67. Val’Tukh, K. K. (1975). A theoretical model of mass consumer behavior and some methodological problemsof social studies. Quality and Quantity, 9(4), 323-337. 10.1007/BF00144052

68. Van Eck, N. J., &Waltman, L. (2011). Text mining and visualization using VOSviewer. arXiv preprintarXiv:1109.2058


69. Van Eck, N. J., Waltman, L., Dekker, R., & van den Berg, J. (2010). A comparison of two techniques forbibliometric mapping: Multidimensional scaling and VOS. Journal of the American Society for InformationScience and Technology, 61(12), 2405-2416.

70. Van, M. J. (1988). Tales of the field: on writing ethnography. Chicago, IL: University of.

71. Verbeke, W., Dejaeger, K., Martens, D., Hur, J., &Baesens, B. (2012). New insights into churn prediction inthe telecommunication sector: A profit driven data mining approach. European Journal of Operational Research,218(1), 211-229.

72. Vidich, A. J., Lyman, S. M., Denzin, N. K., & Lincoln, Y. S. (1994). Handbook of qualitative research.Handbook of qualitative research.

73. Wallendorf, M., & Belk, R. W. (1989). Assessing trustworthiness in naturalistic consumer research. ACRSpecial Volumes.

74. Wei, C. P., & Chiu, I. T. (2002). Turning telecommunications call details to churn prediction: a data miningapproach. Expert systems with applications, 23(2), 103-112.

75. Wilk, R. (2010). Consumption embedded in culture and language: Implications for finding sustainability.Sustainability: Science, Practice, and Policy, 6(2), 38-48.

76. Zhang, X., Zhu, J., Xu, S., & Wan, Y. (2012). Predicting customer churn through interpersonal influence.Knowledge-Based Systems, 28, 97-104.

(Footnotes)1 VOS viewer employs a mapping technique and is an open source software and is available at www.vosviewer.com

with tutorials and relevant papers. It can be used to create visualizations using databases like Scopus and webof science etc. The software is used in many research papers that are published by reputed peer reviewjournals. A few relevant papers are freely available at www.vosviewer.com.


Integrated Reporting for CorporateSustainability: An Exploratory Study

Tulika Bal* & Dr. Sunil Kumar Dhal**

ABSTRACTCorporate reporting over the years has witnessed paradigm shift to meet the information needs of the

stakeholders. It continues to evolve from traditional financial reporting to sustainability reporting to more recently,integrated reporting (IR). IR is a concise communication about how an organization’s strategy, governance,performance and prospects lead to creation of value over short, medium and long-term. It is an integratedrepresentation of a company’s performance in terms of a company’s financial and other value relevant information,which helps stakeholders in their decision-making. IR is expected to bring greater transparency on corporatecommitment to sustainability.It shows the links between financial and sustainability performance in a singledocument. IR is emerging as an innovative reporting tool during last five years in India.This paper has examinedthe recent literature in the area of integrated reporting (IR) and its practices in India and abroad.

Keywords: Financial Reporting, Integrated Reporting, Corporate Sustainability, Stakeholders.

IntroductionCorporate reporting, over the years,is evolving continuouslyto meet the information needs of the

stakeholders of business. Corporate reporting practices are changing from traditional financial reportingto sustainability reporting to more recently, integrated reporting (IR). “The accounting profession haschallenged the traditional financial reporting model, arguing that it does not adequately satisfy theinformation needs of stakeholders for assessing a company’s past and future performance” (Flower,2015). “Organisations are increasingly disclosing financial and nonfinancial performance as they areencouraged to become more accountable and transparent to the providers of capital, and toward otherinterested parties (Camilleri, 2018). “Initially, the idea of managing, measuring and reporting the threeelements of an organisation’s social, environmental and economic impacts gained prominence duringthe late 1990s and early 2000s (Dumay et al., 2016). However, these reports, known as sustainabilityreports, often suffer weaknesses as they appear disconnected from the organisation’s financial reportsand fail to make a link between sustainability issues and the organisations core strategy (Clayton et al.,2015). IR, the latest development in corporate reporting reform, promises to address criticisms andshortcomings of sustainability reporting (Stubbs & Higgins, 2018).

* Research Scholar, Sri Sri University, Cuttack** School of Management, Sri Sri University, Cuttack

43Integrated Reporting for Corporate Sustainability: An Exploratory Study

IR is a concise communication about how an organization’s strategy, governance, performance andprospects lead to creation of value over short, medium and long-term(Wikipedia). It is an integratedrepresentation of a company’s performance in terms of a company’s financial and other value relevantinformation, which helps stakeholders in their decision-making. IR aims at connecting different functionsto form a holistic view of the business, recognizing the value, risks, and opportunities. IR is emergingas an innovative reporting tool for companies for integrating environmental and social thinking intotheir business decision making, which leads to sustainability of the organisation.

BackgroundAn annual report of a company contains two types of information, i.e., ‘backward-looking

information’ and ‘forward-looking information’ (Kilic and Kuzey, 2018). The past financial results andtheir disclosure are considered as ‘backward-looking information. On the other hand, the current plans,future forecasts and future prospects are considered as ‘forward-looking information’. The stakeholdersare interested in both types of information which are relevant for their decision making.Inlate 1990sand early 2000s, sustainability reporting, containing both financial and non-financial information,becamean increasingly relevant topic in business and academia (Hahn and Kuhnen, 2013).Thus, a firm focusedon sustainability and was held responsible for the society at large. Moreover, the stakeholders, whetherinternal or external, have started to look into the non-financial performances of the firms along with itsfinancial performance.

But the global financial crisis in 2007-08 brought into focus that a wide range of factors determinethe value and sustainability of the organization.Sustainability was not fully embedded with businessmodel and corporate reporting. The tangible or financial factors are easy to account for in the financialstatements. Intangible factors like intellectual capital, competition, energy security, employeeengagement, reputation and stakeholder relationships are very complex phenomena and also very difficultto report in specific terms.

Taking into consideration the importance of integrated reporting, the Prince of Wales convened ahigh level meeting in 2009, and invited investors, standard setters, companies, academic bodies, UNrepresentatives, representatives of IFAC and GRI to establish International Integrated Reporting Council(IIRC), a body to oversee the creation of a globally accepted integrated reporting framework. OnDecember 9, 2013, the draft of the internationally recognized integrated reporting framework was releasedafter incorporating the inputs collected from various stakeholders.The IR Framework of IIRC aims tosimplify company reporting and improve its effectiveness by focusing on value creation “as the nextstep in the evolution of corporate reporting” (IIRC, 2015). IIRC has prescribed guiding principles forpreparation of an IR, specifying the contents and presentation of the report. The objective of mergingconventional financial reports and reports on environmental, social and corporate governance (ESG)into one integrated report is to provide quality information to stakeholders and promote sustainability.

Objectives and MethodologyThe specific objectives of this article areas follows:• To examine the IR researchand IR practices in India and abroad• To identify future research opportunities


The study is mainly dependent on secondary data. A number of recent research articles have beenreviewed to find out the progress in IR research and opportunities for future research. Content analysisof annual reports of Sensex 30 companies has been undertaken in this research study to know the IRpractices in India.

Literature ReviewA structured review of literature in the area of IR has been undertaken to develop understanding

into how research is progressing in this area.The research papers have been critically examinedto findout the opportunities for future research.

Eccles and Serafeim (2014) of Harvard Business School in their research paper on “Corporate andIntegrated reporting: A Functional Perspective” presented two primary functions of corporate reporting(information and transformation) and described why IR could be a superior mechanism to performthese functions. They have also explained, through a series of case studies, the contents of an effectiveintegrated report.

Clayton, et al. (2015) made a comparative study on integrated reporting and sustainability reportingfor corporate responsibility in South Africa. The content analysis of the corporate reports revealed thatthe key drivers of sustainability and integrated reporting were regulatory requirements, industry of thecompany, the environmental and social impact of the company, and stockholder perceptions and pressure.

Adams (2015) analysed the integrated thinking required to develop an IR. The paper discussed theintegration of sustainability actions and impacts into corporate strategic planning and decision making.It suggested areas of further research to facilitate this.

Lai et al. (2016) studied whether the decision to adopt IR stems from the need to repair legitimacythreats. They found out that legitimacy pressures did not play a role in explaining IR adoption. Overall,their evidence suggested that corporate engagement in IR was not a matter of strategic legitimation.

Humphrey et al. (2016) studied the emergence of International Integrated Reporting Council (IIRC)and its attempts to institutionalize IR.They observed that IR, as a practice, is critical to the relevanceand value of corporate reporting. They observed that the IIRC has been swift in establishing itself as aglobally recognised body.

Dumay, et al. (2016) reviewed the field of integrated reporting to develop insights into IR researchand outline future research opportunities. They observed that there is little research examining IR practice.They argued that the ‘eco-system approach’ to researching IR is important because the IIRC (2013, p.2) advocates leveraging “financial, manufactured, intellectual, human, social and relationship, andnatural” capital as part of creating value.

Faria (2016) analysed the evolution of IR and discussed arguments in favour or against IR. It wasconcluded that there are several advantages above the disadvantages that need to be improved todisseminate the form of doing IR all over the world.

Perego, et al. (2016) studied IR and observed that IR has fast emerged as a new accounting practice tohelp firms understand how they create value and be able to effectively communicate this to externalstakeholders. The study has contributed to this field by reframing the existing implementation challenges ofIR into promising and inclusive research opportunities that align the priorities of both academia and business.


Maniora (2017) examined the impact of IR on the integration of environmental, social andgovernance (ESG) issues into the business model and the related economic and ESG performancechanges. The research paper provided empirical evidence using three matched samples of companiesfrom around the world for the sample period 2002-2011, that contradicts the general notion of IR as asuperior reporting mechanism, as the benefits of IR are driven by several factors.

Mervelskemper and Streit, (2017) studied the effectiveness of a firm’s strategy to report on its ESG(environmental, social and governance) activities, and whether following the current IR trend is worththe effort. They observed that IR is associated with superior outcomes compared with a standalonereport for composite ESG and corporate governance performance.

Stubbs and Higgins, (2018), in their exploratory study of the preferences of users of non-financialreporting for regulatory or voluntary approaches to IR, found more support for voluntary approaches toIR. They suggested that IR will become the reporting norm over time if left to market forces as moreand more companies adopt the IR practice. However, half of the investors supported mandatory IRbecause, in their experience, voluntary sustainability reporting has not led to more substantive disclosuresor increased the quality of reporting.

Camilleri (2018), in his research on the integrated reporting of financial, social and sustainabilitycapitals, found out that organisations are increasingly disclosing financial and non-financial performanceas they are encouraged to become more accountable and transparent to the providers of capital, andtoward other interested parties. It is inferred that there is both costs and benefits for using IR framework.

Bal and Bal (2019), in their research study on corporate integrated reporting, examined the progressof research in IR area and undertook the content analysis of the annual reports of selected companies inIndia to study the IR practices.They cocluded that there is need for significant transformation in approachand thinking, leading to innovative reporting and IR movement in India.

From the study of the above research articles, it can be inferred that the researchers can undertakefuture research studies to study the relationship of firm value, firm size, capital market, sustainabilityand stakeholder decision making with IR. Content analysis of annual reports can also be undertaken toevaluate the quality of IR. IR practices of companies in other countries can be studied for providingcross-country comparison.

IR: A Conceptual StudyIR is an integrated representation of a company’s performance in terms of both financial and other

value relevant information.It provides a holistic view of the business by connecting different functions.Itrecognizes the value, risks and opportunities of the organisation.It is a transition from sustainabilityreporting to IR.It links the sustainability of a company’s activities and company’s financial performance.Ittakes a wider view of six ‘capitals’ used by the organisation, which are as follows (Bal and Bal, 2019):

• Financial Capital: The pool of funds available to the organization.• Manufactured Capital: Manufactured physical objects as distinct from natural physical objects.• Intellectual Capital: Intangibles that provide competitive advantages.• Human Capital: The skill and experiences of people and their motivations to innovate.


• Social and Relationship Capital: Community, stake holders and other networks to enhanceindividual and collective well-being.

• Natural Capital: Water, land, minerals, forests, bio-diversity and ecosystem health.

Fig. 1: Value Creation

Source:https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2388716 on 22.05.2019

The following are the guiding principles of IR (Morros, 2016, 345-346):• Strategic Focus and Future Orientation:• Connectivity of Information• Stakeholder Relationships• Materiality and Conciseness• Reliability and Completeness• Consistency and ComparabilityThe process of producing an IR requires companies to actively measure environmental, social and

other non-financial impacts.These factors are to be integrated into corporate decision making through aprocess referred to as ‘integrated thinking’. (www.accountingforsustainability.org). The key aspect ofintegrated thinking is that companies must measure and report on all of the various “capitals” a companyuses to create value, rather than focusing solely on financial capital. IR also includes information aboutfuture prospects and uncertainties. This report should include all material facts, both favourable andunfavourable for the company.

Common reporting format for companies following IR has the following elements:• Organizational Overview


• Governance• Business Model• Risk and Opportunity• Strategy and Resource Allocation• Performance• Outlook• Basis of Presentation

IR: Practices in India and AbroadSEBI, in consultation with industry bodies and stock exchanges, asked top 500 listed companies to

voluntarily adopt IR framework from the financial year 2017-18. After this declaration, IR in India isgaining momentum. This move by the market regulator is aimed at providing stakeholders relevantinformation that is useful for making investment and other decisions. SEBI said that information relatedto integrated reporting should be provided in the annual report separately or by incorporating in‘management discussion and analysis’ or by preparing a separate report. The companies can also hostthe IR on their website and provide appropriate reference to the same in their annual report. To avoidduplication of information, if the firm has already provided the relevant information in any other reportprepared it should provide appropriate reference to the same in its IR.

Kirlosker Bothers Ltd. is one of the first companies in India to prepare IR since 2013-14. At present,many large companies in India have already adopted IR. Tata Steel, Reliance Industries Ltd, Tata Motors,HDFC Bank, Wipro, HDFC Ltd. and Induslnd Bank have prepared integrated reports in the current financialyear, 2018-19. RIL aligned the sustainability report content to principles of International IntegratedReporting Framework laid down by IIRC and prepared its IR. HDFC Ltd. has prepared IR which givesholistic view of the long-term strategy and financial performance of the company along with benchmarkstandard with respect to CSR, human rights, environment, society, governance and sustainability.

Yes Bank is the first bank to release the IR in line with IIRC since 2015-16. The report explainsbank’s dependence and impact on the various forms of capital that are fundamental to its ability tocreate long-term value.Tata steel is preparing IR since 2014-15. The IR for financial year 2016-17 hasbeen recognized as Asia’s best integrated report by Asia Sustainability Reporting Awards. Wipro is alsopreparing IR for last three years providing information on six types of capitals and their interdependence.

Many countries and their regulators (Japan, India, South Africa, UK and many European countries)have taken initiatives to implement integrated reporting. South Africa is the only country which madeIR mandatory for all listed companies in the Johannesburg Stock Exchange. Many large multinationalcompanies operating in advanced countries and emerging economies are preparing IR to meet theemerging needs of the stakeholders even though it is voluntary.

A Case StudyTata Steel, formerly Tata Iron and Steel Company Limited, is an Indian multinational steel making

company and one of the respected companies in the world. It has global presence in steel industry


across five continents and is one of the largest steel manufacturers in the world. It’s a member of TataGroup, founded by Jamsetji Tata. Tata steel is preparing IR for the last four years. It provides quantitativeand qualitative disclosures to meet the requirements of various stakeholders. The present case studyanalyses the IR, which it has presented under the required six capitals in its annual report for the periodApril1, 2018 to March 31, 2019.

As regards Tata Steel’s financial capital, its endeavour is to optimise returns for providers of financialcapital and invest the surplus in attractive growth opportunities. It has focused on deleveraging andenhancing cash generation through efficiency and productivity. During the current year, it focussedtowards strengthening its operations in India through the acquisition of Bhushan Steel and investingthe expansion of the Kalinganagar plant in Odisha. The board has recommended higher dividend ascompared to previous years. Its key financial input isRs. 3,677 crorein FY19 towards capital expenditure.During the year under review, the key financial capital outputs are improved turnover, which is 16.7%higher than the previous year, increased EBITDA by 31% and improved EPS.

Regarding manufactured capital of Tata Steel, it is an integrated steel company with backward andforward linkages. During the year under study, it strengthened its operations through a combination oforganic and inorganic growth initiatives which helped it to maintain cost-competitiveness and deriveproduction efficiencies. The goal is to achieve production capacity of 30 MnTPA in India by 2025 andto maintain cost leadership position. It is building production facilities and supply chain efficiency.

As regards intellectual capital, Tata steel aspires to be a pioneer in leading the fourth industrialrevolution and is committed to developing cutting-edge technologies that help to improve efficiencies.Amidst changing customer needs, competition and regulatory risks, it strives continuously to innovateand adapt to change. It is focused on leveraging its R&D capabilities through new products, advancedmaterials, process improvement and digitalisation across value chain to make it future-ready. It has atwo-pronged approach towards innovation, supported by robust resource allocation and organisationalcommitment. It also leads industry efforts in supporting knowledge transfer and capacity buildingacrossand beyond its sector.It regularly supports industry bodies in sharing best practices, training, research,and ideas that enhance the overall performance. Total Quality Management (TQM) initiatives likeShikhar25, are undertaken to achieve excellence in many areas.

To enrich human capital, Tata Steel has industry-leading employee welfare practices and a cultureof working together. It is a pioneer in progressive people practices. Its occupational health and safetypractices help in developing a culture of safety and care. There is 26% reduction in high potentialincidents.It is able to maintain zero fatalities inside plant premises for the last four years. It continues tofocus on employee engagement, diversity and inclusion. In the current year, it implemented an EmployeeProductivity Framework to sensitise employees on productivity improvement. It has a WorkforceCapability and Capacity Framework to assess capability needs for skill and competency building.

Regarding natural capital, Tata Steel continuously strives to protect the environment, minimiseenvironmental impact and promote resource efficiency. Its goal is to achieve zero affluent discharge by2025. It has partnered with the International Union for Conservation of Nature (IUCN) at its raw materiallocations in Jharkhand and Odisha for the implementation of biodiversity management plans. Watermanagement and water conservation strategies are followed to save water.


To enrich social and relationship capital, Tata Steel has taken several initiatives to establish long-term relationships with customers, suppliers and communities. In 2018-19, many initiatives were takento enhance value for customers of automotive, construction and engineering segments. It has valuecreating partnership with more than 5,000 suppliers. It has undertaken a number of interventions forlocal communities in improving access to and quality of education and healthcare. It received manyawards and recognitions for its good work for the society.

The Tata Steel has prepared a separate integrated report with the details regarding six capitals. Thereport contains the both quantitative and qualitative parameters. Even though the report has been preparednicely, but the key inputs, outputs and the resulting outcomes of six capitals have not been specificallyexplained. The report has not clearly specified the information on strategy and governance of six capitals.

Observations and ConclusionIn this LPG era, there is need for anIR movement in India to comply with international best

practices.There is also need for significant transformation in approach and thinking leading to innovativereporting practices. All stakeholders have to play their role in enriching integrated corporate reportingfor their benefit.The main challenge of preparing IR is value identification, its creation, measurement,preservation and reporting.There is need for harmonization of IR standards and regulations.Technologyenabled integrated reporting system is essential for the corporates. Audit and assurance services arerequiredfor the reported data inIR to check reliability, materiality and completeness.

The current system of voluntary disclosers in India has created an uneven playing field, with somecompanies clearly informing investors and others under-reporting or over-reporting. Many companiesdo not disclose ‘forward-looking information’, due to fear of its use by the competitors. IR should becomprehensible, credible and comparable. IR is a radical transformative change in the field of corporatereporting. It has significant potential for future research.The SEBI, ICAI and Ministry of CorporateAffairs have to playproactive roles for the promotion of IR. The guidelines for IR in India, based onbest practices, would be the most constructive way forward for corporate reporting and sustainablity.

References1. Adams, carol A. (2015). The International Integrated Reporting Council: A Call to Action. Critical Perspectives

on Accounting, 27, 23-28.

2. Bal, R.K. and Bal, T. (2019). A Study on Corporate Integrated Reporting.Indian Accounting Review, 23, 1-15.

3. Camilleri, M.A. (2018). The Integrated Reporting of Financial, Social and Sustaionability Capitals: A CriticalReview and Appraisal.International Journal of Sustainable Society.

4. Faria, Maria Jose da Silva. (2016). A New Form of Reporting for Companies: The Integrated Reporting.International Journal of Management and Economics Invention, November, 2-11.

5. Clayton, Alexandra F., Rogerson, Jayne M. and Rampedi, Isaac.Integrated Reporting vs. Sustanability Reportingfor Corporate Responsibility in South Africa.Bulletin of Geography. Socio-Economic Series, 29, 7-17.

6. Dumay, John, Bernardi, Cristianna, Guthrie, James and Demartini, Paola. (2016) Integrated Reporting: AStructured Literature Review. Accounting Forum.

7. Eccles, Robert, and Serafeim, George. (2014). Corporate and Integrated Reporting: A Functional Perspective.(https://www.researchgate.net).


8. Flower, J. (2015). The International Integrated Reporting Council: A Story of Failure. Critical Perspectives onAccounting, 27, 1-17.

9. Hahn, Rudiger and Kuhnen, Michael. (2013). Determinants of Sustainability Reporting: A Review of Results,Trends, Theory, and Opportunities in an Expanding Field of Research. Journal of Cleaner Production, 59, 5-21.

10. Humphrey, Christopher, O’Dwyer, Brendan and Unerman, Jeffrey.(2016). Retheorising the Configuration ofOrganizational Fields: IIRC and the Pursuit of ‘Enlightened’ Corporate Reporting. Accounting and BusinessResearch, 47-1.

11. Kilik, Merve and Kuzey, Cemil. (2018). Determinants of Forward-looking Disclosures in IntegratedReporting.Managerial Auditing Journal,33, 115-144.

12. Lai, Alessandro, Melloni, Gaia and Stacchezzini.(2014). Corporate Sustainable Development: Is ‘IntegratedReporting’ a Legitimation Strategy? Business Strategy and the Environment. 25, 165-177.

13. Maniora, Janine. (2017). Is Integrated Reporting Really the Superior Mechanism for the Integration of Ethicsinto the Core Business Model? An Empirical Analysis.Journal of Business Ethics, 140: 755-786.

14. Mervelskemper, Laura and Streit, Daniel. (2017). Enhancing Market Valuation of ESG Performance: IsIntegrated Reporting Keeping its Promise? Business Strategy and the Environment. 26, 536-549.

15. Morros, J. (2016). The Integrated Reporting: A Presentation of the Current State of Art and Aspects ofIntegrated Reporting that Need Further Development. Intangible Capital, North America, 12. In: http://www.oecd.org/cfe/smes/46404350.pdf.

16. Perego, Paolo, Kennedy, Steve and Whiteman, Gail.(2016). A Lot of Icing But Little Cake? Taking IntegratedReporting Forward. Journal of Cleaner Production, 1-12.

17. Stubbs, Wendy and Higgins, Colin.(2018). Stakeholders’ Perspectives on the Role of Regulatory Reform inIntegrated Reporting.Journal of Business Ethics, 147: 489-508.

51Financial Literacy and Its Dimensions: An Empirical Study in Assam

Financial Literacy and Its Dimensions:An Empirical Study in Assam

Sanjib Das* & Dr. Santosh Kumar Mahapatra**

ABSTRACTFinancial literacy has assumed greater importance in the recent years, as financial markets have become

increasingly complex and as there is information asymmetry between markets and the common people, leading tothe difficulty in making informed decisions. India, a country with low level of literacy and a high rate of financialexclusion, has greater need for financial literacy so as to ensure financial wellbeing to the wider section of thesociety. Very few studies address on all the key dimensions i.e. financial knowledge, financial behaviour and financialattitude and their association with financial literacy. The present study is a moderate attempt to measure the levelof financial literacy and its association with financial knowledge, financial behaviour and financial attitude amongthe people of Assam. The study found a strong association of financial literacy with financial knowledge andfinancial behaviour and weak association with financial attitude

Keywords: Financial Literacy, Financial Dimensions, Financial Knowledge, Financial Behaviour andFinancial Attitude.

Introduction

Financial literacy is considered to be an important life skill in the modern society. Financial literacyrefers to the ability to use knowledge and skills to manage financial resources effectively for lifetimefinancial wellbeing (PACFEL-USA, 2008). Financial literacy is a combination of awareness, knowledge,skill, attitude and behaviour necessary to make sound financial decisions and ultimately achieveindividual financial wellbeing (Atkinson, 2012).

Financial literacy is a major concern among both the developed and developing nations. The levelof financial literacy among the people varies from region to region. Worldwide, 35 percent of men and30 percent women are financially literate (Klapper, L. et al. 2014). In India financial literacy level is 20percent (NCFE, 2014).

Financial literacy has assumed greater importance in the recent years, as financial markets havebecome increasingly complex and as there is information asymmetry between markets and the common

* Research Scholar, Department of Commerce, Gauhati University, Guwahati-781014, Assam, India, E-mail: [email protected]** Associate Professor, Department of Commerce, Gauhati University, Guwahati-781014, Assam, India, E-mail: [email protected]


people, leading to the difficulty in making informed decisions. Both developed and developing countries,therefore, are focusing on promotion of financial literacy among the citizens. In India, the need forfinancial literacy is even greater, considering the low level of general literacy and financial inclusion.

Review of LiteratureSome of the research works in the field of financial literacy have been reviewed to identify the

research gap. The summary of the selected reviews are presented here in brief.Chen, H. and Volpe, P. (2002) examined the personal financial literacy of college students of

different Colleges of Ohio in the U.S.A. and analysed the impact of financial literacy on their financialopinions and decisions. The results of the study showed that the mean score of participants is 52.80percent which means that they have an average knowledge on financial matters. The major findings ofthe study is non-business major students, women students and students in lower classes and with littlework experience possessed lower level of financial knowledge. People with less knowledge tend tohold wrong opinions and make incorrect decisions.

Lusardi, A. and Mitchell, O.S. (2007) studied how workers in America make saving decisions,how they collect the information for making these decisions, and most importantly, whether they possessthe financial literacy needed to make informed decisions. The analysis showed that only half ofrespondents surveyed could answer two simple questions regarding compounding interest and inflationcorrectly. Furthermore, only one-third could correctly answer those two questions as well as an additionalone on risk diversification. It is also found that financial illiteracy was particularly acute for Blacks andHispanics, women, and those with low educational attainment.

Ibrahim, D. (2009) measured financial literacy of degree students of UiTM, Kedah, Malaysia. Inhis study no significant difference was found in financial literacy level between male and female groups.Differences were found in financial knowledge based on mother’s education level. A correlation wasfound between financial literacy and financial attitude. Degree students who had higher financial attitudehad higher level of financial literacy. There was a significant relationship between financial literacyand university courses. Students from business, economics and finance honours were found financiallymore literate as compared to others and the overall financial literacy of the student was poor.

Taft, M.K. et al. (2013) evaluated the relation between financial literacy, financial wellbeing andfinancial concerns. Also the roles of demographic characteristics including age, sex, marital status andeducation level in influencing financial literacy, financial well being and financial concern wereinvestigated. The study found that age and education are positively correlated with financial literacyand financial wellbeing. Again, a link has been established with marital status and financial literacy.Married people and men were found to be more financially literate. The study concluded that higherfinancial literacy leads to greater financial well-being and less financial concerns.

Shaari, N.A. (2013) examined the level of financial literacy among the students of the Universityof Malaysia. The study revealed that five factors- age, gender, spending habits, faculty and year ofstudy significantly affect the financial literacy levels. It was also found that the overall financial literacyof University students was moderate as 65.7 percent of students scored 5-8 out of 12 marks. Besidesthat, some managerial implications are being described.


Aggarwal, N. et al. (2014) measured the level of financial literacy among the farmers of PunjabState. They found that 37 percent of the farmers have sound financial literacy, 47 percent have fairfinancial literacy and 2 percent have poor financial literacy. Financial literacy in terms of interest rateand inflation is found good i.e. more than 50 percent have sound financial literacy. But in terms of timevalue of money and financial principles only 40 percent have shown sound financial literacy.

Mathivathani, V. and Velumani, M. (2014) assessed the level of financial literacy among themarginalised women in Tamilnadu. The researchers have found that the financial literacy of ruralwomen is very low. They also observed some barriers to the financial literacy. Majority of therural women are not earning person in a family. They can’t independently take decision on financialmatters of the family. Further, they can’t afford financial education through paid institution to getknowledge.

Thapa, B. and Nepal, S.R. (2015) measured financial literacy of university students of Nepaland the impact of demographic, educational and personality characteristics on financial literacy.The study result showed that most of the students had basic level of financial knowledge but theylack in understanding credit, taxes, share market, financial statement and insurance. The studyidentified income, age, stream of education, types of college, and attitude of students as keydeterminants of financial knowledge; whereas financial knowledge remained unaffected by gender,university affiliation, financial behavior and influence.

Zulfiqar, et al. (2016) studied the importance of financial literacy and impact of financialliteracy and financial attitude on the financial wellbeing of the working women in Pakistan. Theresult of the study showed that financial literacy is an essential element for the wellbeing. Financialliteracy is significantly and positively related to financial wellbeing. Higher the level of financialliteracy, greater will be the financial wellbeing. Similarity, financial attitude has also positive andsignificant relationship with financial wellbeing.

Devi, A. (2016) measured financial literacy level among women in Kamrup district of Assamand found low level of financial literacy among the women of the district. The mean score for ruralwomen is 19.22 and for urban it is 22.40 and there exists a mean difference of 3.18. It indicates thatfinancial literacy for urban women is considerably higher than that of rural women. It is also observedthat financial literacy among working women is higher as compared to the non-working women.

On review of literature, it comes to the light that financial literacy is a major concern for boththe developed and developing nations. Now-a-days studies on financial literacy have been carriedout in many countries in the world viz. U.S.A., Malaysia, Iran, Pakistan, and Nepal and also indifferent parts of India. But only a few studies have been conducted among the people of Assam.The target population in the majority of the studies is either college students, teachers, workingwomen, young or adult people, although financial literacy is equally important for every one’swellbeing. Only a few studies have targeted general people (all the segments of the population).Furthermore, most of the studies have focused only on specific aspects of the financial literacyand not on all the key dimensions - financial knowledge, financial behaviour and financial attitude.Considering these facts, the idea of conducting the present study is generated and is expected tofill up the gaps and create new stock of knowledge.


Objectives of the StudyThe main objective of the present study is to examine the robustness of the relationship between

financial literacy and its components- financial knowledge, financial behaviour and financial attitudeamong the people of Assam.

Research Hypotheses

Keeping the objective in mind, the following null hypotheses vis-à-vis alternative hypotheseshave been framed for the testing purpose:

Hypothesis-1

H0: There is a strong relationship between financial literacy and financial knowledge of the peopleof Assam.

H1: There is no strong relationship between financial literacy and financial knowledge of the peopleof Assam.

Hypothesis-2

H0: There is a relationship between financial literacy and financial behaviour of the people of Assam.H1: There is no relationship between financial literacy and financial behaviour of the people of

Assam.

Hypothesis-3

H0: There is a relationship between financial literacy and financial attitude of the people of Assam.H1: There is no relationship between financial literacy and financial attitude of the people of Assam.

MethodologyPopulation and Sample size: The population of the study is household families of Assam. The

sample size is 384, which is determined on model suggested by Krejcie & Morgan (1970).Sampling Technique: Multi-stage random sampling technique has been used for selecting the

respondents for the present study. At the first stage, out of the 27 districts (old) in Assam, three districts -Kamrup (M), Nagaon and Dhubri have been selected purposively on the basis of prevailing literacy ratein order to make the samples more representative. These selected districts were further divided into urbanand rural areas. From urban area Municipal corporation/board and from rural area Gram panchayats havebeen selected. In the second stage, one municipal corporation/board was selected comprising of the districthead quarter (urban area) and two gram-panchayats were selected (rural area) from each district. In thethird stage, minimum 30 percent of wards (50 out of the total 165 wards) were selected randomly from therespective municipal corporations/boards and gram-panchayats. And finally, the sample respondents wereselected randomly in equal proportion i.e. 7 to 8 respondents from all the selected wards.

Data Collection & Analysis: Data for the study have been collected through self constructedquestionnaire containing 30 multiple choice questions, 20 questions on financial literacy. Primary data


collected for the study have been analysed using Statistical Package for Social Sciences (SPSS) version16.0. Statistical techniques such as Chronbach’s alpha and Pearson’s correlation analysis have been used.

Results and DiscussionDemographic and Socio-economic Profile of the Respondents: Data relating to demographic

and socio economic status of the respondents have been presented in the Table 1.

Table 1: Profile of the RespondentsVariables Category Frequency Percentage

Place of Residence Rural 138 36

Urban 246 64

Gender Male 192 50

Female 192 50

Marital status

Married 221 58

Unmarried 163 42

Religion

Hindu 275 71

Muslim 96 25

Christian 13 04

Social Category

General 154 40

SC 132 34

ST 30 08

OBC 61 16

MOBC 07 02

Age ( Years)

18 – 30 168 44

31 – 43 115 30

44 – 56 62 16

57 – 69 29 07

70 and above 10 03

Education

Illiterate 34 09

Primary school 72 19

High school 95 25

Graduate 118 30

PG and above 65 17

Occupation

Agriculture 52 13

Business 105 27

Service 101 26

House wife 33 09

Student 80 21

Others 13 04

Income (monthly)

Below Rs.5000 67 13

Rs.5001-15000 97 25

Rs.15001-25000 72 19

Rs.25001-35000 51 18

Above Rs. 35000 97 25


The above table gives the summary of the demographic and socio-economic characteristics of therespondents. A look at the demographic and socio-economic detail shows that percentage of ruralrespondents is 36 percent and urban respondents is 64 percent. Gender wise 50 percent in eachmale and female category. Majority of the respondents belong to the Hindu religion i.e.71 percentand rest of them are Muslim and Christian. More than the average of the respondents are fromGeneral and SC category and lowest percentage of the respondents are from ST and MOBC category.44 percent of the respondents fall in the age group of 18-30 years and 30 percent fall in the age groupof 31-43 years. Majority of the respondents i.e. 55 percent in our samples are High school passed outand graduates. Only a few of them are illiterate i.e. 9 percent and 17 percent are post graduates.Respondents from the profession of business are 27 percent, service 26 percent, agriculture 13 percent,house wife 9 percent, student and others 25 percent. The highest percentage of the respondents i.e.25 percent is having monthly income from Rs.5001-15000. Lowest of the respondents i.e. 13 percentis having monthly income below Rs.5000.

Reliability and Normality of data: Reliability is an assessment of the degree of consistencybetween multiple measurements of a variable. It has to do with the accuracy and precision of ameasurement procedure. The internal consistency is typically measured by using Chronbach’s alpha() test, the value of which ranges from 0 to 1, the higher value indicates the greater internalconsistency (and ultimately reliability).

The internal consistency of the questionnaire has been checked by performing Chronbach’s alpha() test on 100 sample units and the Chronbach’s alpha score is shown in the Table 2.

Table 2: Chronbach’s alpha Score

Test Score No. of Items Case Number Chronbach’s alpha 0.767 30 100

Reliability of the scale assessed by Chronbach’s alpha gives acceptable result of 0.767 for thewhole questionnaire which is over the recommended reliability coefficient of 0.70 (Croasmun &Ostrom, 2011).

Measurement of the Level of Financial Literacy: The level of financial literacy of the respondentshas been measured by combining the individual scores in financial knowledge, financial behaviour andfinancial attitude. The total score can have minimum value of 1 and maximum value of 22. In order toderive the financial literacy level a cut off has been fixed at 15 out of maximum aggregate value of 22.The respondent who scores more than 15 points on aggregate basis has been technically considered asfinancially literate. However, we can further segregate financially literate segment into two categories-moderately literate and highly literate. The respondent who scores more than 15 points on aggregatebasis but less or equal to 20 points on aggregate basis has been considered moderately literate. Therespondent who scores more than 20 points on aggregate basis would be considered highly literate.Table 3 below, shows the minimum and maximum scores required for financial literacy and for eachdimensions.


Table 3: Financial Literacy Score Matrix

Dimensions Minimum Score Maximum Score

Financial Knowledge 6 8

Financial Behaviour 6 9

Financial Attitude 3 5

Financial Literacy: Moderate

High

15 20

20 22

The category and component wise data on the level of financial literacy among the people of Assam

has been presented in the Table 4 which shows that financial literacy among the people is at a satisfactorylevel of 35 percent against the All India average of 20 percent. Out of this, 28 percent have moderatefinancial literacy and 7 percent have high financial literacy. People from urban areas are having morefinancial literacy as compared to rural areas. Male are more financially literate than female. Financialliteracy is more for the married respondents. In the case of religion, respondents belonging to the Hindureligion have the highest level of financial literacy i.e. 38 percent followed by the Muslims and Christianreligion. Respondents of General and SC category have better financial literacy which is 44 percentand 38 percent respectively. Age group of 44-56 years and 31-43 years also exhibits better financialliteracy which is 44 percent and 40 percent respectively. In the case of age of the respondents, financialliteracy is the lowest for the age group of 70 and above which is 27 percent only. So far as education isconcerned post graduates have the highest level of financial literacy of 52 percent followed by thegraduates at 48 percent and the illiterates have the lowest level of financial literacy which is 16 percentonly. Service and business professionals have the highest level of financial literacy among all the groupsi.e. 58 percent and 50 percent respectively. Students and other professionals have the lowest financialliteracy which stands at 18 percent to 25 percent. Financial literacy is more for the respondents belongingto the highest income group and vice-versa.

Table 4: Category and Component wise Financial Literacy[In percentage]

Category Financial Knowledge

Financial Behaviour

Financial Attitude

Financial Literacy

Moderate Financial Literacy

High Financial Literacy

Assam 51 63 80 35 28 7

Place of Residence

Rural 49 59 78 33 27 6

Urban 53 67 82 37 29 8

Gender Male 55 70 83 42 31 11

Female 47 56 77 28 25 3

Marital status Married 49 70 79 38 29 9

Unmarried 53 52 81 32 27 5

(Contd...)


Religion

Hindu 58 69 86 38 30 8

Muslim 54 66 81 36 28 8

Christian 38 50 73 31 26 5

Social Category

General 60 82 88 44 34 10

SC 56 65 82 38 30 8

ST 47 58 76 31 25 6

OBC 49 56 79 35 30 5

MOBC 43 54 75 27 21 6

Age ( Years)

18 – 30 34 51 75 35 26 9

31 – 43 67 68 79 40 33 7

44 – 56 55 65 84 44 34 10

57 – 69 56 75 82 29 24 5

70 and above 43 56 80 27 23 4

Education

Illiterate 26 48 65 16 14 2

Primary school 32 63 72 25 21 4

High school 45 67 77 34 27 7

Graduate 74 71 88 48 38 10

PG and above 78 66 98 52 40 12

Occupation

Agriculture 31 54 67 24 20 4

Business 68 72 89 50 41 9

Service 84 76 98 58 46 12

Student 43 52 86 25 19 6

Others (informal) 24 61 60 18 14 4

Income (monthly)

Below Rs.5000 28 46 71 16 12 4

Rs.5001-15000 30 54 76 18 13 5

Rs.15001-25000 56 65 82 40 33 7

Rs.25001-35000 68 72 83 49 40 9

Above Rs. 35000 73 78 88 52 42 10

To analyse the relationship of financial literacy with its dimensions such as financial knowledge,financial behaviour and financial attitude the Pearson Correlation Analysis has been conducted and theresult of the same has been presented in the Table 5.


Table 5: Pearson Correlation Coefficient

Variables Correlation coefficient (r ) Sig(2 tailed)

Financial Literacy and Financial Knowledge 0.812* 0.000

Financial Literacy and Financial Behaviour 0.840* 0.000

Financial Literacy and Financial Attitude 0.459* 0.000

* Significant at the 0.01 level (2-tailed).

The Pearson correlation (r) may take a range of values from +1 to -1. A value of 0 indicates thatthere is no association between two variables. A value greater than 0 indicates a positive association,i.e., if the value of one variable increases, so does the value of the other variable. A value less than 0indicates a negative association, i.e., if the value of one variable increases, the value of the other variabledecreases. Value of the correlation coefficient(r):1 indicates perfect correlation, 0.7 - 0.9 indicates strongcorrelation, 0.4 - 0.6 indicates moderate correlation and 0.1 - 0.3 indicates weak correlations (Dancey,C. & Reidy, J., 2011).

Financial Literacy and Financial Knowledge: The results as shown in the Table 5 shows thatcorrelation between financial literacy and financial knowledge is 0.812. This is statistically significantat 1 percent significance level. From this it is evident that there is a strong and positive relationshipbetween financial literacy and financial knowledge of the people and we accept the null hypothesis.

Financial Literacy with Financial Behaviour: The a correlation coefficient between financialliteracy and financial behaviour, as computed and shown in Table 5 is 0.84 and statistically significantat 1 percent level of significance. In other words, there is a strong and positive relationship betweentwo variables, viz. financial literacy and financial behaviour among the people of Assam. This led tothe acceptance of our second null hypothesis that there is a strong relationship between financial literacyand financial behaviour of the people of Assam.

Financial Literacy with Financial Attitude: Results of the correlation analysis shows thatassociation between financial literacy and financial attitude is moderately positive as ‘r’ value is 0.459.This is also statistically significant at 1 percent level of significance. It depicts a positive and moderaterelationship between financial literacy and financial attitude of the people and we accept our thirdhypothesis that there is a relationship between financial literacy and financial attitude of the people ofAssam. However, no strong relationship could be established and a moderate relationship is observed.This may be due to the fact that people of Assam lack a strong financial attitude though they are financialliterate.

ConclusionOur study and analysis concluded that the level of financial literacy among the people of Assam is

at a satisfactory level as compared to the national average, but a march towards development is alwaysdesired. The study found a strong and positive relationship between financial literacy and two of itsdimensions – financial knowledge and behaviour. The relationship between financial literacy and financialattitude is not very strong and indicates that people of Assam lack a strong financial attitude. This maybe due to the fact that people are culturally rich and inclined towards simple living. To be a frontrunner, all these three dimensions need to be managed in future.


References1. Aggarwal, N., et al. (2014). Financial Literacy among Farmers: Empirical Evidence from Punjab. Pacific

Business Review International, 6 (7), pp.36-42.

2. Atkinson, A. (2012). Measuring Financial Literacy: Results of the OECD / International Network on FinancialEducation (INFE) Pilot Study. OECD Working Paper No. 15, pp. 01-73.

3. CFPB (2015). Measuring financial well-being: A guide to using the CFPB Financial Well-Being Scale.Consumer Financial Protection Bureau, December.

4. Chen, H. and Volpe, P. (2002). Analysis of personal finance literacy among college students. FinancialServices Review, 7(2), pp. 107-128.

5. Croasmun, J. T., & Ostrom, L. (2011).Using Likert-Type Scales in the Social Sciences. Journal of AdultEducation, 40 (1), pp.19-22.

6. Dancey, C., & Reidy, J. (2011). Statistics without Maths for Psychology. Prentice Hall: London. 5th edition.

7. Devi, A. (2016). Financial literacy among the women: A sample study in the Kamrup District of Assam.EPRA International Journal of Economic and Business Review, 4(2), pp.144-147.

8. Klapper, L., et al. (2014). Financial Literacy around the World, S & P Global Financial Survey Report, pp.04-28.

9. Krejcie and Morgan (1970). Determination of Sample Size for Research Activities. Education and PsychologicalMeasurement, 30, pp. 607-610.

10. Lusardi, A. and Mitchell O. S. (2007). Financial Literacy and Retirement Preparedness: Evidence and Implicationsfor Financial Education. Business Economics, 42(1), pp. 35-44.

11. Mathivathani, V. and Velumani, M. (2014). A study on financial literacy among rural women in Tamilnadu,Indian Journals of Applied Research, 4(12), pp. 556-557.

12. NCFE (2014). NISM -Financial literacy and Inclusion survey, 2014.

13. PACFEL (2008). President Advisory Council on Financial Literacy-Annual Report, 2008.

14. Shaari, N. A. (2013). Financial Literacy: A study among the University students. International Journal ofContemporary Research in Business, 5(2), pp. 279-198.

15. Taft, M. K. et al. (2013). The relationship between financial literacy financial wellbeing and financial concerns,International Journal of Business and Management, p 8(11), pp.63-75.

16. Thapa, B. and Nepal, S.R.(2015). Financial literacy in Nepal: A Survey Analysis from College students. NRBEconomic Review, 27(1), pp. 49-74.

17. Zulfiqar, M. and Bilal, M. (2016). Financial Wellbeing is the Goal of Financial Literacy. Research Journal ofFinance and Accounting, 7(11), pp.94-103.

61Lifecycle Management Using Risk Estimation and Contingency Model for...

Lifecycle Management Using Risk Estimation andContingency Model for Indian Defence Sector

Mukesh Kumar Gupta* & Dr. Gyanesh Kumar Sinha**

ABSTRACTMitigating a risk refers to acting to either reduce the likelihood that a risk will happen and/or to reduce

its impact on the defence project. Risk contingency management on other hand is defined as creating anappropriate provision during life cycle of a project to ensure delivery of equipment sought by armed forcesare in the required timeframe and with the best value for money.

Indian defence industry has been historically a domain of Public Sector Undertakings (PSUs), directimport from overseas and regulatory controlled by the government. Therefore, standard risk measurementprocess and mitigation parameters are not available for private sector, those are entering the industry forthe first time. This study focuses on Management and Technical Contingency component of Project Risk lifecycle and its calculations using three-point estimation approach those are most suited to Indian DefenceIndustry.

The proposed model compares single and three-point approach qualitatively in detail. Furthermathematical illustrations are used to explain various scenarios of risk approach and its possible solutionson the proposed model. It is suggested that the Single point estimates tend to represent a conservative, or‘safe’, position Whereas 3-point estimates, the middle value represents a more optimistic and pessimisticview, respectively and most advisable for defence Industry and its related risk environment.

Keywords: life cycle management, risk management, contingency planning, Indian defence industry.

Indian Defence IndustryThe defence industry of India is among its strategic industries as it relates to the security of the

country. India holds the advantage of having the second largest numbers in armed forces in the worldby active military personnel in 2018(Dilinger, 2018). In 2016, India’s share in global military expenditurewas 3.3% and the focus of the government on promoting defence related manufacturing in India led toincrease its budget allocation for defence from US$ 41 billion in 2017-18 to US$ 62.8 billion in 2018-19(J. Singh, 2018). However, the defence manufacturing sector in the country is still heavily dependenton arms imports, making Indiathe largestimporter of conventional defenceequipment’s.This is equivalent

* Research Scholar, GD Goenka University Sohna Road Gurgaon India. Email: [email protected]** Associate Professor, School of Management, GD Goenka University Sohan Road Gurgaon India. Email:

[email protected]


to 13% share in world’s import of arms. In the period 2008 to2017, total amount spent on arms importwas more than US$100 billion(R. Singh, 2018). Additionally, weapon imports in the five-year period,2013-17 climbed 24% compared to 2008-12 with largest supplies of arms coming from Russia, followedby USA, Israel and France(Pandit, 2018).In a report byIndia Today published in 2017, the importofmilitary hardware by the Indian government was found to constitute 60% of the defencerequirement(Unnithan, 2017). The report mentioned that such huge dependence on imports is due tothe gap between capability and capacity. To reverse this import trend, the government identified defenceas one of the sectors which need a manufacturing boost. For this purpose,make in India is the mostexhaustive plan that has been undertaken so far in this regard.The plan includes several measures toencourage domestic manufacture such as opening the defence industry for 49% foreign direct investment(FDI) from the pre-existing 26%.

Until 2014, theIndian economy faced a dearth in funding options directed to research anddevelopment (R&D) in the public sector. Additionally, it lacked an effective ecosystem for encouragingforeign direct investment (FDI) or the private sector involvement. These factors constrained the growthof defencecapabilities of the nation. However, since 2014 several progressive reforms in the industryhave been made to ensure faster absorption of technologies, efficacious procurement,reduce the entrybarriers, increase competition and enhance ease of business(India Brand Equity Foundation, 2018).Among the recent initiatives, Defence Procurement Procedure (DPP) 2016 was designed for expeditedand efficient procurement of defenceequipment and technology. The policy initiative aimed to promotethe ‘Make in India’ by fostering growth of the defence industry within the nation’sboundaries(Narayanaswamy, Sai Sireesha, Rajababu, Varalakshmi, & Ulla, 2016). DPP 2016 introducedprocurement of defence goods under Indian Buy and Make model and stressed on Buy IndianIndigenously Designed (BIID), Developed and Manufactured (-IDDM) categoryto reduce importdependency of the industry (Press Information Bureau, 2017). To provide the required boost to theMake in India movement, government funding to indigenous projects have increased to 90% committedfor the purpose of prototype development(Panneerselvam, 2016).

Defence industry of a country has a number of inherent uncertainties as a result of the complexindustrial ecosystem it operates in (Heidenkamp, Louth, & Taylor, 2011). The ecosystem involves policymakers, industrialists, military operators, employees, citizens and taxpayers among the multiplestakeholders. In such dynamism, a risk management policy is required to minimize the effect of variousexternal and internal risks that may have an impact on financial as well as non-financial outcomes inthe industry(BEL, 2016). Additionally, in their study, Gaidow and Boey (2005) highlighted that riskmanagement policy symbolizes disciplined management. It is a vehicle for recognizing positive businessopportunities for the firms in the industry. Policy further helps in creation of a transparent environmentin the defence industry allowing firms to sustain their business growth and profitability through structuredrisk taking and mitigation processes (HAL, 2018).

Even today, the technical and commercial framework for defence products manufacturing ismandated by the government at the proposal stage(Ministry of Defence, 2006). The government promotesthe application of best practices and facilitates constant improvement in the operational process.Moreover, the government is actively pushing domestic manufacturers to have competitive advantagesin bidding, winning, executing, maintaining and ensuring all time performance of defence


equipment.Considering the significance of an effective risk management policy this paper havingfollowing objectives.

ObjectiveThis paper has following objectives.(i) To discuss importance of risk estimation in life cycle management of Defence products.(ii) To Study single & 3-point risk contingency estimation models under various scenarios.(iii) To propose most appropriate risk contingency estimation model combined with probability

value for Indian Defence Industry.

Literature Review

Considering the importance of life cycle management in defence, this section begins with thetheoretical background and its elements, challenges associated with risk management, and the popularstrategies used by international defence organisations to manage and mitigate the risks.

Risk ManagementIn generic terms, risk management refers to the activities of identifying, evaluating and selecting

among alternative regulatory actions. It is influenced by many social, economic, ethical and politicalfactors and includes evaluation of risk-benefit, cost-benefit, and trade-offs among different options(Barnthouse, Wayne R. Munns, & Sorensen, 2008).

With respect to the defines industry, several authors in the past have studied the key risks associatedwith different departments of the organisation involved in production of defence equipment. The tablebelow represents some of these risks.

Table 1: Risks Associated with the Defence Industry

Author (Year) Aim of the Study Findings Risks Identified

(Oudot, 2010) To evaluate the risks emerging during implementation and enforcement stages of defence procurement

Contractual risks are the most adverse, while technological risks are the second most significant

Direct financial risk, industrial risk, contractual risk, technological risk.

(Groom & Gray, 1995)

To explain risk assessment methodology developed by the Dynamics Division of British Aerospace Defence Company.

The risk assessment methodology has helped create a pro-active risk-management culture.

Development risk, production risk, subcontrac-ting risk

(Perlekar & Thakkar, 2018)

To analyse the critical issues faced in outsourcing by an organisation in Indian Defence Sector and suggest risk mitigation practices.

Development of a ten-point risk management plan to counter various risks in the outsourcing process.

Delivery risk, production risk, financial risk, material control risk, other external risks

(Cover & Mustafa, 2014)

To determine the role of corruption in different areas of risks in the defence sector

The risk areas display enough internal coherence for its key risk area and helps in reducing corruption.

Political risk, financial risk, personnel risk, operations risk, procurement risk.

(Pavel & Tzimas, 2016)

To identify the risks associated with supply chain management of defence industry

There are significant risks when a country is completely dependent on imports of raw material crucial for development of defence equipment.

Risk of dependence on a single country for procurement, risk of limited availability, risk of increase in demand and price


From the table above, it can be implied that there are critical risks associated with different functionsin the defence industry, most of them being focused on Financial, personnel, production, purchase,political and demand-related factors also play a role in the risk management framework of organisations.

Challenges in Risk ManagementDefence firms have to operate in a dynamic environment. Moore et al., (2015) stated that

organizational mission, operations, as well as their support requirements, keep evolving, whichmakes it difficult for the firms to operate. Additionally, the defence firms also must operate inconditions of regional conflicts which make risk management process difficult for the firms. Further,Arena et al., (2008)are suggestive that rising costs of sophisticated new technologies also pose achallenge to risk management for defence organizations. New age technologies are required tocounter new defence threats that are ever evolving. These technologies are not easy to acquire andcan become outdated in a very short time.

Strategies and Models in Present UseDefence companies operate in a paradoxical situation which requires them to manage their

long-term planning in short-term dynamic environmental change. Another study further highlightedthe strategy of pre-emptive planning for risk mitigation as well as their management in the defenceindustry (Bellais, 2013). Pre-emptive planning refers to those strategies that refrain potential entrantsto invest in the defence technology. The study pointed out that the new age technologies can helppromoting risk central repository that presents the view of formal risk management process instandard situations.

Risk Management in Indian Defence IndustrySingh, and Stevens (2011) in their study highlighted that the risk management is applied by

the firms to ensure that their ventures are potentially rewarding. Firms apply risk management tocounter core challenges and risks in the procurement process in Indian defence industry. Iyer, Pandit,and Mehta (2018)stressed the application of risk management function in creating a holistic risklandscape that includes intelligence on industry trends, geopolitical shifts, emerging risks, andcompliance requirements. The study highlighted that risk management prioritizes development ofrisk portfolio by the firms in their optimization plans. In India, the core problem of risks in thedefence industry involve threat analysis, competence in manufacturing, the support system that isin use, ability to meet cost and schedules of delivery (Suman, 2013).

In a study Thomas (2006) highlighted that risk management in Indiandefence industry is appliedto the process of evaluating, analysing, and controlling of risks. The management process is appliedto reducing of the probability of unwanted events and their impact during either production or useof produced military equipment’s. Risk management allows the firms to understand the challenges posedby Indian defence markets and especially for foreign firms trying to penetrate Indian markets, in thelight of economic dynamism related with the sector and Defence Procurement Policy (DPP) doctrinesof indigenization (Dutta, 2016).


Risk Contingency ModelRisk contingency is a plan for handling a risk if it occurs. This doesn’t reduce the probability of the

risk occurring but reduce the impact should it occur.

Risk Contingency Management and Its ResponsibilityManagement of a Defence Project budget is a continuous activity throughout the Lifecycle, and

the risk element of the budget is subject to varying degrees of review in the mandated LCM reviewsand in the Quarterly Business Review. The emphasis of contingency management evolves over theLifecycle; the most notable change is from the focus on setting the risk element of the Project budgetand to its utilization from next phase onward.

Overall management of the Defence Project budget is the responsibility of the Project Manager.Risk Contingency Management lies within these responsibilities, working with the Finance Manager toplan Margin Trading.

What is Contingency?Collins dictionary defines that “A contingency plan or measure is one that is intended to be used if

possible, situation actually occurs”. Within Lifecycle Management of defence products, contingencycomprises two main elements, these are defined as:

Technical Contingency

National Institute of Standard and Technology define technical contingency as funds set aside orkept available to cover identifiable and specific risks that are outside of the normal Project performance.Changes are authorized by the appropriate authority in accordance with local procedures. The assumptionsand estimates in compiling Technical Contingency recommended to be documented in the defence projectrisk register.

Deriving Technical ContingenciesOutputs from the Risk Management process are used to determine the “Contract Acceptance”

Technical Contingency and to monitor and report status against this amount as the Project progressesthrough its Lifecycle. To form a view on Technical Contingency, Risk Fallback Plan costs (i.e. impactcosts) are coupled with the risk probability data taken from the Risk Register.

The Risk Register provides a list of all the risks identified for a Project. It explains the nature ofeach risk and records information relevant to its assessment and management. Fallback Plans recordedin the Register provide an alternative course of action, should the agreed Mitigation Actions proveineffective and the risk occurs.

Single- and 3-Point ApproachesTwo distinct, alternative approaches to deriving the Technical Contingency are possible, as follows.The first, and historically the most common, is the single point approach, where one value or estimate

of Fallback Plan cost is combined with the risk probability value to calculate a ‘factored’ cost for each


risk. These factored costs are summed to determine the total Technical Contingency. Confidence in thisfigure depends on qualitative judgements made in setting the individual risk assessments. Nonetheless,the approach is transparent and requires no special tools.

The second approach utilizes 3-point estimates, where three values are estimated to reflect thespread of the potential Fallback Plan cost. These ‘Minimum’, ‘Most Likely’ and ‘Maximum’ figures -which characterize uncertainty in the risk cost - are then combined with the risk probability value toinform Technical Contingency evaluations and indicate risk cost confidence in a computer model. The3-point approach requires specialist analysis tools and the skillset to carry out a simulation. Use a 3-point approachis to:

(i) Meet customer requirements that include a mandate that 3-point estimates are conducted forall activities undertaken, including for those covered by risk costs.

(ii) Improve assurance that ‘worst-case’ scenarios have been identified and covered adequately,when the accuracy of risk estimates is a concern (higher levels of uncertainty in risk effects).

(iii) Enable drivers of risk cost outturn variance to be identified, using the model for the analysis.

(iv) Improve dependability in outturn predictions by forecasting based on collective risk effects.

Projects should decide which approach is to be taken early in the Lifecycle. A result of using thethree-point approach is that the simple arithmetic link between the Technical Contingency and individualrisk estimates and their probabilities is replaced by a different relationship, which depends on an analysisof the collective effects of the identified risks. In turn, this significantly affects the presentation of riskin the Contract Review, as a single contingency figure is extracted from a simulated outturn model ofoverall risk cost range. However, by using this method, Technical Contingency is determined at a known,numerical confidence level, in a systematic manner.

Single- and 3-Point Risk Estimating

Whichever of the two approaches is taken, the discipline of determining the costs of individual riskimpacts is fundamental. The features of single and 3-point risk estimating are contrasted below.

In both cases, the assessment of individual risk costs entails making an estimate of the Work (plusmaterials, expenses, etc.) required to implement the risk’s planned Fallback action.

(i) Single point estimates tend to represent a conservative, or ‘safe’, position with good inbuiltconfidence in recovering from the risk’s occurrence. However, the estimate may not cover theworst conceivable outcome.

(ii) In 3-point estimates, the middle value represents the likely cost of recovering, with the minimumand maximum values estimated by considering a more optimistic and pessimistic view,respectively.

Note that whichever method is used, the quality of the risk data is paramount and should be validatedwherever possible by considering historical data.

The relationship between Single- and 3-point estimate approaches is illustrated in Figure 1.


Figure1: Single versus 3-point Estimates

Single - pointMin. ML Max

Single - pointMin. ML Max

(Source: number line representation of variables)

From this, a simple summation of factored Most Likely (ML) values selected from within a 3 Pointrange would be lower than for summed Single Point factored risk estimates. As such, it would tend tounderstate the overall value compared with the Single Point calculation.

However, greater correspondence between the Single and 3-point approaches is seen when all threevalues in the latter are combined in a collective assessment. Such an evaluation is effectively ‘weighted’by the Maximum values, which thereby increases the resulting risk cost assessment, compared withsumming the ML values. The attributes of the 3-point estimates (their ranges and distribution types)affect the characteristics of the collective model of risk cost and, thereby, the level of confidence assignedto a Technical Contingency figure derived in this way.

Note that the estimation of risk costs should account for all financial consequences, even whereschedule and/or performance impacts appear to be the dominant feature.

The Single Point Technical Contingency CalculationIn principle, a factored cost is calculated for each risk by multiplying the estimated Fallback Plan

cost by the probability of occurrence. However, factoring should be applied with care as it may notalways be appropriate to apply a rigid formula - there are instances where it is appropriate to use apercentage higher than the probability figure. This is particularly important to ensure adequate coverageof:

• High probability risks where the expectation is the risk will occur and the cost will becomereal.

• Low probability, high impact risks where factoring by probability may provide inadequatecover.

In these cases, the un-weighted overall contingency budget may prove inadequate.Judgement should always be used to ensure that the contingency budget provides appropriate risk

cost coverage in the prevailing Project conditions. Worked examples are provided below to illustratehow probabilities may be weighted to achieve appropriate coverage.

Worked, Illustrative Examples of Single Point Technical Contingency Calculations

Scenario 1 - Reasonable Balance

A set of risks with similar impact values and mid-range probabilities are likely to ‘balance eachother out’ successfully when their probabilities are used for factoring. Consider the following simpleexample in which, by inspection: any single risk occurrence is affordable within the Total Contingency,


the dual occurrences of risks A + C or C + D can be covered and the worst dual occurrence (B & A or B& D) would exceed the allocated contingency by $ 8k. In these circumstances there would be a reasonablechance of containment within the Total Contingency, if the Impacts proved to have been conservativelyestimated.

Risk Impact Estimate

($ k) Probability of

Occurrence (%) Factoring Percentage (%) Factored Value Estimate

($ k)

A 30 60 60 18

B 35 30 30 10.5

C 25 60 60 15

D 30 40 40 12

Total 120 Total Contingency 57

Scenario 2a - High Probability Risk Problem

If one of the populations has a very high probability, then the balance is distorted as shown in themodification to Scenario 1, below. In this case, the occurrence of B is all-but certain, but only fractionalcoverage has been allowed, amounting to a 10% cost shortfall, effectively. Total Contingency appearsto provide good coverage for the occurrence of risks A, C and D, but B is irrelevant to the averagingprocess. In fact, the effective available Contingency 76.5 - 35 = 41.5, which is marginal cover foranything but a single risk occurrence.



Occurrence (%) Factoring Percentage

(%) Factored Value Estimate

($ k)

A 30 60 60 18

B 35 90 90 31.5

C 25 60 60 15

D 30 40 40 12

Total 120 Total Contingency 76.5

Scenario 2b - High Probability Risk Solutions

Here, the occurrence of B is assumed, and the Fall-back action has therefore been added into thePerformance Measurement Baseline at full value - effectively valuing the risk at 100% and taking it outof the risk assessment. Total Contingency coverage for risks A, C and D, has been improved by minorincreases to their factoring percentages, enough that the dual occurrence of A & C or C & D would

Exceed the allocated contingency by £/$ 4.75k. In these circumstances there would be a reasonablechance of containment within the Total Contingency, if the Impacts proved to have been conservativelyestimated.

[A project in this position, particularly with a few similar risks, could consider adding a balancingopportunity to the Opportunity Register, indicating a 10% probability of recovering the risk impact,should it not occur.


Note: it is not permissible to ‘net off’ risk on the CSR in this way - the opportunity must be realisedbefore it can be accounted for].



Occurrence (%) Factoring Percentage

(%) Factored Value Estimate

($ k)

A 30 60 65 19.5

B 100

C 25 60 65 16.25

D 30 40 45 13.5


Scenario 3a - High Impact / Low Probability Problem

If one of the populations has a relatively large impact but a very low probability, then the balance islost as shown in the modification to the table, below. In this case, the Total Contingency still provides‘comfortable’ coverage for risks A, C and D but the occurrence of B would be catastrophic to thebudget.



Occurrence (%) Factoring Percentage Factored Value Estimate

($ k)

A 30 60 60 18

B 105 10 10 10.5

C 25 60 60 15

D 30 40 40 12

Total 190 Total Contingency 57

Scenario 3b - High Impact / Low Probability Solution

If the Impact value of B cannot be mitigated to a lower value (or the risk transferred), a potentialsolution to cover this ‘killer risk’ is to adjust the Factoring percentage significantly to increase theoverall Contingency cover, as below. In this way, the occurrence of B and of any one of the otherswould be covered.



Occurrence (%) Factoring

Percentage Factored Value Estimate

($ k)

A 30 60 60 18

B 105 10 85 89.25

C 25 60 60 15

D 30 40 40 12



The 3 Point Technical Contingency Calculation

The Model: Simulating the Range of the Possible Risk Cost Outturn

The 3-point approach involves a different method of calculation than the single point approach andproduces additional information about Project status. The 3-point approach utilizes three values torepresent a spread in estimating the cost of each Fallback Plan. The 3 points are judgments of the:

• Minimum (Min.) Value: The lowest value expected• Most Likely (ML) Value: The middle value expected• Maximum (Max.) Value: The highest value expected

Probability

Estimated Risk CostMin. Max.ML

Example of 3-point Estimate DistributionProbability

Estimated Risk CostMin. Max.ML

Example of 3-point Estimate Distribution

Source: Normal Probability Distribution

For each risk, the spread and likelihood of 3-point values are represented in a distribution. Thisinput data is then combined with the probability of risk occurrence in a collective simulation model,utilizing a Monte Carlo type of sampling technique. The resulting simulation effectively merges theseparate assessments of the likelihoods and effects of individual risks by modelling the many possiblecombinations of risk values to predict an overall risk cost range.

A typical output distribution from the simulation is illustrated in below figure.• The vertical axis indicates the likelihood of the collective outturn risk cost on the horizontal

axis.• The maximum width of the (blue) distribution curve shows the full modelled range of possible

risk cost outturn values; the lower limit being if risks materialised at their minimum estimatedcost, and the upper limit if risks materialised at their maximum estimated cost. If risk estimatingis realistic, both possibilities are very unlikely.

• It is more likely that the collective risk cost lies somewhere in the intermediate region - andthe projected likelihood of a risk cost outturn value is indicated by the height of the distributionat the point in question. The Most Likely outturn value is indicated by the highest point on thedistribution.

Figure 1 The Risk Cost Analysis Simulation Distribution

The statistical term “Most Likely” is applied in the context of both inputs to, and the output from,the simulation here. In the former case it represents the best estimate of an individual risk cost. In thelatter it represents a feature of the collective model’s simulated outturn distribution.


Number of times the simulation

comes up with a particular risk cost

outcome

≡ RelativeLikelihood

£/$ Predicted RiskCost

The Most Likely outcome is represented by the tallest ‘stack’ –i.e. the most commonly occurring risk cost result as calculated in the

simulation

ML

Number of times the simulation

comes up with a particular risk cost

outcome

≡ RelativeLikelihood

£/$ Predicted RiskCost

The Most Likely outcome is represented by the tallest ‘stack’ –i.e. the most commonly occurring risk cost result as calculated in the

simulation

ML

Source: Normal probability distribution and probabilities relative to standard deviations from the average.

It can be useful to translate these confidence figures back into the scenario that is being modelled.The simulation is conducted by randomly sampling the individual risk distributions to predict the possiblecombinations. This amounts to imitating many Project scenarios in which different permutations ofrisks occur through the Lifecycle. Consider the example where a risk cost - i.e. contingency - is at the90% confidence point to underpin a fixed price contract. The model characterizes the prospect ofachieving the expected outturn margin on the theoretical basis that the same Project could be run manytimes over and the results measured. So, if the Project ran, say, 100 times, then:

• in 10 instances there would be margin erosion, but• in 90 instances there would be margin improvement

Management ContingencyAt any point in time, Management Contingency covers risks additional to those that underpin the

Technical Contingency. This is because they are risks not yet understood at enough level of detail tomeet the requirements for detailed Technical Contingency evaluation. Management Contingency coverspossible events that cannot be accurately estimated at the level of their impact on defined Work Packages.However, Management Contingency is not determined specifically and solely from the Project riskmanagement process; it is generated from judgement informed by supporting evidence from the riskregister and the planning & estimating processes. Consequently, it is often an expression of confidencein the estimated Project costs, also taking account of schedule effects on cost. Management Contingencyshould take account of experience and knowledge of the constraints on a Project. As for TechnicalContingency, data quality is paramount. Management Contingency is determined and set as part of theRequest for Bid Approval process. The rationale and assumptions for Management Contingency risksshould be documented in the register.

ConclusionThis paper description of the three-point approach and its applicability in the defence industry

suggest that, there is a need to have an active risk contingency management process which can support


to take calculated decision in the defence industry based on the risk appetite and risk tolerance limit oforganizations. In this respect, the contingency builds up with three-point risk estimates will be animprovement over the generally used single point risk estimates. As the main difference between thetwo approaches, the simple mathematical link between individual risk estimates and the technicalcontingency in the single point approach will be replaced by a range estimation by the three-pointapproach which depends on the analysis of collective assessment of identified risk costs. Therefore,there is huge scope for future research about the current study and improve the methodology of riskassessment in defence products during life cycle management.

References1. Arena, M. V, Younossi, O., Brancato, K., Blickstein, I., & Grammich, C. A. (2008). Why has the cost of fixed-

wing aircraft risen? A Macroscopic Examination of the Trends in U.S. Military Aircraft Costs over the PastSeveral Decades. National Defense Research Institute and Project Air Force.

2. Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation.European Journal of Operational Research. http://doi.org/10.1016/j.ejor.2015.12.023

3. Bailey, R. O. (2003). Analysis of current department of defense risk management practices in weapon systemacquisition: a case study of the advanced amphibious assault vehicle (aaav) pdrr and sdd risk managementpractices. Naval postgraduate school Monterey, California.

4. Barnthouse, L. W., Wayne R. Munns, J., & Sorensen, M. T. (2008). Population-Level Ecological Risk Assessment.Boca Raton: Taylor & Francis.

5. Behera, K. L. (2015). “Make in India” for Defence: A Roadmap.

6. Behera, L. K. (2013). Indian defence industry issues of self-reliance (21st ed.). IDSA Monograph Series.

7. BEL. (2016). Modified Risk Management Policy.

8. Bellais, R. (2013). Technology and the defense industry: real threats, bad habits, or new (market) opportunities?Journal of Innovation Economics, 12(2), 59. http://doi.org/10.3917/jie.012.0059

9. CIPS. (2019). Risk Management in Purchasing and Supply Management.10. Cover, O., & Mustafa, S. (2014). Identifying corruption risks in the defense and security sector: empirical

evidence using the government defense anti-corruption index. The Economics of Peace and Security Journal,9(2), 27–33.

11. Crickette, G., Demian, R., Fox, C., Hach, J., Makomaski, J., Mazumdar, R., & McGuire, R. (2012). ExploringRisk Appetite and Risk Tolerance.

12. DDP. (2019). Defence Public Sector Undertakings |.

13. Defence Turkey. (2017). PLM (Product Lifecycle Management). Defence Turkey.

14. Dilinger, J. (2018). 29 Largest Armies In The World.

15. Dutta, A. (2016). India’s Defence Modernisation: Challenges and Prospects. Indian Defence Review.

16. Enincon. (2017). Defence Equipment Market & Manufacturing in India 2017.

17. EY Global. (2017). The top 10 risks in aerospace and defense.

18. Singh, R., & Stevens, D. (2011). Navigating defense procurement challenges in india. India Law News AQuarterly Newsletter of the India Committee, 2(3).

19. Gaidow, S., & Boey, S. (2005). Australian Defence Risk Management Framework: A Comparative Study.Edinburgh.


20. Galinec, D., Možnik, D., & Guberina, B. (2017). Cybersecurity and cyber defence: national level strategicapproach. Automatika. http://doi.org/10.1080/00051144.2017.1407022

21. Ghorbani, S. (2017). How Cost Contingency is Calculated?

22. Groom, H., & Gray, K. (1995). Developing a risk-assessment methodology in the U.K. defence industry. IMAJournal of Mathematics Applied in Business & Industry, 6, 301–314.

23. HAL. (2018). Hal risk management policy.

24. Hamilton, B. (2006). Single Point Estimates.

25. Heidenkamp, H., Louth, J., & Taylor, T. (2011). The Defence Industrial Ecosystem: Delivering Security in anUncertain World. Royal United Services Institute for Defence and Security Studies. London.

26. India Brand Equity Foundation. (2018). “Make in India” in Defence Sector.

27. Iyer, V., Pandit, D., & Mehta, Y. (2018). A new dimension to the three lines of defence.

28. M. L. Cummings. (2017). Artificial Intelligence and the Future of Warfare.

29. Ministry of Defence. (2006). Defence procurement procedure (capital procurements). New Delhi.

30. Moore, N. Y., Loredo, E. N., Cox, A. G., & Grammich, C. A. (2015). Identifying and Managing Acquisitionand Sustainment Supply Chain Risks.

31. Narayanaswamy, K., Sai Sireesha, S., Rajababu, S., Varalakshmi, B., & Ulla, A. M. F. (2016). Make in India.International Journal of Management and Applied Science, 2(4), 6 –7.

32. Obicci, P. A. (2017). Risk Management Strategies in Public-Private Partnerships. Hershey: IGI Global.

33. Oracle. (2010). Successfully Managing Programs and Risk in the Aerospace and Defense Industry.

34. Ordinance Factory Board. (2018). Our Factories/: Indian Ordnance Factories:

35. Oudot, J.-M. (2010). Performance and Risks in the Defense Procurement Sector. Journal of Public Policy,30(2), 201–218.

36. Pandit, R. (2018, March). With 12% of global imports, India tops list of arms buyers: Report. The Times ofIndia.

37. Panneerselvam, P. (2016). DPP – 2016: A New Face of “Make in India” in Defence. International Strategicand Security Studies Programme. International Strategic and Security Studies Programme.

38. Pavel, C. C., & Tzimas, E. (2016). Raw materials in the European defence industry. The Netherlands.Retrieved from https://setis.ec.europa.eu/sites/default/files/reports/raw_materials_in_the_european_defence_industry.pdf

39. Perlekar, N., & Thakkar, J. J. (2018). Risk management framework for outsourcing in the defence sector: acase from India. International Journal of Production Research . http://doi.org/doi.org/10.1080/00207543.2018.1555381

40. Press Information Bureau. (2017, December). Progress under “Make In India” scheme.

41. PWC. (2005). The Defence Industry in the 21st Century: Thinking Global or thinking American?

42. PWC. (2012). Decoding the Indian Aerospace and Defence sector.

43. Sanford, A., & Moosa, I. (2015). Operational risk modelling and organizational learning in structured financeoperations: A Bayesian network approach. Journal of the Operational Research Society. http://doi.org/10.1057/jors.2013.49

44. Singh, J. (2018). Defence Manufacturing: India has the 5th largest defence budget in the world.

45. Singh, R. (2018, March). India still largest arms importer, spent more than $100 b in last 10 years: SIPRI.Hindustan Times. New Delhi.


46. Suman, M. G. M. (2013). Defence Acquisitions: Risk Management — Better Than Crisis Management. IndianDefence Review, 28(1).

47. Thomas, K. T. (2006). Quality Management System for Defence Aeronautical Industry. Defence ScienceJournal,56(1), 21 –30.

48. Tian, N., Fleurant, A., Kuimova, A., Wezeman, P. d., & Wezeman, S. T. (2018). Trends in world militaryexpenditure, 2017.

49. Tominac, S. B., & Palijan, A. (2016). Managing operational risks in banks: Croatian case. In Proceedings ofMAC-MME 2016.

50. Unnithan, S. (2017, February). Unmade in India. India Today.

51. Vanhoucke, M. (2012). Project risk: Statistical distributions or single point estimates?

52. Yoe, C. (2000). Risk Analysis Framework for Cost Estimation. Carbondale.

75Recent Trends in Entrepreneurship (Start-Ups) Development with Reference...

Recent Trends in Entrepreneurship (Start-Ups)Development with Reference to North East-India

Dr. K.C Biswal* & Mr. Dhananjoy Narzary**

ABSTRACTSeveral schemes and projects have been formulated and implemented for entrepreneurship development

specially for women in particular as the Government has recognised entrepreneurship is an importantinstrument in development of societies in several ways. Micro, Small and Medium Enterprises (MSME) hasemerged as a highly vibrant and dynamic agent for industrialization of rural & backward areas in India.Khadi is the proud legacy of our national freedom movement and the Father of the nation. Khadi and VillageIndustries (KVI) are two national heritages of India. One of the most significant aspects of KVI in Indianeconomy is that it creates employment at a very low per capita investment. NABARD is set up as an apexDevelopment Bank with a mandate for facilitating credit flow for promotion and development of agriculture,small scale industries, cottage and village industries, handicrafts and other rural crafts. North East-India isendowed with abundant natural resources which can promote a huge entrepreneurial development in theregion. The NER region has tremendous potential for generating revenue from the primary, secondary, aswell as the tertiary sectors. This study highlights the important factors which can enhance entrepreneurialgrowth and opportunities in the region. Also it examines about the contributions of development agencies/organizations in development of village industries.

Key words: Entrepreneurship trends, Start-ups, KVI, MSME, NABARD

Introduction

Entrepreneurship has been described as the “capacity and willingness to develop, organize andmanage a business venture along with any of its risks in order to make a profit. Demographic trends inIndia, the second most populous country in the world, suggest that a million people join the labourforce every month. This amounts to 12 million Indians joining the labour force every year, which ismore than the entire population of Sweden. With millions of young people joining the labour marketevery month, the question on their minds is if there will be enough jobs for them. India produces toofew entrepreneurs for its stage of development. The pace of creation of new businesses and new start-ups in India is low compared to the rest of the world (World Bank Report, 2017). A slow pace ofentrepreneurship is associated with a slow pace of job creation. An examination of millions of enterprises

* Professor, Department of Management, NEHU. Tura Campus Email: [email protected]** Research Scholar, Department of Management, NEHU Tura Campus.


in India and the US has shown a very strong link between new start-ups and subsequent job growth inboth countries. A detailed examination of enterprise in 600 districts in India confirms the strongrelationship between new start-ups and subsequent job growth. Districts in India that embracedentrepreneurship have experienced faster job growth.

The Micro, Small and Medium Enterprises – Development Organisation (MSME-DO) (earlier knownas SIDO), headed by the Additional Secretary & Development Commissioner (MSME), being an apexbody for formulating and overseeing implementation of the policies for the development of MSMEs inthe country, is playing a very positive and constructive role for strengthening this vital sector. It functionsthrough a network of MSME-DIs, Regional Testing Centres, Footwear Training Institutes, ProductionCentres, Field Testing Stations and specialized institutes Khadi & Village Industries Commission (KVIC)established under the Khadi and Village Industries Commission Act, 1956 (61 of 1956), is a statutoryorganization under the aegis of the Ministry of MSME, engaged in promoting and developing khadiand village industries for providing employment opportunities in the rural areas, thereby strengtheningthe rural economy. KVIC has been identified as one of the major organisations in the decentralisedsector for generating sustainable non-farm employment opportunities in rural areas at a low per capitainvestment.

North-east India comprises the contiguous Seven Sister States such as ArunachalPradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura, and the Himalayan stateof Sikkim. Although the mountainous scenery is arresting, streams, rivers and falls nonchalantlymelancholy, the tribal population being nature worshipper and humble the northeast region remainsone of the least visited but fastest developing part of India and investments started following sinceIndian Chamber of Commerce (ICC) setup its North east Regional Office in Guwahati way back in2000 after organizing 1st North East Business Summit in New Delhi graced by all chief ministers ofNE states to attract investors. The then Hon’ble Prime Minister of India Shree Atal Bihari Vajpayee hadgraced the 1st NEBS as Chief Guest and promoted North east India not only as tourist destination butalso as an ideal investment destination with unlimited opportunities. Northeast India constitutes about8% of India’s size; roughly three quarters the size of the state of Maharashtra. Its population isapproximately 40 million (2011 census), 3.1% of the total Indian population; roughly equal to thatof Odisha. The Siliguri Corridor in West Bengal, with a width of 21 to 40 kilometres (13 to25 mi), connects the North Eastern region with the main part of India. The region shares more than4,500 kilometres (2,800 mi) of international border (about 90 per cent of its entire border area)with China (southern Tibet) in the north, Myanmar in the east, Bangladesh in the southwest,and Bhutan to the northwest. The states are officially recognised under the North Eastern Council(NEC), constituted in 1971 as the acting agency for the development of the eight states. The NorthEastern Development Finance Corporation Ltd (NEDFi) was incorporated on 9 August 1995 andthe Ministry of Development of North Eastern Region (DoNER) was set up in September 2001.The Ministry of Development of North Eastern Region (MDONER) is a Government ofIndia ministry, established in September 2001, which functions as the nodal Department of the CentralGovernment to deal with matters related to the socio-economic development of the eight Statesof Northeast India. It acts as a facilitator between the Central Ministries/ Departments and the StateGovernments of the North Eastern Region including Sikkim in the economic development includingremoval of infrastructural bottlenecks, provision of basic minimum services, creating an environment


for private investment and to remove impediments to lasting peace and security in the North EasternRegion including, Sikkim.

The National Bank for Agriculture and Rural Development (NABARD) took this idea and startedthe concept of micro-finance in India. Under this mechanism, there exists a link between SHGs (Self-help groups), NGOs and banks. SHGs are formed and nurtured by NGOs and only after accomplishinga certain level of maturity in terms of their internal thrift and credit operations are they entitled to seekcredit from the banks. There is an involvement from the concerned NGO before and even after theSHG-Bank linkage. The SHG-Bank linkage programme, which has been in place since 1992 in India,has provided about 22.4 lakh for SHG finance by 2006. It involves commercial banks, regional ruralbanks (RRBs) and cooperative banks in its operations.

Review of LiteratureMany recent research studies have shown that the population dependency and engagement in

agricultural sector in India has been decreasing since last few years. In North Eastern Region (NER) ofIndia, thousands of small households industries are operating in rural areas. These are all traditionalhouseholds industries and operating by some communities and caste. According to a report (MSMEfoundation 2007), India have around 6000 micro enterprise clusters. Another database of UNIDO showsthat there are more than 4000 artisanal and about 363 non- artisanal clusters in India. There is a veryless literature that we have on cluster base poverty reduction. Among this few UNIDO’s study in 2004‘Industrial Cluster and Poverty Reduction’, which says cluster and poverty are related in three distinctways namely through cluster features, cluster process and cluster dynamics.

According to Bird (1995), entrepreneurial competencies are carried by individuals – the entrepreneurswho begin or transform organisations and who add value through their organising of resources andopportunities. She suggests that the competencies necessary to launch a new venture or to plan a newventure may be conceived as “baseline”. Man et al. (2002) defined entrepreneurial competencies as thetotal ability of the entrepreneur to perform a job role successfully. The study also suggested that thecharacteristics of entrepreneurs such opportunity, relationship, analytical, innovative, operational, human,strategic, commitment, learning and personal strength competencies were demonstrated to have eitherdirect or indirect impacts on the entrepreneurial performance.

Sarri & Trihopoulou, (2005) examined the personal characteristics and motivations of womenentrepreneurs in Greece. The study revealed that the education level of the respondents was high; mostlywomen were married and had children. There was also a tendency to enter in to business in old age.The women in Greece were mostly motivated by pull factors like self- fulfilment, need for creativityand independence. Kaippachery (2005) analysed the impact of economic reforms structure schedule onthe 82 rural small scale enterprises (RSSEs) located in Kannur district of Kerala. The results foundnegligible impact of the reforms on employment, earning capacity and availability of raw materialwhereas output, productivity, market access, diversification, safety of labour and capital were found tobe more vulnerable to unsustainably. To support economically unsustainable RSSEs, the study suggesteddevelopment of rural financial markets, trades fares, advertisement, displays etc. Ram Krishna Mandal(2007) in his paper encompasses the present scenario of Khadi and Village Industries in the NorthEastern States, particularly Arunachal Pradesh, in relation to growth, development, problems and


solutions. The author opined that top priority should be given to those small scale industries like KVIswhich need light machine tools and other equipments in order to produce qualitative products becausetoday, a state’s progress is measured by the quality of goods it produces.

Srivastava and Syngkon (2008) study makes an in depth analysis of the development of small scaleindustrial (SSI) sector in the rural areas of the states of NER of India. The study also focuses specificallyon the role and profile of entrepreneurs. It is observed that in most of the North Eastern states,concentration and growth of SSI activities is higher in rural areas than in urban areas. The study alsobrings to light about the rising number of women and tribal entrepreneurs in the region. Khanka (2009)conducted a survey of 248 first generation entrepreneurs in Assam in NE India to understand theirentrepreneurial motivation. The study clearly showed that the entrepreneurs were primarily motivatedby the need for economic achievement, personal growth, autonomy and recognition. The desire tocontribute to the community was not found to be an important reason to become an entrepreneur. Thestudy did not reveal any significant difference in the motivations of men and women entrepreneurs.

Gangadhar Banerjee and Srijeet banerji (2011) conducted a study on rural entrepreneurshipdevelopment programme - an impact assessment in seven states of India namely Andhra Pradesh, Bihar,Chhattisgarh, Himachal Pradesh, Odisha, Uttar Pradesh and west Bengal. The programmes wereconducted through Entrepreneurship Development Institute, Voluntary associations, Non- Governmentalorganisations for providing sustainable employment and income opportunities in rural areas. The studyreveals that REDPs is an efficient instrument in creating income and employment opportunities for therural youth, especially the women in rural and semi-urban areas. The study recommends that there is aneed to adopt a comprehensive strategy to cover adequate number of potential entrepreneurs under REDPthrough EDIs/RUDSET type institutes and select capable VAs/NGOs to operate the strategy. Jyoti kumarand Lalhunthara (2012), in their study on socio-economic background of Micro entrepreneurs in Aizawldistrict, Mizoram found that Education, experience, age and family play an important role in shaping theentrepreneurial ambition of the aspirant. It was found that nearly one-fourth of entrepreneurs were females.Their study also reveals that entrepreneurs were engaged in different lines of business activities rangingfrom tailoring to food processing, involving complex technologies and different skills sets.

Statement of the ProblemThough many rural development agencies had been involved for rural entrepreneurship for decades,

the change in economic scenario in North East Region has been very steady. There is a need for manymore mobilization and awareness programs on the entrepreneurship opportunities and its importance inthe region for the young generation. North East Region is diversified in respect of geographical location,social, cultural, religion, political and economic conditions. There is also need to throw light on thefactors that motivate the rural micro entrepreneurs to establish their units, recognizing their limitationsand interests. This observation is more relevant in the context of educated young generation who needdirection, motivation and to build confidence to start entrepreneurial activities. It has been continuingtrend in the region that young graduates aspire to be employed in government sector. And thoseuneducated unemployed youngsters are diverted towards activities that are socially not desirable. Alsothe tribals of North East Region are reluctant to relocate from their birthplaces which would otherwiseexpose them to greater opportunities in the outside world. In spite of huge available natural resources


in the region for instances, Bodos in Assam, Garos in Meghalaya, Kashis in Meghalaya the younggraduates opt for working under someone but not to self employment.

Significance of the StudySelf-employment is often perceived to be a desperate effort of workers who have been laid off and

unable to find work again; it is viewed as low-paying, and as providing little or no benefit for the localeconomy. But policy and educational programs directed at improving the productivity and earnings ofthe self-employed could have high payoffs in terms of local economic growth and opportunity. As thepopulation is growing, increasing number of literate people, the unemployment rate in North Easternstates is on the rise. It is a high time to take up entrepreneurial activities to utilize abundant localresources. The findings of different studies about the North Eastern region can convey important messageabout various entrepreneurial opportunities and its significance in the modern times.

Objectives of the StudyThe proposed study will focus on the objective as follows-1. To study the trends in entrepreneurship (Start-Ups) development in North East- India.

Research MethodologyData collection: This study is based on the secondary data from the reports published by NABARD,

annual reports of MSME, Government of India, government publications, official website of Assam,Meghalaya and other north eastern states. The researcher has referred to the published and unpublishedresearch papers, dissertations, books, articles and journals for collecting secondary data for the study.The data has been analysed using simple statistical tables and graphs.

Findings and DiscussionThe NER region has tremendous potential for generating revenue from the primary, secondary, as

well as the tertiary sectors. The opportunities in the primary sector exist in cultivation of plantationcrops and commercial exploitation of forest resources. The secondary sector has immense opportunitiesin the form of rich mineral and crude petroleum reserves and also from the tourism sector. Most of thestates have structured IT policies with attractive incentive packages, which may translate into majorrevenue generating avenues.

Entrepreneurial opportunities in North East-India:

The factors driving lucrative business opportunities in the NER are:• Exclusive incentives for NER states – Both the central and state governments have set out

enormous subsidies to support power, transportation, land and infrastructure development forsetting up business in NER.

• Enormous reserves of natural resources – The NER is endowed with considerable naturalresources and hosts about 37 per cent of the country’s river waters, 20 per cent of the totalhydrocarbon potential, large quantities of low ash coal resources, limestone and dolomitedeposits as well as a few other unexplored minerals.


• Favourable climate for lucrative plantation crops – The NER states have ideal climaticconditions for growing tea and rubber hurbal. There is immense potential for further commercialexploitation of resources, with increasing support from the central and state governments.

• Potential for forest-based industries – The NER has 46 per cent of its land under forestcover and thus vast amount of forest resources are available including bamboo, medicinalherbs and wood, which may be utilised for setting up of forest-based industries.

Tea production: The tea industry has contributed substantially to the economy of Assam, with 17per cent of the workers employed in the industry. Tea from Assam has great demand in western countries.In Assam, tea is grown both in the Brahmaputra and Barak plains. The state is home to one of theworld’s oldest and largest Tea Research Centres, started in 1911 at Toklai in Jorhat. It also has theworld’s second largest Tea Auction Centre, established in 1970 at Guwahati, for better marketing of thetea produced in the NER states. The tea produced in Mizoram has a distinct quality and flavour similarto tea grown in high altitudes like the Nilgiris and Darjeeling. There is a proposal for setting up of a teaprocessing plant at Biate in collaboration with the local cooperatives. Temi Tea estate is located insouth Sikkim and is one of the best tea producing estates in the country. Tripura is the 5th largest teaproducer, among the 14 tea-producing states, after Assam, West Bengal, Tamil Nadu and Kerala. Teaplantation is also found in the states like Meghalaya, Manipur etc.

Rubber Plantation: The Rubber Board adopted an integrated approach for rubber development inthe NER during the 10th plan period. In Tripura about 1,000 sq km of area in the state can be broughtunder rubber plantation. Tripura is estimated to have around 26,500 hectares under rubber cultivationat present, which is the second largest after Kerala. The Rubber Board now considers Tripura the secondrubber capital of India. Rubber plantations are also found in other states of North East.

Bamboo Policy for North East: Table 1.Category Central Government Arunachal Pradesh Assam Manipur Meghalaya

Insurance Scheme

Reimbursement of 100% insurance premium; Risk coverage includes fire, lightning, landslides, cyclones, riots, strikes, malicious/terrorist damages

Income Tax Exemption

100% for 10 years

Power Subsidy 50% on cost of laying power lines

@50% for power lines subject to a ceiling of USD 1,242; subsidy on power supply for 3 Years

30-50% of power tariff for 5 years; 20% for drawing power lines

100% to SSI for 5 years; 50% of the cost incurred on linking of power lines

@30-50% on total expenditure on power consumption for 5 yrs, up to USD 497 – 17,391

Excise Duty Exemption

100% for 10 years 100% for 10 years

Sales Tax 100% for 7 years 4% exemption on value of raw materials for 10 years

100% exemption for 7 years

Price Preference @7.5-17% and exemption of EMD

@ 20% for SSI Units

Others Concessions

Certain tax exemptions for IT units, Bio-technology & Power Generating industries, Export Oriented Units

Quality Control, Cost of Feasibility and Project Reports, Manpower Development, Technical Know- How

Incentives for Feasibility Study Cost, Quality Certifi cation, Marketing Assistances, for specific industries, and FDIs

Cost of Feasibility and Project Reports, Training of Tribals, Technical Know-How, Stamp Duty, Quality Up gradation

Cost of Feasibility and Project Reports, Training of Tribals, Technical Know-How, Stamp Duty, Development


Category Mizoram Nagaland Tripura

Insurance Scheme

Income Tax Exemption

Power Subsidy @30-60% on total expenditure on power consumption

@ 25 – 30% for 5 years subject to a ceiling of USD 4,969 annually

Additional 30% of outside peak hours

Excise Duty Exemption 100 % for 10 years

Sales Tax 100% exemption for 7-10 years 100% exemption for 7 years 100% reimbursement for first

5 years

Price Preference @ 100% subject to a ceiling of USD 497 @15% and exemption of EMD @ 10% on purchases by the

Govt

Others Concessions

Cost of Feasibility and Project Reports, Training of Local people, Factory Rent, Export Oriented Units, Stamp Duty

Cost of Feasibility and Project Reports, Training of Local people, Export Oriented Units, Quality Control, Stamp Duty

Reimbursement of Standard Certification Charge; Concession for industries using natural gas as feedstock; grant and loan

Source: IBEF Publications (2015)

The NER has the maximum concentration of bamboo in India owing to its topography and climaticconditions. At present bamboo is put only to traditional use – handicrafts and papermaking. It is truethat importance of bamboo has been increased from edible bamboo shoots to construction, medicine,and bamboos fabric or bio fuel. For the past years, bamboos experts have been experimenting withthe multiple uses of bamboo and are still discovering new applications every day. Bamboo fiber forthe garment and automotive industries, flooring boards, veneers as thin as 0.2 mm, are just some ofmany examples of its usefulness. Bamboo panels, especially floors, are more and more in demand allover the world, because they have the texture of marble and the elegance of wood; in addition, theyare strong, durable, smooth, clean, non-sliding and resistant to humidity. Recently, the Governmentof India announced a bamboo mission for promoting bamboo-based industries in the NER. The statesof Arunachal Pradesh, Assam, Mizoram, Sikkim and Tripura have policies specific to bambooproduction and related activities. Tripura is one of the highest CVP (climate, vegetation, precipitation)index zones (a measure of potential productivity) for bamboo in the country. Thus, more number ofpeople can be engaged in non-farm activities like bamboo plantation which will then promote bamboohandcraft.

Handicrafts and handloom: The NER has a rich heritage of artistic craftsmanship, with uniquecrafts and abundant availability of skilled labour. The crafts of this region are almost entirely orientedto locally available raw materials. The principal handicrafts of this region include basketwork, canefurniture, mats, woodcarvings, terra cotta, artistic textiles, bell metal artwork, brass metal craft, dollsand toys. With various incentives on export oriented units, lucrative business may be set up for exportof the NER handicrafts. Handlooms are a hereditary occupation in the region. Some of the handloomproducts, known for their excellent craftsmanship, are carpets of Arunachal Pradesh, Muga silk productsof Assam, lashingphee of Manipur and shawls of Nagaland and Mizoram. With locally available rawmaterials, large resource of skilled labour and incentives for export oriented units, units may be set upfor export of NER handloom products.


Medicinal and Aromatic Plants Industries: North East India is one of the richest repositories ofmedicinal and aromatic plants (MAP) in the world. The list of commercially important medicinal plantshas already crossed 150 species. NER possesses tremendous scope to be a good business centre forMAP products in the near future. Scientific approach for their exploration, conservation and valueaddition may be the key points for entrepreneurship development by exploiting the indigenoustechnology knowledge. Post harvest processing of MAP crops is another important new area for NEIndia in entrepreneurship development for the sector. Around 300 types of medicinal herbs and plantsare known to exist in abundance in Assam. The Brahmaputra valley itself has 150 varieties of herbsand plants of commercial value. It is estimated that only around five to 10 per cent of the plants andherbs are currently utilised.

Mineral-based industries: The availability of superior quality natural gas at concessional priceoffers opportunity to prospective investors for setting up gas-based industrial units. Besides this,natural gas can also be utilised as a cheaper source of energy for various energy intensive industrialprojects.

Forty-eight per cent of the on-land oil reserves and more than 50 per cent of the in-place gasreserves in India lie in the north eastern states and Assam has one of the biggest pool of professionaland skilled manpower engaged in the oil and petroleum industry. The wells at Digboi, Duliajan andSivasagar also produce natural gas (reserve of 156 billion cu m) accounting for about 50 per cent ofIndia’s total onshore production. This could be used as feedstock for production of fertiliser, electricityand petrochemicals industries and also as fuel in the tea sector. Limestone with reserves of about 500million tonnes is another important resource and is available in various grades. The China clay availablein the Karbi-Anglong district is a vital input for the ceramics industry. Meghalaya with its wealth ofmineral deposits has tremendous industrial potential. There are extensive deposits of coal, limestone,granite, clay and other minerals. The total estimated reserve of coal in the region is around 640million MT. Limestone is another mineral that occurs in an extensive, 200- km-long belt along thesouthern border of Meghalaya. The total inferred reserve limestone within the state is around 5,000million MT. Nagaland offers investment potential in terms of exploration as well as exploitation indevelopment of mineral-based industries, which have high export potential.

The Office of DC (MSME) has MSME-DIs at Gangtok (Sikkim); Guwahati (Assam); Imphal(Manipur); Agartala (Tripura) and also branch MSME-DIs at Aizwal (Mizoram); Dimapur (Nagaland);Itanagar (Arunachal Pradesh); Diphu (Assam); Silchar (Assam); Tezpur (Assam); Shillong (Meghalaya)and Tura (Meghalaya). A Technology Centre has been set up at Guwahati to cater to tooling andtraining need of industries in the North East region. The Technology Centre is equipped with hi-techmachinery for providing common facility services to the industry; conducting various skilldevelopment modular courses, long term and short term programmes in the area of Machinist, Welding,Machine Tool Operation, Manufacturing Technology, Mould Design with CAD/CAM, ElectricalMaintenance, Plastic Processing & IT Application etc. The State Government of Nagaland has alsobeen assisted to set up a Mini Tool Room & Training Centre at Dimapur, Nagaland.


Table 2: Category-wise own contribution and rate of subsidy

Categories of beneficiaries under PMEGP

Beneficiary’s own contribution (on project

cost) Rate of Subsidy (on project cost)

Area (Location of Project/unit) Urban Rural

General Category 10% 15% 25%

Special Category (including SC/ST/OBC/ Minorities/women/ex-servicemen/PWD/NER, Hills and border areas, etc.

05% 25% 35%

Note: (1) The maximum cost of the project/unit admissible under manufacturing sector is `25 lakh. (2) Themaximum cost of the project/unit admissible under business/service sector is `10 lakh. (3) The balanceamount of the total project cost will be provided by Banks as term loan

Table 3: Performance of Khadi in India

Performance 2011-12 2012-13 2013-14 2014-15

Production of Khadi (Rs. in Cr) 716.98 761.93 811.08 879.98

Retail Sales of Khadi (Rs. in Cr) 967.87 1021.56 1081.04 1170.38

Employment (in lakh persons) 10.45 10.71 10.98 11.06

KVIC-annual reports

It is clear from the table above that the performance of khadi industries in terms of total production,total sales and employment generation in the country is progressing but the growth has been slow.

Activities of Office of the Development Commissioner (MSME) in North EasternRegion:

As per the budgetary policy of the Government of India, 10 per cent of total plan budget is earmarkedfor NER for implementation of various Plan schemes in khadi, village industries and coir sectors. Thedetails of the funds released by the Ministry to KVIC and Coir Board for the NER during the last threeyears and 2015-16 are given in the Table below:

Table 4: Release of Funds for North East Region (Value: in lakh)

Year Funds Released

KVIC COIR BOARD TOTAL

2013-14 133.46 1.45 134.91

2014-15 126.47 0.65 127.12

2015-16 99.55 1.85 101.40

2016-17 91.24 0.30 91.54

Source: MSME Annual Reports


Table 05: State-wise KVI Productions in North East Region (Value: in lakh)State 2013-14 2014-15 2015-16 2016-17

Arunachal Pradesh 5188.60 5642.5 5956.62 4765.29

Assam 64350.74** 69940.57** 73780.33** 59024.26**

Manipur 11152.66 12121.76 12784.37 10227.49

Meghalaya 13194.08 14352.91 15142.58 12114.06

Mizoram 25187.43* 27391.38* 28898.20* 23118.56*

Nagaland 13761.33 15043.20 15871.77 12697.41

Sikkim 4534.83 4931.67 5202.91 4162.32

Tripura 11907.82 12949.94 13662.25 10929.80

Total 149277.49 162373.93 171299.03 137039.19

Among all the North Eastern states, the state of Assam leads in the production and employment

generation of khadi and village industries, followed by Mizoram. The total of state-wise production ofKVI in per cent from 2013-2017 is shown in the diagram below.

Figure.1

Table 6: KVI Employment in North East Region (In lakh persons)

State 2013-14 2014-15 2015-16 2016-17 Arunachal Pradesh 0.09 0.15 0.15 0.15 Assam 2.89 4.54 4.69 4.69 Manipur 0.53 0.85 0.87 0.87 Meghalaya 0.33 0.52 0.54 0.54 Mizoram 0.66 1.05 1.08 1.08 Nagaland 0.43 0.68 0.70 0.70 Sikkim 0.18 0.26 0.26 0.26 Tripura 0.49 0.79 0.81 0.81

Total 8.45 8.84 9.10 9.10

Source: MSME Annual Reports


The tables above show that the production of khadi industries and their employment generation inNorth Easter Region of the country is very meagre as compared to the national average. The productionis on the rise, but employment generation has been almost stagnant since the year 2012 till date. Tocater to the needs of skill development in NER, Multi-Disciplinary Training Centres at Kumarikata(Assam) and Doimukh, (Arunachal Pradesh) are being run by the institutions with the financial assistanceof KVIC. In addition, training centers are being run by State KVIBs at Roha, Marigaon (Assam);Zamabank (Mizoram) and Dimapur (Nagaland). Besides, 4 agencies have been accredited for conductingtraining in NE States. The beneficiaries from NE Region are provided rail fare for attending trainingprogrammes and also daily allowance during the training period. The total of KVI employment duringthis three year from 2013 to 2017 is represented by the following diagram.

Figure.2 : KVI Employment in North East Region (In lakh persons from 2013-2017)

The table below depicts the percentage of MSME Establishments in North East Region in comparisonto rest of India.

Figure.3

Source: MSME AR 2016-17


Schemes/Programmes of NABARD: An Analysis and Evaluation

Sl. No Region

Commercial Banks RRBs Cooperative Banks Total

No. of SHGs

Amount of Savings

No. of SHGs

Amount of Savings

No. of SHGs

Amount of Savings

No. of SHGs

Amount of Savings

1 Northern Region 20356 33419.27 7465 6531.88 10285 8346.79 38106

48297.94 (1.29%)

2 North Eastern Region 8793 6250.09 15058 13950.98 2186 1767.63 26,037 21,968.70

(0.59%)

3 Eastern Region 170407 134380.43 136334 146461.13 105835 68647.51 4,12,576 3,49,489.07

(9.38%)

4 Central Region 61869 86933.81 19638 12879.75 2775 19253.17 84,282 119066.73

(3.19%)

5 Western Region 81868 161209.14 13507 14536.97 17150 12886.10 112525 188632.21

(5.06%)

6 Southern Region 788988 2096304.49 278397 722132.17 91412 182798.78 11,58,797 30,01,235.44

(80.49%)

7 Grand Total 1132281 2518497.23 470399 916492.88 229643 293699.98 1832323 3728690.09

Source: Report on the Status of Microfinance, NABARD (2015-16)

Figure.4: Region-wise Status of Bank Loan Disbursed to SHGs during 2015-16

Table.8: Region-wise Status of Bank Loan Disbursed to SHGs during 2015-16(Total Loan Disbursed in Rs. Lakh; Average Loan Disbursed in / SHG)

Sl. No

Regions

2013-14 2014-15 2015-16

No. of SHGs

Total Loans

Disbursed

Average loan

Disbursed

No. of SHGs

Total Loans

Disbursed

Average Loan

Disbursed

No. of SHGs

Total Loans

Disbursed

Average Loan

Disbursed

1 Northern Region 23918 28048 117269 43848 42873 97777 38106 48298 126746

2 North Eastern Region 16201 12819 79125 18791 15795 84056 26037 21969 84375

3 Eastern Region 297478 151067 50783 351800 329602 93690 412576 349489 84709

4 Central Region 66393 61807 93092 109231 110909 101536 84282 119067 141272

5 Western Region 87846 86444 98404 97341 117080 120279 112525 188632 167636

6 Southern Region 874585 2061551 235718 1005227 2141972 213083 1158797 3001235 258996

All India 1366421 2401736 175768 1626238 2758231 169608 1832323 3728690 203495

Source: Report on the Status of Microfinance, NABARD (2015-16)


The overall amount of bank loan disbursed to SHGs over the years has increased in the country. InNorth -Eastern region the average amount of bank loan disbursed to SHGs during the financial years2013-14 to 2015-16 has increased from Rs. 79,125 to Rs. 84,375 (i.e., 6.6%); and the total number ofSHGs increased from 16,201SHGs to 26,037 SHGs (i.e., 60.7%) during the same period. On the otherhand, in Southern region, there was 32.50% increase in number of SHGs; and the average bank loandisbursed to SHGs showed an increase of 9.87% during the same period. Thus, the bank loans disbursedto SHGs in North-Eastern region is not as per the percentage increase in the number of SHGs.

Figure.5: Region-wise Non-performing Assets in per cent

Source: NABARD Annual Reports

The diagram above shows the region-wise non-performing assets in percentage and it can be seenthat in North-Eastern region the percentage is high but better than that of Northern region in the year20015-16, and that of Central region in the year 2014-15. The all India average is 7.4% in the year2014-15 and 6.45% in the year 2015-16. The NPA level in the Southern region is very less as comparedto other regions in spite of having highest number of SHGs, highest loan amount disbursed to SHGs,and highest loan amount outstanding.

ConclusionOn September 16, 2015, Reserve Bank of India awarded the “In-principle approval” to set up Small

Finance Bank (SFB) to 10 Financial Institutions, including RGVN (North East) Micro Finance Limited.The main objective behind setting up small finance bank by RBI was to drive the objective of financialinclusion by making provision of savings and to provide credit to small business units, small and marginalfarmers, micro and small industries and other unorganized sector entities, through high-end technology,low cost operations. The NER is blessed with enormous natural resources including oil, natural gas,abundant reserves of minerals, forest resources such as bamboo and other medicinal plants. The regionhas favourable climatic conditions for tea and rubber plantations and holds immense potential for business


opportunities involving usage of natural resources. The central and state governments have providedfor attractive incentives and subsidies on power, transportation, land and capital investment fororganisations setting up business in the NER. Incentives are proposed for thrust sectors and exportoriented industries such as food processing. All the NER states have high literacy rates, with an averageliteracy rate of 68 per cent, which is higher than the national average. English, the most accepted languageof business, is widely spoken in the NER. But majority take up the general studies in college degreesand very few of the young generation go for professional studies outside the region. There may bemany reasons for this environment among students of the region. Encouragement to students, carrierguidance, more and easy scholarships, setting up of more professional institutes and other facilities areutmost urgency to enhance entrepreneurship in the region. Transport linkages are undergoing a faceliftin the region with substantial investments coming in from government and IFIs for the development ofroads, railways, airways and waterways. This, coupled with the proposed EPZs coming up in somestates, would enhance the logistics infrastructure available in the region. Significant infrastructure isbeing developed in Assam, Manipur, Meghalaya, Nagaland and Tripura, including STPs, EPIPs, IIDCs,EPZs and dedicated industrial growth centres and a food processing park in Assam. Opportunities forinvestment in the industrial and urban sector, particularly under the PPP model, are vast due to itsrecent reforms. Significant infrastructure improvements would catalyse the growth of industries andprovide an ideal business climate for upcoming industries. The geographic location of the NER providesimmense opportunities for international trade with the neighbouring countries of Bangladesh, Myanmar,Bhutan, China and Nepal. Specific initiatives are being undertaken by the government for promotion ofcross – border trade with these countries.

The estimated contribution of Micro, Small and Medium Enterprises (MSME) sector, includingservice segment, to the country’s GDP during 2012-13 as per the Union Minister of MSME was 37.54per cent; while the total employment in the sector is 805.24 lakh; and the share of MSMEs in India’stotal export for the year 2014-15 was 44.70 per cent. Under the PMEGP Programme, which generatesincome and employment, 5851 projects were assisted during the year 2014-15, and the estimatedemployment generated was 40, 915 while the Margin Money Subsidy released and utilized was Rs1,01,900 lakh and Rs 14,474.87 lakh respectively. NABARD is set up as an apex Development Bankwith a mandate for facilitating credit flow for promotion and development of agriculture, small scaleindustries, cottage and village industries, handicrafts and other rural crafts. It also has the mandate tosupport all other allied economic activities in rural areas, promote integrated and sustainable ruraldevelopment and secure prosperity of rural areas. In discharging its role as a facilitator for rural prosperity,NABARD is entrusted with providing refinance to lending institutions in rural areas, bringing about orpromoting institutional development and evaluating, monitoring and inspecting the client banks.NABARD has effectively brought in a number of innovations in the rural credit domains. Some ofthese innovations are: Formation and linkage of SHGs, Farmers Club, Rural Infrastructure DevelopmentFund, Watershed Development, Kisan Credit Card, and District Rural Industries Project. RRBs in Indiaare an integral part of the rural credit structure of the country. The Government of India set up RegionalRural Banks (RRBs) on October 2, 1975. Initially, 5 RRBs were set up on October 2, 1975, which weresponsored by Syndicate Bank, SBI, Punjab National Bank, United Commercial Bank, and United Bankof India. They have been playing a significant role in financing the weaker section of the community inthe rural areas and also in inculcating banking habits among the rural masses.


References1. Bird, B. (1995). “Towards a theory of entrepreneurial competency”, Advances in Entrepreneurship, Firm

Emergence and Growth, Vol. 2, pp. 51-72. Bonnstetter, B.J. (1999),

2. Stuart, R. and Lindsay, P. (1997). “Beyond the frame of management competences: towards a contextuallyembedded framework of managerial competence in organizations”, Journal of European Industrial Training,Vol. 21 No. 1, pp. 26-34.

3. Johnson, S. and Winterton, J. (1999). Management Skills, Skills Task Force Research Paper 3,Department forEducation and Employment, London

4. Man, T., Lau, T. and Chan, K.F. (2002). “The competitiveness of small and medium enterprises. A conceptualisationwith focus on entrepreneurial competencies”, Journal of Business Venturing, Vol. 17 No. 2, pp. 123-42.

5. Dr. Gangadhar Banerjee (2010). Rural Entrepreneurship Development Programme—An impact Assessment”,Bengal Economic Association, 30th Annual Conference (2010) Number.

6. UNIDO (2004). ‘Industrial Cluster and Poverty Reduction: Towards a methodology for Poverty and SocialImpact Assessment of Cluster Development Initiatives’. Vienna.

7. Thangasamy, E. (2014, February). Financial Inclusion in North East India: An Analytical Study. IRACST –International Journal of Commerce, Business and Management (IJCBM), 3(1), 183-185. doi: ISSN: 2319–2828

8. NABARD. (2016). Status of Microfinance in India. Micro Credit Innovation Department, National Bank forAgriculture and Rural Development, Mumbai

9. Annual report (2010). ‘Foundation of MSME Cluster’. New Delhi.

10. Annual reports, MSME, KVIC (2012-13, 2013-14, 2014-15, 2015-16)


Investment Pattern in Coastal Area of Odisha:A Special Reference to Bhubaneswar-CuttackTwin City

Prof. S.K. Baral*

ABSTRACTInvestment is one of the major issues of the middle class families as their small savings of today are to

meet the expenses of tomorrow. This paper examines the investment awareness and pattern in coastal part ofOdisha based on investor’s preferences for different investment opportunities like bank deposits, real estate,small savings, life insurance schemes, gold/silver, commercial deposits, corporate security- bonds, mutualfunds, and equity and preference shares. This paper finds the impact of awareness/knowledge, occupationand income level of the individuals on their investment behavior.

Keywords: Savings, Investment Pattern, Awareness.

IntroductionTime Value of Money (TVM) is a terminology which has been very familiar from a long time and

motivates investors to mobilize their saving. Since value of currency today is more precious than that oftomorrow hence, every individual prefers to maintain the value of currency today with the help of investmentin different saving destinations with the help of investment management. Investment management is theprofessional asset management of various securities (shares, bonds and other securities) and other assets(e.g., real estate) in order to meet specified investment goals for the benefit of the investors.

Investors risk taking ability also influences their investment Portfolio. An individual, who is riskaverse, will always prefer to invest in less risky or risk free assets despite of receiving less return.Moreover, an investor who needs to earn more return instead of keeping the savings idle, he may usehis saving in more risky assets in order to get more return on it. Apart from risk averseness, investorsalso consider various factors which affects investors’ portfolio such as annual income, governmentpolicy, natural calamities, economical changes etc.

Review of LiteratureAn empirical study of “Indian Individual Investors Behavior” by Syed Tabassum Sultana (2010),

was an attempt to know the profile of the investors and also to know their characteristics so as to know

* Professor & Head, Department of Commerce, Indira Gandhi National Tribal University, Amarkantak, Madhya Pradesh,Email id: [email protected]

91Investment Pattern in Coastal Area of Odisha: A Special Reference to...

their preference with respect to their investments. The study also tried to unravel the influence ofdemographic factors like gender and age on risk tolerance level of the investors.

Bhardwaj Rajesh, Raheja Rekh and Priyanka (2011), propounded in their study that savingand investment pattern of salaried class school teachers of govt. and private schools has dependedupon income and they both get salary but the scale of the salaries are different and saving patternsthat’s why is so different. Govt. teachers prefer to invest the money for emergency purposes andprivate teacher’s emphasis on children marriage and education.

Dr. S. Mathivannan and Dr. M. Selvakumar (2011), examined the saving and investmentpatterns of salaried teachers of Sivakasi Taluk, Tamilnadu and they found that there is great importanceof money and money’s worth for them and they are regularly preparing budgets for expenditures andcompare it with the actual expenditure and take necessary actions if there are.

.Dr. Dhiraj Jain and Parul Jain (2012), concluded that the majority of the teachers the moneyplays a big role and they initiated to prepare budgets and future forecasting for income and expenditureand there is comparison between future and Standard budgets to find out the deviations to meetcertain money constraints It has been evident from the study that most of the school teachers aresaving their money for the purpose of their children’s education, marriage and as security afterretirement.

Dr. Ananthapadhmanabha Achar (2012), studied “Saving and Investment Behavior of Teachers- An empirical study”. In the analysis individual characteristics of teachers such as age, gender, maritalstatus, and lifestyle determined the savings and investment behavior of teaching community in thestudy region. They considered monthly family income, stage of family life cycle, and upbringingstatus emerged as determinants of their savings and investment behavior.

Dr. Varsha Virani (2012), propounded in her study that In spite of low income the teachers havebeen saving for future needs. The major impact on savings is due to the level of income of the schoolteachers. The research shows that majority of the respondents are saving money as Bank deposits forthe safety of an unpredictable future. The main avenues of investment are Bank deposits and themain purpose of investment is for children education, marriage, and security after retirement.

After critical review, it can be analyzed that money earned by individual carries many dimensionfor investment point of view. It includes not only behavioral aspect of individual but also the opportunitiesavailable for savings, saving instruments, etc.

Objectives of the StudyPrimary objective of study is to find out trend of saving/investment culture in Coastal Odisha with

specific region of Bhubaneswar-Cuttack twin city district. Study basically follows following objectives.1. To study the saving patterns of the individuals in Bhubaneswar-Cuttack twin city district.2. To analyze the investment preferences of the individuals of the region.3. To study the relationship between saving pattern and investment preferences based on variables

like social, economic, educational and occupational background of the individuals.


MethodologyStudy is based on primary data only. The research is analytical and tool used for data collection is

structured questionnaire. Sample size is of population is 30. Interview of respondents have been doneon 1 to 5 scales. Duration of study was October 2018 to December 2018.

Limitations of Study

1. Some people have refused to share the information regarding investment amount, which theythought was personal.

2. The sample size may not represent the entire population of Coastal Odisha to draw a uniformconclusion.

Investment InstrumentsThe following investment instruments (used in Questionnaire) are being selected for taking into

consideration.Equity: Equity is one of the most risky areas. But, at the same time this is also a place where an

investor can earn high rates of returns that will push up the returns of the entire portfolio. There is aneed for the investor to separate the speculation from the investment. Investment in equities can bemade directly by the purchase of shares from the market or it can be done through the mutual fundroute, whereby the investor buys the mutual funds.

Mutual Funds: This is an emerging area for investment and there is a large variety of schemes inthe market to suit the requirements of a large number of people. In finance, in general, you can think ofequity as ownership in any asset after all debts associated with that asset are paid off.

Corporate Debenture: Corporate debentures are normally backed by the reputation and generalcreditworthiness of the issuing company. It is a type of debt instrument that is not covered by the security ofphysical assets or collateral. Debentures are a method of raising credit for the company and although themoney thus raised is considered a part of the company’s capital structure, it is not part of the share capital.

Fixed Deposits: Fixed Deposits with Banks are also referred to as term deposits. Minimuminvestment period for bank FDs is 30 days. Deposits in banks are very safe because of the regulationsof RBI and the guarantee provided by the deposit insurance corporation. The interest rate on fixeddeposits varies with term of the deposits Bank deposits enjoy exceptionally high liquidity. Loans canraise against bank deposits.

Post Office Savings: Post Office Monthly Income Scheme is a low risk saving instrument, whichcan be availed through any Post Office The interest rate on deposits is slightly higher than banks. Theinterest is calculated half yearly and paid yearly.

Life Insurance Policies: Insurance companies offer many investment schemes to investors. Theseschemes promote saving and additionally provide insurance cover. L1C is the largest life insurance companyin India. Insurance policies, while catering to the risk compensation to be faced in the future by investor,also have the advantage of earning a reasonable interest on their investment insurance premiums.

Gold/Silver: Investing in gold offers many benefits and one is that this is an asset that protectssavings from risks such as currency devaluation. In contrast to paper assets, there is no counterparty


risk when investing in silver or gold. Investors who opt for precious metals are protected against monetaryrisks, including money printing, huge debts, and other actions of governments that result in financialcrisis and deflation.

Real Estate: Investment in real estate also made when the expected returns are very attractive.Buying property is an equally strenuous investment decisions. Real estate investment is often linkedwith the future development plans of the location. At present investment in real assets is booming thereare various investment source are available for investment which are directly or indirectly investingreal estate. In addition to this, the more affluent investors are likely to be interested in other type of realestate, like commercial property, agricultural land, semi urban land, and resorts. The bullion offersinvestment opportunity in the form of gold, silver, art objects (paintings,antiques), precious stones andother metals (precious objects), specific categories of metals are traded in the metal exchange.

AnalysisFollowing table analyses the response of investors on behalf of the interview conducted with the

help of questionnaire.

Weighted Ranking of Preference of Investors (Occupation wise)

Sl. No Type of Investments % Occupation wise Classification

1 Bank Savings 100% Government Employees, Professional, Agriculture, Private Employees, Others

2 Insurance Policies 34% Government and Private Employees

3 Fixed Deposits 27% Private Employees, Professional

4 Real Estate 10% Professional, Agriculturist

5 Gold/Silver 7% Professional

6 Shares/Mutual Funds 3% Private and government employees


Source: Primary Data

According to the survey, 30 different occupation class people have been selected, out of them, 5persons have been selected from each class like government employees, working professional, businesspersons, agriculturist, private employee and further 5 have been selected from category of labor classworkers. As per table, preference of investment options has been specified according to occupation.

As per investors’ point of view, they have given first preferences of their investment to savingsaccount in banks/PO (100%) however; second preference has been given to insurance policies (34%).Reasons of saving in insurance policies happened mainly because of tax benefits and future safety.Moreover, real estate has been a lucrative choice for agriculturist as it belongs to their occupation,hence almost all agriculturist prefer to purchase land. It is also found that very less number of people(3%) are having their investment in share market/mutual fund.

In order to analyze the relationship between annual income and the annual savings, it is found thatout the total respondents 6 having annual income of less than 1 lakh per annum, 15 having 1-5 lakh, 5respondents having annual income of 5-10 lakh and only one respondent is having annual income ofmore than 10 lakh.

FindingsI. Majority of respondents mentioned their investing response in fixed deposits and Savings in

banks because;• The fixed deposits in reputed banks and financial institutions regulated by RBI (Reserve Bank

of India) are very secure and considered as one of the safest investment methods.• Fixed deposits earn fixed interest rates for their entire tenure, which is usually compounded

quarterly. So, those who want an income on a regular basis can invest into fixed deposits and


use the interest rate as their income. This makes a fixed deposit very popular way of investingmoney for retirees.

• Fixed deposits save tax and give high returns on invested money.

II. Respondents has given me the following reasons for investing in Gold/Silver:• Apart from wearing it to gain admiration and an increase in social status, gold is considered

as a safe investment bet by almost all the respondents.

• Many felt that the best way to pass down wealth to their heirs by investing in gold.Manyfelt that it would act as hedge against a monetary disaster

III. Some responses gathered for opting to invest in life insurance was:

• Amount invested is secured.

• Safe and long term returns.

• The main motive behind investing is to fulfill their personal and financial goals.

IV. Mutual Funds in terms of long-term care there is uncertainty among investors, but they remaina bit of a mystery to many. Although such products can help individuals to achieve their financialgoals, lack of knowledge about these products may impact their ability to achieve these goalslater on.

V. Shares: Very less have the knowledge about Share/Stock market and its functioning.

After the finding, following are the conclusions mentioned below

• As 100% respondents are having saving accounts in banks, it indicates that people stillbelieve in bank/po saving regardless of the class they belong to.It reveals that people stillhave faith in traditional way of saving. Bank/Post Offices are still a favorite saving destinationnot only for poor section society but also for elite class people.

• Second investment preference is insurance sector where 34% people deposit their money asa saving against any future risk. For tax saving purpose, insurance is a top choice amonggovernment and private employees.

• 10% investors who belong to agriculturist and professional class prefer to choose real estatefor their investment. Since,this sector has been shown a regular trend of high return so ithas become a hot cake to all the people who are having annual income capacity above 5lacs.

• Return from real estate and mutual fund have changed the idea of investing in gold. Studytells that very less number of people (5%) wish to invest in gold despite of its lower trend inprice movement. It has also been found that frequent price changes in price of gold adverselyaffected the opinion of people regarding investment in this segment of investment.

• Only 3% people are having their investment in share market/mutual funds. During study ithas been found that either the people are not much aware about share/mutual fund or they arescared about possible hazardous loss in stock market.


References1. Bandgar, P.K. (1999), “A Study of Middle Class Investors’ Preferences for Financial Instruments in Greater

Bombay”, Finance India, Vol XIV, No.2, June, 2000, Pp. 574-576.

2. Ch. Kirshnudu, B. Krishna reddy and G. Rama Krishna reddy (2005), “Investment behavior and risk management”.

3. Darshana. P (2008) “A Study on Retail Investor’s Preference towards Various Investment Avenues”.

4. Dr. Mathivannan. S& Dr. M. Selvakumar (2011), Indian Journal of Finance-”Savings and Investment Patternof School Teachers – A Study with Reference to Sivakasi Taluk, Tamil Nadu”, Vol 5, No 4, April 2011, Pp.12-26.

5. Dutta, Abhijit (2000), “Investors Reaction to Good and Bad News in Secondary Market: A Study Relating toInvestor’s Behavior”, Finance India, Vol. XV, No.2, June 2001, Pp. 567-576.

6. Gupta, L.C. (1987), “Shareholders Survey-Geographic Distribution”, ICICI and SCMRD, New Delhi.

7. Indian Household Investors 2005. The Changing Market Environment Investors. Preferences Problems PolicyIssues, Society for Capital Market Research & Development Delhi.

8. Jawahar Lal (1995), “Personal Investing”, Wheeler Publishing, New Delhi.

9. Kaboor.A (2010), “Determinants of investor’s financial literacy”.

10. Kasilingam, R&G. Jayabal (2009), southern economist- “Alternative Investment Option to Small Investors”,Vol 48, No 9, September 1, 2009, Pp. 18-20.

11. Manish Sitlani, Geeta Sharma & Bhoomi Sitlani (2011), The IUP Journal of Behavioral Finance-”Investmentchoice of occupants of financial services industry”, Vol 8, No 1, 2011, Pp. 29-39.

12. Maruthupandian. P (2001), “A Study On Equity Investor’s Awareness” unpublished thesis, Bharathiyar University,Tamilnadu.

13. Mudra-Samir’s (1992), survey on “Working women’s awareness and attitude toward various saving avenues”Economic Times, 2 September.

14. Narayana, D. L. (1976), “Income, Saving and Investment of Household Sector in Chittor District”, S. Chand& Co. Ltd., New Delhi, Pp. 1-187.

15. Rajarajan, V. (2003), “Investors Demographics and Risk Bearing Capacity”, Finance India, Vol. XVII, No.2,June, Pp.565-576.

16. Selvatharangini. P.S (2009), “Post Office Savings Schemes in the Maze of Investment Alternatives”.

17. Sridhar. R (2008). “Investment Practices of Investors in Equity Market”.

18. Sunatankhurana (2008), The ICFAI University Journal of Services Marketing-”Customer Preference in LifeInsurance Industry in India”, Vol 4, No 3, Pp. 60-68.

19. Vikram.S (2008), “Investor perception and preferences towards stock market investments”.

97

Opportunities and Challenges in DevelopingInland Waterways Transport in India

Dr. Pradeepta Kumar Samanta*

ABSTRACTInland Waterways Transport (IWT) is a critical mode of transport in any economy mainly due to its

three distinctive features: cost effectiveness, high fuel efficiency and environment friendly. While such distinctadvantages of IWT over other dominant modes of transport, such as rail and road, are well recognized worldover, developing the IWT to its potential has remained an elusive goal for policy makers in India. India’senormous coastal shipping potential continues to be underutilized compared to most of the emerging anddeveloped countries. Some of the prominent reasons for the low penetration of IWTs in India are: high operatingcosts, longer time to transport goods, uncertainty about availability of return cargo, deforestation in catchmentareas, siltation of rivers, lack of awareness on its benefits and inadequate policy support. Furthermore,environmentalists have been opposing development of IWTs citing insufficient water flow in rivers due tosmall & large dams, and frequent occurrence of extreme climate change events (such as drought, flood, rivererosion etc.) might disrupt the IWTs. On the positive side, the National Waterways Act, 2016 provides light atthe end of the tunnel for development of IWTs in India. Against this backdrop, this paper makes an attempt tocritically examine the underlying opportunities and challenges of developing IWTs in India and the evolvingpolicy response.

IntroductionAn efficient transport sector is vital for development of the economy of any country. In a large

country like India, efficient transportation becomes pivotal to stimulate competitive business environment.Indian transport system comprises various modes, viz; Railways, Roadways, Inland Waterways, CoastalShipping and Airways. Globally, Inland Water Transport (IWT) has been recognized as a fuel efficient,environment friendly and cost effective mode of transport having potential to supplement the overburdened rail and congested road transport system (Ref. Table 1 & 2). India has nearly 14,500 km ofnavigable waterways, of which, about 5,200 km of river and 4,000 km of canals. The logistical costs inIndia are around 18 per cent, much higher than that of other countries; 8 – 10 per cent in China, 10-12per cent in EU (Assocham Resurgent India Study 2016). Despite these advantages India’s coastal shippingpotential continues to be underutilized compared to most of the emerging and developed countries.

* Sr. Associate Professor in Finance, School of General Management (SoGM), National Institute of Construction Management andResearch (NICMAR), Pune. Email: [email protected]


IWT sector currently has a meager modal share of 0.5 per cent in India compared to 42 per cent inNetherlands, 8.7 per cent in China and over 8 per cent in USA.

Water-based transport is especially effective when the source and destination are waterfront locations.The sea ports are gateways for exports and imports of bulk cargo. The evacuation of the imported cargogenerally takes place by road and rail as many of the sea ports may not have waterway connectivity to itshinterland. In case the sea port has waterway connectivity to its hinterland, the best and economical way ofevacuation of traffic is by IWT mode using barges. Similarly, the inbound traffic to the port, i.e., exportoriented cargo can also reach the sea port from its hinterland by barges using waterway mode (Table 3).

Table-1: Advantages of IWT vis-à-vis Rail and Road Transport

Parameters IWT Rail Road

1 HP can move how much cargo (kg.) 4,000 500 150

1 litre of fuel can move how much freight (tkm) 105 85 24

Operating cost (Rs / tkm) 1.1 1.4 2.6

Source: IWAI

Table 2: Inter Modal Comparative Operating Costs Rs / TKM

Mode VOC/Freight (Rs/TKM) Taxes Total Rs/TKm

Railways * 1.36 3.71% 1.41

Highways** 2.50 3.09% 2.58

IWT 1.06 NIL 1.06

Source: Railways- Ministry of Railways, Road- TTSS, IWT – IWAI* Service Tax on rail transport is 12.36% abatement is 70%.** Service Tax on Road transport is 12.36% abatement is 75%.

Table-3: Port Connectivity to National Waterways

National Waterway Connected Sea Port

NW-1 Kolkata Port and Haldia Port

NW-2 Kolkata and Haldia Ports through Protocol route viz., Sunderbans

NW-3 Kochi port

NW-4 Kakinada port, Ennore port, Chennai port

NW-5 Paradip Port & Dhamra Port

NW-6 Kolkata and Haldia Ports through protocol route viz., Sunderbans

Source: IWAI

Literature ReviewSriraman (2010) discussed the various issues involved in the IWT sector and the need of proactive

role of the Government in promoting the sector. There is a need to increase amount of public sector

99

resources allocated to inland water transport sector to reflect the relative importance of this sector.Further, the study has also suggested encouraging partnership between public and private sectors toimprove the overall development, management and operation of inland water transport sector. Anintegrated approach instead of segmented approach, focusing on multi-modal transport system can be asustainable model for improved productivity and efficient utilization of IWT sector. Duan, et.al. (2010)described the important role played by IWT in China’s economic development. The authors observedthat, although inland water transportation developed steadily, it is still uncoordinated with thedevelopment of market economy in some respects. In comparison to the developed countries, China’sinland water transportation resources and its advantages have not yet been fully developed and exploited.The paper comprehensively analyses the development status of China’s inland water transportation, thepresent problems in shipping capacity, ship type, competition, management, technical equipment andsecurity system etc. and suggests measures to improve the IWT system.

Rangaraj and Raghuram (2007) studied the viability of inland water transport in India. The authorshave thoroughly discussed the issues related to IWT such as passenger movement, cargo movement,technological and physical viability, commercial potential, operational viability, environmental issues,and policy issues etc. The study suggests policy recommendations and emphasized the pivotal role ofgovernment policy instruments and institutions in making the sector viable. Rohcs and Simongti(2007) discussed the role of inland waterway navigation in a sustainable transport system. The paperconcludes that inland waterway navigation is still a very environment-friendly, safe, and effectivetransportation mode as it was known for a long time. For sustainable transport development, the necessityof modal shift is inevitable and if IW can achieve a larger share from the modal split, it could greatlycontribute to a more sustainable transport system. Therefore action should be taken to increase its sharein the total transport market.

Sarkar, et.al. (2007) in their study highlighted the financial and economic benefits of investmentsfrom IWT sector in India with reference to NW1 (Ganga-Bhagirathi-Hoogly river system) and NW2(Brahmaputra river system). The authors have quantified the economic benefits in terms of saving inoperating costs, accident cost, Government expenditure, and employment generation. Further, the studyalso discusses the other socio-economic benefits such as boost for tourism sector, least environmentaleffects, improved standard of living, better port-hinterland connectivity, opening of land-locked backwardareas, limited land acquisitions and re-settlements etc.

Awal (2005) studied on the safety aspects of IWT sector in Bangladesh. The study was conductedand analyzed the data of water transport accidents during 1995-2005. A total of 197 cases were consideredfor the study which primarily included accidents of passenger and cargo vessels. The authors haveobserved that the number of accidents in the sector increased significantly over the years and mostpredominant causes of accidents were found to be overloading, cyclone and collision. Finally, the authorshave suggested measures to reduce the number of accidents which will lead to saving human life andpotential economic losses.

Against this, the present study makes an attempt to analyze the present status of the IWT in Indiaand the way forward.


National Waterways in IndiaSince Independence many expert committees studied the Inland Water Transport area and advocated

systematic development of the mode. The National Transport Policy Committee (1980) recommendedthe following principles for declaration of a national waterway.

• It should possess capability of navigation by mechanically propelled vessels of a reasonablesize.

• It should have about 45m wide channel and minimum 1.5m depth.• It should be a continuous stretch of 50 km. The only exception to be made to waterway

length is for urban conglomerations and intra-port traffic.• It should pass through and serve the interest of more than one State (or).• It should connect a vast and prosperous hinterland and Major Ports (or).• It should pass through a strategic region where development of navigation is considered

necessary to provide logistic support for national security (or).• It should connect places not served by any other modes of transport.

As per the recommendations of the National Transport Policy Committee, the Inland WaterwaysAuthority of India (IWAI) was established in 1986 for development, maintenance and regulation ofnational waterways for shipping and navigation in the country. Table 4 depicts the details of Nationalwaterways.

Table-4: National Waterways (NWs)

National Waterways

Distance (km.) Name of the NW Region States

NW-1 1620 Ganga Haldia to Allahabad UP, Bihar, Jharkhand, West Bengal

NW-2 891 Brahmaputra Dhubri to Sadiya Assam, West Bengal, Arunachal Pradesh, Meghalaya

NW-3 205 West Coast Canal Kollam to Kottapuram Kerala

NW-4 1078 Godavari, Krishna and Canals Kakinada to Puducherry Andhra Pradesh, Tamil Nadu, Puducherry (UT)

NW-5 588 Brahmani, Delta Canals, East Coast Canal Goenkhali to Talcher Odisha, West Bengal

NW-6 121 Barak river Lakhipur and Bhanga Assam, Mizoram, Manipur, Tripura

Source: Ministry of Road Transport and Highways (MoRTH)

The Composition of cargo movement on national waterways during 2010-11 to 2014-15 is given inTable 5.

101Table-5: Composition of Cargo Moved on NW-1, NW-2 & NW-3 (in lakh tonnes)

Commodity 2010-11 2011-12 2012-13 2013-14 2014-15

Building material 14.9 15.3 17.3 20.0 20.5

Chemicals 1.0 0.6 0.9 1.2 1.0

Fertilizers 3.4 3.1 3.6 3.0 3.6

Food items 1.5 1.5 4.9 4.1 5.3

Miscellaneous 22.1 24.3 24.4 24.9 25.1

Mix 0.9 21.5 5.6 6.1 5.8

Ore / Minerals 0.6 0.1 3.0 1.4 2.4

POL / POL Products 4.9 4.2 3.4 2.4 2.5

Coal - 0.0 0.8 5.6 17.4

Iron & Steel - - - 0.1 0.3

Total 49.3 70.6 63.8 68.9 83.9


International ExperienceThere are more than fifty countries around the world which have navigable waterways networks of

more than 1,000 kilometers. On most of these waterways, the inland shipping sector is underdeveloped.It experiences many barriers and obstacles not only of technical and technological nature, theysometimes seriously limit smooth access of inland shipping to the transport system and reduceautomatically its potential role in the domestic and international trade. China, USA and EuropeanUnion have the large network of inland waterways. China is having the largest inland waterwaytransport network in the world with more than 110,000 navigable kilometers. In Europe, the biggestfive ports are all connected to inland waterways. The share of IWT in the inland waterwaystransportation is 47 per cent of the total transport in China. In the European Union it is 44 per cent,Korea 43 per cent, Japan 44 per cent and in Bangladesh, it is about 35 per cent (ADB Report). InIndia, however, it is a paltry 3 per cent. The number of vessels carrying cargo that ply on inlandwaterway systems in China and the EU are 2,00,000 and 11,000, respectively, while there are lessthan 1,000 vessels estimated to be using the Indian inland waterway systems. The depth of riversystem to support large vessel fleets is less than 1,500 tonnage as compared to 40,000 tonnes ofcargo in a single voyage in Chine and EU. For those countries which have vast network of inlandwaterways, their realized benefits ranges from reduced congestion in rail and road transport modesto employment generation and lower carbon footprint.

The IWT can supplement as a viable and sustainable alternative mode of transport to the existingoverburdened road and rail network which contributes about 66 per cent and 27 per cent respectivelyin the freight transport segment. The state-wise potential available to develop the IWTs is given inTable-6.


Table-6: Total and Navigable Length of Waterways in Different States (2014-15)

State Total Length of Rivers / Canals / Lakes (km.)

Navigable Length (km.)

Share of Navigable Length to Total Length (%)

Andhra Pradesh 3,579 804 23

Assam 5,290 1,682 32

Bihar 2,229 1,391 62

Goa 273 248 91

Gujarat 653 102 16

Karnataka 2,862 1,215 43

Kerala 2,779 845 30

Maharashtra 631 462 73

Orissa 1,378 508 37

Nagaland 937 375 40

Mizoram 238 81 34

Tamil Nadu 27 12 44

Uttar Pradesh 2,345 425 18

West Bengal 4,741 4,593 97


Major benefits of Developing Inland Waterways:

• It’s a non-water consumptive transportation project with minimal resource depletion.• It will facilitate reduction of pressure on Railway network and Road Network, relieving

congestion, reduced emissions from vehicles and railway engines on non-electrified routes,thereby reducing carbon emission.

• Use of modern inland water vessels, with natural gas as fuel will reduce emission of SulphurOxide (Sox), Nitrous Oxide (NOx) (70%), particulate matter (95%) and Carbon dioxide (CO2)(25%). Hence will have negligible impact on ambient air quality.

• LNG/CNG engines have lower noise level than diesel engines, hence less impact on ambientnoise level.

• Transportation through waterways does not involve huge land acquisition except in few placeswhere terminals are likely to be constructed. In comparison to other infrastructure projects, itis almost negligible. Due to minimum requirement of land acquisition, there will be insignificantimpact on ecology & biodiversity, agricultural activities as well as on the livelihood of thepeople.

• Improved river flow due to improvement / augmentation of navigation facilities will in turnbenefit aquatic flora and fauna.

• Increase in economic opportunities in the form of employment and business opportunities(both in relation to cargo movement and peripheral petty business activities).

103

• Access to local communities in the form of a mode of transport to conduct activities on bothsides of the river.

• Better water flow through maintenance of minimum water levels will provide for better fishproduction and catch, which in turn will directly enable enhanced income for the fishingcommunities along the river stretch.

• The cost of transportation of goods across waterways will be considerably lower compared torail and road transportation.

• Burden on road and rail transportation will come down resulting in less fuel consumption andconsequent environmental pollution.

• Improved access to trading centers and ancillary infrastructure (cargo handling, etc.) alongthe rivers and navigation will benefit local, regional and international business.

• Tourist spots along the rivers will attract considerable number of tourists.• IWT is best for bulk cargo and over dimensional cargo.• Fairway development does not need land acquisition• Lesser per ton per kilometer rate than Railways and Roadways

Recent Policy Initiatives taken by the Central Government

• The National Waterways Act, 2016 which has been enacted since 2017, has declared 106waterways in 24 states as national waterways. The Enactment of such an Act paved the wayfor the Central Government to undertake development of inland waterways. Currently thereare 111 national waterways in the country out of which 12 are already operational /navigableand are being used for transportation.

• In the Budget Speech of Union Finance Minister in 2014-15, it was announced to undertakedevelopment of NW-1 under the aegis of the “Jal Marg Vikas” project with technical andfinancial support from the World Bank at an estimated cost of Rs 4,200 crore to be completedin six years. This project aims for capacity augmentation of NW-1 to enable commercialnavigation by at least 1,500 ton vessels.

• The Central Government has also announced some incentives for carriage of some portion ofcargo by coastal shipping and inland waterways instead of by rail and road with a view tomake waterways an integral part of the country’s logistics chain. The scheme proposes toprovide monetary incentives to beneficiaries when they transport certain identified commodities,containerized cargo or automobiles, on Indian flag vessels, on trips having either a major port(owned by the Central Government), a designated non-major port (owned by the StateGovernment) or a terminal/jetty owned by the Inland Waterways Authority of India (IWAI) asthe point of loading or discharge. It entails compensating the costs incurred in availing thefirst-mile and last-mile connectivity for goods that have the potential to be moved by waterways.

• To ensure pollution level in the river under control due to IWT, the Central Government hasdecided to set up a River Traffic Control System on the lines of Air Traffic Control system.


• The draft National Perspective Plan (NPP), prepared under the Sagarmala Programme, hasrecommended priority development of National Waterways-1, 2, 4 & 5 to enhance portconnectivity to the hinterland. This in turn would enable faster and cheaper movement of keycargo types such as coal, iron ore, food grains etc.

OpportunitiesIndia has 7,551 kilometer coastline and about 14,500 kilometer of navigable inland waterways.

This huge potential has by and large has remained unexploited despite the universal acceptance of thefact that waterways transportation is fuel efficient, environment friendly and more economical ascompared to rail and road. At present, the share of IWT is abysmally low of the total goods transportedwithin the country through various modes such as rail, road and water as compared to other nationsblessed with such a vast river network.

The government has announced some ambitious projects for developing the inland waterways whichincludes developing 2,000 water ports and Roll-on-Roll-off (Ro Ro) services which will be available atfive select places to transport goods and vehicles, across the country. Under this scheme, Varanasi,Haldia and Sahibganj will be developed as multimodal hubs with linkages to roadways, waterways andrailways. The Varanasi terminal was recently inaugurated by the Prime Minister of India. Similarly, thegovernment has also launched several schemes under the ‘Make in India’ initiative with a view topromote IWT such as, vessel building subsidy in which the Government provides financial assistanceof up to 20 per cent for ships build in the country. Equity participation by Govt. in BOT Projects up to40 per cent, Viability Gap Funding, Tax exemption similar to National Highways, Enhancement indepreciation rate for inland vessels, Joint Venture by IWAI, and Customs Duty concessions.

The Government has introduced a new Central Sector Scheme for the development of Inland WaterTransport in North Eastern States including Sikkim. The objective of the scheme is to encourage theState Government of North Eastern States namely – Arunachal Pradesh, Assam, Manipur, Meghalaya,Mizoram, Nagaland, Sikkim, Tripura for taking up various projects for development of Inland WaterTransport in North Eastern Region. 100% Grant will be provided by the Central Government for allprojects sanctioned under this scheme

Further, the government has identified some areas for development under PPP mode in IWT sector.They are: Construction and operation of river terminals or river ports, Ownership and operation ofvessels for cargo and passengers, Provision and operation of mechanized cargo handling systems, Fairwaydevelopment and maintenance, Putting up and maintenance of navigational aids, Provision of Pilotageservices, Setting up and running of IWT training institutions etc. To develop the national waterways,the IWAI would require about Rs 35,000 crore in the next two-three years. While part of these fundingis expected to be through market borrowings, the IWAI is also expected to tap multilateral agencies andcreate consortium in consultation with International Finance Corporation to fund the upcoming inlandwaterways. The Central Government has allocated a sum of Rs 891.13 crore in 2018-19 budget and Rs757 crore in 2019-20 budgets.

Challenges

Some of the major challenges for the low penetration of IWTs so far in India are:• Maintaining required depth and flow of water level in the river is a major prerequisite of

success of IWT. This requires dredging of the river bed and periodic maintenance of river

105

banks. According to IWAI, a minimum, consistent yearlong water depth (water draft) of 2.5 mto 3.0 m has to be maintained along the national waterways to ensure uninterrupted transport.

• Perception of IWT investment as high-risk investment.• Lack of convergence between IWT and other modes of transport• Emphasis on development of rail and road networks.• High cost of development of ancillary facilities.• Lack of proper coordination and support among the different central and state agencies in

regulation, operation and sustenance of IWT.• It takes relatively longer time to transport goods,• Uncertainty about availability of return cargo leading to high operating costs,• Lack of awareness on its benefits and inadequate policy support.• Deforestation in catchment areas resulting in siltation of rivers,• Gradual deterioration of waterways due to inadequate river conservancy measures• Diversion of water for irrigation industrial and other needs reduces the flow in the rivers

resulting in the reduction of depth.• Inadequate vertical and horizontal clearances for plying vessels of economic size in many

traditional waterway routes.• Construction of cross structures such as bridges etc. creates obstacles for movement of vessels.• Lack of investment intervention through PPP in IWT as compared to investment in road

networks.

ConclusionsIWT is globally recognized as operationally cheaper, fuel efficient and environmentally friendly

mode of transportation. India has large number of inland waterways comprising of rivers, canals,backwaters, creeks and lakes etc, which have the potential for development of efficient waterwaystransport network. IWT needs to be actively promoted for a reasonable share in the inter-modal mix ofinland transport. Again, a developed IWT sector will open up other opportunities for private investmentsuch as ship building, terminal construction etc. Large scale private participation should be encouragedthrough PPP mode for creation of infrastructure and fleet operation. In this context, the CentralGovernment has already asserted its preference for the public-private-partnership (PPP) model to developseveral national waterways in the country. Alike the other infrastructure sectors involving PPP model,the terms & conditions set out in the model concession agreement will hold key to effectively developnational waterways on PPP model. Initially, of course, it will be a challenge to draw private investmentinto the IWT sector in India which has largely remained an uncharted territory for such type of investment.Nevertheless, the necessary infrastructure such as fairway, terminals, channel markings, night navigationalaids, including the possible deployment of GPS and river maps and charts for navigation etc. should befacilitated ensuring a wider coverage of national waterways to make IWT sector more competitive andattractive.


References1. Awal, Z.I. (2005) A Study on Inland Water Transport Accidents in Bangladesh: Experience of A Decade

(1995-2005). Conference Paper, Coastal Ships and Inland Waterways, London, UK, pp. 1-6.

2. Awal, Z.I., Islam, M.R., Hoque, M. (2006) Analysis of Passenger Vessel Accidents in the Inland Waterwaysof Bngladesh. Conference Paper, MARTEC.

3. Duan, S. Gongzhi, Y.U., XING, H., and Zhanhua W.U. (2010) Inland Waterway Transport in China: Situationand Problems. ICLEM 2010: Logistics for Sustained Economic Development, ASCE, pp. 379-385.

4. Grzelakowski, A. (2010) Inland Water Transport as a Factor Influencing Mega-Ports and Seaport CitiesDevelopment (from the European North Sea Perspective). Logistics and Transport No 2(11).

5. Planning Commission, (1980) Report of the National Transport Policy Committee. Government of India, NewDelhi.

6. Rangaraj, N. and Raghuram, G (2007) Viability of Inland Water Transport (IWT) in India, India ResidentMission Policy Brief series, Asian Development Bank, pp.1-18.

7. RITES (2013) Preparation of Integrated National Waterways Transportation Grid (Final Report), InlandWaterways Authority of India (IWAI), pp. 1-99.

8. Rohacs, J. and Simongati, G. (2007) The Role of Inland Waterway Navigation in a Sustainable TransportSystem, TRANSPORT, Taylor & Francis, Vol XXII, No 3, 148–153.

9. Sarkar, P.K., Mathur, V., Maitri, V., and Kalra, K. (2007) Study on Potential for Economic Gains from InlandWater Transport in India, with Special Reference to NW 1 (Gnaga) and NW2 (Brahmaputra). TransportResearch Board - Annual Meeting Proceedings, pp.1-19.

10. Sriraman S, (2010) Long Term Perspectives on Inland Water Transport in India, RITES Journal, pp. 18.1-18.14.

11. Sriraman S, (1998) Inland Water Transport in India: Issues and Prospects, Asian Transport Journal, AsianInstitute of Transport Development, New Delhi.

12. Tayal, Praful, (2004) India – 2010 (Inland Water Transport Sector: IWT) - A Vision, Central Inland WaterTransport Corporation Ltd, Kolkata.

13. http://www.iwai.nic.in/

ANNEXURE

Recent Developments in IWT

• The Government in November, 2016 extended the policy for reimbursement of freight for movement of phosphaticand potassic (P&K) fertilizers under the Nutrient Based Subsidy (NBS) and for movement of Urea by coastalshipping and Inland Water Transportation.

• The subsidy that was earlier only applicable to the movement of fertilizers by rail from the plant or the port tovarious rake points in various districts, will now also apply to the movement of fertilizers through coastal shippingand IWT.

• Dalmia Bharat Cement Ltd, on February 5, 2017 transported a consignment of 350 tonnes of cement from Haldiain West Bengal to Patna in Bihar on IWAI vessel MV Zakir Hussain.

• On August 12, 2016, the trial run of two cargo vessels was flagged off from Varanasi on National Waterway -1(NW-1). The first vessel MV VV Giri (300 tons capacity) carried newly assembled cars of Maruti Suzuki IndiaLtd. from Varanasi to Kolkata. The voyage of this vessel was completed in six days. The second vessel, MV JoyBasudev (1400 tons capacity) carried construction material from Varanasi and offloaded it at Gahzipur and Patna.

107

• PepsiCo India has moved 16 containers – equivalent to 16 truckloads filled with food and snacks in the vesselMV RN Tagore in a period of 9-10 days and making a return journey fertilizers belonging to Indian FarmersFertiliser Cooperative (IFFCO) procured from its Phulpur plant near Allahabad.

• IWAI is planning to start the transportation of fertilizers from IFFCO Paradip to various destinations on NW-1by integrating coastal movement with IWT.

• IWAI has started e-connect measures names as ‘Forum of Cargo Owners and Logistics Operators (FOCAL)’ toenable direct interaction among the vessel operators, shippers and cargo owners. It is expected to facilitate responsesfrom the logistics operators against the requirement raised by cargo owners and vice-versa.

• IWAI will be inviting private players for proving their technical qualification and then, they will be given thetask of operation and management (O&M) of the terminals. Keeping the base of the Model Concession Agreementof the Government of India, IWAI will offer the terminals to private players for 30 years on royalty per ton ofcargo on revenue sharing basis.

• Through the World Bank procurement process, IWAI has engaged DST Germany, to design ideal ships for theriver Ganga. DST Germany has come up with 13 classes of ships, ideally suited for the river Ganga whichincludes bulk cargo ships, barge, container ships and car carriers. These require a low draft but have a carryingcapacity ranging from 600 to 2,450 tonnes of cargo.


INCUMBENCY CHART OF OFFICE BEARERSOrissa Commerce Association (OCA) started in 1970 in G. M. College Sambalpur, which was thefirst College to have B. Com. as an under Graduate course in Orissa. The pioneering foundingmembers of OCA are:

1. Prof. Paresh Chandra Ray2. Prof. Suryakanta Das3. Prof. Batakrushna Mohanty4. Prof. Durga Prasad Nayak

Sl. No Year Venue President Secretary

Managing Editor of Orissa Journal of

Commerce

1. 1970 G.M. College, Sambalpur Sri Harihar Patel, Ministry of Industires, Govt. of Orissa * *

2. 1971 Khalikote College, Berhampur Prof. P.C.Ray, Secretary, Board of Secondary Education, Orissa * *

3. 1973 Ravenshaw College, Cuttack Prof. P.C.Ray, Secretary, Board of Secondary Education, Orissa * *

4. 1974 G.M. College, Sambalpur Prof. (Dr) Surya Kant Das Professor of Commerce, Utkal University, Bhubaneswar

Prof. Batakrushna Mohanty, Prof. of Commere, G. M. College, Sambalpur

Dr. Abhaya Kumar, Reader, Department of Commerce, Utkal University

5. 1976 Utkal University, Bhubaneswar Mr. M.P. Modi, I.A.S. Managing Director, IDC

*

*

6. 1977 Bhadrak College, Bhadrak Prof. (Dr) Surya Kant Das Professor of Commerce, Utkal University, Bhubaneswar

*

*

7. 1978 S.C.S. College, Puri Prof. Batakrushna Mohanty, Principal, G.M. College, Sambalpur

*

*

8. 1980 Berhampur University, Bhanja Vihar, Berhampur

Prof. Batakrushna Mohanty, Principal, G.M. College, Sambalpur

*

*

9. 1981 K.S.U.B. College, Bhanjanagar Prof. Ganga Prasad Panda, Principal Lingaraj Law College, Berhampur

*

*

10. 1982 Dhenkanal College, Dhenkanal Shri Durga Prasad Nayak, Principal, Sonepur College, Sonepur.

Dr. Girija Prasad Acharya

Dr. Pramod Ku. Sahu, Berhampur University

11. 1983 Ispast College, Rourkela Prof. Bijay Narayan Pattnaik, Utkal University, Bhubaneswar


*

12. 1985 F.M. College, Balasore Prof. (Dr.) J.J. Rao, Ravenshaw College, Cuttack


*

13. 1986 Ganjam College, Ganjam Prof. (Dr) Ramakanta Jena, Dean, Faculty of Commerce, Utkal University, Bhubaneswar


Dr. Ghanashyam Panda, Berhampur University

14. 1987 L.N.College, Jharsuguda Prof. (Dr) Pramod Ku. Sahu, Professor , Berhampur University, Berhampur * Dr. Ghanashyam Panda,

Berhampur University

15. 1988 Dhenkanal College, Dhenkanal Prof. Sambhu Prasad Mishra, Professor of Commerce, G.M. College, Sambalpur * Dr. Ghanashyam Panda,

Berhampur University

16. 1990 Dept. of Commerce, Berhampur University

Sri S.C. Patro, Head, P.G. Department of Commerce, Khalikote College

Dr. Swaroop Ch. Sahoo

Dr. Gunanidhi Sahoo, Principal, Khalikote, Berhampur

(Contd...)

109

(Contd...)

17. 1994 Bhadrak College, Bhadrak Prof. (Dr) Gunanidhi Sahu, Principal, Khalikote College, Berhampur Dr. Jagannath Panda Dr. Swaroop Ch. Sahoo

18. 1995 S.C.S. College, Puri Prof. (Dr) Girija Prasad Acharya, Professor of Commerce, Ravenshaw College, Cuttack

Dr. Bidhu Bhusan Panigrahi,

Prof. Pramod Ku. Sahu, Berhampur University

19. 1997 Womens’ College, Jharsuguda Shri Ayodhya P. Nayak, BJB College, Bhubaneswar

Dr. Damodar Biswal, S.C.S. College, Puri


20. 1998 Prananath College, Khurda Prof. (Dr.) Pradeep Chandra Tripathy, Professor , Utkal University, Bhubaneswar

Prof. Tahalu Sahoo, Principal Womens College, Jharsugara


21. 1999 Khalikote (Auto) College, Berhampur

Prof. (Dr) R.P. Choudhury, Principal, Khalikote College (Auto), Berhampur

Malay Kumar Mohanty, Ravenshaw College (Auto)


22. 2000 Ispat College, Rourkela Prof. Minaketan Mohapatra Principal, Dehenkanal College

Malay Kumar Mohanty, Ravenshaw College (Auto)


23. 2001 Maharshi College of Natural Law, Bhubaneswar

Prof. (Dr) Damodar. Biswal, Professor, Ravenshaw College (Auto), Cuttack

Malay Kumar Mohanty, Ravenshaw College (Auto), Cuttack


24. 2004 Kendrapara College, Kendrapara Prof. (Dr) Jagannath Panda Professor Berhampur University, Berhampur

Prof. Ranjan Kumar Bal, Utkal University


25. 2005 V.N.College, Jajpur Road Prof. (Dr) Umesh Ch. Pattnaik Professor Berhampur University, Berhampur


Prof. Jagannath Panda, Berhampur University

26. 2006 Rayagada College, Raygada Prof. Tahalu Sahu, Principal Belpahar College, Belpahar



27. 2007 P.G. Department of Commerce Utkal University, Bhubaneswar

Prof (Dr) Samson Moharana Professor Utkal University, Bhubaneswar

Prof. Kishore Ch. Rout, Berhampur University


28. 2008 Fakir Mohan Autonomous College, Balasore

Dr. Arun Kumar Barik, Head, Department of Commerce, Vyasanagar College, Jajpur Road



29. 2009 Govt. Autonomous College, Angul

Maj (Dr.) Abhay Kumar Panda, Principal, Fakir Mohan Autonomous College, Balasore.



30. 2010 Department of Commerce, Ravenshaw University

Shri Baladev Kar, Principal, Govt. College (Auto), Angul

Dr. Kshiti Bhusan Das, Utkal University


31. 2011 P. G. Department of Commerce, Berhampur University

Prof. Malay Kumar Mohanty, Former Registrar, Ravenshaw University, Professor G. M. College, Dean Sambalpur University



32. 2012 P. G. Department of Commerce, Utkal University

Prof. P. K. Biswasray, Professor , Berhampur University



33. 2013 Choudwar College, Choudwar Prof. Prasant Kumar Sahu, Vice- Chancellor, Utkal University

Prof. Kshiti Bhusan Das, Utkal University

Prof. Malay Kumar Mohanty

34. 2014 P. N. (Auto) College, Khurda Prof. Ranjan Kumar Bal, Professor, Utkal University

Prof. Kshiti Bhusan Das, Utkal University


35. 2014-15 Kendrapada (Auto) College Prof. Kshiti Bhusan Das, Professor, Utkal University

Dr. G. K. Panigrahi Prof. Malay Kumar Mohanty

Orissa Journal of Commerce, Volume XXXX, July-September-2019, Issue No. - III


* Information not available: People concerned are requested to provide the above missing information with proper references.If any error has crept in the above incumbency chart inadvertently, persons are requested to intimate the correction with therequired documentation.

36. 2016 Belpahar College, Belpahar Prof. Girish Ku. Patra, Kendrapada (Auto) College


37. 2017 F. M. University, Balasore Prof. Jayanta Kumar Parida, Professor,Utkal University


38. 2018 Ravenshaw University, Cuttack Prof. Bhagaban Das, Professor, F. M. University

Major (Dr) S. A. Taher


39. 2019 P. G. Department of Commerce, Utkal University

Prof. Sanjay Kumar Satapathy, Professor, Ravenshaw University



40. 2019-20 KIIT, Deemed to be University, (Golden Jubilee Year)

Prof. P. K. Hota, Professor, Utkal University



111

Accounting Reform and Ind As Bhagabata Behra 978-81-932322-3-1 2016 `895

Agriculture Economics Manoj Mishra 978-93-86714-14-5 2018 `1195

A Service Marketing View of Customer Delight Shrmistha Sarma 978-93-80752-90-7 2012 `500

Behavioural Finance Principles & Practics Sathya, Debasish, Mallick 978-93-82420-76-7 2015 `950

Capital Structure in Indian Corporate Sector N. Dhal & A.K. Panda 978-93-80752-61-7 2012 `795

Changing Paradigm in Modern Day Management Artta Bandhu Jena 978-93-82420-50-7 2014 `795in Indian Perspective

Compesation Management Practices of Software P. Mahapatra & K.K. Das 978-81-935479-1-5 2018 `495Industry: An Indian Evidence

Consumer Behaviour in FMCG Prospective: Artta Bandhu Jena & 978-81-935461-3-0 2018 `895Evidence From Indian Context* Snehasis Panda

Consumer Retial Store Choice Dynamics: Sangeeta Mohanty & 978-93-80752-60-0 2012 `795An Empirical Analysis A.K. Panda

Consumer Behavoiur in Banking Services A.B. Jena & P. Pati 978-81-933962-5-4 2018 `895An Indian Prospective

Customer Retention Practices in Banking Sector S.K. Mishra & 978-93-86714-88-6 2019 `895An Indian Evidence Kishore Kumar Das

Contemporary Issues and Challenges in Gouri Sankar Lall, 978-93-86714-64-0 2019 `1095Finance and Taxation (Royal Size) V.R. Bhanotu & S.R. Dash

Corporate Disclosure in Developing Countries D.K. Jena 978-81-935479-0-8 2018 `995With Special Reference to India

Mergers and Acquisitions in India A.C. Raul & G. Parhi 978-93-82420-52-1 2014 `1150

Commercial Banks in India: An Appraisal Dey, Panda, Chandra, 978-93-80752-96-9 2012 `895

Comparative Political Economy of Welfare States V.K. Verma 978-93-80752-27-3 2011 `895

Corporate Financing in India: An Indepth Study Sahu, Panda & Das 978-93-80752-97-6 2012 `750

Cost Accounting: Principles and Practices Mallick, Mohanta, Nayak 978-93-82420-72-9 2015 `995

DEBT Finance in Indian Economy: Kishore Kumar Das 978-93-82420-67-5 2014 `1050A Re-Look into the Corporate Sector

Insurance Sector in India: A Way Forword Kishore kumar Das 978-81-932322-1-7 2016 `1150

Displacement & Resuttlement for Deveploment: Alaka Nanda 978-81-933224-9-9 2017 `950A Case Study of Odisha

Econonics of Rural Development in India Manoj Mishra 978-93-86714-16-9 2018 `1195

Insurance Sector in India: A Way Forword Kishore kumar Das 978-81-932322-1-7 2016 `1150

Perception on Stock Market Investment Madhumala Pathy & 978-93-86714-77-0 2018 `895S.K. Sathapathy

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