Relative Importance of the Organisational Factors Capable of ...

( 5 )

INTRODUCTION

Job satisfaction is a complex and multi-dimensional concept and is one of the mostcrucial issues in work and organisational psychology. Although, the concept ofsatisfaction has been researched extensively in the fields of psychology, sociology andbusiness management, satisfaction remains a complex concept because what satisfiesworkers today may not satisfy them tomorrow; and what satisfies them in one placemight not satisfy them elsewhere (Abdulla, 2009). The credit for bringing the term jobsatisfaction into lime light goes to Robert Hoppock (1935), who defined job satisfactionas a combination of psychological, physiological and environmental circumstancesthat causes a person to say, I am satisfied with my job. However, Hoppock’s definitionof job satisfaction only indicates the various factors capable of influencing job satisfactionof employees but tell us nothing about the nature of job satisfaction (Saiyadain, 1988)and the relative importance of the factors determining the job satisfaction of employees.In the context of the study, Job satisfaction can be described as the outcome of anemployee’s judgment of how well his/her job fulfils those aspects/needs which areconsidered important by him or her (Luthans, 2005). Stronger the needs, more closelywill job satisfaction depend on its gratification (Schaffer, 1953).

STATEMENT OF THE PROBLEM

Job satisfaction is considered as a primary dependent variable in terms of whicheffectiveness of an organization’s human resource is evaluated (Mobley, 1979). Jobsatisfaction is one of the most complex areas, facing by today’s managers when itcomes to managing their employees (Aziri, 2011). Job satisfaction is very importantbecause most of the people spend a major portion of their life at their work place andtherefore, it has impact on the general life of the employees also. From the organizationalpoint of view, studying job satisfaction of employees is important because from theexisting literature it is found that the job satisfaction of employees is an important

Key words

Employees, Factor,Importance, Satisfaction

Relative Importance of the Organisational FactorsCapable of Influencing Job Satisfaction of BankEmployees: An Empirical Study

Dinesh Kumar Pandiya, Kingshuk Adhikari and Pinak Deb

ABSTRACT

Job satisfaction is a multi-dimensional phenomenon and it is dependent upon a host of inter-relatedfactors. Employee’s opinions and belief system play a central role in explaining the degree of job satisfactionand is not always guided by rationality. Job satisfaction is often associated with the fulfilment of thoseneeds which are considered important by an employee. The study makes an attempt to analyse therelative importance of the select organisational factors capable of influencing job satisfaction of employeesworking in branches of United Bank of India (UBI) in four districts (Cachar, Karimganj, Hailakandi andDima-Hasao) of South Assam. The study reveals that the factor Pay and Allowances, irrespective ofgender, marital status and category of employment, was perceived as the most important factor influencingjob satisfaction of the bank employees.

The Indian Journal of CommerceVol.69, No. 2, April-June, 2016

( 6 )

determinant in increasing the productivity and efficiencyof an organisation. Therefore, stable and satisfied workforceis one of the pre-condition for the survival and developmentof the organisation in the long run.

The introduction of banking sector reforms coupled withfinancial sector reforms and globalization has practicallychanged the scenario of the Indian banking sector. Theimpact of reforms in the financial sector and moreparticularly in the banking sector along with the entry ofprivate sector banks and foreign banks has practicallymade the environment precarious for which the employeesof public sector banks were not prepared. A fundamentalshift in the work attitude and the work style has beenexperienced in the banking sector due to the intensity ofinter-bank competition and also on account of the adventand adoption of information technology in performingbanking operation. This demands a radical change in thework patterns of the bank employees and downsizing ofthe work force in the sector. The implications of the abovesaid transformations have affected the social, economicaland psychological domains of the bank employees andtheir relations. Whether the banks are public or privatetheir success depends upon its employees but existingliterature states that the bank employees often remaindissatisfied with their job. The moods, preferences andpriorities of bank employees of 21st century are supposedto be different than that of the bank employees in the yester-decades. Against this backdrop, it became necessity toidentify the organizational factors capable of influencingthe job satisfaction of bank employees on the one handand to understand the relative importance of various factorscapable of influencing the job satisfaction of the bankemployees on the other. The employees of United Bank ofIndia (UBI) working in South Assam have been selectedfor the present study. The UBI one of the 14 major bankswhich were nationalized on July 19, 1969 and in SouthAssam (Cachar, Karimganj, Hilakandi and Dima-Hasao),with Fifty-one (51) bank offices, it is the leading bankamong these fourteen banks. Thus, the present study isundertaken to identify the organizational factors capableof influencing the job satisfaction of employees of UBI andto analyse the relative importance of various factors capableof influencing their job satisfaction.

REVIEW OF LITERATURE

Over the years researchers have identified number offactors capable of influencing job satisfaction. Some of thefactors came out from various studies over and over again

whereas some factors varied from study to study. In hisstudy, Hoppock (1935) summarised that the factorsinfluencing job satisfaction are the relative status of theindividual within the social and economic group withwhich he/she identifies himself/herself. He identified sixmajor components of job satisfaction, such as, the way anindividual reacts to unpleasant situations, the facility withwhich he/she adjusts himself to other person, the relativestatus in the social and economic group with which he/she identifies himself/herself, the nature of the work inrelation to abilities, interest and preparation of the worker,security and loyalty (Pestonjee, 1991; Purohit, 2004;Naganna & Ramana, 2007; Dakshinamurthy & Kulkarni,2012). Herzberg et.al (1959) identified two set of factorscontributing to job satisfaction/ dissatisfaction. These areHygiene factors such as salary, relation with superior, co-workers and subordinates, technical supervision,company policy and administration, working condition,job security etc. and Motivators such as advancement andpossibility of growth, achievements, recognition, workitself and responsibility. Robbins (1997) identified five keyelements of job satisfaction- which are nature of the work,pay, promotion opportunities, supervision and relationwith co-workers and Newstrom & Davis (1997) addedimmediate working conditions along with the above fivefactors identified by Robbins.

Lather & Jain (2005) found need for autonomy and selfactualization as significant positive predictors of jobsatisfaction for top level managers. Need for self controland need for monetary gains were found to be thepredictors of job satisfaction of middle level managers.Vigg et.al (2007) revealed social and economical benefit asone of the most important factors that influence the level ofjob satisfaction of bank employees. Rahman et.al (2007)revealed that payment, healthy relationship withcolleagues, sense of personal accomplishment, availabilityof adequate information to do job, ability to implementnew ideas were the most important factors influencing thelevel of job satisfaction of bank employees. Srivastava(2008) revealed that working condition, welfare provision,interpersonal relationship and trust and supportpredominantly contribute to employees’ job behaviour andorganizational effectiveness. Hanif & Yasir (2009)identified eight variables, namely recognition, work effort,self expression, pay, supportive management, promotion,job involvement and organizational commitment, capableof influencing job satisfaction of bank employees. Khalid& Irshad (2010) revealed that the factors such as pay andbenefits, job security and recognition play a significant

Relative Importance of the Organisational Factors Capable of Influencing Job Satisfaction of Bank Employees: An Empirical Study

( 7 )

role in influencing one’s perception of job satisfaction.Hadi & Adil (2010) revealed that job characteristics likeskill variety, task identity, task significance, autonomy andfeedback were the most important positive predictors ofjob satisfaction. Samartha et al. (2011) identified six factors,such as personal factors, work environment,administrative bottlenecks, work pressure, job insecurityand psychological strain, are capable of influencing jobsatisfaction in the changing competitive world. Sowmya& Panchanatham (2011) found that the bank employeesperceived pay and promotion as an indispensible factordeciding their satisfaction level. Mansor et.al (2012) foundthat factors namely, competition, work environment andreward system were the most influential factors associatedwith job satisfaction.

OBJECTIVES OF THE STUDY

The objectives of the study are as follows:

1. To identify the organisational factors capable ofinfluencing job satisfaction of bank employees.

2. To study the relative importance of selectorganizational factors capable of influencing thedegree of job satisfaction of employees of UnitedBank of India working in South Assam.

METHODOLOGY OF THE STUDY

Selection of Factors

In order to attain the objectives of the study initially anextensive review of the existing literature was carried outto identify the various factors capable of influencing thedegree of job satisfaction of bank employees. In order toensure the correctness and the applicability of the factorsidentified through the said literature review an in-depthpersonal interview with employees of United Bank of Indiawas conducted. These two exercises became basis ofinclusion of factors in the pilot questionnaire. All theseexercises finally formed the basis of selection of factors forthe study.

Survey Instrument

Since the requirement of the study was to depend on theprimary data, after having identified the organisationspecific factors, the dependence was made on thestructured schedule prepared for the purpose. The constantsum scaling technique (100 points) was employed to getthe response of the bank employees.

Survey Design and Data Analysis

The population of the study comprised of the employees,in the ranks ranging from Single Window Operator (SWO)to Senior Manager, working in 51 bank offices of UnitedBank of India (UBI) scattered over four districts (Cachar,Karimganj, Hailakandi and Dima-hasao) of South Assam.The Census Survey method of data collection was used tohave the responses of the bank employees. For the reasonsbeyond the control of the researcher only 85% (approx) ofthem could be brought in the purview of the study i.e. outof 283 employees, the responses of only 240 employeescould be had. Based on mean score of relative importancethe ranks of the factors have been determined. Thefollowing table shows the profile of the respondents.

Table 1: Profile of the Respondents

Gender Number of Employees Percentage

Male 215 89.6

Female 25 10.4

Marital Status

Single 111 46.2

Married 129 53.8

Category of Emplacement

Officer 141 58.8

SWO 99 41.2

Source: Field Survey

SCOPE AND LIMITATION OF THE STUDY

• The scope of the study is confined to the employeesonly in the ranks ranging from SWO to SeniorManager of United Bank of India working in thefour districts of South Assam.

• The major concentration of the study of jobsatisfaction of employees is based on organisationalfactors (specifically) selected for the study.

RELATIVE IMPORTANCE OF THE FACTORSCAPABLE OF INFLUENCING JOB SATISFACTIONOF THE BANK EMPLOYEES

The responses obtained from the bank employees on eightselect factors have initially been presented in the tabularform followed by the requisite analyses and interpretationsto arrive at the findings of the study, to address the


( 8 )

objectives. Following are the tables presenting the relativeimportance of the select organisational factors capable ofinfluencing job satisfaction of employees of United Bankof India working in South Assam.

Table 2: Relative Importance of the OrganizationalFactors Capable of Influencing Job Satisfaction of

Bank Employees

Factors Mean Score of

Relative Importance

Rank

Difference with the

Next Ranked Factor

Pay and Allowances 23.21 1st 8.61

Welfare Facilities 10.76 5th 0.65 Promotion and Transfer 14.58 3rd 2.58

Working Conditions 14.60 2nd 0.02

Nature of the Job 12.00 4th 1.24 Inter-Personal Relation 10.11 6th 2.57

Supervision 7.20 8th --- Leave 7.54 7th 0.34


Table 2 reveals that the factor ‘Pay and Allowances’ wasperceived as the most important factor determining thedegree of overall job satisfaction of the bank employees.This revelation by the respondents is on the expected linesas this high priority of the salary paid employees overmonetary benefits has been and still is a major determinantof job satisfaction in the developing countries where theworkers are, in many case, still not getting the expectedmonetary benefits. In other words, what got discovered bythe probe, as indicated by the concerned mean score (23.21),was that- this factor is capable of determining the jobsatisfaction/dissatisfaction of the employees to the highestextent. The extent of its importance may also be understoodfrom the fact that the difference of mean score with thefactor ranked next is 8.61 which is quite a significant aspectassociated with this factor.

The factor which is ranked second in being able toinfluence the feeling of job satisfaction of the bankemployees is ‘Working Conditions’ (14.60), meaningthereby, the bank employees had considered thearrangements to facilitate hassle free work environmentin the office premises as the second most important sourceof satisfaction followed by the ‘Promotion and Transfer’

(14.58), indicating that the bank employees had rated thisfactor as the third important factor influencing degree ofjob satisfaction. To put it differently, the bank employeestend to get comparatively little more satisfaction when theysee opportunities to excel in their career, which is veryusual with the youths of present decade. It may benoteworthy to mention here that in terms of importance,there is very marginal difference (0.02) between the secondand the third ranked factors. The fourth important factorin the list, as perceived by the bank employees, is ‘Natureof the Job’ (12.00), which means the bank employees wereof the opinion that the very nature of their work in terms ofjob rotation, opportunities to use skills and abilities, workload, working hours, autonomy etc. is one of the prominentfactors influencing their overall job satisfaction and in termsof degree of importance, the factor was rated 2.58 pointshigher than the next ranked factor.

The factor which is ranked fifth is ‘Welfare Facilities’(10.76), which is followed by, with little lesser points (0.65)of importance, the factor ‘Inter-Personal Relation’ (10.11),which means, unlike the previous factors, the bankemployees had considered the informal relation amongcolleagues as a comparatively weaker source of getting jobsatisfaction. The bottom two factors in the list of eightfactors are ‘Leave’ (7.54) and ‘Supervision’ (7.20). It maybe noteworthy to highlight here that the bottom threefactors, based on rank, in the list of eight factors has nodirect relation with any monetary gains.

Table 3: Gender wise Relative Importance of theOrganizational Factors Capable of Influencing Job

Satisfaction of Bank Employees

Factors Male Female

Mean Score of Relative

Importance Rank

Mean Score of Relative Importance

Rank

Pay and Allowances 22.94 1st 25.48 1st

Welfare Facilities 10.73 5th 11.00 5th

Promotion and Transfer 14.59 3rd 14.48 2nd

Working Conditions 14.72 2nd 13.56 3rd

Nature of the Job 12.32 4th 9.28 6th

Inter-Personal Relation 9.99 6th 11.16 4th

Supervision 7.15 8th 7.68 7th Leave 7.56 7th 7.36 8th



( 9 )

Table 3 reveals that irrespective of genders the factor ‘Payand Allowances’ was perceived as the most importantfactor in determining the degree of overall job satisfactionof the bank employees. In other words, it made the highestcontribution towards the feeling of overall job satisfactionof the bank employees which is evident from the allocatedmean score of relative importance allocated against thefactor by both male (22.94) and female (25.48) bankemployees. However, the female bank employeesconsidered this factor little more important than theircounterpart. To put it differently it can be said that eventhough this factor is capable of influencing the jobsatisfaction/dissatisfaction of the bank employees to thehighest extent, there remains some difference in the priorityand the perception of the employees belonging to twogenders as for males it was less influencing than theirfemale counterparts.

Based on the mean score of relative importance, in case ofmale bank employees, the factor ‘Working Conditions’ isranked second most important factor followed by thefactors ‘Promotion and Transfer’, ‘Nature of the Job’,‘Welfare Facilities’, ‘Inter-Personal Relation’, ‘Leave’ and‘Supervision’. In case of female bank employees, based onthe mean score of relative importance, the factor ‘Promotionand Transfer’ is ranked second followed by the factors‘Working Conditions’, ‘Inter-Personal Relation’, ‘WelfareFacilities’, ‘Nature of the Job’, ‘Supervision’ and ‘Leave’. Itmay be noteworthy to mention here, apart from the factor‘Pay and Allowances’, the factor ‘Welfare Facilities’ hasgot the same rank (i.e. 5th) in case of both male and femaleemployees, though, compared to the male (10.73)employees, female (11.00) employees rated this factor littlemore important which is evident from the mean score ofrelative importance. In case of all the other six factors thereexists difference in the ranks, meaning thereby, both maleand female employees prioritised the factors differently.

Table 4 reveals that irrespective of marital status of theemployees the factor ‘Pay and Allowances’ was perceivedas the most important factor in determining the degree ofoverall job satisfaction of the bank employees. In otherwords, it made the highest contribution towards the feelingof overall job satisfaction of the bank employees which isevident from the allocated mean score of relativeimportance allocated against the factor by both unmarried(23.61) and married (22.86) bank employees. However, theunmarried ones considered this factor little more importantthan the married ones. It may be said that even though this

factor is capable of influencing the job satisfaction/dissatisfaction of the bank employees to the highest extent,there remains some difference in the priority and theperception of the bank employees belonging to the twocategories of employees based on their marital status.

Table 4: Marital Status Wise Relative Importance ofthe Organizational Factors Capable of Influencing Job

Satisfaction of Bank Employees

Factors Unmarried Married


Rank Mean Score of Relative Importance

Rank



Promotion and Transfer 15.78 2nd 13.56 3rd

Working Conditions 13.04 3rd 15.93 2nd





Based on the mean score of relative importance, in case ofunmarried ones, the factor ‘Promotion and Transfer’ isranked second most important factor in being able toinfluence job satisfaction of bank employees followed bythe factors ‘Working Conditions’, ‘Nature of the Job’,‘Welfare Facilities’, ‘Inter-Personal Relation’, ‘Leave’ and‘Supervision’. In case of the married ones, based on meanscore of relative importance, the factor ‘WorkingConditions’ is ranked second in the list followed by thefactors, ‘Promotion and Transfer’, ‘Nature of the Job’,‘Welfare Facilities’, ‘Inter-Personal Relation’, ‘Supervision’and ‘Leave’. Interestingly, apart from the factor ‘Pay andAllowances’, the factors ‘Nature of the Job’, ‘WelfareFacilities’ and ‘Inter-Personal Relation’ has got the samerank (i.e. 4th, 5th and 6th respectively) in case of bothunmarried and married employees. However, with respectto all these three factors, the married employees hadassociated little more importance than the unmarried ones.In case of all the other four factors, there exists differencein the ranks, meaning thereby, both unmarried and marriedemployees prioritised the factors differently.


( 10 )

Table 5: Category of Employment wise RelativeImportance of the Organizational Factors Capable of

Influencing Job Satisfaction of Bank Employees

Factors Officer SWO


Rank Mean Score of Relative Importance

Rank



Promotion and Transfer 15.25 2nd 13.64 3rd

Working Conditions 14.47 3rd 14.77 2nd




Source: Field SurveyTable 5 reveals that irrespective of category of employment,the factor ‘Pay and Allowances’ was perceived as the mostimportant factor determining the degree of overall jobsatisfaction of the bank employees. In other words, it iscapable to make the highest contribution towards thefeeling of overall job satisfaction of the bank employeeswhich is evident from the allocated mean score of relativeimportance allocated against the factor by the officers(21.62) and the SWOs (25.47). However, the SWOsconsidered this factor more important than the officers. Itmay be said that even though this factor is capable ofinfluencing the job satisfaction/dissatisfaction of the bankemployees to the highest extent, there remains somedifference in the priority and the perception of the bankemployees belonging to the two categories of employeesbased on the category of employment.

Based on the mean score of relative importance, in case ofofficers, the factor ‘Promotion and Transfer’ is rankedsecond most important factor in being able to influence jobsatisfaction of bank employees followed by the factors‘Working Conditions’, ‘Nature of the Job’, ‘WelfareFacilities’, ‘Inter-Personal Relation’, ‘Supervision’ and‘Leave’. In case of the SWOs, based on mean score ofrelative importance, the factor ‘Working Conditions’ isranked second in the list followed by the factors, ‘Promotionand Transfer’, ‘Nature of the Job’, ‘Welfare Facilities’, ‘Inter-Personal Relation’, ‘Leave’ and ‘Supervision’. Similar tothe results based on marital status, apart from the factor‘Pay and Allowances’, the factors ‘Nature of the Job’,

‘Welfare Facilities’ and ‘Inter-Personal Relation’ has gotthe same rank (i.e. 4th, 5th and 6th respectively) in case ofboth officers and SWOs. However, in regard to the factors‘Nature of the Job’ and ‘Welfare Facilities’, the officers hadperceived them little more important than the SWOs,whereas, it is the reverse in case of the factor ‘Inter-PersonalRelation’. In case of all the other four factors, there existsdifference in the ranks, meaning thereby, both officers andSWOs prioritised the factors differently. On the expectedlines, the officers were found to give more importance onpromotion than the SWOs, whereas, SWOs were foundmore concerned about the arrangements for hassle freework environment so as to carry out the routine worksefficiently.

CONCLUSIONJob satisfaction is dependent upon a host of inter-relatedfactors. Employee’s opinions and belief system play acentral role in explaining the degree of job satisfactionand is not always guided by rationality. Apart fromindividual characteristics, both monetary and nonmonetary aspects of a job are very much capable ofinfluencing job satisfaction of employees. The study revealsthat the factor ‘Pay and Allowances’, irrespective of gender,marital status and category of employment, was perceivedas the most important factor capable of influencing thedegree of job satisfaction of the bank employees and thetwo factors namely, ‘Supervision’ and ‘Leave’ wereperceived as the two least important factors out of the eightselect factors. Further, the factors, namely, ‘WorkingConditions’ and ‘Promotion & Transfer’ were also foundas important determinants of job satisfaction of the bankemployees. In fine, it may be concluded that the employeesattach more importance to hygiene factors as compared tomotivating factors and thus signifying the socio-economicconditions of the employees hailing from anunderdeveloped economy.

REFERENCES

Abdulla, J. M. (2009). Determinants of Job Satisfaction amongDubai Police Employees. Ph.D Thesis, University ofGlamoran. Source: http://dspace1.isd.glam.ac.uk/dspace/bitstream/ 10265/336/1/abdulla2009.pdf

Aziri, B. (2011). Job Satisfaction: A Literature Review.Management Research and Practice, 3 (4), 77-86.

Dakshinamurthy, K. & Kulkarni, M. V. (2012). JobSatisfaction of Women Teachers. Global VisionPublishing House, New Delhi, pp. 4 – 5.


( 11 )

Hadi, R. & Adil, A. (2010). Job Characteristics as Predictorsof Work Motivation and Job Satisfaction of BankEmployees. Journal of the Indian Academy of AppliedPsychology, 36(2), 294-299.

Hanif, F. M. & Yasir, K. (2009). Pay and Job Satisfaction: AComparative Analysis of Different PakistaniCommercial Banks. MPRA Paper No. 16059, 25,source: http://mpra.ub.uni-muenchen.de/16059/.

Herzberg, F., Mausner, B. & Snyderman, B. B. (1959). Themotivation to work (2nd ed.). New York: Johns Wiley.

Hoppock, R. (1935). Job Satisfaction. New Work, USA:Harper and Bros.

Khalid, S. & Irshad, M. Z. (2010). Job Satisfaction amongBank Employees in Punjab, Pakistan: A ComparativeStudy. European Journal of Social Sciences, Volume 17.

Lather, A. S. & Jain, S. (2005). Motivation and JobSatisfaction: A Study of Associates of Public andPrivate Sector. Delhi Business Review, Vol. 6, No. 1,pp. 77 – 84.

Luthans, F. (2005). Organisational Behaviour. Tata McGrawHill, New Delhi, pp. 211-212.

Mansor, N., Noor, J. M. M. & Hassan, N. F. N. (2012). JobSatisfaction among the Bankers: An investigationon Islamic Financial Institution in Eastern Regionof Malaysia. Asian Social Science, Vol. 8, No. 10, pp.186 – 197.

Mobley, W. H., Griffeth, R. W. & Hand, H. H. (1979). Reviewand Conceptual Analysis of the Employee TurnoverProcess. Psychological Bulletin, 86 (2), 493-522.

Naganna, D. & Ramana, A. V. (2007). Employee Morale andJob Satisfaction in Selected Commercial Banks: AComparative Study. The Associated Publishers,Haryana, p. 52.

Newstrom, J. W. & Davis, K. (1997). OrganizationalBehaviour: Human Behaviour at Work. McGraw Hill,NewYork, pp. 208-210.

Pestonjee, D. M. (1991). Motivation and Job Satisfaction. 1st

Edition, McMillan India Ltd., New Delhi, p. 145.

Purohit, P. (2004). Job Satisfaction and Work Motivation.Sarada Publishing House, New Delhi, p. 46.

Rahman, M. I., Gurung, H. B. & Saha, S. (2007). Where theJob Satisfaction of Bank Employees Lies: AnAnalysis of the Satisfaction Factors in Dhaka City.Source: http://ssrn.com/abstract =1349453.

Robbins, S. P. (1997). Organizational Behaviour. PrenticeHall.

Saiyadain, M. S. (1988). Human Resource Management, TataMcGraw Hill, New Delhi, p. 28.

Samartha, V., Begum, M. & Lokesha (2011). Impact of JobStress on Job Satisfaction - An Empirical Study.Indian Journal of Commerce and Management Studies,Volume 2, Issue 2, pp. 85 – 93.

Schaffer, R. H. (1953). Job Satisfaction as Related to NeedSatisfaction in Work. Psycho. Monogr., Vol. 66, No.14.

Sowmya K. R. & Panchanatham, N. (2011). FactorsInfluencing Job Satisfaction of Banking SectorEmployees in Chennai, India. Journal of Law andConflict Resolution, 3(5), 76-79, Source: http://www.academicjournals.org/JLCR.

Srivastava, A. K. (2008). Effect of Perceived WorkEnvironment on Employees’ Job Behaviour andOrganizational Effectiveness. Journal of the IndianAcademy of Applied Psychology, 34(1), 47-55.

Vigg, S., Mathur, G. & Holani, U. (2007). A Study of FactorsAffecting Job Satisfaction in Bank Employees. JIMS8M, pp. 10 – 13.

Prof. Dinesh Kumar PandiyaEx. Pro – Vice Chancellor, Assam University,Diphu CampusProfessor, Department of Commerce, Assam University,Silchar

Dr. Kingshuk AdhikariAssistant ProfessorDepartment of Commerce, Assam University, Silchar

Pinak DebResearch (Ph.D.) ScholarDepartment of Commerce, Assam University, Silchar


( 12 )

INTRODUCTION

Job satisfaction/dissatisfaction is simply an attitude about how content or discontentan individual is with his or her job. Individuals have certain aspirations and goals inlife. Entry into the organization is made with those aspirations and goals expecting it tobe fulfilled. But, it is also true that an organization also has its own goals. When thereis a match between the goals or objectives of the two separate ends, both the individualand the organization gets motivated or vice versa (Lee & Bruvold, 2003). Job satisfaction/dissatisfaction may be taken as a result or outcome of those aspirations between anemployee and the organization.

The success of an organization depends upon its effectiveness in accomplishing thenecessary objectives. However effectiveness itself is a relative term determined dependingupon the motivation and satisfaction/dissatisfaction of employees in the organization.In the present competitive world any resource possessed by one organization can beacquired easily by the other. The only competitive advantage that an organization maypossess is the human resource which is difficult for any organization to possess i.e.,skilled human resource and to keep it motivated.

The CEO of HCL Technologies, Vineet Nayar (2010) authored a book entitled EmployeesFirst, Customers Second (EFCS) where he narrated his own initiatives in driving the workforce to excel and argued vehemently that if the organizational priority gets shiftedfrom customers to employees it would result in better overall performance of anorganization. Hence the organizations have to put in place systems and processes so

Key words

Job Satisfaction,Dissatisfaction Expression,Hirschman, EVLNframework, India

How would You Express Dissatisfaction? Test ofHirschman’s Evln Model

Vijay Kumar Shrotryia, Liha Mena and Vicky Sangma

ABSTRACT

The level of satisfaction with one’s job has been studied through time because of its importance forattaining goal as well as improving performance. High levels of Job satisfaction have been seen to resultin good work behaviors, increase in production, promotion of better work environment etc. On the otherhand absence of satisfaction or presence of dissatisfaction among the workforce is a challenge as it also hassome negative consequences. To express their dissatisfaction employees may opt for any active or passivemeasures which are either constructive or destructive. Following the Exit, Voice, Loyalty and Neglect(EVLN) framework of dissatisfaction expression as given by Hirschman and further modified by manyother scholars, this study examines the perceived mode of dissatisfaction expression among employees, ina favorable job market and to measure any difference that arises due to the individuals’ demographics(age, gender, level of education and marital status) and their sector of operation. The present study iscarried out among 776 employees of four major sectors in Meghalaya viz; Power, Education, Governmentand Banks & Insurance to understand the differences better. Employees’ satisfaction and their choice ofdissatisfaction expression are measured. An attempt has also been made to establish an explanation forthe relationship between Job satisfaction level and perceived mode of dissatisfaction expression.


( 13 )

that employees feel engaged and part of decision making.It practically resulted in improving the performance ofHCLT through following EFCS. It positively resulted intheir job satisfaction and with this result employeeturnover was reduced.

Satisfaction from one’s job is of as much importance to anindividual as it is to the organization providing the job;the proof of which can be seen in the ocean of literatureavailable on the subject. High levels of Job satisfactionhave been seen to result in good work behaviors, increasein production, promotion of better work environment etc.On the other hand absence of satisfaction or presence ofdissatisfaction among the workforce is a challenge as italso has some negative consequences.

As mentioned earlier job satisfaction/dissatisfaction is anoutcome which is caused by the conditions posed byorganizations, hence the responsibility of HR departmentbecome more crucial to find out reasons of dissatisfactionand the ways in which the employees might express theirdissatisfaction which would inadvertently affectorganizational performance. In this backdrop the presentpaper is designed to study the expected expression ofemployees in different organizations.

This paper is an attempt to test the framework as developedby Hirschman for expressing dissatisfaction and it isexpected that this would lead to further researches to digdeeper into the domains of dissatisfaction expression andto further help design appropriate HR strategies to managethe employees effectively.

LITERATURE REVIEW

Job satisfaction is a multi-dimensional psychologicalresponse to one’s job and like any attitude, has cognitive,affective and behavioral components (Fishbein & Ajzen1974; Hulin & Judge 2003). It has been categorized as oneof the first job attitudes an employee builds up post hisjoining an organization with compatibility in individualand organizational goals (Lee & Bruvold, 2003). Thepositivity or negativity of the subject is important for anyorganization (Wiggins & Steade, 1976). Thus, determiningemployee job satisfaction has received considerableattention within recent years and morale or job attitudinalsurveys have been eagerly employed by large and smallindustrial concerns alike (Lee & Bruvold, 2003; Saari &Judge, 2004; Gazioglu & Tansel, 2006; Lange, Pacheco &Shrotryia, 2010) in order to tackle the problem ofdissatisfaction.

From the management perspective the subject is of interestdue to its consequent behavioral impact. Satisfiedemployees have been seen to be more productive, moreregular and promote healthy work environment in anoverall sense (Nayar 2010). However disgruntledemployees often pose as a threat when they choose toexpress themselves (Saari & Judge, 2004; Gazioglu &Tansel, 2006; Lange, Pacheco & Shrotryia, 2010).

Dissatisfied employees express their dissatisfaction indifferent ways depending on their individual behavioralcharacteristics. Hirschman (1970) listed 3 broad modes ofdissatisfaction expression, viz., exiting the organization,voicing their dissatisfaction and by showing loyalty. Thiswork was further extended by many other scholars(Rusbult, Zembrodt & Gunn, 1982; Farrell, 1983; Rusbult& Zembrodt, 1983; Withey & Cooper, 1989; Rusbult, Farrell,Rogers & Mainous III, 1988; Farrell & Rusbult, 1992, etc)and a fourth dimension of neglect was added. The studydone by Farrell (1983) on the multiple dimensions scalingsupported these four categories of expressions. From theorganization’s perspective, while voicing and exiting areboth active the former is constructive and the laterdestructive. Staying loyal (passive) has been considered alittle of both constructive and destructive however; Neglectis passive and destructive.

When we read about the factors that help determine jobsatisfaction, Herzberg’s (1965, 1968) two factor theory isthe most often cited wherein classification is made on twobroad categories of intrinsic (specific individual related)and extrinsic factors (work/job related).

For the purpose of our study we have considered fiveindependent variables which may be grouped intodemographic variables (age, gender, education, maritalstatus) and the sector of employment. It has been provedthat demographic analysis is imperative to understandemployee attitudes (Khan, Nawaz & Jan, 2012).

The effect of AGE on job satisfaction is very much evidentin literature and the pattern of relationship is U-shape innature (Loscocco & Kalleberg, 1988; Clark, Oswald, &Warr, 1996; Clark, 1997; Gazioglu, 2010; Lange, Pacheco,& Shrotryia, 2010). It could be because young workers feelsatisfied while entering a labor market as they have onlylittle experience. As the experience grows satisfactiondrops during the middle ages. But when age grows alongwith time the aspirations on the other hand drops downand alternative choices are reduced and also an employeegets attached emotionally to the job with time while


( 14 )

satisfaction increases. However Lange, Pacheco, &Shrotryia (2010) reported that age does not display astatistically strong impact on job satisfaction except forthe influence of age on the job security domain.

GENDER is said to determine the level of expectation fromtheir jobs (Clark, 1997; Okpara, Squillace & Erondu, 2005;Kim, 2005; Bernal, Castel, Navarro, & Torres, 2005). Thedissatisfaction level of women has been reported as lessthan their male counterparts irrespective of the similarityin job/functional level and the difference is said to arisebecause of the expectations and difference in the feature ofvalue. Females’ expect relatively lesser than males fromtheir jobs and place more importance to intrinsic rewardswhile male employees place higher value for extrinsicrewards.

Job Satisfaction and individual’s level of EDUCATIONhave been seen to have negative relation; as when oneincreases the other decreases. The more educated are lesssatisfied with the way organization is managed (Gordon& Arvey; 1975) and furthermore; make comparisons whenthey have lesser educated individuals working at the samelevel. Education raises expectation and aspirations of theemployees, when not met, results in dissatisfaction (Glenn& Weaver; 1982) however, Clark & Oswald (1996) made astatement that if education was backed with higher income,dissatisfaction could be reduced. Through a step-wiseregression analysis Khan et al (2012) found both MARITALSTATUS and Sector as of individuals is also seen to havea significant impact on Job Satisfaction.

While comparisons have been made between private andpublic sector, intra-sector comparisons have not beenstudied extensively. Though most of the organizations inour study are from the government SECTOR, we attemptto see the differences between the four sectors of Banking& Insurance, Power, Government (administration) andEducation.

Though there were studies on different aspects ofsatisfaction and dissatisfaction both in India and abroad,studies on expression of dissatisfaction by the employeesworking in India could not be found which encouragedthe researchers to pursue this study. Hence the study hasfollowing two key objectives:

• To examine the level of job satisfaction andexpression of dissatisfaction among employees

• To find out demographic and sectoral variations inexpressing dissatisfaction

Based on the literature and objectives, we form and test thefollowing hypotheses

H1: Demographic variables do not affect Job Satisfaction

H2: Demographic variables do not affect Dissatisfactionexpression

H3: Sector does not affect Job Satisfaction

H4: Sector does not affect Dissatisfaction expression

METHODOLOGY

Through a survey based study 868 questionnaires werecollected from individuals working in four major sectors;Banking and Insurance, Power, Government andEducation. The sampling was done on the basis of sheerconvenience; however the effort was to have a roughrepresentation of the population working so far as theirdemographic variables were concerned. The questionnairemeasured job satisfaction on a scale of 1 to 5 andDissatisfaction was expressed through Hirschman’sfactors of Exit, Voice, Loyalty and Neglect; a fifth option of‘Others’1 was also provided. 776 of the total questionnaireswere usable and had complete entries.

Since the objective was to have an idea, the data wasanalyzed using normal frequencies of responses indifferent categories and it was assumed that therespondents would choose best option according to them.Analysis were made using SPSS 22.0.

DATA ANALYSIS AND RESULTS

Most of the respondents (Table 1) were chosen fromdifferent public sector banks and few private sector banks,from insurance companies like Life Insurance Corporationand General Insurance Company (including Oriental,New India, United, and National), employees working inpower sector (North-Eastern Electric Power Corporation),state electricity board, state and central governmentemployees working in the district collector’s office,Meghalaya secretariat, Accountant General’s Office, AllIndia Radio, Income Tax Office, Excise, Customs etc andteachers working in schools, colleges and university.Around 90% respondents were found to be permanentemployees whereas while being asked whether they wereworking in the organization of their choice, more than80% gave affirmative answer. The effort was to haverepresentative sample from these four important sectorsviz., Bank and Insurance Companies (n = 191), Power

How would You Express Dissatisfaction? Test of Hirschman’s Evln Model

( 15 )

Table 1: Profile of the respondents

Banks & Insurance

Co

Power Corporations

Government Employees

Teachers Total

n = 191 n = 174 n = 195 n = 216 N = 776 % Gender Male 130 103 116 114 463 60 Female 61 71 79 102 313 40 Age (in years) 30 & below 10 18 21 56 105 14 31-40 70 73 76 99 318 41 41-51 90 69 71 41 271 35 51 & above 21 14 27 20 82 11 Education Up to XII 13 51 37 3 104 13 Up to Grad 144 106 138 54 442 57 Up to PG 34 17 20 111 182 23 Doctorate & above 0 0 0 48 48 6 Marital status Married 166 161 165 159 651 84 Unmarried 25 13 30 57 125 16 Source: Respondents survey results from the field

Table 2 (a) Job satisfaction and Individual characteristics (in %)

Very Dissatisfied

Dissatisfied Average Satisfied Very Satisfied

Gender Female 1 4 17 37 41 Male 2 6 17 47 28 Age 31 and below 4 3 24 39 30 31-40 1 6 19 46 29 41-50 2 6 16 41 35 51 and above 0 4 7 45 44 Education upto XII 1 6 14 26 53 Graduate 2 6 18 42 32 Post Graduate 2 5 19 52 23 Doctorate & above 0 0 8 56 35 Marital Status Married 4 2 24 44 26 Unmarried 1 6 16 43 34 Sector Banking & Insurance 2 3 23 45 29 Power 3 10 14 37 37 Govt 2 6 18 39 35 Education 0 3 14 50 32 Source: Respondents survey results from the field


( 16 )

Corporations (n = 174), Government Employees directlyworking with state and central government offices (n =195) and teachers (n = 216). In the banking and insurancecompanies the difference between male and female wasmore as compared to the respondents from other threesectors; however education sector had most femalerespondents. The details about the personal characteristicsare provided in Table 1.

Table 2(a) and 2(b) show the dispersion of responses injob satisfaction and dissatisfaction expression respectivelyin relation with the demographic variables and sector ofoperation.

Of the total 776 respondents we see found 43% satisfiedand 33% very satisfied with their respective jobs. We alsoobserve more satisfaction among females than males andas per literature, could be attributed to the fact that womenvalue intrinsic rewards more than extrinsic rewards,unlike males. We see respondents from the Age group of31- 40 (46%) being the most satisfied and also observe thatwith increase in age people become lesser dissatisfied andmore satisfied. An interesting observation can also be madein the education category as we see a positive relationshipwith education and satisfaction. Marital status of the

individual does not seem to make much of a difference insatisfaction; however we may refer to other test results tocome to a more meaningful conclusion. In the sectorcategory we find more satisfied respondents in theEducation sector with around 82% respondents eithersatisfied or very satisfied.

Table 2(b) clearly shows that most respondents chose tovoice rather than opt for any other mode of expression.There seems to be not much of a difference between bothcategories of gender as the responses are more or lesssimilar with both categories giving more preference to Voice(48% each) followed by Neglect, Exit and Loyalty, in theorder.

Considering the effect of age on dissatisfaction expressionwe see that with increase in age respondents also becomemore willing to Voice. We also observe that the youngerrespondents give equal (36%) preference to quitting or Exitas to Voice. We may attribute this behavior to the fact thatjob-hopping is easier for the younger employees and asemployees get older they prefer more stability. This can besupported by additional observations that with increasingage employees are decreasingly willing to Exit howevermore increasingly willing to stay Loyal or even Neglect

Table 2 (b): Dissatisfaction Expression & Individual Characteristics (in %)

Exit Voice Loyalty Neglect Others Gender Female 18 48 4 30 1 Male 16 48 6 28 2 Age (in years) 31 & below 36 36 5 21 2 31-40 18 48 4 28 2 41-50 11 51 5 31 1 51 & above 9 51 6 34 0 Education Up to XII 7 43 3 43 4 Graduate 16 44 7 32 1 Post Graduate 26 52 3 18 1 Doc & above 15 77 0 8 0 Marital status Married 26 46 2 22 3 Unmarried 15 48 5 30 1 Sector Banking & Ins 14 50 4 31 1 Power 13 37 6 41 3 Govt 16 44 6 32 2 Education 23 58 4 13 1 Source: respondents survey results from the field


( 17 )

their jobs to avoid the situation of Exit. We find thisobservation also to be consistent with the existingliterature2.

The Level of Education also shows a positive relation withthe choice of Voice as the percentage increases withincrease in education. An overwhelming 77% ofrespondents are from the highest educated respondents(doctorate and above). The category with the lowest levelof education shows the highest respondents opting toNeglect (43%) their jobs rather than Exit (7%). In thecategories of marital status we find more marriedrespondents willing to leave their jobs than unmarriedones while more unmarried willing to compromise withtheir dissatisfaction and either stay Loyal or Neglect theirjobs. We also find unmarried employees more willing toVoice.

In the category of Sector of operation we find the mostrepresentation in Voice from the education sector (58%)followed by Banking & Insurance (50%). We also find aninteresting observation in the Power sector that though ithas the lowest Exit (13%), it also has the highest percentageof Neglect (41%) which is not a very healthy sign. As perTable 2(a) we saw that the education sector had the highestlevel of job satisfaction however in the situation ofdissatisfaction, respondents chose to Exit (highest at 23%)rather than Neglect or stay Loyal.

To test the hypotheses the tools used have been Chi squaretest for independence and Median test for k samples (fordistribution that is not normal). For variables Age andMarital status (2 categories each) we verified the resultsusing Mann-Whitney U as well. The results are in Tables3(a) and 3(b).

Table 3 (a): Job Satisfaction

Chi-square test Median test (k sample)

Variables P Result* P Result* Gender 0.003 Reject 0.000 Reject1 Marital Status

0.006 Reject 0.108 Accept2

Age 0.042 Reject 0.064 Accept Education 0.000 Reject 0.000 Reject Sector 0.005 Reject 0.381 Accept *at 5% level of significance

H1: Demographic variables do not affect Job Satisfaction

From the above results of Chi square test we seeassociation between the demographic variables and

Job satisfaction significant at 5% and therefore RejectH1 and conclude that Demographic variables of gender,age, educational qualification and marital status affectJob satisfaction.

The Median test for k samples was done to see ifthere was any consistency in the medians acrossdifferent categories of all demographic variables.

H2: Sector does not affect Job Satisfaction

As per the Chi square test we see an associationbetween sector and job satisfaction as well andtherefore we reject the H2 and accept the alternateconclusion that the Sector of operation affects level ofJob satisfaction.

Table 3 (b): Chi-square test for DissatisfactionExpression

Variables P Result* Gender 0.419 Accept Marital Status 0.000 Reject Age 0.000 Reject Education 0.000 Reject Sector 0.000 Reject *at 5% level of significance

H3: Demographic variables do not affect Dissatisfactionexpression

With the exception of variable Gender all otherdemographic factor show association withDissatisfaction expression (at 1% level ofsignificance as well) and therefore we conclude thatDissatisfaction is not affected by Gender but other factorsof Age, Educational Qualification and Marital statusaffect the way individual’s dissatisfaction.

H4: Sector does not affect Dissatisfaction expression

The Sector of operation also seems to be importantto predict dissatisfaction expression as the chi squaretest result shows significance at 1% level. Wetherefore conclude and accept the alternatehypothesis that Sector affects dissatisfaction expression.

Another important analysis may be made of the attitude-behavior relationship through this study. Prior to the 1960sthe attitude-behavior relationship suffered due to theinability of the contributors to link the two adequately,However; later studies proved more promising with theirpositive (though limited) results. Our study follows theline of the theory of reasoned action approach developed by


( 18 )

Ajzen & Fishbein (1977) & Ajzen (1991) that states thatbehavior intention can be predicted by adding collectiveattitudes [(both towards the target and performing anaction) with their respective weights] and individualsubjective norms (again, with weights). Returning to ourstudy, while on one hand we have an overall 76 percent ofrespondents reporting either high or above averagesatisfaction, on the other, we have voicing (47.8 percent)and loyalty (28.9 percent) as the best modes of expressingdissatisfaction.

Few things we may want to remember here are, our studyis based on the premise of EVLN framework and hence,believe Voicing as the most constructive and favorableoption of the four, followed by Loyalty. Secondly, theresponses are only intended behaviors and not overtactions.

The general notion of consistency sates that, logically, peopleholding a favorable attitude can be predicted to behavefavorably. Hence, we can conclude that because therespondents showed high levels of satisfaction, highestpercentage of them also chose Voicing, followed by Loyalty.This statement also implies that had the respondentsshowed lower levels of job satisfaction the option ofdissatisfaction expression would have been either Exit orNeglect.

Chi square test shows a significant relationship betweenthe two at 5 percent level of significance (0.037) and across tabulation (Table 3.c) also shows an increasing trendin opting for Exit and Neglect with increase inDissatisfaction (except for Dissatisfied category (5%)

which could be a result of sampling error). Interestingly,we also see decreasing Exit with higher satisfaction.

LIMITATIONS AND CONCLUSION

Through this study we tried to put forth a generalizedidea of how employees in the concerned geography feeltowards their jobs and how they would express theirdissatisfaction in their respective organizations. HRmanagement practices can be designed to retain good talentand to prioritize the areas of concern. The antecedentsalso would determine the HR policy direction in futureand shall certainly help the organizations to manage theirworkforce at different stages of the cycle in more efficientways. This work is also expected to contribute to theliterature pool on the expression of dissatisfaction fromthis geography of the globe and some comparative studiesacross cultures can be made for to relate the outcomes withsocio-cultural, environmental and behavioralbackgrounds of the employees. Deeper exploration androbust studies are required especially in Indian workingconditions and it is expected that this paper shall help usunderstand the mindset of the employees so far as theirperceived action is concerned.

This study throws significant light to explain employeebehavior in presence or absence of job satisfaction however;it is not free of limitations. One of the most considerablelimitations is the population size which, though large, isnot large enough when stratified. A larger representationin each category and sub category would have given aclearer and more absolute result. This study also was

Table 3(c): Cross-tabulation of Job Satisfaction and Dissatisfaction Expression

Level of Job Satisfaction

Exit Voice Neglect Loyal Others Total

Very Dissatisfied

4 3 1 4 1 13

30.77 23.08 7.69 30.77 7.69 100 Dissatisfied 2 18 3 16 1 40 5 45 7.5 40 2.5 100 Average 24 52 10 42 5 133 18.05 39.1 7.52 31.58 3.76 100 Satisfied 61 168 15 86 4 334 18.26 50.3 4.49 25.75 1.2 100 Very Satisfied 40 130 9 76 1 256 15.63 50.78 3.52 29.69 0.39 100 Total 131 371 38 224 12 776 16.88 47.81 4.9 28.87 1.55 100


( 19 )

limited to a very simple analysis. More complex tools andtechniques couldn’t be used due to the sampling size andinability to fulfill various test assumptions. Anothernoteworthy shortcoming may be pointed out as that ofbias in responses. Respondents may have opted for the‘most socially desirable’ response while responding to thequestion of expressing dissatisfaction.

Hirschman’s EVLN model has stood the test of the timeand its further validation in different geographies provesthat employees’ response in general moves along in similarlines.

REFERENCES

Ajzen, I. (1991). The theory of planned behaviour.Organizational Behaviour and Human DecisionProcesses, 50, 179-211.

Ajzen, I. & Fishbein M. (1977). Attitude-Behavior Relations:A Theoretical analysis and review of Empiricalresearch. Psychological Bulletin, 84(5), 888-918.

Becker, H.S. (1960). Notes on concept of commitment.American Journal of Sociology, 66 (1), 32-40.

Bernal, J. G., Castel, A. G., Navarro, M. M. & Torres, P. R.(2005). Job satisfaction: Empirical evidence of genderdifferences. Women in Management Review, 20(4), 279-288.

Clark, A. E. & Oswald, A. J. (1996). Satisfaction andcomparison income. Journal of Public Economics, 61,359-381.

Clark, A. E. (1997). Job satisfaction and gender: Why arewomen so happy at work? Labour Economics, 4, 341-372.

Clark, A. E., Oswald, A.J., & Warr, P. (1996). Is jobsatisfaction U-shaped in Age? Journal of Occupationaland Organtzational Psychology, 69, 57-81.

Farrell, D. (1983). Exit, voice, loyalty, and neglect asresponses to job dissatisfaction: A multidimensionalscaling study. Academy of Management Journal, 26,596–607.

Farrell, D. & Rusbult, C. E. (1992). Exploring the exit, voice,loyalty, and neglect typology: The influence of jobsatisfaction, quality of alternatives, and investmentsize. Employee Responsibilities and Rights Journal, 5(3),201-218.

Farrell, D., Rogers, G. & Mainous III, A. G. (1988). Impact ofexchange variables on exit, voice, loyalty, andneglect: An integrative model of responses todeclining job satisfaction. The Academy ofManagement Journal, 31(3), 599-627.

Fishbein, M., & Ajzen, I. (1974). Attitudes towards objectsas predictors of single and multiple behavioralcriteria. Psychological Review, 81, 59-74.

Gazioglu, S. & Tansel, A. (2006). Job satisfaction in Britain:Individual and job related factors. Applied Economics,38, 1163-1171.

Glenn, N. D. & Weaver, C. N. (1982). Further evidence oneducation and job satisfaction. Social Forces, 61(1),46-55.

Gordon, E. M. & Arvey, R. D. (1975).The relationshipbetween education and satisfaction with jobcontent.The Academy of Management Journal, 18(4),888-892.

Herzberg, F. (1965).The new industrial psychology.Industrial and Labor Relations Review, 18(3), 364-376.

Herzberg, F. (1968). One more time: How do you motivateemployees? Harvard Business Review, 86-96.

Hirschman, A. O. (1970). Exit, Voice, and Loyalty: Responsesto decline in firms, organizations, and states. Cambridge,MA: Harvard University Press.

Hulin, C. L., & Judge, T. A. (2003). Job attitudes. In W. C.Borman, D. R. ligen, & R. J. Klimoski (Eds.), Handbookof psychology: Industrial and organizational psychology(pp. 255-276). Hoboken, NJ: Wiley

Loscocco, K. A. & Kalleberg, A. L. (1988). Age the meaningof work in the United States and Japan. Social Forces,67(2), 337-356

Khan, S., Nawaz, A. & Jan, F. A. (2012). Impact ofdemographic diversities on the Job satisfaction andits consequences: Case study of Academicians inHigher Learning Institutions of Pakistan(Application of stepwise multiple regression). GlobalJournal of Management and Business Research, 12(19),35-43.

Kim, S. (2005). Gender differences in the job satisfaction ofpublic employees: A study of Seoul MetropolitanGovernment, Korea. Sex Roles, 52(9), 667-681.


( 20 )

Lange, T., Pacheco, G. & Shrotryia, V. K. (2010). Culture,industrialization and multiple domains ofemployees’ job satisfaction: A case for HR strategyredesign in India. The International Journal of HumanResource Management, 21(13), 2438-2451.

Lee, C. H. & Bruvold, N. T. (2003). Creating value foremployees: Investment in employee development.TheInternational Journal of Human Resources Management,14(6), 981-1000.

Nayar, V. (2010). Employees first, customers second. USA:Harvard Business Press.

Okpara, J. O., Squillace, M. & Erondu, E. A. (2005). Genderdifferences and job satisfaction: A study ofUniversity teachers in the United States. Women inManagement Review, 20(3), 177-190.

Rusbult, C. E., Zembrodt, I. M. & Gunn, L. K. (1982). Exit,voice, loyalty, and neglect: Responses todissatisfaction in romantic involvements. Journal ofPersonality and Social Psychology, 43(6), 1230-1242.

Rusbult, C. E. & Zembrodt, I. S. (1983). Responses todissatisfaction in romantic involvements: Amultidimensional scaling analysis. Journal ofExperimental Social Psychology, 19, 274-293.

Saari, L.M. & Judge, T. A. (2004). Employee attitudes andjob satisfaction. Human Resource Management, 43(4),395-407.

Withey, M. J., & Cooper, W. H. (1989). Predicting exit, voice,loyalty, and neglect. Administrative SciencesQuarterly, 34, 521–539.

Wiggins, R. L. & Steade, R. D. (1976). Job satisfaction as asocial concern. The Academy of Management Review,1(4), 48-55.

Footnotes

1 In the analysis of chi square test for independence forDissatisfaction Expression and variable Age due tonon-fulfillment of the condition of expected countless than 20%; the option‘Others’ (opted by only 12respondents) has been dropped.

2 As per Becker’s (1960) side-bet theory due to continuousaccumulation of investments in an organizationprolonged interaction makes it more difficult forindividuals to leave. Age is considered a proxy oftime investment in this study.

3 Median test across categories of Gender as per

Mann-Whitney U test (P = 0.002) is also consistent withthe Chi square test results.

4 Median test across categories of Marital status as per

Mann-Whitney U test (P = 0.062 is also consistent with theChi square test results

Vijay Kumar ShrotryiaProfessor, Department of Commerce, Delhi School ofEconomics, University of Delhi, Delhi, India (formerlyProfessor & Head, Dept of Commerce, North-Eastern HillUniversity, Shillong)

Liha MenaResearch Scholar, Department of Commerce,North-Eastern Hill University, Shillong,India

Vicky SangmaResearch Scholar, Department of Commerce,North-Eastern Hill University, Shillong,India


( 21 )

INTRODUCTION

Composition of work and family life spheres has significantly changed over a period oftime. Today’s working male and female face a broad set of daily challenges whichmany times create imbalance between their working life and personal/family life. Lackof work-life balance thus influences working individual’s performance at workplace aswell as in personal life. In the current economic scenario, organisations are hard pressedfor higher productivity and can face the recessionary challenges better if their employeesare more engaged with work and workplace. Organisations, more than ever, needemployees with improved work-life balance. An employee with better work-life balancewill contribute more meaningfully towards the organisational growth and success.

REVIEW OF EARLIER STUDIES

In the early years of communal living (Phase one) usually the entire family engaged inwork for subsistence at home or near home (Carlson et al. 2005). In pre-industrialisationperiod (Phase two) growing size of trade and craft business partially segregated theworkplace and family life. During the industrial revolution in mid 1800s (Phase three)use of machines for mass production necessitated setting up of factories away fromhome. Men dominated the workforce in factories while household work was taken careof primarily by women who stayed back at home (Voydanoff 2006). During late 18thand early 19th century (Phase four) due to division of labour and between early 19thcentury and 1950s (Phase five) due to technological factors (which depended on physicalstrength, giving men an advantage over women at the workplace) separation of workfrom family was more consolidated and men took the main role of bread earners andwomen took primarily the charge of home and family work (Snooks 1996).

In early part of second half of the 20th century (Phase six) gender division was reverseddue to the technological advancements and computerisation which reduced the

Key words

Life balance, Work-lifebalance model, Work-lifespheres, Work-lifesegments, Work-lifeConflict

Causes of Work-life Imbalance and its Impact onthe Behaviour of Women Gynaecologists.

Susha D, Anitha S and P.N.Harikumar

ABSTRACT

During the second half of 20th century, with work demands increasingly encroaching on family andpersonal time at a faster pace, employers acknowledged the need of work-life balance programmes tofacilitate employees maintain a healthy balance between the conflicting demands of their work andpersonal life. Availability of work-life balance facilities to employees witnessed a phenomenal growthbetween the late eighties of the 20th century and early years of the 21st century. This growth has beenabruptly interrupted by the current economic downturn. Increasing numbers of organisations, in thename of cost cutting, have either curtailed work-life balance facilities or are contemplating to do the same.This paper analyses the causes of work-life imbalance and its impact on the behavior of womenGynaecologists working in government and private hospitals in kerala.


( 22 )

dependence on physical strength in factories thusfacilitating greater participation of women in workforce(Snooks 1996). As the number of women increased in theglobal workforce, 1980s and 1990s (Phase seven) witnessedincreasing number of companies offering work-lifeprograms primarily to support working mothers(Lockwood 2003). Later such programs evolved into lessgender-specific programs and recognized othercommitments of life (Lockwood 2003) by the early years of21st century. From 1950’s up to early years of 21st century(Phase six and Phase seven) a wide array of socio-economicfactors has been responsible which significantlyinfluenced the work and personal life of employees. Threeimportant categories of such factors are family andpersonal life, work and other factors (Naithani and Jha2009).

With increasing participation of women in workforce, theparticipation of working mothers, dual earner couples andsingle parents also increased. This trend immediatelyenhanced the child and elder care burden on a largenumber of employees and in addition created newchallenges in balancing work and family life. Atorganizational level, 1950s onwards, significantenhancement in long hour culture, unpaid overtime,changing work time and work intensification started to bewitnessed. This resulted into enhanced work related stress,time squeeze for home and family and employee demandfor shorter working hours. Conflict between work andpersonal life aggravated further due to 24x7 work culturebecoming popular due to rise of service sector industry,technological complexities at workplace, ageingpopulation and loss of social support network. Thoughinfluence of socioeconomic factors on family, personal life,work and other factors was noticed by researchers andorganizations as early as 1930s, yet it was only after the1960s that the focused research on work and personal lifeand their influence on each other under changedconditions became apparent.

INTRODUCTION AND GROWTH OF WORK-LIFEBALANCE RESEARCH

History of work/life programs can be traced back to 1930s,when introduction of reduced working hours with fourshifts of six-hours instead of the usual three daily eighthours shifts in W.K. Kellog Company resulted intoenhanced employee morale and productivity (Lockwood2003). In the 1960s, research on working mothers and dualearner families came into light as women’s participation

grew significantly in the workforce (Lewis et al. 2007).Rappaport and Rappaport in 1960’s researched on howin the agrarian societies work and family were closer toeach other and how industrial revolution in the 18th andthe 19th century created a divide between work andpersonal life and further how electricity and machinesmade mass production possible which essentially meantsetting up of factories away from home . Their researchstudied segmentation of work and family life due tomovement of work away from home/family to the factoriesand cities (Rappaport and Bailyn 1996). Rappaport andRappaport covered a limited scope of work and life balance.Their research was primarily concerned with work andits impact on family and did not relate work and its impacton other aspects of life. Still, theirs’ was a significantbeginning and more research followed soon. Prior to 1970s,‘work’ and ‘family’ were primarily treated as separatesegments (Blunsdon et al. 2006). Interdependence of ‘work’and ‘family’ was highlighted by Kanter (1977) whohighlighted aspects of work affecting family life andaspects of family life affecting work. During the same timePleck (1977) analyzed work family role system as acollection of male work role, female work role, male familyrole and female family role. Pleck (1977) further stated thatwomen experience spill-over from family role into workrole and men experience spill-over from work role intofamily role. The ‘spill over theory’ was furtherstrengthened by Staines (1980) who suggested that spill-over from one segment of life into another can have bothpositive and negative consequences. Staines (1980)supplemented the discussion on work-life aspects through‘compensation theory’, according to which a personattempts to compensate deficit in one aspect of life throughadditional investment in other aspect of life. As cited byPickering (2006), Greenhaus & Beutell (1985) gave a newdirection of work-family research by presenting the work-family conflict theory according to which an individualhas to perform different roles and family and work competein demanding time, attention and commitment to performthese roles. Role behaviours in family and work thusconflict with each other, and create work-family conflict.According to Greenhaus and Beutell (1985), as cited bySkinner and Pocock (2008), primary causes of conflictsdue to paucity of time are time related stress and paucityof time for life outside workplace. Initial work-life policiesand programmes in the 1980s were primarily focused onwomen with children (Lockwood 2003). 1990s witnessedthe shift from working mother specific narrow focus to abroader focus on married and unmarried men and women

Causes of Work-life Imbalance and its Impact on the Behaviour of Women Gynaecologists.

( 23 )

with or without children. Focus on ‘work-family’ and‘family-friendly policies’ broadened to a larger ‘work-lifebalance’ discourse (Lewis et al. 2007). The theory ofboundary work (Nippert-Eng 1996a; 1996b as cited byWarhurst et al. 2008 and Nippert-Eng 1996a; 1996b ascited by Blunsdon et al. 2006) presented a broader meaningof work-life balance through classification of workers as‘segmentors’ and ‘integrators’. Work-life is integratedwhen there is no distinction and mental boundary betweenwork and home and segmentation occurs when there is aclear-cut mental boundary separating work and home. Inbetween segmentation and integration lies a range. Anindividual can be at either ends of segmentation orintegration or can be at any point of the range, activelyengaged in mentally defining the boundaries. A simplerunderstanding of work-life balance can be presented withthe help of balanced wheel of life which is commonly citedin work-life balance literature. Byrne (2005) presented theage-old concept of balanced wheel of life and related work-life balance with it. Byrne (2005) suggested eight importantsections of life as the eight spokes in a wheel. The sectionsare work, finances, spiritual, hobbies, self, social, familyand health. According to Byrne, all these eight sections oflife are important for every human being and eachindividual attempts to achieve a balance amongst thesedifferent sections. Byrne thus treats all the eight sectionswith equal weight and importance, which might not betrue with every individual. Over looking this limitation ofthe model, the balanced wheel of life can be termed as theeasiest way to understand the concept of work-life balanceas this model look into different segments of life.

Every individual’s life has multiple segments such asfamily, finances, social, self, spiritual, health and hobbies.In each of these life segments, an individual needs to devotecertain period of time, energy and effort while major partof daily time, energy and effort is consumed in the worksegment. Males and females play professional roles at workplace and the difference in roles at workplace is primarilynot gender dependent but is rather decided by thequalification, experience and designation of the employee.In contrast, male and female roles have traditionally andsocially been gender defined in life segments. Though maleparticipation in household work, especially in dual workercouples is increasing, yet a significant part of the householdwork (including childcare) is expected to be the domain ofthe female. This gender biased role differentiation at thefamily level creates different work-life balance pressuresfor males and females. But in today’s over competitiveworld, which continuously demands more time for work

and career, high level of segmentation of work and familyis not easy. In some cases individuals will be able to keeplife segmented from work (life not encroaching on worktime, energy and effort) or keep work segmented from life(work not encroaching on life time, energy and effort). Highintegration on the other hand brings out opposite resultsand might create high levels of work-life conflicts andimbalance. With increasing demands of time for work,integration of high levels between work and life isbecoming a necessity. While an individual is balancingbetween the continuum of segmenting and integratingbetween work and life, he/she will also attempt tocompensate loss in one segment from results in another.An individual who has higher degree of work-lifesegmentation will have lesser opportunities to compensatefor loss in one segment from gains in other segment. Whereas a person who has high integration of work and life willhave higher opportunities for compensation. While theprocesses of segmentation, integration and compensationare continuing (at different degrees) work and life willcreate their own individual outputs, which will be ofpositive and negative nature. These negative and positiveoutputs will tend to spill over from segment to another,especially when the work and life have higher degree ofintegration.

OBJECTIVE

The main objective of the paper is to examine the impact ofworklife imbalance of women Gynaecologists in kerala.

METHODOLOGY

The study is a descriptive and analytical one. The sampleGynaecologists were selected by applying stratifiedrandom sampling method. Here, the Gynaecologists werestratified as those lady doctors working in Private andGovernment hospitals in the state.

SAMPLE SIZE

Based on the results of the pilot study, the sample size wasfixed statistically by using a formula. The modified dataafter Reliability Analysis, collected from the 60respondents, were studied in detail to identify the extentof variations in the responses. It may be stated that thesample size was proportional to the level of variation andthe assumed level of the error of the estimate of thepopulation parameter of the study variable. The seventy-five statements relating to the measurement of relevantvariables were used to determine the sample size. For an


( 24 )

assumed level of 10 per cent error in the estimate of meansof these 75 responses using the information on variancefrom the pilot study, sample size was obtained based oneach response. The formula used is n e” (1.96s/d)2. Where‘n’ is the sample size, ‘s’ is the estimate of standarddeviation, ‘d’is the standard error of the estimation ofpopulation parameter and the value 1.96 is the criticalvalue from normal test at 5 per cent level of significance.The sample size of 127 calculated was the maximumamong the sample sizes obtained from responses for allthe statements. Hence, the sample size was fixedstatistically as 150.

TOOLS FOR ANALYSIS

a. Step-wise Multiple Regression (Linear)

Step-wise Multiple Linear Regression attempts tomodel the relationship between two or moreexplanatory variables and a response variable byfitting a linear equation to observed data. Everyvalue of the independent variable X is associatedwith a value of the dependent variable, Y. Thus,rather than modeling the mean response as astraight line, as in simple regression, it is modeledas a function of several explanatory variables. Thetechnique takes a group of random variables andtries to find a mathematical relationship betweenthem. The model creates a relationship in the formof a straight line (linear) that best approximates allthe individual data points.

b. Friedman’s Test

Friedman’s test is a non-parametric test thatcompares two or more variables. This test first ranksthe values in each variable from low to high. Theranks assigned by the respondents on each variableare averaged and tested to find out whether themean rank variation is significant or not.

RESULTS AND DISCUSSION

As per Table 1, it is clear that out of the selected 150 womenGynaecologists 60 doctors are working in rural area and90 in urban area. 70 selected doctors are working ingovernment hospitals and remaining Gynaecologists areselected from private hospitals. Majority of the selecteddoctors have PG degree and 20 per cent doctors have dualspecialisation. 130 Gynaecologists are living in a nuclearfamily system.

Table 1 : Demographic Profile of the selectedWomen Gynaecologists

Categories Frequency

Area of Hospital

Rural 60 Urban 90

Type of hospital

Government 70 Private 80

Marital Status

Married 120 Unmarried 30 Others 0

Education MBBS only 20 MBBS with MD 100 MBBS with dual specialisation

30

Others 0 Family Structure

Nuclear 130 Extended 18 Joint 2

Monthly Income

Up to 100000 100 100001-200000 30 2000000-300000 20 Above 300000 0


FACTORS AFFECTING WORK-LIFE IMBALANCE

The following table shows the step-wise multipleregression coefficient and R square for proving therelationship of worklife conflict and other factors affectingsuch work-life imbalance.

From the above table, it can be seen that 83 per cent of thevariation in the work-life imbalance is explained by sixfactors such as no success in family life, no job enrichment,dissatisfaction in family life, no sharing of familyresponsibility, job insecurity and no leisure time work,considered as independent variables in the Multiple linearregression model. The beta coefficients and the associatedt values of these variables are statistically significant, asthe p values are less than .05. Therefore, it can be inferredthat all these factors affect the work-life imbalance of thewomen Gynaecologists working in government andprivate hosiptals in Kerala.


( 25 )

Impact of worklife imbalance on the behavior of womenGynaecologists

Worklife imbalance creates problems on the behavior ofthe women Gynaecologists when they deal with theirfamily affairs or job assignments. Here the selected ladydoctors are directed to rank seven possible outcomes ofworklife imbalances and the mean rank matrix and itsassociated output of friedman test are presented in thefollowing tables.

Table 3 : Mean rank

Factors Mean Rank

Private Hospitals

Government Hospitals

Uncontrollable stress 4.14 5.91

Imbalance in fulfilling the family responsibility

4.34 4.30

Unable to concentrate in official duty

5.33 3.28

Physically unfit 5.21 5.24 Too much family problems 7.66 7.26

No appreciation from the management

7.43 6.42

Frustration in job 7.74 7.01

Table 4 : Friedman Test

Friedman Test Statistics

Hospital Type

Private Hospitals

Government Hospitals

N 80 70

Chi-Square 146.990 124.911

Df 6 6

Asymp. Sig. .000* .000* Source : Survey Deta*Significant at 5 per cent level of significance

From the above table, it can be observed that the outcomesof the worklife imbalance having the least means areuncontrollable stress (4.14 for lady doctors of privatehospitals) and unable to concentrate on official duty (for3.28 women Gynaecologists of government hospitals).Further, the mean rank variation is statistically significantat 5 percent level of significance. (Observe the value ofFriedman Chi-square, with p<.05).

Table 2 Regression coefficient and R square

Coefficientsa

Model Unstandardized

Coefficients Standardized Coefficients T Sig.

B Std. Error Beta 1 (Constant) 3.235 2.559 5.482 .000*

No Success in family life 2.317 .559 .073 2.355 .009* No Job enrichment 1.726 .574 .143 4.751 .020* Dissatisfaction in family life

2.091 .038 .075 2.381 .028*

No scope for Sharing family responsibility

2.252 .085 .077 2.958 .000*

Job in security 1.608 .038 .457 15.997 .010* No Leisure time in work 1.417 .027 .514 15.621 .020* a. Dependent Variable: Worklife imbalance

ANOVA F Sig. 382.393 .000a

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .894a .830 .726 6.38233

Source : Survey data**Significant at 5 per cent level of significance


( 26 )

CONCLUSION

1. Success in family life, job enrichment, andsatisfaction in family life, sharing familyresponsibility, job security and leisure time work ofwomen Gynaecologists resulted in work and family-life harmony. The impact of these factors on work-to-family life harmony is validated statistically inthe multiple linear regression model with beta co-efficient and corresponding t values, significant at5 per cent level.

2. Considering the outcome of the worklife imbalanceof the women Gynaecologists working in privateand government hospitals, it is found that worklifeimbalance creates uncontrollable stress among thoselady doctors in private hospitals and at the sametime women Gynaecologists working in governmenthospitals are unable to concentrate their official androutine work.

REFERENCES

Adams, G. A., King, L. A., & King, D. W. (1996).Relationship of job and family involvement, family socialsupport and work family conflict with job and lifesatisfaction. Journal of Applied Psychology, 81(4), 411–420.

Amha, W., & Ademassie, A. (2004). Rural financialintermediation program and its role in strengthening therural financial system in Ethiopia. Journal of MicrofinanceDevelopment Review, 3(2), 230–365.

Anitha, H. S., & Lakxmisha, A. A. (1999, 15 June). Womenentrepreneurs. Southern Economist, 38(9), 1–9.

Ayyadurai, S. (2006). An insight into the constraints facedby women entrepreneurs in a war-torn area: case study ofthe northeast of Sri Lanka. Journal of Asia Entrepreneurshipand Sustainability. Retrieved 25 November 2010, from http://findarticles.com/P/articles/ mi_qa5499/is_200607/ai_n21407208/

Barnett, R. (1998). Towards a review andreconceptualization of the work/family literature. Genetic,Social and General Psychology Monographs, 124, 1–50.

Blim, M. (2001). Italian women after developmentemployment, entrepreneurship and domestic work in thethird Italy. History of the Family, 6, 57–270.

Bohle, P., & Tilley, A. J. (1989). The impact of night work onpsychological well-being. Ergonomics, 32, 1089–1099.

Bohle, P., Quinlan, M., Kennedy, D., & Williamson, A.(2004). Working hours, work-life conflict and health inprecarious and permanent employment. Revista De SaúdePubica, 38, 19–25.

Brand, S., Hermann, B., Muheim, F., Beck, J., & Tranchsler,E. H. (2008). Strain among young students in hospitalityand tourism. Industrial Health, 46, 199–209.

Dex, S. & Bond, S. (2005). Measuring work-life balanceand its covariates, Work, Employment and Society, vol.19(3), pp: 627-637.

Frone, M. R., Russell, M., & Cooper, M. L. (1992).Antecedents and outcomes of workfamily conflict: Testinga model of the work-family interface, Journal of AppliedPsychology, vol. 77, pp: 65-78.

George, J.M. (2000). Emotions and leadership: The role ofemotional intelligence , Human Relations, vol.53 (8), pp:1027-1055.

Greenhaus, J. H., & Beutell, N. J. (1985). Sources of conflictbetween work and family roles, Academy of ManagementReview, vol. 10, pp: 76-88.

Gould, S. and Penley, L. (1984). Career strategies and salaryprogression: a study of their relationships in a municipalbureaucracy, Organizational Behavior and HumanPerformance, vol. 34, pp. 244-65.

Hepburn, C. G & Barling, J. (1996). Eldercareresponsibilities, interrole conflict, and employee absence,A daily study, Journal of Occupational Health Psycholog, vol.1, pp: 311-318.

Higgins, C.A & Duxbury, L.E (1992). Work-family conflict:A comparison of dual-career and traditional-career men,Journal of Organizational Behavior, vol.13, pp: 389-411.

Iverson RD, Buttigieg DM (2008). Affective, normative, andcontinuance commitment: Can the right kind ofcommitment be managed, J. Manage. Studies, 36: 307-333.

Jackson, S. E. & Schuler, R. S. (1985). A meta-analysis andconceptual critique of research on role ambiguity and roleconflict in work settings, Organizational Behavior andHuman Decision Processes, vol.36, pp: 16-78.

Kinnunen, U., Feldt, T., Geurts, S. and Pulkkinen, L. (2006).‘Types of Work-Family Interface: Well-Being Correlates ofNegative and Positive Spillover Between Work and Family,Scandinavian Journal of Psychology,vol. 47 (2), pp: 149-1


( 27 )

Netemeyer, Richard G., James. S. Boles, and Robert C.McMurrian (1996). Development andValidation of Work-Family Conflict and Family-Work Scales, Journal of AppliedPsychology, 18 (August), 400-410.

Poele, LT (2003). Emotional intelligence, job satisfactionand collective bargaining effectiveness: A relational study,Journal of Managerial. Psychol, vol.22 (2), pp: 121-130.

Porter, L.W.; Steers, R.M.; Mowday, R.T.; & Boulian, P.V.(1974). Organizational commitment, job satisfaction, and

turnover among psychiatric technicians, Journal of AppliedPsychology, 1974, 59, 603-609.

Porter, L.W.,Crampon, W. & Smith, F. (1976).Organizational commitment and managerial turnover: Alongitudinal study, Organizational Behavior and HumanPerformance, 15, 87-98.

Quick, J. D; Henley, A. B and Quick, J. C (2004). TheBalancing Act At Work and At Home, OrganizationalDynamics, Vol. 33, No. 4; pp. 426-438.

Susha DPart-time Research Scholar in Management Studies,Loyola College of Social Science, Sreekariyam,Thiruvananthapuram,Kerala

Dr.Anitha SResearch Supervising Teacher in Management Studies,Loyola College of Social Science, Sreekariyam,Thiruvananthapuram,Kerala

Dr. P.N.HarikumarAssociate Professor & Head, Post-graduate Departmentof Commerce & Tourism, Catholicate College,Pathanamthitta, Kerala.


( 28 )

INTRODUCTION

Microinsurance is the insurance for low income people, who generally because ofpoverty, unawareness and lower affordability do not have an access to insurancefacilities. Microinsurance is having the potential to assist the poor people to cope upwith shocks, such as health shocks, death, crop loss and natural hazards (Dercon,2005; Dror and Jacquier, 1999; Barnet Barrett and Skees, 2008; Gine Townsend andVickery, 2008). Risks which are uninsured have a welfare implication which go beyondconsequences for short term consumptions and is a cause of persistent poverty (Dercon,2004; Townsend, 1994). Microinsurance as having a protective mechanism has thepotential to reduce these welfare costs. By offering a payout on happening of someunfavorable outcome, it reduces their need to adopt costlier strategies against healthrisks which they cannot bear because of low income. Of all the risks facing poorhouseholds, health risks proba1bly pose the greatest threat to their lives and livelihoods.It thrusts health expenditure on a poor household precisely at a time when they can ill-afford it due to income shortfall resulting from the shock. Moreover, the uncertainty ofthe timings of illness and unpredictability of its costs make financial provision forillness difficult for households receiving low and irregular income (Tenkorang, 2001).Health microinsurance (HMI) offers a promising way to mitigate risks of disease and illhealth, which are disproportionately borne by the world’s poorest citizens. In developingcountries, illness is mentioned more frequently then job loss as the main cause of poverty(Dodd et al., 2002; Asfaw, 2003) and many low-income individuals cannot afford medicaltreatment. Research indicates that 26 per cent of households in low- and middle-income countries resort to selling assets and borrowing to cover healthcare expenses(Kruk et al., 2009), suggesting that there is a huge gap in healthcare financing.

Like other countries, India too has been committed to develop a protective mechanismfor the poor, and to provide them a financial shield against adverse consequences ofrisk exposures. A Universal Health Coverage Program (Rashtriya Swasthya Bima

Key words

Microinsurance, Financialprotection, RashtriyaSwasthya Bima Yojana andFund mobilization

Microinsurance and Financial Protection in India:An Assessment of Rashtriya Swasthya Bima Yojana

Sheikh Aftaab-Ul-Maroof and Mohi-Ud-Din Sangmi

ABSTRACT

Microinsurance aims to provide financial protection to the poor against different perils and their adverseconsequences, and the most critical among them is the risk attached to health. Poor households withlower resource base are often not in a position to bear the rising health expenditure following the healthshock. The present study is an impact assessment of Rashtriya Swasthya Bima Yojana, a Governmentof India sponsored health coverage scheme. The study has been conducted in three north-Indian statessuch as Haryana, Punjab and Himachal Pradesh. The scheme has been assessed in terms of financialprotection available to the beneficiaries who availed the scheme. Overall, the health coverage scheme hasbeen successful in reducing the hospital expenditure of the poor households together with improvingtheir fund mobilization and smoothing the household consumption at the time of health shock.


( 29 )

Yojana) was started by the Government of India in 2008,to cover in-patient healthcare expenditures of belowpoverty line households, and hence the steps were initiatedto develop Health Microinsurance within the country. Thepresent study is an attempt to assess the working ofRashtriya Swasthya Bima Yojana, a microinsurancemechanism, in terms of providing financial protection tothe people under poverty.


Impact encompasses the changes that microinsurancemakes to the economic or social circumstances of insuredpeople or their households, enterprises or communities. Itcan be positive or negative, affect both insured anduninsured populations, occur either before, ex-ante, orafter, ex-post, insured events happen, and have micro-,mezzo- and macro-level implications, often in ways thatare linked.

Financial protection occurs when microinsurancesafeguards low-income households form using inefficientcoping mechanisms in response to shocks and stress.These mechanisms can include depleting savings andadditional supplies of goods like food land livestock,selling valuable and sometimes income-generatingpossessions, borrowing at typically high interest rates,adjusting labour supply, altering purchasing andconsumption patterns, engaging in reciprocal mutualsupport practices, capitalizing on self-help groupmemberships and withdrawing children from school togenerate the resources necessary to handle the shocksinvolved (Radermacher et al., 2012). Besides reducingreactive measures taken by households in crisis, thefinancial protection provided by microinsurancetheoretically allows individuals to proactively makedecisions that improve their incomes and standards ofliving. Microinsurance is believed to encourage“households to allocate resources to more profitable ends(which were previously precluded for being too risky)”(Morduch, 1995). After reviewing the current literatureon HMI, the major indicators of financial protection hasbeen identified by Pamer et al. (2012); Naguyen et al., (2012);Wagstaff and Yu, 2007; Wagstaff and Lindelow, (2008);Wagstaff et al., (2009); King et al. (2009); Galarraga et al. (2010);Thornton et al. (2010); Jowert et al. (2004); Wagstaff andPradhan, (2005); Aggarwall, (2010); and Chanakova et al.(2008), are as:

• Health expenditure (which includes out-of-pocketexpenditure and catastrophic expenditure).

• Fund mobilisation.

• Income and consumption smoothing

The most important and direct impact of health insuranceis on out-of-pocket (OOP) health expenditure. Studies fromVietnam like Jowertt et al. (2003) have observed that healthinsurance reduces average OOP expenditure byapproximately 200%. In the same line Healthcare Fundfor Poor (HCFP), not only reduces sharply the OOPexpenditure, but was also successful in reducing thecatastrophic payment following the health shock (Phamand Pham, 2012). A very popular health insurance schemein Mexico known as Seguro Popular (SP) has beensuccessful in reducing the OOP and catastrophic healthexpenditure (Galarraga et al., 2010). The same observationis true of a couple of studies from China where a positiveimpact of health insurance on OOP and catastrophicexpenditures has been found (Wagstaff and Lindelow,2008; Wagstaff et al., 2009). Evidence from Ghana(Naguyen et al., 2011) also indicate that the NationalHealth Insurance Program running in the country has beenable to achieve a reduction in OOP expenditure that rangesfrom 0.5 percentage points to 1 percentage point (whichamounts to a reduction of 36% to 67% of the sample mean).

There are number of strategies available to a household tosupport OOP health expenditure like using cash andexisting savings, sale of assets, loans, incomediversification, wage labour, etc. There are other time-coping strategies like intra-house labour substitution,changing the capital labour mix of production, hiringlabour, free community labour etc. Out of the abovementioned strategies depleting savings, selling productiveassets (livestock etc) and taking loan at higher cost affectsthe household in longer run. Parmer et al. (2012) in theirstudy found that in the absence of adequate savingshousehold resort to selling productive assets like live stock,which could have asserted the household in agriculturalproduction (e.g. Ox or Donkeys). Due to the availability ofa few research studies, evaluating the impact onmobilization of funds by a poor household following ashock, there is a need of further research as also realizedby Parmer et al. (2012) and Radermacher et al. (2012).

Severe adverse health event imposes the twin challengesof both coping with the expenses of the events in questionand continuing to meet on-going household needs(Radernacher et al. 2012). Under such pressingcircumstances, low-income people may pursue anundesirable action like eating less or less nutritious food.


( 30 )

By reducing the financial burden of shocks,microinsurance aims to enable policyholders to maintaintheir incomes and standards of living in times of crises(Radermacher et al. 2012).

After assessing the above raised issues, the role ofmicroinsurance seems to be wider and quite significant inproviding protection to the poor. Most of the studiesconducted earlier, have restricted their assessment tohealthcare expenditures only, while evaluating thefinancial protection dimension. Health risk as having acatastrophic exposure and microinsurance a significantrole, the financial protection needs to be assessed in abroader way by including fund mobilization andconsumption (Radermacher et al., 2012).

OBJECTIVES

The study has been undertaken to achieve the followingobjectives:

1. To study the impact of health microinsurance oninpatient healthcare expenditure.

2. To assess the incidence of catastrophic expenditureamong the policy holders as compared to non-policyholders.

3. To critically evaluate the source of finances availedby the households for supporting healthcareexpenditure.

4. To assess the impact of Health Microinsurance onEssential Household Consumption

HYPOTHESIS

There is no significant difference between Inpatienthealthcare expenditures of policy holders as compared tonon-policy holders.

DATA COLLECTION

The study is mainly based on primary data and the datacollection was done by using a pre-tested and structuredinterview schedule from beneficiaries of RashtriyaSwasthya Bima Yojana. A total of 450 respondents fromthree North-Indian states (Himachal Pradesh, Punjab andHaryana) have been contacted during the survey. Out ofthem 150 were RSBY enrolled and 300 not-covered underRSBY households. From each state, data has been collectedfrom one district performing better in terms of enrolling

poor under RSBY (See table 1.1) for the sample composition.The selection of sample is described as follows:-

SAMPLING DESIGN

The impact of microinsurance is assessed by a comparisonof ‘treatment’ group, consisting of programme participants,to a ‘control’ group of non-participants. Participant groupof respondents were selected after receiving list of insuredhouseholds from the Ministry of Labor and Employment,Government of India, where at least one hospitalizationwas occurred and where the household has received thetreatment. Participant group of respondents were selectedthrough a multi-stage sampling method. Each nonparticipant household for comparison was selected fromthe same locality where a participant household waslocated after taking the due care that the characteristics ofparticipant and non-participant should be similar.

Table 1.1 : Sample composition

S.NO State (District)

No. of Insured

HH

No. of Uninsured

HH Total

1 Himachal Pradesh (Kangra)

50 100 150

2 Punjab (Amritsar) 50 100 150

3 Haryana (Rohtak) 50 100 150

Total Households 450

PERIOD OF THE STUDY

The present study has collected the data from therespondents pertaining to the year 2013-14.

RESULTS AND DISCUSSION

The study has been conducted under the following heads:-a) Health Expenditure (out-of-pocket)b) Fund mobilization to support healthcare

expenditurec) Financing healthcare expenditure by the Sale of

Household Assetsd) Consumption Protection

(a) Health expenditureOut-of pocket expenditureReducing healthcare expenditure is one of the basicobjectives of RSBY. Results reveal that it has been able toachieve its target to a greater extent as inpatient OOPE per

Microinsurance and Financial Protection in India: An Assessment of Rashtriya Swasthya Bima Yojana

( 31 )

hospitalization is significantly lower for the RSBYhouseholds as compared to the Non-RSBY households.Table 1.2 shows the significant difference between the twogroups of respondents (Insured and Uninsuredhouseholds). The t values being more than 1.96, the nullhypothesis in this case is rejected.

Incidence of Catastrophic Expenditure (CE)

Out of pocket Expenditure (OOPE) becomes catastrophicwhen it absorbs a considerable amount of annualhousehold income (often defined as 10 per cent)(Radermacher et al., 2012). Table 1.3 shows the incidenceof catastrophic expenditure. Among the sampled RSBYhouseholds 4.67% of the households have incurredcatastrophic healthcare expenditure, where as it is 53.67%in case of households not covered under RSBY, whichclearly highlights a protective shield.

(b) Fund Mobilization to support healthcareexpenditure

Poor households in case of health shocks use adversestrategies for mobilizing funds. Table 1.4 shows that thehouseholds not-covered under RSBY have householdsavings and borrowings as their main source of finance tosupport inpatient health expenditure, but in case of Treated

group major source is household savings to support out-of- pocket expenditure. Importantly there are 1.33% ofhouseholds in case of control group who have soldhousehold assets to support health expenditure, but suchhouseholds are not found within the control group, henceshows a positive sign.

Table 1.5 further elaborates the type of borrowings whichhouseholds raise are not often without interest, andtherefore, adds to the worry of the poor households.Households under RSBY are not compelled to raise hugeamount of money through borrowings, as being under thecover. Hence, to support the out-of-pocket expenditure,they have managed small borrowings from friends andrelatives and these are generally without interest.Households without RSBY cover, in contrary to it, arecompelled to borrow money on heavy interest rates, fromthe money lenders due to the requirement of large amountof money for treatment.

Furthermore, in rural areas people pay interest to moneylenders on monthly basis and table 1.6 shows that it isaround 2% to 3% per month which compounds annually,thus adds to the misery of these households.

Table 1.2 : Out-of-Pocket ExpenditureVariable Sample Treated Control Difference S.E T-stat

Inpatient OOPE per Hospitalization

Unmatched 1418.17 8005.75 -6587.58 853.85 -7.72 ATT 1459.61 8025.95 -6566.33 2070.40 -3.17

Table 1.3 : Incidence of catastrophic expenditureIncidence of Inpatient

CE Status of Sampled Household Total Control Treated

Not incurred CE 139 (46.33%) 143 (95.33%) 282 (62.67%) Incurred CE 161 (53.67%) 7 (4.67%) 168 (37.33%)

Total 300 (100%) 150 (100%) 450 (100%)

Table 1.4 : Sources of Finance

Source of finance to support Inpatient treatment

Status of Sampled Household Total Control Treated RSBY 0 (0%) 1 (0.67%) 1 (0.22%)

HH Savings (A) 128 (42.67%) 144 (96%) 272 (60.44%) Raised borrowings (B) 26 (8.67%) 1 (0.67%) 27 (6%)

Sold Household assets (C) 2 (0.67%) 0 (0%) 2 (0.44%) D=A+B 138 (46%) 4 (2.67%) 142 (31.55%) E=A+C 4 (1.33%) 0 (0%) 4 (0.88)

F=A+B+C 2 (0.67%) 0 (0%) 2 (0.44%) Total 300 (100%) 150 (100%) 450 (100%)


( 32 )

(c) Financing the healthcare expenditure by Sale ofHousehold Assets

An attempt has also been made to assess the sale ofhousehold assets by the poor households, to support theirhealthcare expenditure. Information has been acquiredabout the realized and market value of the asset that weresold to support out-of-pocket health expenditure. Therewere only 8 households where assets have been sold andthese belong to the households not-covered under RSBYand 6 out of them have suffered loss on sale (table 1.7).

Table 1.8 shows that all the assets sold were non incomegenerating, which reveals no loss of a household asset asa source of income.

(d) Consumption Protection

Poor households in adverse conditions, to support the out-of-pocket health expenditure, reduce the essential non-medical household consumption expenditure, likeexpenditure on food, children education, clothes, housingetc. Table 1.9 clearly shows that health expenditure hasdisturbed the essential household consumption more incase of non-RSBY households (40.67%). 15.34% ofhouseholds covered under RSBY have reported ofreduction in household consumption which is a positivesign as compared to households not-covered under RSBY.

Table 1.5 : Type of Borrowing

Type of Borrowing (Inpatient)

Status of Sampled Household Total Control Treated

Interest based 98 (59.76%) 2 (40%) 100 (59.17%) Non-interest based 66 (40.24%) 3 (60%) 69 (40.83%)

Total 164 (100%) 5 (100%) 169 (100%)

Table 1.6 : Average Rate of interest (monthly) at which borrowed

Rate interest Status of Sampled Household

Control Treated 2.51% 2%

Table 1.7 Occurrence of Loss on the sale of Asset

Occurrence of Loss (Inpatient)

Status of Sampled Household Total Control Treated 0 (No loss occurred) 2 (25%) 0 (0%) 2 (25%)

1 (loss occurred) 6 (75%) 0 (0%) 6 (75%) Total 8 (100%) 0 (0%) 8 (100%)

Table 1.8 Shows kind of Asset Sold

Asset sold Status of Sampled Household Total Control Treated Income generating 0 (0%) 0 (0%) 0 (0%)

Non-income generating 8 (100%) 0 (0%) 8 (100%) Total 8 (100%) 0(0%) 8(100%)

Table 1.9 Impact of illness on Essential household consumption

Household consumption

Status of Sampled Household Total Control Treated Reduced 122 (40.67%) 23 (15.34%) 145 (32.23%)

Remained same 178 (59.34%) 127 (84.67%) 305 (67.78%) Total 300 (100%) 150 (100%) 450 (100%)


( 33 )

CONCLUSION

Microinsurance provides a promising protectivemechanism against risk exposures which often havepressing financial implications. Rashtriya Swasthya BimaYojana (RSBY) being a government of India sponsoredhealth coverage scheme, has been successful in providingthe financial protection by reducing health expendituresof policyholders significantly. It has restricted the poorhouseholds to use costlier sources of finances by providingthe financial support. Poor households are less compelledto sell their household assets. It has helped in smoothingthe essential household consumption in times of healthshock.

REFERENCES

Dercon, S. 2005. Insurance against poverty. Oxford UniversityPress.

Dercon, S. 2004. Growth and shocks: Evidence from ruralEthiopia. Journal of Development Economics, 74, 309–329.

Dror, D. M., & Jacquier, C. 1999. Microinsurance: ExtendingHealth Insurance to the Excluded. International socialsecurity review, 52(1), 71-97.

Barnett, B. J., Barrett, C. B., & Skees, J. R. 2008. Poverty trapsand index-based risk transfer products. WorldDevelopment, 36(10), 1766-1785.

Giné, X., Townsend, R., & Vickery, J. 2008. Patterns ofrainfall insurance participation in rural India. TheWorld Bank Economic Review, 22(3), 539-566.

Townsend, R. M. 1994. Risk and insurance in village India.Econometrica: Journal of the Econometric Society, 539-591.

Dodd, R., & Munck, L. 2002. Dying for change: Poorpeople’s experience of health and ill health (Geneva,World Health Organization, World Bank, Voices ofthe Poor).

Asfaw, A. 2003. Costs of illness, demand for medical care, andthe prospect of community health insurance schemes inthe rural areas of Ethiopia. Peter Lang Publishing.

Kruk, M. E., Goldmann, E., & Galea, S. 2009. Borrowingand selling to pay for health care in low-and middle-income countries. Health Affairs, 28(4), 1056-1066.

Morduch, J. 1995. Income smoothing and consumption

smoothing. The journal of economic perspectives, 103-114.

Radermacher, R., McGowan, H., & Dercon, S. 2012. Whatis the impact of microinsurance. Microinsurancecompendium, 2.

Parmar, D., Reinhold, S., Souares, A., Savadogo, G., &Sauerborn, R. 2012. Does CommunityBased HealthInsurance Protect Household Assets? Evidence fromRural Africa. Health services research, 47(2), 819-839.

Wagstaff, A., & Yu, S. 2007. Do health sector reforms havetheir intended impacts? The World Bank’s HealthVIII project in Gansu province, China. Journal of healtheconomics, 26(3), 505-535.

Wagstaff, A., & Lindelow, M. 2008. Can insurance increasefinancial risk? The curious case of health insurancein China. Journal of health economics, 27(4), 990-1005.

Wagstaff, A., Lindelow, M., Jun, G., Ling, X., & Juncheng,Q. 2009. Extending health insurance to the ruralpopulation: An impact evaluation of China’s newcooperative medical scheme. Journal of healtheconomics, 28(1), 1-19.

Thornton, R., L. E. Hatt, E. M. Field, M. Islam, F. Solis Diaz,and M. A. Gonzalez. 2010. Social security healthinsurance for the informal sector in Nicaragua: Arandomized evaluation. Health Economics 19(1), 181-206.

Wagstaff, A., & Pradhan, M. 2005. Health insurance impactson health and nonmedical consumption in a developingcountry (Vol. 3563). World Bank Publications.

Nguyen, H. T., Hatt, L., Islam, M., Sloan, N. L., Chowdhury,J., Schmidt, J. O., ... & Wang, H. 2012. Encouragingmaternal health service utilization: an evaluationof the Bangladesh voucher program. Social science &medicine, 74(7), 989-996.

King, G., Gakidou, E., Imai, K., Lakin, J., Moore, R. T., Nall,C., ... & Ávila, M. H. 2009. Public policy for the poor?A randomised assessment of the Mexican universalhealth insurance programme. The lancet, 373(9673),1447-1454.

Jowett, M., Deolalikar, A., & Martinsson, P. 2004. Healthinsurance and treatment seeking behaviour:evidence from a low-income country. Healtheconomics, 13(9), 845-857.


( 34 )

Galárraga, O., Sosa-Rubí, S. G., Salinas-Rodríguez, A., &Sesma-Vázquez, S. 2010. Health insurance for thepoor: impact on catastrophic and out-of-pockethealth expenditures in Mexico. The European Journalof Health Economics, 11(5), 437-447.

Chankova, S., Sulzbach, S., & Diop, F. 2008. Impact ofmutual health organizations: evidence from WestAfrica. Health policy and planning, 23(4), 264-276.

Aggarwal, A. 2010. Impact evaluation of India’s‘Yeshasvini’communitybased health insuranceprogramme. Health Economics, 19(S1), 5-35.

Jowett, M., Contoyannis, P., & Vinh, N. D. 2003. The impactof public voluntary health insurance on privatehealth expenditures in Vietnam. Social Science &Medicine, 56(2), 333-342.

Pham, T. T. T. & Pham, T. L. 2012. Does microinsurancehelp the poor? Evidence from the targeted healthmicroinsurance program in Vietnam 2004-2008.Microinsurance Innovation facility, InternationalLabour Office, Geneva.

Sheikh Aftaab-Ul-MaroofSenior Research FellowDepartment of Business Financial StudiesUniversity of Kashmir

Email : [email protected]

Prof. Mohi-Ud-Din SangmiDepartment of Business and Financial StudiesDirector, Human Resource Development CentreUniversity of Kashmir



( 35 )

INTRODUCTION

The Indian Telecom Industry is one of the fasted growing sectors globally. The revenueis growing by approximately 15 % per annum. Indian government has provided aconductive environment for service providers. Therefore, the sector has become verycompetitive and the services are available up to the reach of last mile population at veryaffordable rates. The mobile services market is diverting from voice services to data(Internet) services rapidly. Latest 3G and 4G technologies are operational in variousmajor cities and districts. There will be huge growth in coming years as the governmentalso declared many ambitious projects like Digital India campaign, Smart City program,creation of Wi-Fi zones and Hot Spots around import tourist & commercial places etc.More than 1.1 billon US$ investment will be made in these programs. As per study ofGSMA (GSM Association) 67 % mobile phones will be smart phones by 2020. Theoverall Tele-density of India is 80 %. Total connections have touched the mark of oneBillion (as on 30.04.15). The details of operator-wise market share are as shown belowin Table-1:

Table-1S.

No. Name of Operator Market Share

S. No. Name of Operator

Market Share

1 Bharti Airtel 23.18 8 Uninor 4.68 2 Vodaphone Essar 18.47 9 Sistema Shyam 0..89 3 Idea 15.93 10 MTNL 0.71 4 Reliance Telecom 11.10 11 Videocon 0.73 5 BSNL 9.37 12 Quadrant Televentures 0.30 6 Aircel 8.21 13 Loop Mobile 0 7 Tata Indicom 6.43 Total 100

Key words

Mobile Service Quality,Internet, Data services,Customer Services, Tariff,Customer Loyalty,Switching intention,Loyalty, Churn, CustomerSatisfaction

Service Delivery and Customer Satisfaction inMobile Communication Sector in India(With Specific Reference to West Central India)

P.K. Sharma and Vishwas Pandey

ABSTRACT

The Indian Telecom Industry is one of the fasted growing sectors worldwide. This sector is dominated bya few operators in each circle (State). Ever-increasing use of internet in each part of human life has madethis service luxury to most essential. The voice service is being dominated by data services. Users arebothered more about internet speed than clarity of voice. Here the question comes of quality. Measuringcustomer’s satisfaction provides an indication of how successful the organization is in providing servicesto the market. The primary objective of this research is twofold: (i) Constructing a scale for measuringoverall mobile service quality keeping focus on Internet ( Data) services , and (ii) Examining the effectsof mobile Service Quality, Tariffs, Customer Care Services and Perceived value on customer satisfaction.This research tried to establish relationship among customer satisfaction with service quality, tariffs, andcustomer care services. This research also tried to establish the relationship between overall satisfactionand switching intention among mobile phone users. This study will be helpful to Telecom players toanalyse reasons of customer’s dissatisfaction, parameters important for quality of service and ultimatelyhow to retain the existing customers and gain the market share.


( 36 )

Presently around 40% mobile phones are smart phones.By 2020 , the use of smart mobiles phones will increasethree times. Due to falling cost, ease of operation, improvedusability, better network coverage, smart mobile phonesare becoming choice of every mobile user. Most of the dayto day essential activities are being done through use ofsmart phones such as shopping, health services, insurance,recruitment , Govt. functions, complaints, banking,education, entertainment, personal identity (Aadhar) andso on uncounted list of works. Presently 30 % subscribersare urban and 70 % are rural. The demand of smart phoneis increasing in rural area. The mobile application marketis also growing by the rate of 70 %.

All the above mentioned services are data driven. Theyneed an internet connection to use. Here network qualityof services providers plays very important role. Customerservice is another vital dimension for a service providerbecause it is the platform where a customer contacts witha company or vice versa. Consequently, when they have aquestion or product/Service issue, they expect a company’scustomer service department to resolve their issues. It isalso important to an organization because it can helpdifferentiate a company from its competitors.

The objective of the study is to assess the extent to whichthe fundamentals of quality management are beingpracticed by Telecom operators in India, identify barriersand to suggest measures for improving theircompetitiveness by adopting best quality practices. Thisstudy tried to identify the gap in customer satisfactionlevel, quality of service being rendered to customers ofmobile services.

INSIGHTS

Customer satisfaction represents a modern approach forquality in enterprises and organizations and serves thedevelopment of a truly customer-focused management andculture. Customer satisfaction measures offer a meaningfuland objective feedback about client’s preferences andexpectations. Customer Satisfaction research is one of thefastest growing segments of the marketing field. Marketingand management sciences, nowadays, are focusing on thecoordination of all the organization’s activities in order toprovide goods or services that can satisfy best specificneeds of existing or potential customers. To reinforcecustomer orientation on a day-to-day basis, a growingnumber of companies choose customer satisfaction as theirmain performance indicator. However, it is almost

impossible to keep an entire company permanentlymotivated by a notion as abstract and intangible ascustomer satisfaction. Therefore, customer satisfactionmust be translated into a number of measurable parametersdirectly linked to people’s job-in other words factors thatpeople can understand and influence. The literaturereviewed below is relevant to the research theme andcategorized into four thematic areas; the concept ofCustomer Satisfaction, Perceived Service Quality, Tariff(Perceived Price), Perceived Switching Cost (Retention).

Customer Satisfaction: The most common interpretationsobtained from various authors reflect the concept thatsatisfaction is a feeling which results from a process ofevaluating what has been received against what wasexpected including the purchase decision itself and theneeds and wants associated with the purchase (Armstrongand Kotler, 2014)[1]. Zeithaml and Bitner (2003)[2] statedthat satisfaction is the customers’ evaluation of a productor service in terms of whether that product or service hasmet their needs and expectations. According to Boselie,Hesselink, and Wiele (2002) [3] satisfaction is a positive,affective state resulting from the appraisal of all aspects ofa party’s working relationship with another. Thedefinition provided by Boselie et al. (2002) [3] has beenused for this study. All the above indicate the importanceof identifying customer satisfaction (Gulledge, (1996) [4] ;Metawa and Almossawi, 1998) [5]. However, this is not aneasy task because customers’ expectations are difficult tomeasure and businesses come to know only after theproduct has already been delivered (Bamfo, 2009) [6]. Sadia,Tasneem, and Khan (2011) [7] examined customer loyaltyin the telecommunication industry in Pakistan and foundthat customer loyalty is shaped mainly by: trust, servicequality, staff loyalty, and switching cost. The results ofthis study agree, partially, with a study by Boohene andAgyapong (2011) [8] of 460 clients of Vodafone TelecomCompany in Ghana. This study concluded that satisfactiondoes not necessarily lead to loyalty, while service qualitywas found to be strongly and positively correlated withloyalty. However, it can be noticed from the findings ofthis study that customer satisfaction is already built intoservice quality.

Customers perceive service quality positively if they aresatisfied with the service provider and with the servicesoffered to them. The importance of service quality in thechoice decision for a mobile phone operator was alsoemphasized by Rahman, Haque, and Ahmad (2011) [9]

who conducted a study of 400 mobile telecom customers

Service Delivery and Customer Satisfaction in Mobile Communication Sector in India (With Specific Reference to West Central India)

( 37 )

from major cities in Malaysia. This study concluded thatnetwork quality is one of the important factors in overallservice quality. In addition to service quality, the studyfound that price plays an important role in the choicecriteria for mobile telephone operators in Malaysia. Theyconcluded that in order to retain customers and attractnew customers, mobile service providers must provide“service with reasonable quality without any hidden price,the two most important determinants of consumersatisfaction”. .

Service Quality: Compared with physical products,Service is thought to be intangible, heterogeneous,produced and consumed simultaneously, unable to be keptin stock . A widely accepted definition of service is proposedby Grönroos (2000) [10] as: A service is a process consistingof a series of more or less intangible activities that normally,but not necessarily always, takes place in interactionsbetween the customer and service employees and/orphysical resources or goods and/or systems of the serviceprovider, which are provided as solutions to customerproblems. This definition implied that service is a processwhere interactions between customer and service providermost often exist. Hence, in a service context, there is almosta relationship between customer and service provider;such relationship can be used as a basis for marketing. Inorder to retain loyal customers who will bring long-termprofit to the firm, the key issue for service provider is tomake use of this relationship in the way it managescustomers by offering what customers’ need and want.The quality of a service is subjectively perceived bycustomers during the interactions with a firm.

Parasuraman et al. (1988) [11] defined service quality as the“Consumers’ judgment about a firm’s overall excellenceor superiority”. What is perceived by customers in theinteraction process will obviously have critical impact oncustomers’ evaluation of service quality (Grönroos, 2000)[10] Due to the peculiar attributes of service, the evaluationof service quality is more complex than evaluation ofproduct quality. There have been various ways formeasurements of service quality proposed by previousresearches and literatures. The famous measurement modelof service quality is SERVQUAL developed byParasuraman et al. (1988) [11], who measured the differencebetween customer expectations and perceptions by fivedeterminants like: Tangibles, Reliability, Assurance,Responsiveness and Empathy.

Perceived Price : Price is distinguished between objectiveprice (the actual price of a product) and perceived price(the price as encoded by the consumer) (Jacoby and Olson,1977) [12]. This distinction indicates that the objectivemonetary price is frequently not the price encoded by theconsumer. Zeithaml (1988) [13] also delineated thecomponents of price: objective price, perceivednonmonetary price, and sacrifice. Some studies reveal thatconsumers do not always remember the objective prices ofproducts, but they do encode prices in ways that aremeaningful to them (Zeithaml, 1982, 1983, 1988) [14][15][13].Perceived price can be defined as “the customer’s judgmentabout a service’s average price in comparison to itscompetitors” (Chen et al., 1994) [16[. Perceived price focuseson customers’ concerns as to whether they are beingcharged more than or about the same as charged bycompetitors. Zeithaml (1988) [13] insisted that consumerperception of value is highly related to the perception ofprice, and that the measurement of perceived value includesprice perception. The National Council of the GreenConsumers Network (2012) in Korea reported that manymobile phone subscribers were dissatisfied with the leveland types of service charges. Ryu and Han (2010) [17] foundthat the perceived price has a significant effect on therelationship between quality and customer satisfaction inthe quick-casual restaurant industry. That is, customers’perception of a reasonable price enhances the effect ofservice quality on customer satisfaction.

Perceived Switching Cost : Switching cost is defined asthe cost of changing services in terms of time, monetaryvalue, and psychological factor (Dick and Basu, (1994) [18];Lai L., (2011) [19]). Switching cost includes the search cost(the cost of time spent for searching information) and thetransaction cost (the cost of time and effort) (Schlesingerand Schulenburg, 1991) [20] . In the case of mobile phoneservices, the intention of customers to churn reduces dueto switching costs, such as time spent for searchinginformation about subscript conditions and the effortneeded for changing mobile phone service providers.Additionally, switching cost not only produces barriers tocustomer churn, but also weakens the effect of satisfactionon customer loyalty. Their results show that whencustomers perceive that they must spend a greater amountof time and effort to search for service providers with ahigher level of customer satisfaction, they are more willingto keep their current service providers regardless of howhigh or low the satisfaction is.


( 38 )

STATEMENT OF THE PROBLEM

This research study is propelled by the need to empiricallymeasure customer satisfaction with service delivery ofMobile Telecommunication services in INDIA. The stateof customer satisfaction with service delivery is not clearas there is very little documentation of the issue in WestCentral India. The industry has witnessed a remarkableincrease in subscriber growth rate for all the mobile telecomoperators. This growth trend could not be recognized tocustomer satisfaction; it is fundamentally due to thesubstantial growth in investment and expansion ofnetwork access during the past years. This seems a successstory, and there are high hopes that the service qualitydelivered by the Mobile Telecommunication Networks inIndia meets customer expectations, ideal service orsatisfaction.

However, since the beginning of mobile telephony, therehad been many complaints from customers about theservice delivery of the Mobile TelecommunicationNetworks in India. From the firm’s perspective, it isimportant to ensure that customers are satisfied with theproduct they purchase as well as with the way the productis delivered. Customers have specific needs, expectations,and perceptions, but if a company is not able to exceed orat least meet these expectations the customer becomesdissatisfied and probably does not consider a repurchase.One prerequisite for customer satisfaction is, therefore, thatthe company knows their customer’s needs andexpectations. Satisfying customers is essential to thecontinuous existence of any customer-focusedorganization, including telecommunication companies inIndia. This fact has supported the researcher’s interest inconducting an analysis of customer satisfaction in theIndian Telecommunication industry with emphasis onmobile telephony. It is against this backdrop that, the studyseeks to empirically assess/determine the degree ofsatisfaction customers get from the services provided byIndian Cellular Mobile Telecom Operators. The mainproblem in which the research focuses is the qualitymeasures that help to improve service quality and customerloyalty which is identified by asking relevant questions tothe customers of different service providers. Theinformation needed for the study is the customer’sperception level of using mobile services of different serviceproviders, an overview of the problem, situation and whatsort of problems the subscriber faces regarding theseservices. For this research, judging perception aboutquality and loyalty level for the mobile services have been

obtained by asking questions and doing survey on theusers of different service providers. After a careful studyand to the best of the researcher’s knowledge, a few ofsuch related studies existed in West Central India.However, such studies did not make attempt to linkcustomer satisfaction with overall satisfaction, reliabilityof services, switching intentions and perceived value inthe Indian mobile telecoms industry, which this studyseeks to achieve.


Based on literature review and in depth study of customersof mobile services , it is proposed to achieve the certainobjectives through the proposed study .The primaryobjective of this study was to develop a tool to measureoverall customer satisfaction of mobile phone users and toprovide a suggestions to telecom operators to improve theirQuality of Services (QOS) which in turn will improvecustomer satisfaction and eventually customer retention.

SCOPE OF THE STUDY

The study was limited to GSM Mobile Telecommunicationservice providers in India. Again, only subscribers whouse these networks within India were used in the studyfor analysis. Moreover, customers in this study werelimited to only individuals and not institutions who arealso customers of significance in considering customersatisfaction with service delivery. Furthermore, this studydidn’t measure and analyze customer satisfaction withspecific services delivered by each of the MobileTelecommunication Networks in India. The survey wasconducted and restricted to subscribers using the Fourmajor GSM mobile phone operators (BSNL, Airtel,Vodafone and Idea) in West Central region of India.

RESEARCH METHODOLOGYMeasurement and Scaling Process

For measurement and scaling, Non-Comparativetechnique was selected because each object was scaledindependently from other objects in the stimulus test. ALikert Scale had been used for the measurement andscaling. A Likert scale is a psychometric scale commonlyused in questionnaires and is the most widely used scalein survey research such that the term is often usedinterchangeably with rating scale even though the two arenot synonymous. When responding to a Likertquestionnaire item, respondents specify their level of


( 39 )

agreement to a statement. For gaining full view ofcustomer’s perception of the prepaid services and theirresponse level on each questions five response categoriesare used starting from “Very Unsatisfied” to “VerySatisfied”. To conduct the analysis, each statement wasassigned a numerical score ranging from 1 to 5. So thepoint of very satisfied is “5”, and very unsatisfied is “1”.To confirm the content validity, the measures for allconstructs were taken from the existing literatures. Fiveitems were used to measure the Service Quality: Sixth itemis “Overall Network quality of this provider”. These itemswere rated by “Very Unsatisfied”, “Unsatisfied”, “NeitherSatisfied nor dissatisfied” “Satisfied” and “VerySatisfied”. These items were used to measure the overallnetwork quality of services based on a series of adjectives.To measure perceived price (Value for Money and Tariff),ten items were used and eleventh was “How will youover all rate Value for money “? Six items were used tomeasure customer satisfaction and seventh item was“Overall, how satisfied are you with this provider”? Theseitems were also measured on a Five-point Likert scaleranging from “Very dissatisfied” to “Very satisfied.”Customer loyalty is related to a service provider’s abilityto maintain its customers’ loyalty and persuade them torecommend its services to potential customers (Zeithamlet al., 1996) [21] . Two items were used to measure customerloyalty (Cronin et al., 1997 [22] ; Brady and Robertson, (1999)[23]: “The chance that I would use this service provideragain” and “The probability that I would recommend thisprovider’s services to a friend.” These items were measuredon a five-point Likert scale ranging from “Very low” to“Very high.” One item was used to measure Perceivedvalue on five point Likert scale. Perceived value was atradeoff between what customers gain and what theysacrifice (Cronin et al., (1997) [22] ; Zeithaml, (1988) [13] ,Lee, 2010a [24] ). Perceived value was measured by a singleitem: “Overall, the value of this provider’s services to me ishigh,” and was assessed on a five-point Likert scaleranging from “Strongly disagree” to “Strongly agree”.

The purpose of this research was to examine customersatisfaction , reliability of services rendered and customerloyalty in the Indian Mobile Telecommunications operatorswith considering four major players in the sector and alsoto measure the switching intention of mobile network usersin India. The population consisted of individual customersof mobile telecommunication operators in India ( BSNL,Airtel, Vodafone and Idea). In order to collect data of highquality that reflected the customers’ opinion, a survey was

conducted among the customers of four major GSM mobiletelecom service providers in West Central India. Thesample consists of 208 telecom subscribers. To improverepresentativeness, data collection was done in the socioeconomic zones of the West Central India , using a simplerandom sampling technique. This was aimed at having afair spread of the sample to enable the researcher build aninformed judgment about the general customer satisfactionlevel in India.

Research Hypotheses

The following Hypotheses are stated in the null form forthe purpose of study:

Ho1 There is no significant relationship betweenNetwork Quality and overall customer satisfactionof Mobile Telecommunication services in India.

Ho2. There is no significant relationship betweenReliability ( Value for Money and Tariff ) andcustomer satisfaction

Ho3 There is no significant association betweenCustomer Loyalty and Churning (MNP) amongcustomers of Mobile Telecommunication services inIndia.

RELIABILITY AND VALIDITY

Before assessing the service quality it was necessary toestablish the validity and reliability of the instrument fordata collection. Concerning the reliability of the instrumentfor the internal service quality scores, the Cronbach’s alpharesulted in the values indicated in Table 2. These resultsare similar as those found in the literature, e.g. 0.920 byParasuraman et al. (1988) [11] , 0.900 and 0.927 by Frostand Kumar (2001) [25] . Therefore, the results of total scalefor the developed instrument could be considered reliable.

Table 2: Source SPSS V.22 Output,2015

Case Processing Summary N % Cases Valid 208 100.0

Excludeda 0 .0 Total 208 100.0

Reliability Statistics Cronbach's

Alpha N of Items .805 27


( 40 )

LIMITATIONS

Exhaustive Survey was not be possible due to shortage oftime and large size of population. Ignorance/Carelessnesson the part of respondents may affect results. As thesampling size is small, results of survey may not berepresentative. Survey was restricted to West Central Indiaonly so overall view of industry couldn’t be judged. Noncooperation of Telecom Operators also affected the results.

DATA ANALYSIS AND INTERPRETATION

This section presents the data generated for the study. Theresults are interpreted and the findings discussed. Whilepercentage scores were used to analyze the data, correlationanalysis was used to test the hypotheses. The interpretationfrom the data so collected and the results obtained fromthe test of hypotheses are hereby presented in Table-3

Table 3 : Distribution and Retrieval of Questionnaire

Operator Questionnaire distributed

Questionnaire Received

Valid Percent

Cumulative Valid

Percent BSNL 70 53 25.48 25.48

AIRTEL 70 49 23.56 49.04 VODAFONE 70 58 27.88 76.92

IDEA 70 48 23.08 100 TOTAL 280 208 100

To achieve the objectives of the study, 280 questionnaireswere distributed out of which 208 questionnaires werereturned. The researcher was able to use 208 or 74.8 %collection rate . The percentage of Respondents are shownin above Table No.2

SERVICE DELIVERY AND OVERALL CUSTOMERSATISFACTION (HO1)

Analysis was done using a Pearson product-moment correlation coefficient through SPSS V.22 to assessthe relationship between Network Quality service deliveryand overall customer satisfaction of MobileTelecommunication service providers in India using sixattributes. A good correlation was found between the twovariables [r = 0.315, n =208, p = 0.000]. Overall, there wasa positive correlation between service delivery and overallcustomer satisfaction of Mobile TelecommunicationNetworks in India. This indicates that if service delivery isgood, the overall customer satisfaction will be high andvice versa. Analysis is given in below Table-4.

Table 4 : Relationship between Network Parametersand Overall Customer Satisfaction

Correlations

Items Network Quality

Customer Satisf-action

Network Quality

Pearson Correlation 1 .315*

Sig. (2-tailed) .026 N 208 208

Customer Satisfaction

Pearson Correlation .315* 1

Sig. (2-tailed) .026 N 208 208

*. Correlation is significant at the 0.05 level (2-tailed). SPSS V.22 Output,2015

The null hypothesis Ho1 is therefore rejected based on theresults. From the data analysis, it was found that customersof BSNL are more dissatisfied. It resulted into reduction incustomer base from 15 % to 10%. The network of Airtelwas reported best among the four operators studied. Thesecond priority was Vodafone, third one was Idea andBSNL stood at fourth position in network parameters.

RELATIONSHIP BETWEEN RELIABILITY ANDCUSTOMER SATISFACTION ( HO2 )

This dimension of service quality was selected as a measureof service reliability with GSM mobile service providers inIndia. The dimension consists of eleven (11) attributeswhich measure the ability of the service providers toperform the promised service dependably and accurately.The reliability Service Quality Dimension describes to howthe company perform and complete their promised service,quality and accuracy within the given set of requirementsbetween the company and the customer. This hypothesisexamined if there is a significant relation betweenreliability of service reliability and customer satisfaction.The results are shown Table-5 below:


( 41 )

Table-5 Relationship between SERVQUAL reliability of service quality and customer satisfactionCorrelations ( Source SPSS V. 22 Output 2015 )

Correlations

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 ROVALL

R1

Pearson Correlation 1 .400** .735** .449** .349* 0.276 .453** .342* .379** 0.216 .660**

Sig. (2-tailed) 0.004 0 0.001 0.013 0.052 0.001 0.015 0.007 0.131 0 N 208 208 208 208 208 208 208 208 208 208 208

R2

Pearson Correlation .400** 1 .344* 0.212 0.13 0.044 0.123 0.182 .343* 0.134 .348*

Sig. (2-tailed) 0.004 0.014 0.139 0.368 0.761 0.395 0.207 0.015 0.354 0.013 N 208 208 208 208 208 208 208 208 208 208 208

R3

Pearson Correlation .735** .344* 1 .284* .356* 0.213 .464** .472** .291* .283* .555**

Sig. (2-tailed) 0 0.014 0.045 0.011 0.137 0.001 0.001 0.041 0.046 0 N 208 208 208 208 208 208 208 208 208 208 208

R4

Pearson Correlation .449** 0.212 .284* 1 0.118 .457** 0.214 0.026 0.146 0.129 0.268

Sig. (2-tailed) 0.001 0.139 0.045 0.416 0.001 0.136 0.857 0.31 0.372 0.06 N 208 208 208 208 208 208 208 208 208 208 208

R5

Pearson Correlation .349* 0.13 .356* 0.118 1 -0.018 .388** 0.19 0.148 0.148 0.261

Sig. (2-tailed) 0.013 0.368 0.011 0.416 0.902 0.005 0.186 0.306 0.304 0.047 N 208 208 208 208 208 208 208 208 208 208 208

R6

Pearson Correlation 0.276 0.044 0.213 .457** -0.018 1 0.182 0.205 0.136 0.269 0.16

Sig. (2-tailed) 0.052 0.761 0.137 0.001 0.902 0.206 0.153 0.347 0.059 0.037 N 208 208 208 208 208 208 208 208 208 208 208

R7

Pearson Correlation .453** 0.123 .464** 0.214 .388** 0.182 1 0.201 0.273 0.22 .494**

Sig. (2-tailed) 0.001 0.395 0.001 0.136 0.005 0.206 0.161 0.055 0.125 0 N 208 208 208 208 208 208 208 208 208 208 208

R8

Pearson Correlation .342* 0.182 .472** 0.026 0.19 0.205 0.201 1 0.139 0.172 0.266

Sig. (2-tailed) 0.015 0.207 0.001 0.857 0.186 0.153 0.161 0.335 0.232 0.061 N 208 208 208 208 208 208 208 208 208 208 208

R9

Pearson Correlation .379** .343* .291* 0.146 0.148 0.136 0.273 0.139 1 -0.043 .536**

Sig. (2-tailed) 0.007 0.015 0.041 0.31 0.306 0.347 0.055 0.335 0.765 0 N 208 208 208 208 208 208 208 208 208 208 208

R10

Pearson Correlation 0.216 0.134 .283* 0.129 0.148 0.269 0.22 0.172 -0.043 1 .411**

Sig. (2-tailed) 0.131 0.354 0.046 0.372 0.304 0.059 0.125 0.232 0.765 0.003 N 208 208 208 208 208 208 208 208 208 208 208

ROV

AL

L

Pearson Correlation .660** .348* .555** 0.268 0.261 0.16 .494** 0.266 .536** .411** 1

Sig. (2-tailed) 0 0.013 0 0.06 0.067 0.267 0 0.061 0 0.003 N 208 208 208 208 208 208 208 208 208 208 208

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).


( 42 )

A correlation for the data revealed that reliabilitySERVQUAL dimension and customer satisfaction weresignificantly related, R1 (r = .66, N = 208, p < .01, 2-tailed),R2 (r = .34, N = 208, p < .01, 2-tailed), R3 (r = .55, N = 208, p< .01, 2-tailed), R4 (r = .26, N = 208, p < .01, 2-tailed), R5 (r =.26, N = 208, p < .01, 2-tailed) R6 (r = ..16, N = 208, p < .01,2-tailed) R7 (r = .494, N = 208, p < .01, 2-tailed) R8 (r = .266,N = 208, p < .01, 2-tailed) R9 (r = .536, N = 208, p < .01, 2-tailed) R10 (r = 0.41, N = 208, p < .01, 2-tailed). Higherservice reliability was associated with increased overallcustomer satisfaction.

Based on the analysis above, since the Significance. valuefor the various variables (Roverall, R1, R2, R3, R4,R5,R6,R7,R8,R9 and R10) is less than .05, (p < .05), we cansay that there is a significant positive correlation betweenreliability of service and customer satisfaction. The nullhypothesis (Ho2) is therefore rejected. Although, thestrength of the relationship differs among differentvariables, they all reflect a moderate positive correlation.The results reveal that service reliability has effect oncustomer satisfaction and that there is a positiverelationship between service reliability and customersatisfaction.

Further it was also found in the study that customers awardfair ranking to BSNL regarding price (Tariff) fairness. Thecomplaint of undue deduction of balance was found morein Airtel, Vodafone and Idea. Therefore it is advised tothese private operators to adopt fair policy regarding undueactivation of Value Added Services (VAS) which is themain cause of undue balance reduction.

Customer Loyalty and Churning ( Ho3 )

As shown in Table-6 Below, a high proportion (23.08%)reflecting 48 of the respondents expressed the desire toswitch mobile service providers while five respondentssaid that they will definitely switch. 41.83% were not verysure (87).These customers may switch is proper grade ofservices not provided and they can be retained by offeringsatisfactory services. Only 32.69 % respondents were foundwho firmly said not to switch. This illustrates howdissatisfied the subscribers are with the service delivery ofmobile telecommunication networks in India.

A correlation for the data revealed that customersatisfaction and switching intention were significantlyrelated, r =( -) 0.133, N = 208, p < .01, 2-tailed. The analysisdemonstrates a negative relationship between customersatisfaction and switching intention. Higher customer

satisfaction was associated with lower switching intentionand a lower customer satisfaction correlates with a higherswitching intention among the subscribers. The detailsare shown in Table-7

Table 6: Switching Intention among mobile phone users

Switching Intention

Response Frequency % Cumulative %

Valid

No 68 32.69 32.69 Not sure 87 41.83 74.52

Yes 48 23.08 97.6 Definitely 5 2.40 100

Total 208 100

Table-7

Correlations R1 R2

R1 Pearson Correlation 1 -.133 Sig. (2-tailed) .043

N 208 208 R2 Pearson Correlation -.133 1

Sig. (2-tailed) .043 N 208 208

Correlations (Source SPSS V. 22 Output 2015)

From TRAI data it was found that due to lower customersatisfaction and degraded services, BSNL had stood atfirst position in loosing of its customers. Somehow theAirtel succeeded to control the churning while Vodafoneand Idea capture the port out customers of BSNL andAirtel. Therefore, the study suggests to BSNL to improveits quality of service to further maintain and increase thedata base.

During the survey, following findings were also observed:

• 38% Respondents were more concerned about calldisconnection during the call when issue of networkparameters questioned.

• 28% Respondents reported that calls do not maturein single dial.

• 52% Respondents were also concerned aboutunwanted telemarketing calls and SMS throughunauthorized callers.

• 24 % Respondents reported that private operatorsare offering data for Net use at comparatively higherrates than BSNL.

• 68% Respondents reported slow speed of internet


( 43 )

especially during the peak hours.

• Customer Care services of BSNL were found worstamong the four operators (37%) while best that ofVodafone (73%).

• Respondents also suggested that operators shouldoffer economic plans for domestic CUG (CommonUser Group) users.

• Respondents also suggested for launching economicplans for accessing social networking sites

CONCLUSION

This study investigated the factors influencing thecustomer satisfaction of India’s mobile phone subscribers.Specifically, the study focused on the factors moderatingthe relationships of service quality, customer satisfaction,and customer switching intention. The results of thecorrelation analysis indicated that service quality andcustomer satisfaction significantly correlated. The resultsalso exposed that service quality was the major ancestorof customer satisfaction. Thus, the results suggest thatcustomer satisfaction may be most significantly influencedby high-quality services, and that service quality is stillcritical for retaining customers and maintainingcompetitiveness. That is, if customers perceive a high-quality mobile phone service, they may be more likely tostay with their existing service provider and recommendthe provider to others as well as encourage customers toshare their positive experiences with others. In addition,when customer satisfaction was entered into the linkbetween service quality and customer loyalty, there was asignificant mediating role of customer satisfaction on therelationship between service quality and customer loyalty.Thus, customer satisfaction was found as a key factor inthe relationship between customers and service providers.These results have important implications for practitioners;they should determine the exact roles of the perceived value,perceived price, and perceived switching cost in theircustomers’ satisfaction and loyalty. They need to discardthe view that improvements in customer retention can onlybe achieved through improved customer satisfaction. Byconsidering the roles of perceived value and price in therelationship between service quality and customersatisfaction, marketing practitioners may be better able toimprove customer satisfaction. This study was limited bythe fact that the respondents were residents of Kota City.Therefore, future research using nation-wide data isnecessary to strengthen the findings of this study.

REFERENCES

Armstrong, G., Adam, S., Denize, S., & Kotler, P. (2014).Principles of Marketing. Pearson Australia.

Zeithaml, V. A., and Bitner, M.J. (2003), Services Marketing:Integrating Customer Focus Across the Firm.

Boselie, P., & Hesselink, M and Van Der Wiele, T. (2002).Empirical evidence for the relationship betweencustomer satisfaction and businessperformance.Managing Service Quality: AnInternational Journal, 12(3), 184-193.

Gulledge, K. G. (1996). U.S. Patent No. 5,490,204.Washington, DC: U.S. Patent and Trademark Office.

Metawa, Saad A., and Mohammed Almossawi. (1998)“Banking behavior of Islamic bank customers:perspectives and implications.” International Journalof Bank Marketing 16.7, 299-313.

Bamfo, B. A. (2009). Exploring the relationship betweencustomer satisfaction and loyalty in the mobiletelecommunication industry in Ghana. IndianJournal of Economics & Business, 8(2).

Sadia Jahanzeb, Tasneem Fatima, and M. Bashir Khan.(2011) “An empirical analysis of customer loyaltyin Pakistan’s telecommunication industry.” Journalof Database Marketing & Customer StrategyManagement 18.1, 5-15.

Boohene, Rosemond, and Gloria KQ Agyapong. (2010)“Analysis of the antecedents of customer loyalty oftelecommunication industry in Ghana: The case ofVodafone (Ghana).” International Business Research4.1, p229.

Rahman, S., Haque, A., & Ahmad, M. I. S. (2011). Choicecriteria for mobile telecom operator: empiricalinvestigation among Malaysiancustomers.International Management Review, 7(1), 50-57.

Grönroos, C. (2000). Service Management and Marketing:A Customer Relationship Management Approach. .2nd Edn., John Wiley and Sons Ltd., , 46-287 .

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988).Servqual. Journal of retailing, 64(1), 12-40.

Jacoby, J., & Olson, J. C. (1977). Consumer response to price:an attitudinal, information processing perspective.Moving ahead with attitude research, 39(1), 73-97.


( 44 )

Zeithaml, V. A. (1988). Consumer perceptions of price,quality, and value: a means-end model and synthesisof evidence. 2-22 . Journal of Marketing, 52(July) , 2-22.

Zeithaml, V. A. (1982). Consumer response to in-store priceinformation environments. . Journal of ConsumerResearch, 8(March), 357-369 .

Zeithaml, V. A. (1983). Conceptualizing and measuringconsumer response to price. In R. P. Bagozzi, and A.M. Tybout (Eds.). Advances in Consumer

Chen, I. J., Gupta, A., & Rom, W. (1994). A study of priceand quality in service operations. InternationalJournal of Service Industry Management, 5(2), 23-33.

Ryu, K., & Han, H. (2010). Influence of the quality of food,service, and physical environment on customersatisfaction and behavioral intention in quick-casual restaurants: Moderating role of perceivedprice. Journal of Hospitality & Tourism Research, 34(3),310-329.

Dick, A. S., & Basu, K. (1994). Customer loyalty: toward anintegrated conceptual framework. Journal of theacademy of marketing science, 22(2), 99-113.

Lai, L. L. (2011). The moderating effects of switching costsand inertia on the customer satisfaction-retentionlink: auto liability insurance service in Taiwan.Insurance Markets and Companies: Analyses andActuarial Computations, 2(1).

Schlesinger, H., & von der Schulenburg, J. M. G. (1991).Search costs, switching costs and productheterogeneity in an insurance market. Journal of Riskand Insurance, 109-119.

Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996).The behavioral consequences of service quality. theJournal of Marketing, 31-46.

Cronin, J. J., Brady, M. K., Brand, R. R., Hightower Jr, R., &Shemwell, D. J. (1997). A cross-sectional test of theeffect and conceptualization of service value. Journalof services Marketing, 11(6), 375-391.

Brady, M. K., & Robertson, C. J. (1999). An exploratorystudy of service value in the USA and Ecuador.International Journal of Service IndustryManagement,10(5), 469-486.Research (vol. 10) AnnArbor, MI: Association for Consumer Research , 612-616 .

Lee, H. S. ( 2010a ). Effects of perceived value and servicequality on customer satisfaction in the mobile phoneservice market. INFORMATION. An InternationalInterdisciplinary Journal, 13(4), , 1207-1218.

Frost, Frederick A., and Mukesh Kumar. (2001) “Servicequality between internal customers and internalsuppliers in an international airline.” InternationalJournal of Quality & Reliability Management 18(4), 371-386.

Prof.( Dr.) P.K. SharmaDirector, School of Commerce and ManagementVardhman Mahaveer Open University, Kota ( Raj)


Vishwas PandeyResearch ScholarVardhman Mahaveer Open University, Kota ( Raj)



( 45 )

INTRODUCTION

Patrick Kilby of the NCDS, Australian national University puts Microfinance in thefollowing way: “Microfinance aims at supporting communities economically excludedto attain greater levels of asset creation and income security at the household andcommunity level”1. In mostly developing and under developed countries, financing tothe rural and poor persons through formal financial services failed to meet the creditrequirements of the rural poor people. Near about half of the world’s population arebreathing on the income of less than two dollars a day. Among these poor people, onechild in five does not live to see his or her fifth birthday2. To boost the internationaldevelopment, UNO announced the millennium development goals which aimed toalleviate poverty by 20153. The poor people need different kinds of services to solve theirwide range of financial problems at different points of time during their survival. StuartRutherford (2000) pointed to three main categories of events4 viz. life-cycle events,emergency needs and investment opportunities. Naturally, these events involve moneyand for its requirements, there should be proper financial inclusion that serves theneeds of poor sections of the society. A single-dose infusion of credit into a poorhousehold is not viable. The poor people need money in amounts, at specific times andfor purposes that make the money materially useful to them. The requirements ofmaterially useful sums of money can come in one of several ways, of which the threemost important are through (a) savings where current consumption of money is

Key words

Self Help Groups, Savings,Loan, Credit Utilization,Repayments.

Factors Determining Self Help Groups and theirPattern: An Experience of Mewat District ofHaryana

Tej Singh and Parul Mittal

ABSTRACT

This paper analyses the various factors determining the SHGs (Self Help Groups) and their pattern ofsavings, group and bank loan, credit utilization by members and repayment of loan etc. the study isbased on primary data which was collected through interview schedule and group discussion in Mewatdistrict of Haryana state. The selected schemes for the study are MDA (Mewat Development Agency)and SGSY/NRLM (Swaranjayanti Gram Swarozgar Yojana/National Rural Livelihood Mission). In thestudy it was found that the main motivational factors for SHG members to join the group were savingsand financial help. NGOs’ workers were the main motivating agents to join the group followed by theGovernment /Bank Officials, Neighbor/Relatives/Friends, Members of other SHGs and family members.The study also found that the mean frequency of bank loan was same in MDA and SGSY both. The meanfrequency of group loan was less under MDA than SGSY. The highest loan amount was in MDAfollowed by SGSY. The results of large sample test for two sample mean show the significant differencebetween the values. In the same way, the average group loan was calculated for both programmes andhighest amount was found in MDA followed by SGSY. Again, value of |Z| was calculated and resultsshow significant difference. The study found that all members stated that they had used loan amount forconsumption purpose in all programmes. It was followed by Investment in Livestock, Purchase Fodderfor Animals, Festivals/Marriage/Other Events and Children Education etc. As regards to repayment ofloan, most of the respondents stated that they managed to repay the amount of loan on time.


( 46 )

postponed to yield lump sums at future dates, (b) loans –where a lump sum is obtained at present in exchange forsurrendering future consumption, and (c) sale of assets –which may either represent a planned process of financialmanagement or be a crisis response.

The poor can and do savings in a many ways. Yet, theirpoverty compels them to take loans from financialinstitution time to time. Because of their miserablesituations, they may or may not be able to get adequateservices. The origins of micro-credit can be traced torecognition of these realities and truths based on asystematic observation of people’s coping mechanisms andbehavior in relation to money5. Access to formal sectorcredit is one of the identified key constraints being facedby the poor, especially in rural areas. Most people in thedeveloping world do not have any access to formalfinancial services (Brigit Helms, 2006). Collateral, creditrationing, preferences for high-income clients and largeloans, bureaucratic, lengthy procedures of providing loansin the formal sector keep most of the rural people outsidethe boundary of the formal sector financial institutions indeveloping countries. Monopolistic power, excessivelyhigh interest rate and exploitation through undervaluation of collaterals have restricted the informal sectorfrom providing credit to the rural poor6. It is believed thatcredit boosts income levels, increases employment at thehousehold level, and thereby alleviates poverty. Creditfacilitates poor people to accomplish their liquidityconstraints and undertakes some income-generatingactivities and helps the poor to smoothen theirconsumption patterns (Khandler, 1998). The improvedconsumption is an investment in the productivity of thelabour force or human capital. Hence, credit maintainsthe productive capacity of rural poor household (Hulme& Mosely, 1996; Navajas et.al, 2000)7. The lack of access tocredit for the poor may have negative consequences forvarious rural household in the context of income,employment, agricultural productivity, technologyadoption, food security, nutrition, health, education andoverall welfare.

The common reasons found by many researchers are thepolitical difficulties for governments to enforce loanrepayment and the selection of relatively wealthy andinfluential people, rather than the poor, for bank loans(Adams et al., 1984; Adams and Vogel, 1986; World Bank,1989)8. Various studies (World Bank, 2003; Basu, 2006;Deshpande and Niraj, 2003; Robin et al, 2004; Nair, 2000;Yunus, 2003) also revealed that in India, generally, banks

are for the people with money; not for the people without.To overcome poverty, poor people need to be able to borrow,save and invest money to protect their families fromadversity. Therefore, a need was felt for alternative policiesand procedures, saving and loan products, othercomplementary services which would fulfill the needs/requirements of the poorest rural in India9. Thedevelopment of any country is possible only if women folkare also developed. It is observed that the social, economicand political status of women in rural areas remains atvery low level. Thus, the inability of formal creditinstitutions to deal with the credit requirements of pooreffectively has led to emergence of microfinance as analternative credit system for the poor. Microfinanceprogramme provides a wide range of financial services topeople who have nothing in the way of traditionalcollateral. It helps them to build up assets, survive crisesand to establish small business to come out of the poverty10.Microfinance has gained a lot of significance andmomentum in the last decade. The role of microfinanceprogramme as the most suitable and feasible alternativein accomplishing the goal of growth and povertyalleviation is now well recognized.

Microcredit11 or Micro-finance is a relatively new term inthe field of development literature. These terms -microcredit and microfinance - are often usedinterchangeably, but it is important to highlight thedifference between them. Micro-credit refers to the provisionof credit-services to low-income clients, usually in the formof small loans for the purpose of micro-enterprise andincome-generating activities12. Micro-credit as defined bythe Grameen Bank of Bangladesh symbolizes small loansextended to very poor people for self-employment projectsthat generate income, allowing them to care for themselvesand their families. The defining criteria used are thus thesize of loans and the targeted population comprising micro-entrepreneurs, particularly from low-income households.These loans are generally offered without any collateral13.On the other hand, microfinance is a financial serviceprovided by various financial institutions to the rural poorpeople. These services include all banking and financialfacilities like savings, credit, insurance, leasing, moneytransfer, equity transfer etc14. These are provided tocustomers to meet their needs and requirements with thequalifications that (1) transaction value is small and (2)customer is poor (Dasgupta and Rao, 2003).

National Bank for Agriculture and Rural Development(NABARD) defines micro-finance as: “provision of thrift,

Factors Determining Self Help Groups and their Pattern: An Experience of Mewat District of Haryana

( 47 )

credit and other financial services and products of verysmall amounts to the poor in rural, semi-urban and urbanareas for enabling them to raise their income levels andimprove living standards” (NABARD, 2001)15.

According to James Roth, “Microfinance is a bit of a catchall-term. Very broadly, it refers to the provision of financialproducts targeted at low-income groups. These financialservices include credit, savings and insurance products.A series of neologisms has emerged from the provision ofthese services, name micro-credit, micro-savings andmicro-insurance”.16

A Self-Help Group (SHG) is an informal association of 10-20 persons, who have voluntarily come together for thebusiness of saving and credit and to enhance the members’financial security as primary focus and other commoninterest of members such as area development, awareness,motivation, leadership, training and associating in othersocial intermediation programmes for the benefit of anentire community (Gangaiah et al. 2006)17.


Kumaran (1997) studied the functioning of self helpgroups in the state of Andhra Pradesh. Saving and Creditwere the main objective of clients to enter into the group.He found that money contributed by the members waspooled together and used as a revolving fund to disburseloans on a priority basis. The interest rate on loans variedfrom 3 % to 5 % between the groups. The members alsostarted various IGAs in the group. Satish (2001)highlighted certain issues related to formation of SHGs.When forming SHGs adequate care should be taken toensure homogeneity of socio-economic status of themembers. He maintained that only a systematic andscientific approach with genuine purpose can ensuresustainability of the groups. NGOs are more suited forforming and nurturing of the SHGs, therefore, it is essentialto strengthen them and their resources so that they couldincreasingly undertake this work. Narayanaswamy et al.(2005) examined the functioning of SHGs under the SGSYscheme in one district in the state of Tamil Nadu. He usedboth quantitative and qualitative methods with a sampleof 235 groups. Prominent reasons among members to jointhe group were credit requirements, freedom frommoneylenders, initiating income generation activities andto improve socio-economic conditions. The average savingof each group was 28,000. There was a smooth credit

disbursement with high loan repayment. The majority ofthe loans were used in animal husbandry (24 %),household expenses (17 %) medical expenses (16 %) andmicro-enterprises (13 %). More than 70 % members saw anincrease in income of Rs. 2000 per month and remainingreported from 1000 to 1500 per month. Members were highlyinvolved in IGAs. Rajasekhar et. al. (2007) studied thegovernance and impact of SGSY in two districts of MadhyaPradesh i.e. Betul & Chattarpur. On the issue of governance,the researchers found that the process of socialmobilization was poor. They further highlighted thelimited participation of people, the indifferent attitude oflocal governance system, violation of rules and regulations,irregular meetings and saving and lack of transparency inthe disbursement of loans. The survey demonstrated theabsence of coordination between the groups, the GramPanchayat and line departments. The banks were alsounwilling to extend credit to the SGSY groups. Reji (2010)had opined that SHGs plays vital role in the country byhelping 45 million household accesses financial rive fromthe formal banking system in the country. He alsomentioned that some of the SHGs are highly succeed andsome not to that extent. He also revealed that affectivefunctioning of groups is influenced by the key factors; IGAs;capacity building and government and official support;quality of group meetings; saving habits; group leadership;group interaction; sense of self-equity, accountability andtransference etc. Batra (2012) analyzed the factorsdetermining the women Self Help Groups and patterns ofsavings, loan, credit utilization and repayment etc. Heselected three schemes for SHGs i.e. SGSY, SCRIA andSwayamsiddha. In the study, it was found that the mainmotivational factors for SHG members were saving, accessto cheaper credit, contribution to household income andto spend more on children. Government officials were themain motivational agent to join the group followed byneighbor/relatives, social animators deputed by DRDA,NGO workers, family members, members of other groupsand Anganwadi workers and bank officials. The studyalso found that the frequency of loan was highest in SCRIAgroups followed by SGSY and SwayamSiddha. Highestloan amount was in SCRIA followed by SGSY andSwayamSiddha. The average group loan was highest inSCRIA followed by SGSY and SwayamSiddha. On theissue of timely repayment of the loans, a good %age ofmembers claimed that they could not manage to repay ontime.


( 48 )


1. To understand the motivational factors and agentsto join the SHGs.

2. To study the savings patterns of SHGs’ members.

3. To find out the sources of loan, credit utilizationand repayment pattern of loan by members of SHGs.

RESEARCH METHODOLOGY

The present study is empirical in nature as it is mainlybased on primary data which was collected throughinterview schedule and FGD during field survey. Theselected schemes for the study are MDA (MewatDevelopment Agency) and SGSY/NRLM (SwaranjayantiGram Swarozgar Yojana/National Rural LivelihoodMission). A multistage random sampling method wasadopted for the study. At the first stage, district wasidentified on the basis of numbers of SHGs and availabilityof programmes. All five blocks were selected of Mewatdistrict. After the selection of blocks, the list of villageswas prepared with comparatively high numbers as wellas matured SHGs. Villages were selected on random basis.SHGs were selected through screening of a list providedby the NGOs/ MDA/ DRDA officials. A total of 80 SHGswere selected from all blocks of Mewat district of Haryanastate. A purposive and random sampling techniques wasused to select SHGs. For this, separate lists of SHGs, underMDA and SGSY were prepared. Out of these lists, thoseSHGs which had existed for last 3 or more years as on 31stDecember, 2013 were separated out to form the lists ofSHGs eligible to be selected for the study. From these lists,60 SHGs operating under MDA guidelines and 20 SHGsunder SGSY were randomly selected for the study.Dysfunctional SHGs credit linked under these programmeswere not considered for the study. SHG members(including 3 members and 1 group leader) were selectedfrom each of the selected SHG randomly.

RESULTS AND DISCUSSIONSMotivating Agents and Factors to Join the SHGAs far as motivating agents to join the SHG are concerned,table1 shows that 80.63% of respondents submitted thatNGOs’ workers were the main motivating agents to jointhe group followed by the Government /Bank Officials(8.13%), Neighbor/Relatives/Friends (5.94%), Membersof other SHGs (4.68%) and family members (0.62%). InMDA, 81.67% of members stated that they joined the SHGwith the influence of NGOs’ workers. It was followed by

Neighbor/Relatives/Friends (7.08%), Government /BankOfficials (6.25%), Members of other SHGs (4.17%) andFamily members (0.83%). In case of SGSY, about 77.50% ofmembers submitted NGOs’ workers as the main agent tojoin the SHGs, followed by the Government /Bank Officials(13.75%), Members of other SHGs (6.25%) and Neighbor/Relatives/Friends (2.50%).

The motivating factors to join the SHG are manifold. Thestudy found that savings and financial help were mainreasons to join the groups. Out of all 320 members, all themembers (100%) joined the group to promote savingshabits, to get financial support from the SHG and tocontribute in HH income. It was followed by access ofcheaper credit (90%), to promote IGAs (70.63%), to spendmore on children (32.50%) and to repay old debts (5.00%).In MDA, all the members (100%) also joined the group topromote savings habits, to get financial support from theSHG and to contribute in HH income followed by accessof heaper credit (86.67%), to promote IGAs (74.17%), tospend more on children (36.25%) and to repay old debts(5.00%). While in SGSY, to promote savings habits, to getfinancial support from the SHG, to contribute in HHincome and access of cheaper credit were main factors asclaimed by the 100% of members. On the issues of to repayold debts, to promote IGAs and to spend more on children,15%, 60% and 21.25% of SGSY members claimed as motivefactors respectively (Table 1).

Saving Pattern of SHGs Members

The average saving per member per month in all the groupswas Rs. 125. Programme wise, the highest saving amountwas Rs. 150, occurring in MDA, followed by the SGSY (Rs.100). On the issue of the source of savings within the HH,43.75% of the respondents stated that they arranged thesaving amount from the home expenses. It was followedby husband’s income (40.31%), owned earned money(15%) and Old age/Widow pension (0.94%). In MDA,44.58% stated husband’s income as the main sourcefollowed by amount of house expenses (34.17%), ownedearned money (20%) and Old age/Widow pension (1.25%).In SGSY, there was major difference in sources of savingsof the members as comparison to MDA members. Majorityof members (72.50%) claimed the main source of theirsavings in the group was house expenses and remaining27.50% of respondents stated that they contribute savingamount from husband’s income (Table 2).


( 49 )

Table 2 also shows that all members from all programmesclaimed that meetings emergency and basic needs werethe main purpose. This was followed by agriculturedevelopment (36.88%), Marriage & other events (33.44%),education for children (32.5%), assets building (31.56%),festivals (8.44%) and medical expenses (4.69%). In MDA,40% of members submitted that the main purpose ofsavings was agriculture development and farmingfollowed by Marriage & other events (38.75%), education

for children (36.25%), assets building (28.33%), festivals(7.50%) and medical expenses (6.25%). In SGSY, 41.25% ofmembers claimed the assets building as the main factor tojoin the SHG which followed by agriculture development(27.5%), education for children (21.25%), marriage & otherevents (17.5%) and festivals (11.25%). There was noevidence found as regard to medical expenses.

Table 1: Motivating agents and factors to join the SHG

Particulars MDA SGSY Total Motivating Agents to Join the SHG Self Motivation 0(0.00) 0(0.00) 0(0.00) Neighbor/Relatives/Friends 17(7.08) 2(2.50) 19(5.94) NGO Workers 196(81.67) 62(77.50) 258(80.63) Family Members 2(0.83) 0(0.00) 2(0.62) Government/Bank Officials 15(6.25) 11(13.75) 26(8.13) Members of Other Groups 10(4.17) 5(6.25) 15(4.68) Anganwadi Workers 0(0.00) 0(0.00) 0(0.00) Reasons/Factors for Joining SHGs To Promote Saving Habits 240(100.00) 80(100.00) 320(100.00) To Obtain Financial Support 240(100.00) 80(100.00) 320(100.00) To Repay Old Debts 4(1.67) 12(15.00) 16(5.00) To Promote IGAs 178(74.17) 48(60.00) 226(70.63) To Contribute In HH Income 240(100.00) 80(100.00) 320(100.00) To Access Cheaper Credit 208(86.67) 80(100.00) 288(90.00) To Spend More on Children 87(36.25) 17(21.25) 104(32.50)

Source: Computed from Survey Data.Note: Figures given in parenthesis show percentage.

Table 2: Saving pattern of SHGs membersParticulars MDA SGSY Total Mean Value of Savings in Group per month (Rs.) 150 100 125 How Pay Saving Amount From Owned Earned Money 48(20.00) 0(0.00) 48(15.00) From Husband’s Income 107(44.58) 22(27.50) 129(40.31) From House Expenses 82(34.17) 58(72.50) 140(43.75) Old Age/ Widow Pension 3(1.25) 0(0.00) 3(0.94) Purpose of Saving To Meet Emergency/Basic Needs 240(100.00) 80(100.00) 320(100.00) Agriculture Development 96(40.00) 22(27.5) 118(36.88) To Meet Medical Expenses 15(6.25) 0(0.00)1 15(4.69) Education For Children 87(36.25) 17(21.25) 104(32.5) Assets Building 68(28.33) 33(41.25) 101(31.56) Marriage & Other Events 93(38.75) 14(17.5) 107(33.44) Festivals 18(7.50) 9(11.25) 27(8.44)

Source: Computed from Survey Data.Note: Figures given in parenthesis show percentage.


( 50 )

CREDIT UTILIZATION PATTERN

During the survey, it was also asked from the membersthat whether they had taken any loan from SHG and Bank/MFIs. Out of all 320 respondents, 100% members had takenloans from SHG and Bank/MFIs. As regards to source ofloan, 4.06% members had taken loan from SHG, 11.56%only from bank and 84.38% had taken loan from bothsources. In MDA, 5.42% members had taken loan fromSHG, 12.08% only from bank and 82.50% of members inMDA had availed loan from both sources i.e. bank loanand group loan. In case of SGSY, not any single memberregistered that they had taken loan form group only andonly 10% of respondents submitted that they had takenloan from banks. While majority of members (90%) statedthat they had availed loan from bank and group both.

The mean amount of bank loan in all groups found to beRs. 28163.80 (Figure1). The highest loan amount was inMDA (Rs. 33569.96) followed by SGSY (Rs. 22757.63). Theresults of large sample test for two sample mean show thesignificant difference between the values. In the same way,the average group loan was calculated for bothprogrammes and highest amount was found in MDA (Rs.24773.08) followed by SGSY (Rs. 14654.88). Again, valueof |Z| was calculated and results show significantdifference (Table 3).

The mean frequency of bank loan was same (1.0) in MDAand SGSY both. The mean frequency of group loan was2.5 in case of MDA and 3.1 in SGSY. The rate of interestcharged on group loan was 24% in MDA and 12% in SGSYwhile interest rate of bank loan was 11.4% and 12% inMDA and SGSY respectively. The average number of grouploan taken by members was 4 in MDA and 5 in case ofSGSY. While average of number of bank loan were 3 incase of MDA and 2 in SGSY (Table 3).

Figure1: Mean Amount of Loan under All Programmes

05000

100001500020000250003000035000

MDA SGSY TOTAL

33569.96

22757.6328163.8

24773.08

14654.8819713.98

in Rupees

MEAN AMOUNT OF BANK LOANMEAN AMOUNT OF GROUP LOAN

Source: Calculated from survey data.

Members of SHGs are always in need of money to meettheir daily requirements, family needs and domestic needs.

For this, members have to depend on money lenders andpay high rate of interest over their borrowings. So, SHGprovide the financial facilities on easy terms to theirmembers. The study found that all members (100%) statedthat they had used loan amount for consumption purposein all programmes. It was followed by Investment inLivestock (61.25%), Purchase Fodder for Animals (54.69%),Festivals/Marriage/Other Events (40.63%), ChildrenEducation (32.50%), Self Employment (32.19%), AssetsBuilding (30.63%), Cultivation/Agriculture (29.69%), ToRepay Old Debt/Loan (24.06%), To Start Business/Shop(17.5%), House Construction/Sanitary Repair (13.13%),and Medical/Health Contingencies (4.38%). Programmewise loan use pattern shows that in MDA, all 100%members used loan amount for consumption purposefollowed by Investment in Livestock (67.5%), PurchaseFodder for Animals (61.67%), Festivals/Marriage/OtherEvents (47.50%), Children Education (36.25%), SelfEmployment (38.75%), Assets Building (27.08%),Cultivation/Agriculture (31.67%), To Repay Old Debt/Loan (24.58%), To Start Business/Shop (19.58%), HouseConstruction/Sanitary Repair (15.83%), and Medical/Health Contingencies (5.38%). In SGSY also, all membersused loan amount for consumption purpose whichfollowed by Investment in Livestock (42.50%), PurchaseFodder for Animals (33.75%), Festivals/Marriage/OtherEvents (20%), Children Education (21.25%), SelfEmployment (12.50%), Assets Building (41.25%),Cultivation/Agriculture (23.75%), To Repay Old Debt/Loan (22.50%), To Start Business/Shop (11.25%) andHouse Construction/Sanitary Repair (5%). It shows thatmembers used loan for non productive purpose in mostlycases. In all programmes, no collateral was used to takeloan and in all 70.62% cases, the loan amounts were usedfor individual based IGAs which include 74.17% and 60%for MDA and SGSY respectively (Table 3).

REPAYMENT SYSTEM OF LOAN

As regards to repayment of loan, 68.75% of respondentsstated that they managed to repay the amount of loan fromthe profit and income earned from loan financed activitieswhich followed by income of husband/son (25.31%),income from employment (4.38%) and borrowing fromgroup members (1.56%). Programme wise repaymentsystem shows that in MDA, 74.17% of members submittedthat they managed the amount from the profit and incomeearned from loan financed activities which followed byincome of husband/son (17.92%), income fromemployment (5.83%) and borrowing from group members


( 51 )

Table 3: Credit utilization patternParticulars MDA SGSY Total Whether Loan taken after Joining the Group Yes 240(100.00) 80(100.00) 320(100.00) No 0(0.00) 0(0.00) 0(0.00) Sources of Loan Only Group Loan 13(5.42) 0(0.00) 13(4.06) Only Bank Loan 29(12.08) 8(10.00) 37(11.56) Both 198(82.50) 72(90.00) 270(84.38) Mean Amount of Bank Loan (Rs.) 33569.96 22757.63 28163.80 S.D of Bank Loan (Rs.) 3096.52 2980.00 303826 C.V (%) 9.22 13.09 11.16 Ho= Mean Amount of Bank loan are same between both programmes. |Z| = 20.08, At 5% level of significance, the critical value of Z for one tailed test = 1.645. The calculated value |Z| > critical value of Z at 5% level. Hence, null hypothesis is rejected. So, Mean Amount of Bank loan are different between both programmes. Mean Amount of Group Loan (Rs.) 24773.08 14654.88 19713.98 S.D of Group Loan (Rs.) 3593.82 4026.55 3810.19 C.V (%) 14.50 27.48 20.99 Ho= Mean Amount of Group loan are same between both programmes. |Z| = 14.83, At 5% level of significance, the critical value of Z for one tailed test = 1.645. The calculated value |Z| > critical value of Z at 5% level. Hence, at 5% level of significance, null hypothesis is rejected. So, Mean Amount of Group loan are different between both programmes. Mean Frequency of Bank Loan 1.0 1.0 1.0 Mean Frequency of Group Loan 2.5 3.1 2.8 Rate of Interest (% p.a) Group Loan 24 12 18 Bank Loan 11.4 12 11.7 Average Number of Loans Taken From the Formation of Group Group Loan 4 5 4.5 Bank Loan 3 2 2.5 Actual Utilization of Loan Amount Cultivation/Agriculture 76(31.67) 19(23.75) 95(29.69) Investment in Livestock 162(67.50) 34(42.50) 196(61.25) Purchase Fodder for Animals 148(61.67) 27(33.75) 175(54.69) Assets Building 65(27.08) 33(41.25) 98(30.63) To Start Business/Shop 47(19.58) 9(11.25) 56(17.5) Festivals/Marriage/Other Events 114(47.50) 16(20.00) 130(40.63) Children Education 87(36.25) 17(21.25) 104(32.50) House Construction/Sanitary Repair 38(15.83) 4(5.00) 42(13.13) To Repay Old Debt/Loan 59(24.58) 18(22.50) 77(24.06) Medical/Health Contingencies 14(5.83) 0(0.00) 14(4.38) To Meet Consumption Expenditure 240(100.00) 80(100.00) 320(100.00) Self Employment 93(38.75) 10(12.50) 103(32.19) Collateral Used to Secured Loan Yes 0(0.00) 0(0.00) 0(0.00) No 240(100.00) 80(100.00) 320(100.00) Loan Amount Used for IGAs Yes 178(74.17) 48(60.00) 226(70.62) No 62(25.83) 32(40.00) 94(29.38)

Source: Computed from Survey Data. Note: Figures given in parenthesis show percentage.


( 52 )

Table 4: Repayment system of loanParticulars MDA SGSY Total Sources of Repayment Income From Employment 14(5.83) 0(0.00) 14(4.38) Profit/Income From Loan Financed Activities 178(74.17) 42(52.50) 220(68.75) Form Husband/Son’s Income 43(17.92) 38(47.50) 81(25.31) Pension 0(0.00) 0(0.00) 0(0.00) Borrow From Money Lender 0(0.00) 0(0.00) 0(0.00) Borrow From Group Members 5(2.08) 0(0.00) 5(1.56) Selling Assets 0(0.00) 0(0.00) 0(0.00) Repayment Arrangement Bi-Weekly Installment 0(0.00) 0(0.00) 0(0.00) Monthly Installment 240(100.00) 80(100.00) 320(100.00) Quarterly Installment 0(0.00) 0(0.00) 0(0.00) Repaid Loan Amount on Time Yes 224(93.33) 56(70.00) 280(87.50) No 16(6.67) 24(30.00) 40(12.50) Ho = Repayment time is independent of programme. χ2 = 29.866, significant at 5% significance level. Hence, null hypothesis cannot be accepted. Reason For Delay Payments Failure of Business 6(37.50) 0(0.00) 6(15.00) Family Expenses 13(81.25) 14(58.33) 27(67.50) Out of Village 3(18.75) 0(0.00) 3(7.50) Poor Harvest 6(37.50) 7(29.17) 13(32.50) Sickness In Family 8(50.00) 2(8.33) 10(25.00) Animal Dead 4(25.00) 3(12.50) 7(17.50) Loan Amount Sufficient Adequate 93(38.75) 0(0.00) 93(29.06) Inadequate 147(61.25) 80(100.00) 227(70.94) Taken Loan From Other Sources After Joining The Group Yes 25(17.01) 6(7.50) 31(13.66) No 122(82.99) 74(92.50) 196(86.34) Other Sources of Loan Other Banks 3(12.00) 0(0.00) 3(9.67) Friends & Family 13(52.00) 2(33.33) 15(48.39) Money Lenders 7(28.00) 1(16.67) 8(25.81) Neighbor 2(8.00) 0(0.00) 2(6.45) Any Other 0(0.00) 3(50.00)1 3(9.68) Rate of Interest of Loan Taken From Other Sources (% p.a) Other Banks 12 12 12 Friends & Family 0 0 0 Money Lenders 36 36 36 Neighbor 0 0 0 Any Other 0 25% less

price -

Reasons For Dependence on Other Sources of Loan Delay in Getting Loan From SHG 0(0.00) 0(0.00) 0(0.00) Do Not Get Sufficient Loan From SHG 13(52.00) 1(16.67) 14(45.16) Have Not Repaid Group Loan 4(16.00) 5(83.33) 9(29.03) Group Has Not Sufficient Funds/Balance 8(32.00) 0(0.00) 8(25.81)

Source: Computed from Survey Data. Note: Figures given in parenthesis show percentage.


( 53 )

(2.08%). In SGSY, 52.50% of members stated that theymanaged to repay the amount from the profit and incomeearned from loan financed activities. It was followed byincome of husband/son (47.50%). (Table 4)

The arrangement of the repayment on a period basis wascommon in all groups as in both programmes; the monthlyrepayment schedule had been fixed both by banks andgroups. On the basis of timely payment of loan, only12.50%of members claimed that they could not repay theloan amount on time. The highest frequency of irregularrepayments were observed in SGSY (30%) followed by MDA(6.67%). The chi-square test shows the significantdifference between both programmes (Table 4).

The study also observed the reasons behind the untimelyand irregular repayments f loan amount by members. Table4 shows that 67.50% of members stated use of loan for HHexpenses followed by poor harvest (32.50%), sickness infamily (25%), animal dead (17.50%), failure of business(15%) and out of village (7.50%). Programme wise analysisshows that in MDA, the main reason for non repayment ofloan amount was family expenses (81.25%) which followedby sickness in family (50%), poor harvest (37.50%), failureof business (37.5%), animal dead (25%) and out of village(18.75%). In SGSY, the main factor behind untimely andirregular repayment was again family expenses (58.33%).It was followed by poor harvest (29.17%), animal dead(12.5%) and sickness in family (8.33%). As table 4 indicatesthat about 70.94% of members stated that the loan amountwas inadequate to meet their needs. In MDA, 61.25% ofrespondents felt loan amount insufficient while in case ofSGSY, all the 100% members stated that loan amount wasnot adequate for them. Total of 86.34% of respondents hadnot taken loan from other sourced even after joining theSHG. Programme wise, its status was 82.99% and 92.50%in MAD and SGSY respectively. The main other source ofloan was friends and family (48.39%) followed by moneylenders (25.81%), other banks (9.67%) and neighbor(6.45%). In MDA, 52% of members had taken loan fromfriends and family followed by money lenders (28%), otherbanks (12%) and neighbor (8%). In SGSY, majority ofmembers (50%) had taken loan from other sources. It wasfollowed by friends and family (33.33%) and moneylenders (16.67%). The rate of interest charged by the allother sources was same under all programmes as clearedfrom the table data. The main reason for the dependence ofmember on other sources even after joining the SHG wasinsufficient loan amount disbursed to members (45.16%).

It was followed by members didn’t repay loan (29.03%)and SHG hadn’t sufficient balance (25.81%). (Table 4)

CONCLUSION

The study found that majority of members joined the groupthrough NGO’s workers and government/bank’s officialsfor the purpose of promoting savings habits, to get financialsupport, to contribute in HH’s income and to access cheapercredit. Mostly members contributed savings fromhusband’s income and house expenses for the purpose ofmeeting emergency and basic needs of their HH. The loanamount was used by members for agriculture purpose,livestock related activities, business purpose, consumptionexpenditure, assets building and education of children.The sources of repayment of loan were income fromfinanced activities and husband’s income on monthlybasis. Nearby 87.50% of members repaid loan timely. Somemembers made delay payment due to family expenses,livestock problem etc. A majority of members stated thatamount was inadequate to meet their needs. They hadalso to borrow from other sources mainly due to inadequateloan amount and delay repayment of loan. The studyconcludes that to streamline the whole pattern, sustainableefforts should be undertaken by government officials andSHGs as well for the welfare of rural poor people.

REFERENCES

Batra, Vikas (2012). Economic Affairs Quarterly Journal ofEconomics. March, 57 (1) 107-118.

Kumaran, K. P. (1997). Journal of Rural Development,January, 16, (3) 30-33.

Narayanswamy et al. (2005). Journal of Rural Development.24, (2) 15-16.

Rajasekhar et.al. (2007). Good governance and povertyalleviation: A study of SGSY programme. NewDelhi: Concept Publishing Company.

Reji, E.M. (2010). Journal of rural development, January.29, (1) 89-92.

Satish, P. 2001. Indian Journal of Agriculture Economics.April,2001,Vol- 56, (3) 20-22.


( 54 )

FOOTNOTES

1 http://dspace.thapar.edu:8080/dspace/bitstream/10266/1143/3/1143.pdf

2 Submitted to University of Malaya on 2014-05-08

3 http://iaesjournal.com/online/index.php/IJPHS/article/view/6028

4 Life-cycle events include those once-in-a-life timeoccurrences or recurrent incidents that everyhousehold faces; emergencies include personalcrises like sickness or injury, the death of a bread-winner or the loss of employment and loss by theft;third is opportunities to invest in businesses, land,or household assets.

5 http://www.isec.ac.in/shdr_kar05.pdf

6 http://www.ifpri.org/2020/nw/nwpapers/tanzrr200308.pdf

7 http://www.isec.ac.in/WP%20-%20205.pdf

8 http://shodhganga.inflibnet.ac.in/bitstream/10603/3031/11/11_chapter%203.pdf

9 Batra,Vikas and Sumanjeet. “The State of Microfinancein India: Emergence, Delivery Models and Issues”,Journal of International Economics (0976-0792),2012.

10 http://shodhganga.inflibnet.ac.in/bitstream/10603/3031/11/11_chapter%203.pdf

11 2005 is known as the international year of Micro-credit.

12 http://www.cid.org.nz/training/microfinance.pdf

13 Submitted to Indian Institute of Technology, Bombay on2014-11-05

14 http://researchreport4u.blogspot.com/2012/02/financial-inclusion-and-microfinance-in.html

15 http://stellamariscollege.org/Literary_Journal/Ankur_2007-08.pdf

16 http://umu.diva-portal.org/smash/get/diva2:141240/FULLTEXT01.pdf

17 http://pnrdassam.nic.in/SuccesStory/SUCCESS%20STORIES%20OF%20SGSY%20%20CACHAR%20.pdf

18 In this case, people do not save in group by keeping inmind to use saving for meeting their medicalexpenses. But whenever they need, they use theirsaving and take amount from group for medicalpurpose later. I found no evidence in my surveyregarding this.

19 In this case, respondents borrowed money from milkbarber. They do not pay in monetary terms. Theycharge less price than market price for milk sold. Inthis way, they pay their debt amount.

Prof. Tej SinghDean & Chairperson, Dept. of CommerceIndira Gandhi University, Meerpur (Rewari)


Dr. Parul MittalAsst. Prof., Dept of Commerce,KLP College, Rewari-123401



( 55 )

INTRODUCTION

BR and FR are two significant terms in the literature of risk management. The two wellaccepted traditional measures of BR and FR are DOL and DFL. The combined effect ofthese two measures as indicated by DTL is universally applied as the sole measure ofTR. DOL, DFL and DTL were originally invented to measure the extent of operatingleverage (OL), that of financial leverage (FL) and that of total leverage (TL) respectively.But, gradually these three became the respective measures of BR, FR and TR, too. Thepresent paper attempts to examine whether the aforesaid measures can be consideredas appropriate measures of BR, FR and TR in all situations. The paper also suggestssome alternative measures of the aforesaid risks instead of the conventional ones.

The paper is organised as follows: In Section 2, the objectives of the study are stated.Section 3 evaluates the relevance of DOL as a measure of BR, points out its limitationsand suggests alternatives. The limitations of DFL as a measure of FR are discussed inSection 4. The alternatives to DFL to gauge FR are also mentioned in this Section. Section5 is concerned with the examination of DTL as a measure of TR and suggestingalternatives. Section 6 narrates some prevailing misconception about the applicabilityof the concept of shut-down point in practical scenario. Finally, in Section 7, concludingremarks are provided.

Key words

Business Risk (BR),Financial Risk (FR), TotalRisk (TR), Degree ofoperating leverage (DOL),Degree of financialleverage (DFL), Degree oftotal leverage (DTL),Faulty Measures of risks.

Reliability of DOL, DFL and DTL as Measures ofRisks – An Investigation

Aloke Gupta and Debasish Sur

ABSTRACT

The total risk (TR) associated with a company can broadly be divided into two components, viz. businessrisk (BR) and financial risk (FR). BR is inherent in the business operation of the company. It arises outof dispersion of the operating profitability of the company. On the other hand, FR arises out of thepossibility of failing to meet fixed commitments or contractual obligation and possibility of fluctuation inincome available to owners’ equity. The higher the proportion of external equity in the capital structureof the company, the higher is the FR associated with it. In other words, BR is associated with theinvestment decision while FR stems from the financing decision of the company. These risks, if significantand ignored, may cause serious damage to the financial health of any corporate house in this competitivebusiness environment. Degree of operating leverage (DOL) and Degree of financial leverage (DFL) aretwo age-old universally recognised measures of BR and FR of a business firm. Their joint impact i.e., TRcan be measured by Degree of total leverage (DTL). It is found in the literature of finance that DOL, DFLand DTL can be greater than or equal to 1. The present paper, however, shows that these two measurescan also be less than one or zero or negative or even indeterminate. By highlighting some grossirregularities of the established theories on DOL, DFL and DTL as the measures of BR, FR and TR, thepaper suggests a few alternative measures to assess these risks associated with a business firm. Theauthors also argue that while DOL, DFL and DTL can continue to be the respective measures ofoperating leverage, financial leverage and total leverage, these are faulty measures of BR, FR and TR.


( 56 )


The present paper has the following objectives:

(i) To identify the limitations of DOL, DFL and DTL asthe respective measures of BR, FR and TR.

(ii) To suggest alternative measures of risks to removethe limitations of the traditional ones.

DOL, ITS LIMITATIONS AND ALTERNATIVES:

Concepts of OL, DOL and BR:

OL is the firm’s ability to use fixed operating costs tomagnify the effect of changes in sales volume on itsoperating profit i.e., earnings before interest and taxes(EBIT). OL indicates that a business firm is able to utiliseits fixed operating costs in such a fashion that increase inits EBIT is more than proportionate increase in its fixedcosts. It is similar to the existence of lever where benefitobtained is more than proportionate application of power.The major difference of OL, FL and TL with BR, FR and TRis that the first three indicate advantageous situation to afirm where it is able to manage its fixed costs for its benefitwhile the latter three are computed to determine thevolatility in its profits which may prove to be dangerousfor its financial health if these cross permissible limitsapplicable to the firm.

DOL is considered as a well-accepted measure of OL aswell as BR. DOL is the proportionate or percentage changein EBIT due to proportionate or percentage change in salesvolume. The formula of DOL is given as: Contribution (C)/EBIT= Q(s-v) / Q(s-v)-F, where Q = number of units sold,s = unit selling price, v = unit variable cost, F = total fixedoperating cost. So, higher the amount of fixed cost in thecost structure, the lower is the denominator and the higheris the value of DOL. In that situation, even a small changein sales will have large effects on operating income. Onthe contrary, if there is no fixed cost in the cost structure ofthe firm, the denominator will be equal to the numerator,the value of DOL will be 1 and in that case EBIT will varyin direct proportion to sales volume. So, it is said that thevalue DOL can only be equal to or greater than 1. Thehigher the value of DOL, the higher is believed to be the BRassociated with the firm. Because, in case of a firm havinghigh DOL, the rate of increase in EBIT will be higher thanincrease in its sales volume; on the flip side, if there isdecline in sales volume, there will be more thanproportionate decrease in EBIT and after meeting interestand taxes, net result may be a loss. So, DOL depends on

fixed costs. Again if fixed costs are high, the break-evenpoint will also be reached at a high level of sales.Consequently, the margin of safety would be low. So, if afirm’s fixed costs are high, OL as well as BR will also behigh. Therefore, in case of declining tendency in salesvolume, it is prescribed to keep the fixed costs at a lowlevel so that OL as well as BR will be low and there will beless chance of facing net loss.

Limitations of DOL as a Measure of BR:

But, there are some cases, enumerated herein under, whenthe value of DOL may be less than one, zero, indeterminateor even negative:

Case I (0<DOL<1): If C<0, which arises when the sum ofvariable costs (V)> sales revenue (S), then in such situationC-F=EBIT < 0 (assuming F>0). In such situation, DOL=C/EBIT>0 but < 1, for which the interpreter lands in aconfusing situation. For instance, if S= Rs. 1000, V=Rs.1,200 (it is very much possible that the ‘ideal’ situation ofV<S may not hold true), then C= S-V=Rs. (1,200-1,000) = -Rs. 200. Now, if F=Rs. 500, then EBIT=C-FC=Rs. (-200-500) = -Rs. 700. Hence, DOL= C/EBIT= -200/-700= 0.29(approx). Thus, in this case, 0<DOL<1. Again, in the sameexample, if F increases, say, to Rs. 600, then C remains thesame, but EBIT further declines to (Rs. -200 -Rs. 600) i.e., -Rs. 800 and DOL=-200/-800= 0.25. So, increase in F makesthe DOL decline when C and EBIT both are negative. Itagain mismatches with the theory that increase in F causesincrease in DOL i.e., BR. In this way, DOL fails to gaugethe BR associated with the concerned business house.

Case II (DOL=0): If C=0, which is quite possible in actualscenario where V = S, then C-F<0 (assuming F>0) andDOL=C/EBIT=0. For example, if C=0, F=Rs. 20, then EBIT=-Rs. 20 and DOL= 0/ -20=0. It again contradicts with theestablished principle. In the same example, even if Fincreases to Rs. 50, it will have no impact on DOL as C stillremains 0. So, DOL remains the same even if F changes inthe situation mentioned here. It again goes against theconventional theory.

Case III (DOL indeterminate): If C>0, but after meeting thefixed operating costs, operating profit becomes nil i.e., C-F= EBIT =0, then DOL=C/ EBIT becomes indeterminate.For example, C=Rs. 20, F=20, then EBIT=0 and DOL=20/0!”, indicating that BR is indeterminate which is absurd.In the same example, if F decreases to Rs. 15 keeping theother information intact. In that case, EBIT would be Rs.(20-15) i.e., Rs. 5 and DOL becomes 20/5=4. So, only

Reliability of DOL, DFL and DTL as Measures of Risks – An Investigation

( 57 )

reducing F by Rs. 5 in this example yields the DOL valueas 4 whereas in case of F of Rs. 20, the same measure DOLbecomes indeterminate. So, DOL fails to assess the correctBR of a business firm in this type of situation.

Case IV (DOL <0): If C>0 but, the amount of F > C, then C-FC= EBIT<0. So, in those cases DOL=C/EBIT<0. Forinstance, if C=Rs.100, F=Rs. 120, then EBIT= C-FC= - Rs.20. So, in that case, DOL=100/-20= - 5 which is misleadingand absurd as it indicates negative BR. Again, in the sameexample, if F increases to Rs. 300, then EBIT=Rs. 100-Rs.300= - Rs. 200 and DOL=100/-200= - 0.5. So, increase in Fcauses decline in DOL when EBIT is negative. It againmismatches with the theoretical argument.

Hence, it is evident from the above discussion that insituations mentioned in cases I to IV, DOL may be lessthan one, zero, indeterminate or even negative. Only incase of ‘ideal’ situation i.e., when S>0, V<S and F<C, EBIT=(S-V)-F >0 and DOL=C/EBITe”1. But, in the practicalworld, it does not hold good always. So, for measuring BRi.e., variability of operating profit with respect to variationin sales volume in all the situations, DOL fails to establishitself as the appropriate measure.

Alternative Measures for Ascertaining BR

Some financial ratios and some conventional as well asmodern statistical tools can be used as alternative measuresof BR. These are explained as follows:

(I) Fixed Cost to Total Cost Ratio (FCTC) or Fixed Cost toVariable Cost Ratio (FCVC): It can be used to measure thedegree of BR. It is accepted that the genesis of BR lies in thepresence of fixed operating costs in the cost structure ofthe firm. So, for measuring this type of risk for anyparticular year or series of years, FCTC may be calculated.It is quite difficult for an outsider of a firm to identifywhether any cost is fixed or variable in nature from thepublished financial statements. She / he has to classifythe costs into fixed and variable using some logical bases.But an insider can easily identify the nature of the costs.The higher the ratio, the higher is the BR as it indicatesthat after meeting F from the contribution, the residualvalue i.e., EBIT will be lower leading to the risk of higherfluctuation in operating profit with respect to sales volumeas compared to any other organisation of which F is lower.Similarly, FCVC ratio can also be used for the same purpose.

(II) Fixed Asset to Total Asset Ratio (FATA): This ratiomay be also be used to assess BR. It is expected that thehigher the proportion of fixed assets, the larger part of the

expenses will be fixed in nature resulting in higher level ofbreak-even and hence the higher will be the value of BR(Porterfield, 1965; Chakraborty, 1977; Mallik and Mallik,1985). Definitely, the quantum of fixed assets and the natureof the business should be taken into consideration beforeselecting this ratio for the purpose of ascertaining its BR.For example, in heavy industries, the proportion of fixedassets to total assets is expected to be higher where FATAmay be suitable for the indicating BR while in many serviceindustries or retail businesses the proportion of fixed assetsto total assets may be lower as compared to that of short-term assets to total assets. So, in service providing firms orretail businesses, FATA may not reflect the true picture ofBR.

(III) Coefficient of Variation (CV) of operating profit ratio(OPR): According to Robicheck and Myers, BR arises fromthe inability to insure absolutely stable sales, costs andprofits. So, CV of OPR can be effectively used as a measureto ascertain BR for a period consisting of more than oneyear / accounting period. CV is considered as a bettermeasure of instability in any variable as compared toStandard Deviation (SD) especially in case of inter-firmcomparison. The higher the value of CV of OPR, the higheris the BR and vice-versa.

(IV) Ginni’s Coefficient of Concentration (G) of OPR: Thiscan also be used for the purpose of measurement of BR. Gis one of the popular statistical measures of dispersionwhich can also be used in order to calculate BR of a businessfirm for a period of time consisting of more than a year. Gis considered as an improved measure over CV especiallyin case of a highly skewed distribution. The higher thevalue of G of OPR, the higher is the BR and vice versa.

(V) CV or G of Operating Cost Ratio (OCR): CV or G ofOCR may be used to calculate the fluctuation in operatingcost with respect to fluctuation in sales. Fluctuation inOCR indicates volatility in the proportion of sales revenue(S) which is lost or consumed up in meeting operatingcosts and results in dispersion of residual operating profitsi.e., EBIT. It is to be calculated for a period consisting ofmore than a year in case of annual data. A higher value ofCV or G of OCR indicates a higher variability in operatingcosts w.r.t. sales leading to a high BR and the opposite isalso true.

One or more of the above-mentioned alternative measurescan be used to determine the BR of any businessorganisation to get a correct, better and complete picture ofthis type of risk instead of the traditional one. But, volatility


( 58 )

from one year to another cannot be accurately measuredwith the help of any measure which is based on the data ofany single year. So, in case of intra-firm analysis of BR,measures stated in (III) to (V) which determine averagedispersion of a data series would perhaps give better resultsas compared to measures (I) and (II) which simply giveaverage of a data series. In case of inter-firm comparison ofBR, all the measures from (I) to (V) may be applied.

Practical Examples:

Some of the limitations of DOL as discussed in 3.2 areenumerated with practical examples:

(Rs. in crore)Sl. No. Company Year

Ended Situation DOL Remark

1 Ranbaxy

Laboratories Ltd.

201112

S=Rs. 7590.18, V=Rs. 9759.27

(i.e., S<V). So, C = -Rs.2169.09 i.e.,

<0. Given, F=Rs.859.2.

Hence, EBIT= C-F=-Rs. 3028.29

i.e., <0.

0.7163

0<DOL<1 (Case I)

2 Cadila

Healthcare Ltd.

201003

C=Rs. 153.9 i.e.,>0, but F=Rs. 236.8 i.e., >C. So, EBIT= C-F=Rs. -

82.9 i.e., <0.

-1.85645

DOL<0 (Case IV)

Note: In the above calculations Employee Cost given in the database was only considered as the fixed cost whereas, the sum of (Cost of Raw Materials+ Power & Fuel Cost + Other Manufacturing Expenses + Selling and Administration Exp + Miscellaneous Expenses + Cost of Depreciation) was considered as the total variable operating costs. Source: Compiled and computed from ‘Capitaline Corporate Database’ of Capital Market Publishers (I) Ltd., Mumbai.

It is to be noted that the calculated figures may changebased on the assumptions made or the accuracy ofavailable data regarding fixed and variable operating costs.But, the same situations may crop up in case of one or theother companies as logically the cases are very natural tooccur in practical scenario.

DFL, ITS LIMITATIONS AND ALTERNATIVESConcepts of FL, DFL and FRFL may be defined as the firm’s ability to use fixed financialcharges to magnify the effects of changes in EBIT on itsearnings per share (EPS). It indicates that a business firmis able to utilise its fixed financial costs in such a fashionthat EPS increases more than proportionate increase in itsEBIT.

DFL is considered as the best or rather only well-acceptedmeasure of FL as well as of FR. DFL is the proportionate orpercentage change in EPS due to proportionate orpercentage change in EBIT. The formula for DFL is:

DFL=EBIT/EBT (if there is no preference dividend), whereEBT=earnings before tax. So, two firms having same EBITmay have different EPS depending upon the quantum ofinterest burden (I) (or fixed charge bearing capital) in theircapital structures. The value of DFL is said to be more thanor equal to 1. If there is no interest burden, then EBT will beequal to EBIT and hence the value of DFL will be 1. Thehigher the proportion of fixed charge bearing capital orexternal equity to total capital employed, the lower will bethe EBT and hence the higher will be the DFL (i.e., DFL>1).A high DFL indicates that EPS will increase at a faster ratethan the rate of increase in EBIT. But, that is a risky situationas well, as a slight fall in EBIT will lead to more thanproportionate fall in EPS. So, the presence of fixed chargeor contractual obligation in the capital structure is thegenesis of FR. It arises out of the possibility of failing tomeet the fixed financial commitment or contractualobligation and possibility of fluctuation in incomeavailable to equity shareholders.

Limitations of DFL as a Measure of FR

But, there are some cases, enumerated herein under, whenthe value of DFL may be less than one, zero, indeterminateor even negative (using the notations used in the previousparagraphs):

Case I (0< DFL<1): If EBIT <0 and interest burden is there,EBT will be further negative. As a result, DFL=EBIT/EBT>0 but <1. For example, EBIT= -Rs. 100, I= Rs. 20. ThenEBT= Rs.(-100-20)= - Rs. 120. In that case, DFL=EBIT/EBT=-100/-120=0.83 (approx). Hence, 0<DFL<1. Again, if inthe same example, ‘I’ increases to Rs. 40, then EBT=Rs. (-100-40) = -Rs. 140. So, DFL in that case becomes =-100/-140= 0.71 (approx). So, increase in ‘I’ has caused declinein DFL. It is again contrary to the established theoreticalprinciple that increase in fixed financial obligation (I)causes increase in DFL i.e., FR. Thus, in situationsdescribed here, DFL fails to gauge the FR associated withthe concerned business house.

Case II (DFL=0): If EBIT=0, which is quite possible as aftermeeting variable and fixed operating costs, operatingprofit may become zero, then DFL=EBIT/EBT=0 (for anyvalue of I). For example, if EBIT=0, I = Rs. 20, then EBT= -Rs. 20 and DFL=0/-20=0 which goes against the theoreticalargument. In the same example, even if F increases to Rs.50, it will have no impact on DFL as EBIT still remains 0.So, DFL i.e., FR remains the same even if F changes in thesituation mentioned herein which again goes against thetraditionally accepted theory.


( 59 )

Case III (DFL indeterminate): If EBIT> 0, but after meetingthe fixed financial costs, EBT becomes nil i.e., EBIT-I = EBT=0, then DFL=EBIT / EBT becomes indeterminate. Forexample, EBIT=Rs. 20, I=20, then EBT=0 and DFL=20/0!”. It indicates BR is indeterminate which is absurd. Inthe same example, if ‘I’ decreases to Rs. 15 keeping theother information intact, EBT would be Rs. (20-15) i.e., Rs.5 and DFL becomes 20/5=4. So, only reducing ‘I’ by Rs. 5in this example yields the DFL value as 4 while in case of‘I’ of Rs. 20, the DFL was indeterminate which is peculiar.So, DFL fails to give the correct picture of FR of a businessfirm in this type of situation.

Case IV (DFL <0): If EBIT >0 but, the amount of I > EBIT,then EBIT - I = EBT<0. So, in those cases DFL=EBIT/EBT<0.For instance, if EBIT=Rs.100, I=Rs. 120, then EBT= EBIT-I= - Rs. 20. So, in that case, DFL=100/-20= - 5 which ismisleading and absurd as it indicates negative FR. Again,in the same example, if only ‘I’ increases to Rs. 200 keepingthe EBIT constant, then EBT=Rs. 100-Rs. 200= - Rs. 100and DFL=100/-100= - 1. So, increase in ‘I’ causes declinein DFL i.e., FR when EBT is negative. It again mismatcheswith the theoretical argument.

Hence, it is clear from the above discussion that insituations mentioned in Cases I to IV, DFL may be lessthan one, zero, indeterminate or even negative. Only incase of ‘ideal’ situation i.e., when EBIT>0 and I<EBIT, EBT=(EBIT-I) remains>0 and DFL=EBIT/EBT gives a valuewhich is e”1. But, in the practical world, it does not alwayshold good. So, for measuring FR i.e., variability of owners’profitability with respect to fluctuations in operating profitin all types of situations, DFL fails to establish itself as theappropriate measure.

Alternative Measures for Ascertaining FR

Some financial ratios and some conventional as well asmodern statistical tools can be used as alternative measuresof FR. These are explained as follows:

(I) Interest to Sales Ratio (ISR): We know that

, where T= amount of tax,

=preference dividend and N=number of equity shares.

So, the amount of ‘I’ definitely impacts EPS as well as the

FR of a business firm. Now, if ‘I’ (plus , if it is there) as

a proportion to sales increases, EBIT remaining the same,EBT decreases and the residual surplus left for equity

shareholders also decreases. So, it increases the probabilityof more fluctuation in EPS. So, ISR may be used in assessingthe FR associated with a business enterprise. The higherthe ratio, the higher the FR and vice-versa. It is significantto mention in this context that any ratio between Interestand EBIT would not fulfil the purpose as EBIT may be zeroor negative which, in turn, will lead to similar limitationsas point out in case of the conventional measure i.e., DFL.

(II) Debt-Equity ratio (DER): It may also be used inmeasuring FR where Debt-Equity ratio=Long-term Debt/Owners’ equity. The higher the proportion of debt capitalto owners’ equity, the higher is the interest burden andconsequently the higher is the FR. Here, net owners’ equityshould be avoided as after deducting miscellaneousexpenses from shareholders’ fund the resultant figure maybecome negative and if it happens, it will make the DERnegative. So, gross owners’ equity should be consideredin this regard.

(III) CV of Earnings per Share to Earnings before Interest& Tax Ratio (EER): FR, by definition, can be measured bythe volatility in EPS due to variability in EBIT. Hence, CVof EPS to EBIT ratio, in short EER, can be calculated todetermine the dispersion of EPS w.r.t. EBIT whichrepresents the FR associated with a company where theperiod of time consists of more than one year. The higherthe value of the measure, the higher will be the FR andvice-versa. The benefits of using CV over SD have alreadybeen discussed in 1.3 (III) in this write-up.

(IV) G of EER: The variability of EPS due to fluctuation inEBIT, as mentioned in the previous paragraph, can also beassessed with the help of G of EER where the period underconsideration is atleast two years. The superiority andapplicability of G over CV has already been mentioned in1.3 (IV) of this article.

One or more of the above-mentioned alternative measurescan be applied in ascertaining the FR of a business firmmore accurately as compared to the DFL. But, volatilityfrom one year to another cannot accurately be measuredwith the help of any measure which is based on the data ofany single year. So, in case of intra-firm analysis of FR,measures stated in (III) and (IV) which determine theaverage dispersion of a data series would perhaps givebetter results as compared to measures suggested in (I)and (II) which simply give average of a data series. In caseof inter-firm comparison of FR, all the measures from (I) to(IV) may be applied.


( 60 )

Practical Examples:

(Rs. in crore)Sl. No. Company Year

Ended Situation DFL Remark

1 Piramal Healthcare Ltd.

201203

SR=Rs. 1153.48, TC

(i.e., VC+FC)=Rs. 1379.3 (i.e.,

SR<TC). So, EBIT= SR-TC=

-Rs. 225.82. Now,

I=Rs.199.9. Hence,

EBT=EBIT-I=-225.82-199.9= - Rs 425.72 <0.

0.5304

0<DFL<1 (Case I)

2 Panacea Biotec Ltd.

200403

EBIT= SR-

TC=Rs. 4.47 i.e., >0.

Now, I=Rs. 13.93. So,

EBT=EBIT-I=-Rs. 9.46

i.e., <0.

-0.4725

DFL<0 (Case IV)

Note: In the above calculations Total Operating Cost (TC) was computed as = (Cost of Raw Materials+ Power & Fuel Cost + Other Manufacturing Expenses + Selling and Administration Exp + Miscellaneous Expenses + Cost of Depreciation+ Employee Cost). Source: Compiled and computed from ‘Capitaline Corporate Database’ of Capital Market Publishers (I) Ltd., Mumbai.

It is to be noted that the calculated figures may changewith the change in any assumptions made regarding stockadjustments etc. But, the same situations may crop up incase of one or the other companies as logically the casesare very natural to occur in practical scenario.

DTL, ITS LIMITATIONS AND ALTERNATIVES

Concepts of TL, DTL and TR: DTL is the firm’s ability touse fixed operating costs and/ or fixed financial chargesto magnify the effect of changes in sales on its EPS. Thecombined effect of OL and FL is called Total Leverage (TL)which can be measured by Degree of Total Leverage (DTL).If a business firm is able to increase its EPS more than theproportionate increase in its sales revenue, the firm is saidto have TL. As per the conventional finance literature, DOLreflects the BR and DFL highlights the FR of a businessfirm. Similarly, DTL measures the TR. It is accepted as theuniversal measure of TR. Its formula is given as: DTL= C/EBT (if there is no preference dividend). Alternatively, DTL

can be calculated as: DTL=DOL x DFL. DTL measures theproportionate or percentage change in EPS due toproportionate or percentage change in sales revenue.Traditional theory says that the value of DTL can only begreater than or equal to 1 as it is derived from DOL andDFL.

Limitations of DTL as a Measure of TR: The value of DTLwill not always be greater than or equal to 1 in reality ifany or both of DOL and DFL is/ are less than one or zeroor indeterminate or negative. From another point of view,it can be said that if C and/ or EBT become(s) zero ornegative, the value of DTL would not remain within thetraditionally fixed periphery. So, DTL fails to determine ofcombined risk or TR of any business firm in those casesand reflects distorted or misleading pictures of total riskprofile of the firm.

Hence, it is clear from the above discussion that only incase of ‘ideal’ situation i.e., when C>0, EBIT>0 and EBT>0and DTL=C/EBT or, DOL x DFL gives a value which ise”1. But, in the real world situation, this does not alwayshold good. So, for measuring TR i.e., volatility of EPS withrespect to variation in sales in all types of situations, DTLfails to establish itself as the appropriate measure.

Alternative Measures to Calculate TR: Some modernstatistical tools can be utilised to overcome the limitationsof DTL as a measure of TR. These are explained as follows:

(I) CV of EPS/Sales Ratio (EER): TR can be calculated bymeasuring the volatility in EPS due to variability in salesusing CV where the data of more than one year areavailable.

(II) G of EER: The above-mentioned dispersion can also beassessed with the help of G.

(III) Multiplying the measures of BR and FR: TR, being thecombined risk, may also be calculated by multiplying thevalues of the suggested alternative measures of BR and FRas mentioned in 3.3 and 4.3.

MISCONCEPTION THAT BUSINESS OPERATIONCANNOT CONTINUE IN LOSS MAKINGSITUATION

It has been noticed that some academicians or theoreticiansbelieve that a business firm cannot run under the situationof loss. According to them, whenever there is loss and theprice reaches the shut-down point, the operation isstopped. So, as per their argument, the limitations of the


( 61 )

traditional measures mentioned hereinbefore cannot ariseat all. To rectify their misconception, this section highlightsthat many business firms may run under situations of loss.At times, some business houses have proved themselvesto be excellent performers even after remaining in the loss-making zone for a considerable period of time.

Traditional theory of shut-down point

It is well known from the theory of cost that Average Cost(AC) = Average Fixed Cost (AFC) + Average Variable Cost(AVC). Now, it is said in the theory of Economics that in aperfect market condition, if price (P) of a product or servicee” AVC, production will continue even if P <AC. Because,in that situation, the amount of total loss < amount of totalfixed cost (TFC). That means even below the break-evenpoint, where P=AC, the operation is not stopped until andunless the P goes below the AVC i.e., the firm’s total revenueis even less than its total fixed cost. So, the conventionaltheory of Economics indicates that a firm cannot continuein situations where it is unable to recover atleast its fixedcost. Some theoreticians even misunderstand the theoryas no firm can continue under situations of loss even for acouple of years.

Practical scenario

Many companies continue to run its operations undersituations of loss and the quantum of loss may be evenmore than the amount of its TFC. This is because in practice,irrespective of the nature and type of market, a businessfirm is not only guided by the motive of immediate financialsurplus, but by the long-term financial and social goals. Ithas to be kept in mind that the assumptions of the theorydo not hold strictly in the real world situation. In the earlyphase of any business firm, the start-up costs i.e.,preliminary expenses may be much more than its revenues.In that situation, if they follow the theory of shut-downpoint in short-run, they may never be able to see profits inany of their ventures in the long-run. This is more so incase of heavy industries. It has been witnessed in Indiancorporate sector also that a good number of corporatehouses were in the red zone after which they again startedmaking profits. Some of them became excellent performersalso in course of time. It has happened in many public aswell as private sector companies in India. Some examplesare given hereunder which show that private as well aspublic sector companies also run under loss makingsituation and return to profit zone even after that:

(Rs. in crore)

Company Situation Remark

SAIL

Annual Reported Net Profit starting from

the Year 2000 to 2011 were: Rs. -1720.02, Rs. -728.66, Rs.-1706.89,

Rs. -304.31, Rs. 2512.08,

Rs. 6816.97, Rs. 4012.97, Rs.6202.2, Rs. 7536.78, Rs. 6170.4, Rs.

6754.37, Rs. 4904.74.

Faced loss for 4 years and

started to make profits

thereafter.

JSW Ispat

Annual Reported Net Profit starting from Year 2000 to 2011

were: Rs. 3.67, Rs. -312.46, Rs. -442.85, Rs.

82.83, Rs. 44.32, Rs. 696.06, Rs.

-812.67, Rs. -9.53, Rs. 34.8, Rs.-688.11, Rs. -322.34, Rs. -

1805.88

Continues operation even

after facing losses in most of the years during

the period.

Wockhardt

The amounts of reported net profit from 2009 to 2011

were: Rs. -348.76, Rs. -794.21 and Rs. -132.06

Even after three years of loss, the

company continues to be

one of the significant

Pharma company in

India.

Force

Motors

From 2000 to 2011, faced reported net profits and losses

intermittently: -Rs. 14.94, -Rs. 17.35,

Rs. 1.6, Rs. 32.17, Rs. 44.21, Rs. 2.72, Rs. 30.13, -Rs. 37.49, -Rs. 83.65, Rs. 124.56, Rs.

60.42, Rs. 58.62

The company succeeded to

earn profit even after facing

losses intermittently.

Whirlpool

India

From 2000 to 2012, earned reported net profit as follows: Rs.

20.46, Rs. 9.12, Rs. 8.65, -Rs. 33.65, -Rs. 99.8, -Rs. 38.1, -Rs.

5.32, Rs. 32.32, Rs. 70.52, Rs. 145.02, Rs. 166.03, Rs. 123.73

Continues with prestige in the

Consumer Durables

industry even after facing oscillating profits and

losses. Source: Capitaline Corporate Database of Capital Market Publishers (I) Ltd., Mumbai.


( 62 )

In all the above cases it is seen that the companies did notstop operation even after facing losses in many years. Insome cases, EBIT was negative, too. So, DOL, DFL andDTL fail to measure risks of these firms in the years oflosses.

CONCLUDING REMARKS

The conventionally and universally accepted measures ofrisks become incapable of assessing BR, FR and TR as andwhen a company gets negative returns. But, perhaps thenecessity for measuring risks is rather more in case thecompanies are facing losses than the situation wheneverything is going on smoothly. So, DOL, DFL and DTLcan continue to be used as determinants of OL, FL and TLrespectively, but not as the measures of BR, FR and TR of abusiness firm. Alternative measures suggested in thisarticle can be used in measuring the aforesaid risks.

REFERENCES

Banerjee, B. (2002). Financial Policy and ManagementAccounting, The World Press Private Limited,Calcutta.

Chakraborty, S.K. (1977). Corporate Capital Structure andCost of Capital, ICWAI, P.240.

Chandra, P. (2007). Financial Management- Theory & Practice,Tata McGraw-Hill, New Delhi.

Financial Management: Study Material of the Institute ofChartered Accountants of India for Course-II (October2004), New Delhi.

Gupta, A. and Sur, D. (2013). Business and Financial Risksin Hindustan Unilever Ltd.: An EmpiricalAnalysis. Asia-Pacific Finance and Accounting Review,1(4), 77-93.

Gupta, A. (2015). Business risk in Indian Corporate Sector:An Empirical Analysis’, Unpublished Doctoral Thesisunder the University of Burdwan, West Bengal,India.

Kapil, S. (2011), Financial Management, Pearson Education,New Delhi.

Khan, M.Y. and Jain, P.K. (2005). Financial Management-Text & Cases, Tata McGraw- Hill, New Delhi.

Kishore, Ravi.M.(2006). Financial Management, TaxmannAllied Services (P) Ltd., New Delhi.

Kuchchal, S.C.(2006), Financial Management-An Analytical& Conceptual Approach, Chaitanya PubishingHouse, Allahabad.

Maheswari, S.N.(2007), Financial Management- Principlesand Practices, Sultan Chand & Sons, New Delhi.

Mallik, A. and Mallik, U. (1985). Risk Analysis andMeasurement from Published Financial Statements-A Case Study. Research Bulletin, IV(1), 45-48.

Pandy, I.M. (2007). Financial Management. Vikas PublishingHouse private Limited, New Delhi.

Porterfield, J. (1965). Investment Decisions and Capital Costs.Prentice Hall, Englewood Cliff.

Robicheck, A.A. and Myres, S.C. (1965). Optimal FinancialDecisions. Prentice Hall, Englewood Cliffs, p. 17.

Sur, D. (2007). Business and Financial Risks of NTPC Ltd.inthe Pre-and Post-Liberalization Periods: AComparative Study. The Icfai Journal of AppliedFinance, 13(10), 66–78.

Sur, D. and Mitra, S. (2011). Business Risk AnalysisThrough Ginni’s Coefficient: A Study of Select ITCompanies in India. International Journal of Researchin Computer Application and Management, 1(1), 49-55.

Sur, D. (2012). Financial Statement Analysis: A ComprehensiveApproach. Excel Books, New Delhi.

Van Horne, J.C. (2008). Financial Management & Policy. PHILearning Private Limited, New Delhi.

Dr. Aloke GuptaAsst. Professor, Department of Commerce,Chandernagore College (Govt. of W.B.),Dist- Hooghly, West Bengal-712136

E-mail: [email protected]

Dr. Debasish SurProfessor, Department of Commerce,The University of Burdwan,Dist.- Burdwan, West Bengal-713104

E-mail : [email protected]


( 63 )

INTRODUCTION

Service-dominant Logic (SDL), developed by Vargo and Lusch (2004) is broader andcomprehensive concept based on exchange of intangibles such as knowledge and skillsamong stakeholders (Lusch and Vargo 2008 and Gronroos 2008). Vargo and Lusch(2004) claimed that SDL focuses on application of operant resource that is, serviceswhich are the fundamental source of competitive advantage. Weigand and Jeewanie(2009) also put forth that SDL should focus on service provision rather than on viewingservices as a particular kind of good that should be produced and marketed in sameway as traditional goods. Further the underlying principle of SDL considers that valueis created by an organisation along with other stakeholders, instead of organisationitself (Vargo and Lusch 2008) which is well accepted by the same science scholars.

The literature also talks about Service Competencies Orientation (SCO), which isinterchangeably used with SDL (Chahal and Mahajan 2014). In this context Karpen,Bove and Lukas (2009) remarked that SCO can be considered as a significant outcomeof SDL that addresses a firm’s service capability. Similarly Chahal and Mahajan (2014)also stated that functioning of the SCO/SDL based organisation focuses on theinteraction between members of an organisation. In fact organisations adopting servicecompetencies enables organisational stakeholders to work in a coordinated andtransparent manner to create value. In other words it encourages members to work in aself-motivated environment, to participate in decision– making and to get regularfeedback from their peers. The interaction among various members ultimately helps inbuilding foundation for achieving desired organisational performance. Hence SCOcan be defined as value co-creation chain in which all relevant stakeholders collaboratedynamically to deliver high quality service according to the organisational goals. It can

Key words

Service-dominant Logic,Service–competenciesOrientation,Organisational justice,Organisationalcommitment,

Service Competencies Orientation- Its Relationshipwith Organisational Justice and OrganisationalCommitment (in Higher Education Sector)

Hardeep Chahal and Rupa Mahajan

ABSTRACTPurpose – To measure the service competencies orientation and analyse its relationship with organisationaljustice and organisational commitment in the higher education service system/ SDL based organisation.Design/Methodology - 575 supporting members of University of Jammu (UOJ) and Guru Nanak DevUniversity (GNDU), were contacted for data collection.Findings –The study resulted into three factors of SCO (Service Competencies Orientation) namely,absorbo-collaborative contributing highest, followed by collaborative competencies and absorptivecompetencies. The result conclude that procedural justice dimension of organisational justice iscomprehending SCO more as compared to organisational commitment.Research Limitation – The study is limited to supporting staff perception and needs to be explored withrespect to other stakeholders in higher education to understand SCO. .Originality/Value- The study is first of its kind that establishes relationship of SCO with organisationaljustice and organisational commitment. The study conceptualises SCO as composite of absorb-collaborative,absorptive competencies and collaborative competencies..


( 64 )

also be said that interactive behaviour of stakeholders todeliver customer service and to create value reflect servicecompetencies of the organisation and the manner in whichit is created reflects SCO of the organisation.

Although the concept of SDL has started receivingsignificant contribution, however SCO is yet to be explored.The scanned literature signifies number of research gapswhich need to be undertaken for grounding the conceptualframework of SCO. Lusch, Vargo and Brien (2007), Abelaand Murphy (2008), Arnould (2008) Ford and Bowen(2008) and Edvardson, Tronvoll and Gruber (2011) arguedthat there is a need for SDL to be further worked out to gainmore empirical validation. Various other scholarsremarked to explore the relationship of SDL with differentpsychographic organisational factors (Karpen, Bove andLukas 2009 and Chahal and Mahajan 2014).

Few studies are found in the literature that theorised andmeasured relationship of SCO with regard to behaviouralaspects such as justice which is significant to enhance fairand ethical relationship among various organisationalmembers remarked by Liu et al. (2008 and Nga et al. (2010).Liu et al. (2008) commented that SDL based oncollaboration of provider and customer relationshipresults in creation of value only if such collaborations areinvolved fairly, that is based on organisational justice.Further Kimpakorn and Tocquer (2007) and Oyewobi,Sulieman and Jamil (2012) in their studies remarked thatorganisations to maintain long-term relationship in a SDLbased organisation, should motivate employees andcustomers (Hazre and Srivastava 2009) which mayconsequently lead to quality improvement in the long run(Sramek et al. 2009). Thus both motivation and commitmentplay important role in improving the organisationalperformance (Tyagi 1985, Miao Lund and Evans 2009 andMundhra 2010). Furthermore, various other scholarsrecommended to study SDL in relation to personality traitsBommer, Miles and Grover 2003), employee satisfaction(Saks 2006), employee orientation customer participation(Groth 2005, Rodgers 2007). Further researchers such asLittleton and Whitelock (2004), Dong, Evans and Zou(2008), Chan, Yim and Lam (2010), Randall, Pohlen andHanna 2010). Gronoos, (2011) and McColl-Kennedy (2012)recommended to explore SDL from the stakeholder’sperspective where all members work collaboratively in anetworked based organisations to create value.

Both SDL and SCO are significant in service dominant eraand both are yet to be explored and conceptualised.

Against this background, the purpose of paper is to presentthe development of a psychometrically sound measure ofSCO and to examine its relationship with two significantorganisational factors namely, organisational justice andorganisational commitment.

REVIEW OF LITERATURE AND HYPOTHESESFORMULATION

SDL/ SCO

The basic tenet of SDL is that service is exchanged forservice, where service is the process that appliescompetencies for the benefit of another and is the basis forall exchange (Vargo and Lusch, 2008 and Brodie, Sarenand Pels 2011). Gummenson (2008), Maglio and Spohrer(2008) and Edvardson, Tronvoll and Gruber (2011) in theirstudies stated that that the best way to achieve high levelof organisational performance is through the applicationof service competencies and SDL, which are primarilybased on knowledge and skills, and also refers to theapplication of absorptive and collaborative competencies(Lusch, Vargo and Brien 2007, Lusch and Vargo 2008 andOrdanini and Parasuraman 2010). Initially Ballantyne andVarey (2008), Gummenson (2008) and Lusch and Vargo(2008), opined that application of organisationalcompetencies namely collaborative and absorptivecompetencies are pivotal for benefit of all stakeholders andthe organisation. Even Ordanini and Parasuraman (2010)remarked the significance of collaborative competenciesin terms dynamic and knowledge interfaces. They statedthat these competencies play vital role in enhancing theperformance of organisation. T h eservice orientation of an organisation based oncompetencies reflects SCO. Lopes and Pineda (2013)defined that SCO has a primary focus on competenciesand is capable of creating value. It is seen as sharableservice; skills and talent management, knowledgemanagement and library resources (Ballantyne and Varey2008). Even Schulz and Gnoth (2008) suggested thatsharing of new ideas and knowledge within the firm canhelp in improving effective interaction, organisationalenvironment and adoption of networking system. Basicallyin SCO/SDL system members are encouraged to work in atransparent system to create dynamic environment, toparticipate in decision– making and to get regular feedbackfrom members of the organisation. All these subsequentlycan help in improving the competencies of variousstakeholders and lead to co-creation of value.

Service Competencies Orientation- Its Relationship with Organisational Justice and Organisational Commitment in Higher Education Sector

( 65 )

Based on the seminal contribution by Vargo and Lusch(2008) absorptive and collaborative competencies can becondensed as pivotal for value co-creation. Absorptivecompetencies relate to symmetric information andconversation among various members of organisationwhich require employees to provide correct and accurateinformation and not to mislead any other stakeholderinvolved in the organisation (Lusch and Vargo 2008).Abela and Murphy (2008) and Maglio and Spohrer (2008)remarked that the application of absorptive competenciesare necessary to strengthen the integration between thedifferent parties of the organisation to co-create value. Onthe other hand, collaborative competencies involve allemployees to collaborate with each other and to enablethem to adjust with the changing vis-a-vis newenvironment (Lusch and Vargo 2008). Collaborativecompetencies focus on two way interaction betweenproducer or other social and economic integrators to co-create value suggested byOrdanini and Parasuraman(2010) and Randall, Pohlen and Hanna (2010).

The study argues that both the competencies that is,absorptive and collaborative when applied in service sector(for example education sector) encourage employees towork in collaboration while interacting with otherstakeholders. In this context, Chahal and Mahajan (2014)in their study remarked that absorptive and collaborativecompetencies, encourage university members to createdynamic environment where all members participate intransparent decision– making system. These interactionsconsequently enhance relations between differentstakeholders and lead to value creation for university.Chahal and Mahajan (2014) in their writings further addedthat collaborative competencies when adopted ineducation sector encourage faculty members to work inteam- spirit in an open and fair system. Basicallycollaborative competencies enable members to acquaintthemselves with specialised capabilities. It facilitatesmembers to consult others before taking any action etc. inorder to provide benefit to all stakeholders and to treat allmembers of the organisation equally. On the other handabsorptive competencies enable employees to providecorrect and accurate information to their colleagues andnot to provide such information that mislead their co-workers. Absorptive competencies allow members toabsorb new information from various social and economicintegrators such as co-workers, students, scholars.Employees with such competencies are able to adjust withthe changes in the environment both internally and

externally. Thus these competencies when followedproficiently can enhance relation between differentstakeholders and hence reflects service competenciesorientation. Based on the backdrop following hypothesisis framed:

H1: Absorptive and collaborative competencies contributesignificantly to SCO.

Service Competencies and Organisational Justice

Organisational justice relates to fair and ethical treatmentof individuals in organisations (Nga et al. 2010 and Tatumet al. 2003). It also refers to the role of fairness in individualsperception at the workplace (Shah 2010). In other words ifemployees perceive their exchanges with organisationsas fair, they reciprocate by performing in ways that benefitorganisation (Rego and Cunha 2010). Organisationaljustice as three dimensional construct comprisingdistributive, procedural and interactional given byGreenberg (1987) is well accepted in literature. Distributivejustice refers to fairness in firm efforts while dealing withcustomer / employee problems (Casielles, Alvarez andMartin 2010) and affects employee work related outcomes,such as pay and job assignments (Shah 2010). Proceduraljustice reflects perceived fairness in complaint handlingprocess. It refers to method the firm uses to deal withproblems such as easy and timely accessibility of work(Casielles, Alvarez and Martin 2010). Unfair proceduresnot only make employees dissatisfied with their outcomesbut also lead them to reject the entire system as unfair(Ahmadi, Ahmadi and Taverh 2011). Lastly interactivejustice is interpersonal in nature and senses to employeesbehaviour in handling customers complaints. It includescustomer perceptions about employees empathy,friendliness, courtesy, and their honesty and responsecapacity (Casielles, Alvarez and Martin 2010).

Organisational justice based on the principle of fairnessand trust enables individuals to work collectively in a SCObased system which ultimately may lead to organisationaleffectiveness or value creation. Hannam and Jimmieson(2002), Jahangir, Akbar and Haq (2004), Camilleri (2006),Radzi et al. (2009), Mohammad, Habib and Alias (2010),Malik and Naem (2011) and Najafi et al. (2011) remarkedthat interaction and collaboration of organisationalmembers results in improving organisational performanceand innovations, if such collaborations are fair, that isbased on organisational justice. The nature of suchrelationship also reflects the role of SDL/SCO in valuecreation. Thus fair collaborative customer- provider


( 66 )

relationship results in value creation in the organisation(Liu et al. 2008). Hence following hypothesis is formulated,

H2a: There is a positive relationship between Distributive,Procedural and Interactional justice and Organisationaljustice

H2b: There is a positive relationship between Organisationaljustice (Distributive, Procedural and Interactional justice) andService competence orientation.

Note- OJ -Organisational Justice, DJ- Distributive Justice, PJ-Procedural Justice, IJ- interactional Justice and SCO- ServiceCompetencies Orientation, CC- Collaborative Competencies, AC-Absorptive Competencies

Fig. 1

Service Competencies and Organisational Commitment

Organisational commitment is a psychological state thatbuilds employees relationship with an organisation(Gatum et al. 2004). It is the relative strength of anindividual’s involvement in a particular organisation(Ensher, Vallone and Donaldson 2001, Somech and Bogler2002, Chugtai and Zafar 2006, Dickinson 2009, Mogosti,Boon and Fietcher 2011 and Oyewobi, Sulieman and Jamil2012). In other words it may be thought of as a measure ofdevotion and loyalty that an employee feels towards theorganisation (Mogosti, Boon and Fietcher 2011). Majorityof the scholars have recognized organisationalcommitment as three dimensional construct comprisingaffective, continuance and normative commitment. Thisconcept was developed by Allen and Meyer (1990).Affective commitment refers to employee identification andemotional attachment with their employing organisation(Allen and Meyer 1990). Continuance commitment isperceived cost to the employee of leaving the organisation,and may include the loss of benefits or seniority statuswithin the organisation (Allen and Meyer 1990). The thirdcomponent, normative commitment, depends on the priorattitudes and values of employees before joining theorganisation (Allen and Meyer 1990). The same is alsoreferred by (Newman, Thanacoody and Hui 2011).

Organisational commitment is also pivotal for enhancingemployee commitment (Kimpakorn and Tocquer 2007).

Employees with high organisational commitment showconsiderable interest to achieve organisational goals.Commitment which is primarily based on provider-customer relationship is equally important for SCO basedorganisations (Hazra and Srivastava 2009). As such,organisations with committed employees and customerscan improve its quality and performance in the long run(Sramek et al. 2009). Thus this interaction betweencommitted employees and customers helps in attainmentof organisational goals and ultimately leads to enhancevalue of the organisation (Kimpakorn and Tocquer 2007and Oyewobi, Sulieman and Jamil 2012). Hence,

H3a: Affective, Normative and Continuance commitmentpositively influences Organisational commitment

H3b: Organisational commitment (Affective, Normativeand Continuance) positively influences Servicecompetence orientation.

Note- OC- Organisational Commitment, AC- Affective Commitment,CC- Continuance Commitment, NC- Normative Commitment, SCO-Service Competencies Orientation, CC- Collaborative Competencies,AC- Absorptive Competencies.

Fig. 2

RESEARCH MODEL

Note- OJ -Organisational Justice, DJ- Distributive Justice, PJ-Procedural Justice, IJ- interactional Justice, OC- OrganisationalCommitment, AC- Affective Commitment, CC- ContinuanceCommitment, NC- Normative Commitment, SCO- ServiceCompetencies Orientation, CC- Collaborative Competencies,AC- Absorptive Competencies.

Fig. 3


( 67 )

RESEARCH CONTEXT – HIGHER EDUCATIONSECTOR

Akin to business organisation success of higher educationsector requires significant marketing tools to enhance andto sustain organisational performance and growth(Mihaela and Amalia 2012). Sustainability of highereducation institution can be achieved by satisfying itsvarious core stakeholders through imparting knowledge,values, and skills (Nandi 2014). Mihaela and Amalia (2012)remarked that value in higher education can be determinedmainly by the abilities and skills of its stakeholders. Inthis context among various marketing concept SCO can beseen as most appropriate to be applied in higher educationsector, with knowledge and skill exchange which is veryimportant to be supervised and supported by servicecompetencies orientation (Karpen, Bove and Lukas 2009,Golooba and Ahlan 2013 and Ronald and Amelia 2014).Service competencies (SC) or SDL in education sector,encourages employees to work in a networking system topromote effective interaction among various stakeholders.These interactions create dynamic environment where allthe stakeholders collaborate and participate in decision–making to get regular feedback from various members ofthe organisation. Such efforts consequently enhancerelation among different stakeholders and lead to valuecreation for the university. Further employees with suchcompetencies are able to adjust with the changes in theenvironment both internally and externally (Chahal andMahajan 2014). Moreover, it also enables them to absorbnew information from various social and economicintegrators such as co-workers, students, scholars, to makethe educational organisation more efficient and effective.

METHOD

Sample

Data was collected from supporting staff of two highereducational state level institutions namely, University ofJammu and Guru Nanak Dev University working since1969. University of Jammu (UOJ) and Guru Nanak DevUniversity (GNDU) have approximately 350 and 200supporting members respectively. The hierarchy ofsupporting staff of both the universities was somewhatsimilar and included deputy registrars, assistantregistrars, section officers, superintendents, assistantlibrarians, programmers, stenographers etc. Out of 550questionnaires distributed a total of 355 questionnaireswere received. About 7– 10 visits were made to collect the

questionnaires from the supporting staff and the responserate came out to be 64.54 per cent.

Generation of Scale Items

The items that are used in the study have been developedthrough review of literature and deliberations with thesubject experts. The SDL/SCO scale items was generatedfrom studies namely Lusch and Vargo (2008), Maglio andSpohrer (2008), Karpen, Bove and Lukas (2009) Ordaniniand Parasuraman (2010), Edvardson, Tronvoll andGruber (2011) and Chahal and Mahajan (2014). The itemsfor organisational justice were framed consulting Hannamand Jimmieson (2002), Jahangir, Akbar and Haq (2004)and Mohammad, Habib and Alias (2010). Lastly,Organisational Commitment items were formulatedthrough the reference of Somech and Bogler (2002), Yilmazand Bokeoglu (2008) and Oyewobi, Sulieman and Jamil (2012!)

Initially a detailed questionnaire is prepared covering allthe aspects SCO, organisational justice and organisationalcommitment Finally, after discussing with the expert andconcerned employees a refined questionnaire is framedwhich consist of 55 items with 16 items of SCO, 21 items oforganisational justice and 18 items of organisationalcommitment. Hence this helped in formation of contentvalidity.

DATA ANALYSIS

Descriptive statistics

Prior to analysing the data, the response score for negativeitems are reversed. The study identified and removedtwenty nine outliers in the data making effective samplesize as of 316 respondents. Further, the results of normalprobability plots show that all observed values are closerto the straight diagonal line and no point is strayed outside,which indicates that data are normally distributed.Moreover, the skewness and kurtosis tests suggest thatmajority of the values are within the acceptable range (Table1).This further confirms that the data is normallydistributed. The data purification and finalisation is doneusing EFA, item analysis, and CFA. These stages areexplained as under.

First stage: EFA results

Exploratory factor analysis, a data reduction andsummarisation technique, is used to identify the underlyingrelationships among set of interrelated variables to


( 68 )

represent them in terms of minimum number ofmanageable factors (Malhotra and Dash, 2010). First ofall, Kaiser-Meyer-Oklin (KMO) value (greater than or equalto .5) along with measure of sampling adequacy (MSA)greater than .70 were examined to determine the relevancyof items for factor analysis. Besides, the appropriatenessof factor analysis is also identified by examining thecorrelation matrix. Bartlett test of sphericity (BTS), astatistical technique, is used to assess the presence ofsignificant correlation among the variables (Hair et al.,2009). The factor identification is done on the basis of eigenvalue (EV), while item identification is done using factorloading (FL) and communality value (CV). Eigen valuewhich denotes total amount of variance explained by eachfactor is used to decide about the number of factors. Thevalues greater than or equal to one is considered so thateach of the factor accounts for at least as much variance asone of the original variables. Communality value greaterthan .50 is used to find out the extent to which the variablesare explained by the factors. The study adopted a factorloading value of equal to and greater than .50 to retain theitems. EFA based on the aforesaid criteria is run on SCO

and organisational justice and organisationalcommitment. Different runs are employed on the threeconstructs till clean factors are emerged. The final EFAresults for the three constructs are discussed as under.

Service Competencies Orientation

The final SCO construct contains twelve items clubbedinto four factors after four runs of EFA. The four factorsolution explicates 73.412% of variance withcommunalities and factor loadings above the thresholdcriteria range after 12 iterations. The KMO=.715 and BTS(chi- square= 1858.371, df= 66 and p= .000) values supportthe factor result (Table 2). Four items out of sixteen itemswere deleted in different data purification steps. Thus EFAresulted in four factors namely, absorb-collaborative,absorptive competencies I, absorptive competencies II andcollaborative competencies.

Organisational Justice

Organisational justice consisting of twenty one items wascondensed to seven items under two factors namely,procedural justice and distributive justice in the fourteenth

Table 1 Descriptive Statistics

Constructs Mean Standard Deviation

Skewness Kurtosis

Min Max Min Max Min Max Min Max SCO 3.23 3.96 .539 .982 .007 -.872 -.052 -.984 Organisational Justice 3.00 3.44 .636 .960 .047 .859 .011 1.571 Organisational Commitment 2.99 3.66 .740 .969 -.008 .633 .074 -1.725

Table 2 EFA Results of SCOFactors Mean FL Communalities CA

Factor 1 –Absorptive Collaborative Competencies , Eigen Value = 2.539, % of Variance = 21.155

.790 Departmental decisions taken in an unbiased manner. 3.46 .773 .670 Regular feedback is necessary 3.47 .769 .788 Specialized programmes and courses are organised 3.79 .763 .700 Co-workers are provided with relevant information. 3.56 .727 .738

Factor 2 – Absorptive Competencies (I), Eigen Value = 2.270, % of Variance = 18.917 .740 Department utilizes the capabilities 3.44 .791 .793 Free flow conversation and dialog is practiced 3.23 .750 .621 Department utilizes the needs of all its stakeholders 3.50 .731 .811

Factor 3 – Absorptive Competencies (II), Eigen Value =1.985, % of Variance =16.545 .640 Department is open to new ideas 3.67 .881 .842

Departmental members are flexible 3.56 .624 .678 Factor 4 –Collaborative Competencies, Eigen Value = 2.015, % of Variance = 16.795

.746 Departmental goals are accomplished collaboratively 3.62 .801 .788 University/ department make regular efforts to excel 3.65 .766 .704 Image of the department enhances the goodwill 3.96 .670 .675

Variance= 73.412%, Overall CA= .834


( 69 )

Table 3 EFA Values of Organisational Justice and Organisational Commitment

Factors Mean FL Communalities CA ORGANISATIONAL JUSTICE

.833

Factor 1 – Organisational Justice, Eigen Value = 2.650, % of Variance =37.855 Decisions in an unbiased manner. 3.18 .868 .779 Allowing me to appeal against the decisions 3.00 .847 .751 Procedures and policies are based on ethical standards

3.31 .816 .686

Taking into account my education level, I fairly rewarded.

3.10 .658 .630

Factor 2 – Financial Justice, Eigen Value = 2.174, % of Variance = 31.052

.747

In general, the rewards and salaries that I receive are fair

3.14 .855 .730

Taking into account my efforts, I feel I am fairly rewarded.

3.13 .810 .677

Organisation/department procedures are consistently

3.34 .728 .591

Variance = 68.907 % ORGANISATIONAL COMMITMENT

Factor 1 Affective Commitment, Eigen Value = 2.418, % of Variance = 21.985

.876

I do not feel like 'part of the family' 3.06 .955 .912 I do not feel emotionally attached' to this department.

3.09 .866 .788

I think I could easily become attached to another department

3.08 .850 .725

Factor 2 –Emotional Attachment, Eigen Value = 2.340, % of Variance = 21.272

.780

I would be very happy to spend the rest of my career

3.53 .888 .819

I really feel as if this department problem as my own.

3.54 .793 .737

This department has a great deal of personal meaning

3.23 .758 .643

Factor 3 – Continuance Commitment, Eigen Value = 1.823, % of Variance = 16.589

.670

Too much of my life would be disrupted 3.52 .833 .725 It would be very hard for me to leave my department

3.15 .689 .671

I feel that I have too few options to consider to leave

3.57 .683 .624

Factor 4 – Normative Commitment, Eigen Value =1.643, % of Variance = 14.935 Factor was deleted during item analysis Moving from organisation to organisation 3.06 .885 .799

I do not believe that a person must always be loyal

2.99 .878 .773

Variance = 74.762%, Overall CA= .710


( 70 )

run of EFA. Precautions were taken before condensing theitems for final deletion. The KMO value of .726 and BTSmeasure (chi- square= 1533.869, df= 21 and p= .000)indicate that the data are suitable for conducting factoranalysis (Table 3). The factors identified includeprocedural and distributive justice while interactionaljustice is not playing significant role.

Organisational Commitment

Organisational commitment comprises of eighteen itemsreduced to eleven under four factors after five iterations.The factor explains 74.762% of variance, with KMO= .583,BTS (chi- square= 1533.869, df= 55 and p= .000). The valuesof factor loadings and communality values are withinrange. The final result was arrived after seven runs of EFA(Table 3). The factors identified include affectivecommitment I, affective commitment II, continuancecommitment and normative commitment.

Second Stage: Item analysis

Item analysis is a set of procedures that analyses responsesto individual test items to discover which items bestmeasure the construct. It is used to assess the quality ofindividual test items and overall scale. In other words,item analysis examines the relationships between itemcharacteristics and test characteristics (Netmeyer, Bearder& Sharma, 2003). The scale items of each constructs of thestudy are analysed on the bases of varied criteria whichincludes cronbach alpha (greater than 0.7), inter- itemcorrelation (correlation among all test items which shouldbe within 0.3 to 0.9), item mean (consistency in the meanvalues), item variance (consistency in the variance values),cronbach alpha value if item deleted (AIID), (greater thanscale alpha value) scale mean if item deleted (SMID)(consistency with scale mean) item–to-total correlationcoefficient (CITC) which reflect the extent to which anyone item is related to other items of the construct (greaterthan 0.3), (Netmeyer, Bearder & Sharma, 2003). The resultsof item analysis for the three constructs are discussed asbelow:


The overall alpha value of the SCO items is found to be.834 which is above the recommended criteria. Further,the majority values of item-total correlation, rangedbetween .430 to .688 indicate that the items are correlatedwith overall scale excluding two values (that is, .283 and.299) which are retained being near to .3. Similarly, squaredmultiple correlation values ranged between .521 and .703.

The item mean values came out 3.575 (Mean), .037(Variance), item variance as .624 (Mean), .049 (Variance)whereas scale statistics reveal overall mean as 50.05, overallvariance as 38.721 and overall standard deviation as 6.223(Table 2). All the four factors as identified under EFA areretained.


The study retains seven items of organisational justiceunder two factors that is, procedural justice anddistributive justice after conducting reliability analysis(Table 3). The cronbach alpha value of 0.808 suggestsrobust reliability of organisation justice scale. Moreover,range of item-total correlation between .441 and .659 andsquared multiple correlation between .395 and .663 furtherprovide support for the internal consistency of the scaleitems. The overall mean is found to as 22.19, overallvariance as 15.89 and overall standard deviation as 3.98with item mean as 3.170 (Mean) and 0.014 (Variance) whileitem variance as .698 (Mean) and 0.028 (Variance). Hence,no item is identified for further deletion.


The application of item analysis on eleven items oforganisational commitment resulted in complete deletionof two items of normative commitment as their SMC valueswere very below the threshold criteria. As a result it reflectsadequate degree of consistency of data as the value ofcronbach alpha came out to be .710. CITC for the item ‘Toomuch of my life would be disrupted if I decide I want toleave my department’ is .190 (below the usual benchmarkof .300) but is retained as it is supported by SMC value of.368 which is above the threshold criterion. Further, thevalues of item mean as 3.285 (Mean) and.43 (Variance)and item variance as .820 (Mean) and.023 (Variance)suggest that all the items met the threshold criterion andthere is consistency in the mean and variance valuesrespectively (Table 3). The final analysis resulted in threefactors namely, affective commitment I, affectivecommitment II and continuance commitment.

Third Stage: CFA

CFA is a technique which estimates the measurementmodel. This technique seeks to test the hypothesis thatrelationship between observed variables (i.e. the variablesthat can be directly measured) and their underlying factorsor latent constructs (i.e. the variables that cannot be directlymeasured) exists (Hair et al., 2009). The study performedCFA with maximum likelihood estimation (MLE) to refine


( 71 )

and evaluate the factor structure of all the scales. Further,to assess fitness of all the measurement models, the studyused indices which include chi- square divided by degreeof freedom (÷2/df), root mean square error of approximation(RMSEA), normed fit index (NFI), comparative fit index(CFI), Tucker-Lewis index (TLI), relative fit index (RFI) andincremental fit index (IFI). A rule of thumb regarding Chi-square / df criterion indicates model to be well-fit if itsvalue is less than 2, acceptable if value is less than 3 anddefinitely not acceptable if greater than 5 (Malhotra andDash, 2010). The RMSEA value is acceptable if the value isless than .08. And all other fitness indices should be closeto .90. Moreover, path value criteria that is, critical ratio,standardised regression weight (SRW) and squaredmultiple correlation (SMC) are also used. The critical ratiorefers to test the estimate divided by the standard error. Itis the value of a test statistic which indicates a specifiedsignificance level. Values greater than 1.96 which denotesan estimate that is statistically significantly different fromzero at the .05 level is used to retain the items. Similarly,standardised regression weight (SRW) reflects the changein the dependent variable for each unit change in theindependent variable (Hair et al, 2009). The SRW valueless than .50 is considered to delete the items from analysis.However, utmost care is taken not to remove those itemswhich are significant for the study. The CFA results of thethree constructs are discussed below.


The application of CFA on twelve items under four factorsresulted in deletion of five items (Figure 4). The sevenmeasured indicators that were retained reflect good andsignificant SRW but with somewhat poor model fit. Theuse of four modification between “relevant and accurate

information and decisions taken in an unbiased manner”,“relevant and accurate information and utilizingcapabilities and needs of stakeholders”, “image of thedepartment and utilizing capabilities and needs ofstakeholders”, and “efforts to excel in teaching andspecialized programmes”, resulted in improving the modelfitness. All the values of fit indices are per the selectedcriteria (X2/df 3.184, RMR .033, GFI .926, AGFI .924, NFI962, RFI .911, IFI .973, TLI .937, CFI .973, RMSEA .083)(Table 6). While applying CFA on the SCO the result revealthat all the three competencies namely, absorbo-collaborative, absorptive I and collaborative contributesignificantly with high SRW values. Further the modelfitness is also attained with ÷2/df= 3.184 and RMSEA=.083thus accepting H 1 (Table 4).

ACC

CC5 0.04

e1 1

1

AC2 e2

ACI AC7 e6

1 AC8 e7 1

CC

CC6 e8 1

1 CC7 e9 1

CC8 e10

SCO

1

e13 1

e14 1

0.04 e15

1

1

1

1

Note: SCO- Service Competencies Orientation, CAC(Collaborative Absorptive Competencies), ACA (AbsorptiveCollaborative Competencies) & CCA (CollaborativeCompetencies) are the manifest factor, and e1, e2, e5, e7, e8. e9 &e10 are the error terms of manifest variables

Fig. 4

Item Measurement Model Model Fit Indices SRW Critical

Ratio p-

value χ2/df= 3.184 RMR=.033 GFI =.926

AGFI=.924 NFI=.962, RFI=

.911 IFI=.973 , TLI= .937

CFI= .973 RMSEA= .083

Specialized programmes and courses .948 Ref Ref Co-workers are provided with information .681 15.548 .000

Free flow conversation and dialog .753 7.018 .000 Stakeholders are consulted .756 Ref Ref

Departmental goals are accomplished .814 9.860 .000 University/ department make regular efforts to

excel .650 9.572 .000

Image of the department enhances the goodwill .675 Ref Ref

Table 4 CFA results of SCO


( 72 )


The application of CFA on organisational justice constructcomprising seven items are clubbed into two factorsnamely procedural justice and distributive justice. All thefit indices (÷2/df =3.649, RMR= .035, GFI = .977, AGFI =.919, NFI=.962, RFI= .905, IFI=.972, TLI=.929, CFI=.972)are as per the criteria excluding RMSEA (.092), which issomewhat more than .08 (Table7) reflected mediocre modelfit. The values are arrived at after deleting “Organisation/department take decisions in an unbiased manner”.However precaution is taken before deleting it so that thedeletion does not result in reducing the impact andmeaning of the construct. Modification between “takinginto account my efforts, I feel I am fairly rewarded andtaking into account my education level, I feel I am fairlyrewarded”, and “taking into account my efforts, I feel I amfairly rewarded” and “organisation /departmentprocedures are consistently followed”, resulted in bettermodel fitness Further, SRW values for all the items areabove the cut-off criterion (Table 5), Henceforth we acceptthe hypotheses H2a.

PJ

DJ

OJ

DJ4e1

1

1

PJ3e31

PJ2e41

PJ7e51

1

DJ6e61

DJ3e71

0.5

0.5

e8

1

e9

1

Note- OJ (Organisational Justice), PJ (Procedural Justice) &DJ (Distributive justice) are the manifest variable, and e1,e3, e4, e5,e6 & e7 are the error terms of manifest variables

Fig. 5


Three factor solution of organisational commitmentidentified after item analysis was used for confirmatoryfactor analysis. During CFA, one factor that is, affectivecommitment II (AFC) consisting of three items got deleteddue to low standard regression weight. The final factorretained includes affective commitment I and continuancecommitment. The model yielded good results (÷2/df

=1.255, RMR = .015, GFI = .990, AGFI = .973, NFI=.987,RFI=.975, IFI= .997, TLI=.975, CFI=.997 and RMSEA=.028).The item ‘I do not feel like ‘part of the family’ at myorganisation/department/supervisor’ records highestSRW values of .979. While lowest SRW (.466) value is seenfor the item ‘It would be very hard for me to leave mydepartment right now”. Two modifications between “I donot feel emotionally attached’ to this department and Ithink that I could easily become as attached to anotherdepartment” and “I do not feel like ‘part of the family’ atmy organisation/department/ and moving fromorganisation to organisation does not seem at all unethicalto me”. are added to make the model fit (Table 5) Thus allthe values are as per the required criteria, hence we acceptthe hypotheses H3a.

AFCI

AFC7 e1

1 1

AFC6 0.04

e2 1

AFC5 e3 1

COC

COC4 e9 1 1

COC3 e10 1

COC2 e11 1

OC 1

1

e14 1

e15 1

Note- OC (Organisational Commitment), AFC (AffectiveCommitment) & COC (Continuance Commitment) are themanifest variables and e1, e2, e3, e9, e10, e11, e14 & e15 arethe error terms of manifest variables

Fig. 6

RELIABILITY AND VALIDITY

Reliability

Reliability of the constructs in the study is examined usingcronbach alpha and composite reliability (Table 6). Thestudy concludes that the scale items are reliable, that is,the values of cronbach alpha for SCO (.769), organisationaljustice (.626) and organisational commitment (.720) areclose or above the usual benchmark of .70.

Composite reliability: The composite reliability of the threeconstructs that is, 701 (SCO), .610 (organisational justice)and .639 (organisational commitment) suggest acceptablereliability for SCO. The overall cronbach’s alpha values


( 73 )

are above .7 for SCO and organisational commitment but.626 for organisational justice (Table 6).

Validity

Convergent validity: The results of the study suggest theexistence of convergent validity as the average varianceextracted values for SCO, organisational justice andorganisational commitment are above the thresholdcriteria of .50, as given in the table 6.

Discriminant validity: The study evaluated thediscriminant validity of all the measurement scales, theresult of which is shown in the table 6. All values ofcorrelation estimates are greater than square root of AVEwhich established discriminant validity.

Table 6 : Composite Reliability, Average VarianceExtracted and Correlation Matrix

Const-ructs

Cronbach Alpha

CR AVE Correlation SCO OJ OC

SCO .769 .701 .539 .734 - - OJ .626 .610 .525 .501 .724 - OC .720 .639 .588 .038 -.002 .761

*Values in the diagonal of correlation matrix are the squareroot of AVE.

HYPOTHESES TESTING

Individual Relationship Level: Organisational Justiceand SCO

Structural Equation Modelling was used to test therelationship between organisational justice and SCO. Therelation resulted in ÷2/df =5.313, RMSEA = .117, GFI=.967,AGFI=.900, NFI=.912, CFI=.931. Further the SRW valuesare also found to be within the set range that is .400 and942. Since majority of the values are found as per the criteriathe model is acceptable (Kenny, Kaniskan, and McCoach2014) (Table 7). The relationship between organisationaljustice and SCO is found to be positive and accepted inhigher education sector. Thus organisational justice is asignificant antecedent of SCO in higher education sectorleading to acceptance of hypothesis H2b.

Individual Relationship Level: OrganisationalCommitment and SCO

Structural Equation Modelling was used to test therelationship between organisational commitment andSCO. SCO and organisational commitment model reflectedacceptable model fitness (÷2/df =4.641 RMSEA = .108).Further the result reflected that SRW values are rangedbetween .011 and .918 (Table 7). The p value is also greater

Table 5 CFA results of Organisational Justice and Organisational Commitment

Item Measurement Model\ Model Fit Indices Organisational Justice SRW CR p-value χ2/df=3.649, RMR=.035

GFI =.977, AGFI= .919

NFI=.962, RFI=.903 IFI=.972, TLI= .929

CFI=.972, RMSEA= .092

Procedures and policies are based .882 10.104 .000 Organisation/department procedures .615 9.638 .000 I feel I am fairly rewarded .697 Ref Ref The rewards and salaries that I receive fair

.726 8.399 .000

Taking into account my efforts .742 8.397

Organisation /department procedures are consistently followed.

.605 Ref Ref

Organisational Commitment χ2/df=1.255 RMR=.015 GFI =.990

AGFI=.973 NFI=.963, RFI= .975 IFI=.997, TLI= .995,

CFI= .997,RMSEA= .028

I do not feel like 'part of the family' .979 25.547 .000 I do not feel emotionally attached' .752 Ref Ref I think that I could easily become attached

.829 14.441 .000

Too much of my life would be disrupted .633 6.549 .000 It would be very hard for me to leave .466 5.992 .000 I feel that I have too few options to consider to leave this department

.832 Ref Ref


( 74 )

than .05 (p = .853). Thus the relationship betweenorganisational commitment as an antecedent of SCO inhigher education sector is not established thus hypothesisH3b is not accepted.

Overall Relationship: Organisational Justice,Organisational Commitment and SCO

The relationship between organisational justice and SCO(H2b) and organisational commitment and SCO (H3b) asantecedents of SCO in the comprehensive research model(Figure 3) is studied through SEM. The SRW and criticalratio value of organisational justice (SRW=.626 and CR=5.562) and organisational commitment (SRW= .219 andCR= .314) with respect to SCO reflect that justice is morecomprehending SCO as compared to commitment. Thesignificant relationship is found between organisationaljustice and SCO relationship (p=.000) while insignificantrelationship is found between organisation commitmentand SCO relationship (p=.751). However the overall modelfitness is not attained (÷2/df= 6.746 and RMSEA=.135)(Table 7), hence hypotheses H2b and H3b are rejected

SCO

meansdlF1 e1 1 1

meansdlF2 e2 1

meansdlF3 e3 1

OJ

OC

meanojF2 e4 1 1

meanojF1 0

e5 1

meanocF2 0

e7 1

meanocF1 e8 1

1

e17 1

e18 1

1

Note – SCO (Service Competences Orientation), OJ (OrganisationalJustice), OC (Organisational Commitment), are the manifest factor,and e1,e2,e3, e4, e5, e7, e8, e17 and e18 are the error terms ofmanifest variables

DISCUSSIONS AND IMPLICATIONS


SCO resulted into three factors in the final analysis namely,absorptive, collaborative and absorbo-collaborativecompetencies. All the three contribute significantly whichreveals that these competencies are crucial incomprehending SCO (Chahal and Mahajan 2014).Absorbo- collaborative competencies is contributinghighest (SRW=.948), followed by collaborativecompetencies (SRW= .814) and absorptive competencies(SRW=.756). The result reflects that employees areequipped with competencies and are following themeffectively. Chahal and Mahajan (2014) also remarked thatapplication of these competencies enable employees towork in a supportive environment to collaborate with co-workers and to adapt to organisational situations. Thesame is also supported by Gummenson (2008), Maglioand Spohrer (2008), Vargo and Lusch, (2008), Brodie,Saren and Pels (2011) and Edvardson, Tronvoll andGruber (2011).


The result shows that distributive and procedural justicecontributes significantly towards organisational justice.However procedural justice contributes more (SRW=.882)than distributive justice (SRW =.742). The same results arealso supported by Malik and Naem (2011), Najafi et al.(2011) and Radzi et al. (2009). This might be becauseemployees give much importance to the procedure indealing with organisational activities assigned to themand their co-partners. Further organisational justicecontributes significantly to SCO but at a moderate level.Since it is proven that the perception of fairness of rewardallocations and procedures received in the organisationprompt the employees to reciprocate accordingly, it isimportant for the organisation to improve employeesbehaviour through organisational justice (Najafi et al2011). Employees who receive justice tend to improve andmaintain communal relationships within the organisation

Table 7 : Hypotheses ResultsVariable Hypothesis CR Range SRW Range p-

value Model-fitness Accept/Reject

Individual Level OJ- SCO H2b 7.229 -8.243 .400 - .942 .000 χ2/df= 5.313, RMSEA= .117 Accepted OC-SCO H3b .184 -5.587 .011 - .918 .853 χ2/df= 4.641, RMSEA= .108 Rejected

Overall Level OJ-SCO H2b 5.562 .626 .000 χ2/df=6.746, RMSEA= .135 Rejected OC-SCO H3b .314 .219 .751


( 75 )

(Radzi et al. (2011). An employee who is stressed on thejob is much likely to experience dissatisfaction with thejob and this could lead to reactions of aggressive behaviourtowards other stakeholders (Ahmadi, Ahmadi and Taverh2011).


Among the two dimensions of organisational commitmentaffective commitment (SRW=.979) contributes more ascompared to continuance commitment (SRW=.832). Theresults suggest that to increase the level of support givento supporting staff by the organisation employees shouldbe emotionally attached and well -versed with the norms,policies and rules and regulations of the organisation. Byimplementing policies, work processes, and fair rewardsystems employees can be convinced that the organisationcares about their well-being and value their contributions.This consequently can increase employees self-esteem andtheir level of organisational commitment (Ucar and Otken2010). In the same context Najafi et al (2011) remarked thatwhen employees feel that they are treated fairly by theirorganisation, they are probably to hold more commitment,trust, satisfaction, and control. Further relationshipbetween SCO and organisational commitment is found tobe not much appealing. SCO is based on interaction ofvarious stakeholders through its varied competencies.Thus to enhance organisational commitment all employeeswithin an organisation must have sense of belief that theyhave necessary skills and capability to perform their workwhich consequently can increase their level of commitmentin the organisation. Angle and Perry (1981) stated that tocompete in the dynamic network environment,organisation should guarantee commitment for improvingorganisational performance

Overall study result shows that organisational justice isexplaining SCO more as compared to organisationalcommitment. Further among the two dimensions oforganisational justice, procedural justice is morecontributing than distributive justice. This reflects thatsupporting employees being educated and well versed withnorms and procedures, follow them explicably. The resultalso indicates that SCO competencies enable employees tocollaborate and absorb information required for theeffective functioning of the organisation justifiably. Itenables supporting staff to be satisfied with the fair andethical treatment they receive in an organisation. Howeverin context of organisational commitment affectivecommitment is more contributing than continuance

commitment. This might be because employees thoughcommitted to some extent are reluctant to approach to theorganisation or department to express out their feelingsand problems, affecting their level organisationalcommitment inversely. Thus employees thoughcommitment are not involved in collaborating andabsorbing activities in the context of SCO environment.The overall integrated relation does not seem to besignificantly acceptable as per the result attained. Thusefforts should be made to improve the relation that is,organisation justice and organisation commitment asantecedents of SCO.

LIMITATIONS AND FUTURE RESEARCH

Utmost care was taken while collecting data fromsupporting staff members of the selected universities.However subjectiveness in the responses of respondentsis unavoidable limitation (due to use of primary data).Secondly, only supporting staff were contacted. Hencestudy results are limited to understand the concept of SCO.Thus to have a more better understanding of the conceptthe future studies need to be explored to includestakeholders like higher authorities, faculty members,scholars etc. Further only two antecedents namely,organisational justice and organisational commitment areexamined with respect to SCO in the study. Various otherantecedents like motivation, personality traits andemployee participation identified in the literature shouldalso be explored to conceptualise SCO. Lastly, the conceptof SCO may also be examined in relation to consequencesof SCO namely, employee productivity, customersatisfaction, organisational performance, value co-creation. etc. in other service areas also.

REFERENCES

Abela AV, Murphy PE (2008) Marketing with integrity:ethics and the service-dominant logic for marketing.J Acad Mark Sci 36 (1):39-53

Ahmadi FS, Ahmadi AA, Tavreh N (2011) SurveyRelationship between Organisational Justice andOrganisational Citizenship Behaviour (OCB) ofFood Product Firms in Kurdestan Province. Inter JCont Res Bus 2(10):272-281

Allen NJ, Meyer JP (1990) The measurement andantecedents of affective, continuance and normativecommitment to the organisation. J OccupationalPsychology 63: 1-18


( 76 )

Angle HL, Perry JL (1981) An empirical assessment oforganisational commitment and organisationaleffectiveness. Administrative science quarterly26(1):1-14

Arnould EJ (2008) Service-dominant logic and resourcetheory. J the Academy of Marketing Science 36(1):21-24

Ballantyne D, Varey RJ (2008) The service-dominant logicand the future of marketing. J the Academy ofMarketing Science 36(1):11-14

Baron S, Anthony P, Gary W, Kim H (2010) Service–dominant logic: marketing research implication andopportunities. J Customer Behaviour 9(3):253- 264

Bommer H, Edward W, Miles W, Grover SL (2003) DoesOne Good Turn Deserve Another? Co-workerInfluences on Employee Citizenship. JOrganisational Behaviour 24:181-196

Brodie RJ, Saren M, Pels J (2011) Theorizing about theservice dominant logic: The bridging role of middlerange theory. J Marketing Theory 11(1):75-91

Camilleri E (2006) Towards developing an organisationalcommitment-public service motivation model for theMaltese public service employees. Public policy andadministration 21(1):63-83

Casielles RV, Alvarez LS, Martin LMD (2010) Perceivedjustice of service recovery strategies: Impact oncustomer satisfaction and quality relationship.Psychology and Marketing 27(5):487–509

Chahal H, Mahajan R (2014) Exploring role of servicecompetence orientation (SCO) in creating value inhigher education sector. Amity Business School15(2):67-83

Chan KW, Yim CK, Lam SS (2010) Is customer participationin value creation a double-edged sword? Evidencefrom professional financial services across cultures.J Marketing 74(3): 48-64

Chughtai AA, Zafar S (2006) Antecedents andconsequences of organisational commitment amongPakistani university teachers. Applied HRMResearch 11(1):39-64

Dickinson L (2009) An Examination of the FactorsAffecting Organisational Citizenship Behaviour.Departmental Honors Thesis (Accounting), The

University of Tennessee atChattanooga,www.utc.edu/Administration/Departmental Honors/ Dickinson.pdf, accessed on16 July 2011, 1-43

Dong B, Evans KR, Zou S (2008) The effects of customerparticipation in co-created service recovery. JAcademy of Marketing Science 36(1):123-137

Edvardsson B, Tronvoll B, Gruber T (2011) Expandingunderstanding of service exchange and value co-creation: a social construction approach. J Academyof Marketing Science 39(2):327-339

Ensher EA, Grant-Vallone EJ, Donaldson SI (2001) Effectsof perceived discrimination on job satisfaction,organisational commitment, organisationalcitizenship behaviour, and grievances. HumanResource Development Quarterly 12(1):53-73

Ford RC, Bowen DE (2008) A service-dominant logic formanagement education: It’s time. Academy ofmanagement learning and education 7(2):224-243

Gautam T, Dick RV, Wagner U, Upadhyay N, Davis AJ(2004) Organisational Citizenship Behaviour andOrganisational Commitment in Nepal. AstonAcademy for Research in Management, Researchpaper, Aston University, UK, 1-25,www.segi.edu.my/ onlinereview/... pg 23.php,Accessed on April 03, 2011.

Golooba M, Ahlan AR (2013) Service Value Co-creation inResearch andInnovation Practices in HigherEducation Institutions in Malaysia. ProcediaTechnology 11:342-347

Greenberg J (1987) A taxonomy of organisational justicetheories. Academy of Management Review 12(1):9-22

Gronroos C (2008) Service logic revisited: who createsvalue? And who co-creates. European BusinessReview 20(4):298-314

Gronroos C (2011) Value co-creation in service logic: Acritical analysis. Marketing Theory 11(3):279-301

Groth M (2005) Customers as Good Soldiers: ExaminingCitizenship Behaviour in Internet ServicesDeliveries. J Management 31(7):7-27

Gummesson E (2008) Extending the service-dominantlogic: from customer centricity to balanced centricity.


( 77 )

J Academy of Marketing Science 36(1):15-17

Hair JF, Robert PB, Dravid JO (2009) Marketing Research.Tata McGraw Hill Publications, Delhi, 318- 319

Hannam RL, Jimmieson NL (2002) The relationshipbetween extra-role behaviours and job burnout forprimary school teachers: A preliminary model anddevelopment of an organisational citizenshipbehaviour scale. In 2002 Annual Conference of theAustralian Association for Research (1-17) AARE.

Hazra SG, Srivastava KBL (2009) Impact of service qualityon customer loyalty, commitment and trust in theIndian banking sector. The IUP J MarketingManagement 53(3 and 4):74- 95, accessed on 4 June2011

Jahangir N, Akbar MM, Haq M (2004) Organisationalcitizenship behaviour: Its nature and antecedents.Journal of BRAC 1(2):75-85

Karpen IO, Bove LL, Lukas BA (2012) Linking service-dominant logic and strategic business practice: Aconceptual model of a service-dominant orientation.J Service Research 15(1):21-38

Kenny DA, Kaniskan B, McCoach DB (2014) Theperformance of RMSEA in models with smalldegrees of freedom. Sociological Methods & Research0049124114543236

Kimpakorn N, Tocquer G (2007) Employees’ commitmentto brands in the service sector: Luxury hotel chainsin Thailand. J Brand Management 16(8):532-544

Littleton K, Whitelock D (2004) Guiding the creation ofknowledge and understanding in a virtual learningenvironment. Cyberpsychology & Behaviour7(2):173-181

Liu Y, Tao L, Li Y, Ansary AIE (2008) The Impact of adistributor’s trust in a supplier and use of controlmechanisms on relational value creation inmarketing channels. J Business and IndustrialMarketing 23(1):12–22

Lopes AJ, Pineda R (2013) Service Systems EngineeringApplications. Procedia Computer Science 16:678-687

Lusch R F, Vargo SL (2008) The service- dominant mindset.In Bill Hepley and Windy Murphy (Ed). ServiceScience Management and Engineering, Education

for the 21st Century, Springer 89-96

Lusch RF, Vargo SL, O’Brien M (2007) Competing throughservice: insights from service - dominant logic. JRetailing 83(1):5-18

Lusch RF, Frederick EWJr (2011) A Stakeholder-unifyingco-creation philosophy for marketing. J Macro-marketing 31(2):129-134

Malhotra. N, Dash S (2010) Marketing research: an appliedorientation (6th Ed). Pearson Publications. NewDelhi

Maglio PP, Spohrer J (2008) Fundamentals of servicescience. J Academy of Marketing Science 36(1):18-20

Malik ME, Naeem B (2011) Impact of perceivedorganisational justice on organisationalcommitment of faculty: empirical evidence fromPakistan. Interdisciplinary J Research in Business1(9):92-98

McColl-Kennedy JR, Vargo SL, Dagger TS, Sweeney JC,Van Kasteren Y (2012) Health care customer valueco-creation practice styles. J Service Research1094670512442806. 1-20

Miao CF, Donald JL, Kenneth RE (2009) Re-examining theInfluence of Career Stages on SalespersonMotivation: a Cognitive and Affective Perspective. JPersonal Selling and Sales Management 29(3):243–255

Mihaela D, Amalia P (2012) The partnership relationshipbetween economic academic and businessenvironment, component of modern universitymarketing orientation. Procedia-Social andBehavioural Sciences 62:722-727

Mohammad J, Habib FQB, Adnan M, Alias B (2010)Organisational Justice and OrganisationalCitizenship Behaviour in Higher Education. GlobalBusiness and Management Research: anInternational J 2(1);13-32

Mogotsi IC, Boon JA, Fletcher L (2011) Modelling therelationships between knowledge sharing,organisational citizenship, job satisfaction andorganisational commitment among School Teachersin Botswana. African J Library 21(1):41-58

Mundhra WCD (2010) Intrinsic motivational canvass in


( 78 )

the Indian service sector: An empirical study. Vision:The J Business Perspective 14(4):275-284

Najafi S, Noruzy A, Azar HK, Nazari-Shirkouhi S, DalvMR (2011) Investigating the relationship betweenorganisational justice, psychological empowerment,job satisfaction, organisational commitment andorganisational citizenship behaviour: An empiricalmodel. African J Business Management 5(13):5241-5248

Nandi R (2014) India’s Position in the Global Community:With Respect to Higher Education Scenario. Int JEducational Planning & Administration 4(1):37-48

Netemyer RG, Bearder W, Sharma S (2003) ScalingProcedures, Issues and Applications. SagePublications. London

Newmana A, Thanacoody R, Hui W (2011) The impact ofemployee perceptions of training on organisationalcommitment and turnover intentions: a study ofmultinationals in the Chinese service sector. Int JHuman Resource Management 22(8):1765–178

Nga GB, Hackermeier I, Jiao X, Wagdarikar SP (2010)Organisational Citizenship Behaviour andPerception of Organisational Justice in StudentsJobs. Psychology of Excellence, Instructional Design,Job Analysis and Job Design. Books on Demand,GmbH, Nordestedt Germany. ISBN 978-3-640-64435-3, 2-14

Ordanini A, Parasuraman A (2010) Service innovationviewed through a service-dominant logic lens: aconceptual framework and empirical analysis. J SerResearch 1094670510385332. 1-21

Oyewobi LO, Suleiman B, Muhammad-Jamil A (2012) Jobsatisfaction and job commitment: A study ofquantity surveyors in Nigerian Public Service. Int JBusiness and Management 7(5):179-192

Radzi SM, Ramley SZA, Salehuddin M, Othman Z (2009)An empirical assessment of hotel departmentalmanagers turnover intentions: The impact oforganisational justice. Int J Business andManagement 4(8):173-183.

Randall WS, Pohlen TL, Hanna JB (2010) Evolving a theoryof performance–based logistics using insights fromservice dominant logic. J Business Logistics31(2):35-61

Rego A, Cunha MP (2010) Organisational justice andcitizenship behaviours: A study in the Portuguesecultural context. Int Association of AppliedPsychology 59(3)404–430

Rodgers T (2007) Measuring value added in highereducation: A proposed methodology for developinga performance indicator based on the economicvalue added to graduates. Education Economics15(1):55-74

Ronald, Amelia (2014) Measuring Service Quality onHigher Education Base on Service Dominant Logic.Interdisciplinary J Contemporary Research inBusiness 6(5):95-106.

Saks AM (2006) Antecedents and Consequences ofEmployee Engagement. J Managerial Psychology21(7):600-619.

Shah N (2010) A study of the relationship betweenorganisational justice and employee readiness forchange. J Enterprise Information Management24(3):224-236

Schulz M, Gnoth J (2008) Understanding the service-dominant (S-D) logic from within the firm. OtagoForum 2: Academic Papers. 127 -138

Somech A, Bogler R (2002) Antecedents and consequencesof teacher organisational and professionalcommitment. Educational administration quarterly3894):555-577

Sramek BD, Cornelia D, John TM, Matthew BM (2009)Creating commitment and loyalty behaviour amongretailers: What are the roles of service quality andsatisfaction?. J Academic of Marketing Science37:440–454

Tatum BC, Eberlin R, Kottraba C, Bradberry T (2003)Leadership, decision making and organisationaljustice. J Management 41(10):427-439

Tyagi PK (1985) Relative Importance of Key JobDimensions and Leadership Behaviours inMotivating Salesperson Work Performance. JMarketing 76- 86

Ucar D, Otken AB (2013) Perceived organisational supportand organisational commitment: The mediating roleof organisation Based self-esteem. Dokuz EylülÜniversitesi Ýktisadi ve Ýdari Bilimler FakültesiDergisi 25(2)


( 79 )

Vargo SL (2008) Customer integration and value creationParadigmatic Traps and Perspectives. J ServiceResearch 11(2):211-215

Vargo SL, Lusch RF (2004) Evolving to a new dominantlogic for marketing. J Marketing 68(1):1-17

Vargo SL, Lusch RF (2008) Service-dominant logic:continuing the evolution. J Academy of MarketingScience 36(1):1-10

Weigand H, Jeewanie JA (2009) Value encounters:Modelling and analyzing co-creation of value. AISTransactions on Enterprise Systems 2(1):32-41

Yilmaz K, Bokeoglu OC (2008) Organisational citizenshipbehaviour and organisational commitment inTurkish primary schools. Work Applied Sciences J3(5):775-780.

Prof. Hardeep ChahalDepartment of CommerceDept. of Commerce, University of Jammu,Jammu & Kashmir, 180006

Email : [email protected])

Ms. Rupa MahajanPh.D. ScholarDept. of Commerce, University of Jammu,Jammu & Kashmir, 180006

Email : [email protected])


( 80 )

INTRODUCTION

Changing customer demands, increased expectations for superior quality ofproducts or services and the global competition has created a competitiveenvironment among different industrial sectors. Quality has become an icon for thecustomers while selecting a service or product and at the same time organizationsare making efforts for providing quality products or services as per customer’sneeds and wants. Quality has been considered as a strategic advantage for theorganizations to gain success and to sustain in the business world. Themanufacturing sector in many countries around the globe had successfullybenefited by implementing the quality management principles and gained remarkablesuccess both at local as well as international market. Products are tangible andquality of products is intangible in nature and can easily be measured whereas theservices are intangible in nature and difficult to measure as compared with theproducts. Anderson and Zeithaml 1984; Parasuraman et al., (1985) stated thatQuality has become a key determinant in both industrial and service sector to gainmaximum return on investment and also significantly contributed in reduction ofcost. Spreng & Mackoy, (1996); Reichheld & Sasser, (1990) observed that Serviceorganizations are now well aware about the facts that they need to take preventivequality measures to gain customer satisfaction and retention. A study by Berry etal., (1989); Reichheld & Sasser, (1990); Rust & Zahorik, (1993); Spreng & Mackoy,(1996); Cronin et al., (2000); yoon & Suh, (2004); Kang & James, (2004) found thatthe importance of service quality has been recognized and its implications escortsthe organizations to increase organizational performance, customer satisfactionand loyalty.

Like the other service organizations; healthcare sector has also become a highlycompetitive and rapidly growing service industry around the world. The biggestchallenge faced by the health marketers is to define and measure the service

Key words

Service-dominant Logic,Service–competenciesOrientation,Organisational justice,Organisationalcommitment,

Perception of Patients Regarding Service QualityDimensions : An Empirical Study of SantokbaDurlabji Memorial Hospital, Jaipur

Ankita Jain and Varsha Choudhary

ABSTRACT

Quality has been considered as a strategic advantage for the organizations to gain success andto sustain in the business world. Like the other service organizations; healthcare sector has alsobecome a highly competitive and rapidly growing service industry around the world. The biggestchallenge faced by the health marketers is to define and measure the service quality.

The paper presents an empirical investigation to measure different dimensions of perception ofpatients regarding service quality with the help of descriptive analysis and chi-square test. Datawere collected through field research among 100 patients and the data were analyzed usingdescriptive analysis and chi-square test.


( 81 )

quality. A study by Babkus & Mangold, (1992) statedthat It was recognized in previous study that the‘SERVQUAL’ is a comprehensive scale to empiricallyestimate the level of quality services delivered tocustomers, and it is best suitable in the hospitalenvironment.

Tabish, (1998) found that a review of health sectorsindicated that because of the technical and managerialinefficiency within hospital, large recurrent expenditureson hospitals involve a huge waste of resources. Astudy by Ramsaran - fowdar, (2008) state thatSatisfaction of patients and service quality are criticalcomponents in strategic planning process; because as aresult of increasing in technology, patients are moreaware of the facts than ever and if patients are notsatisfied, they will switch to another health careprovider. Zeithmal, (2000) found that a good customerexperience affects corporate business performance, whichincludes profitability, productivity, market share, andreduced costs.

The objective of the study is to measure differentdimensions of hospital service quality by descriptiveanalysis and chi-square test. In addition, the studyanalyzes the perception of patients regarding selecteddimensions of SERVQUAL model in SDMH hospital.

LITERATURE REVIEW

Zahra Khamda, Nazanin Pilevari (2013), The papertitled “Presenting a Model to Rank Hospital Wards onthe Base of Service Quality Case Study: An IranianHospital” states that to measure service providers’perceptions and preferences towards quality ofhealthcare services and to present a model for rankingservice quality among four Iranian hospital wards byusing a 20-item scale questionnaire based on a modifiedSERVQUAL model developed by Parasuraman, Zeithamland Berry (1988). The studied wards orderly ranked asDialysis Unit, Emergency Unit, Coronary Care Unit,and Intensive Care Unit, based on different levels of theservice quality, by using the algorithm of PreferenceRanking Organization Method for EnrichmentEvaluations.

Fethi Calisir, Cigdem Altin Gumussoy, Ayse ElvanBayraktaroglu and Burcu Kaya (2012), The paper titled“Effects of Service Quality Dimensions on CustomerSatisfaction and Return Intention in Different HospitalTypes” states that a modified SERVQUAL approach

including usability as the six dimensions of servicequality which has been used to evaluate the effect ofservice quality dimensions on customer satisfactionand return intention for four different hospital typesoperating in Turkey: public, private, university, andmilitary hospitals.

Arun kumar G, Dr. S.J Manjunath, Chethan K.C(2012), The paper titled “Service Quality at Hospital –A Study of Apollo Hospital in Mysore” mentionedthat the quality of service is considered as a veryimportant factor in differentiation of services. It is abasis of competitive. In this article it was concludedthat the service is a global judgment and high standardsof their service leads to the customer loyalty andsatisfaction.

Johan de Jager and Therese du Plooy (2011), Thepaper titled “Tangible Service- Related Needs ofPatients in Public Hospitals in South Africa”mentioned the in - patients and out-patients’expectations, perceptions and satisfaction related toservices’ tangibility provided by public healthcare inSouth-Africa are measured by using SERVQUAL. Themajor findings were that all patients demand excellentlevels of response, but none of these are currently beingm et, resulting in dissatisfaction.

RESEARCH METHODOLOGY

The current study is based on primary and secondarydata both for the collection of primary data thequestionnaire was developed. The universe of thestudy was the people who were the patients of SantokbaDurlabji Memorial Hospital of Jaipur, Rajasthan.

Data collection method: - Questionnaire

Sample size: - The size of respondents is 100

Research design: - Exploratory and Descriptive researchdesign

The overall sample size for the study will include 100patients as explained below:-

Name of the hospital Size of the respondents

Santokba Durlabji Memorial Hospital

100

Sampling Technique – Simple random Probabilitysampling technique has been used for identifying the


( 82 )

respondents of the study. Simple random samplingtype of probability sampling is been used for thesurvey.

OBJECTIVES

• To study the perception of patients on dimensionsof service quality.

• To study the impact of service quality dimensionson patient satisfaction.

HYPOTHESIS

• H0: There is no significant difference in theperception of patients regarding selecteddimensions of SERVQUAL model in SDMHhospital.

• H1: There is a significant difference in theperception of patients regarding selecteddimensions of SERVQUAL model in SDMHhospital.

ANALYSIS AND DISCUSSION

Table 1 : Descriptive Analysis

Dimension Factor N Mean Std. Deviation

Dimension Mean

Dimension Std.

Deviation Rank

Tang

ibili

ty

Helpful administration (T1) 100 4.4000 .55048

4.2570 .59407 I

Proper sign boards (T2) 100 4.3400 .58981 Availabilities of amenities (T3) 100 4.3900 .49021

Clean and modern looking infrastructure ( T4) 100 4.3700 .54411

Specialized health care service are available (T5) 100 4.2800 .66788

Emergency trolley equipped with medicines. (T6) 100 4.3600 .48242

Pathology lab is in hospital premises (T7) 100 3.7000 .88192

Cleanliness at entry & exit (T8) 100 4.4200 .51601

Clean and comfortable beds (T9) 100 4.3300 .55149

Emergency exit is available (T10)

100

3.9800

.66636

Rel

iabi

lity

Proper fire protection (R1) 100 4.0700 .63968

3.8530 .92804 IV

Treatment is affordable (R2) 100 3.0500 1.37345 Reports are understandable (R3) 100 3.2000 1.32574

Reports are accurate (R4) 100 3.5900 1.18998 Medicines are available at same price as outside (R5) 100 3.7100 1.12182

Patients are priority (R6) 100 3.7800 1.05964 Food is hygienic (R7) 100 4.3800 .56461 Nurses are available on a call (R8) 100 4.1700 .68246

Waiting system is same for all (R9)

100 4.4400 .51874

Recommendations are reliable (R10) 100 4.1400 .80428

Perception of Patients Regarding Service Quality Dimensions : An Empirical Study of Santokba Durlabji Memorial Hospital, Jaipur

( 83 )

R

espo

nsiv

enes

s

Clear Treatment explanation (RS1) 100 4.1100 .82749

4.0110 .77634 II

Satisfactory hours of treatment (RS2) 100 4.0300 .83430

Proper ventilation (RS3) 100 3.9700 .90403 Proper air conditioning /room heating(RS4) 100 4.0100 .78490

Availability of drainage (RS5) 100 4.0400 .80302

Laundry services available (RS6) 100 4.1500 .57516

Accessible emergency trolleys (RS7) 100 4.0000 .71067

Every time staff is available(RS8) 100 4.3900 .49021

Different wards are available(RS9) 100 4.3600 .48242

Administration solves problem (RS10) 100 3.0500 1.35121

Ass

uran

ce

Fee charged information is provided (A1) 100 3.2300 1.21319

3.2100 0.98508 V

Easy fee collection (A2) 100 2.8700 1.30000 Installation system available (A3) 100 3.6900 1.04151

Basic information of disease provided (A4) 100 2.7600 1.16446

Documentation is understandable (A5) 100 3.4000 1.20605

Necessary test recommended (A6) 100 3.4000 1.20605

Life insurance offers available (A7) 100 2.3500 .72995

Pre and post treatment services available (A8) 100 4.1900 .56309

Life insurance available (A9) 100 2.3500 .72995 Proper security (A10) 100 3.8600 .69660

Empa

thy

Good care received by nurses (E1) 100 3.8500 .68718

4.0800 .74226 III

Nurses are polite (E2) 100 3.8400 .69224 Good care received by doctors (E3) 100 4.2200 .52378

Doctors are polite (E4) 100 4.2600 .64542 Specialized professionals are polite (E5) 100 4.0400 .87525

Patients are informed about treatment (E6) 100 4.2900 .59110

Doctors and nurses are concern (E7) 100 4.0600 .86246

All patients are same for administration (E8) 100 4.0600 .86246

Doctors listens about the problem (E9) 100 4.1100 .81520

Administration is concerned about the comfort (E10) 100 4.0700 .86754


( 84 )

Above table no. 1 shows that patients of SDMH aremost satisfied with the Tangibility i.e. physical facilitiesprovided by the hospital as it has maximum meanscore (4.2570). The Hospital staff’s willingness to helppatients i.e. responsiveness with mean score (4.0110) isplaying the second leading role in providing satisfactionto the patients. The Empathy, Reliability and Assurancewith mean score of 4.0800, 3.8530 and 3.2100 holdsthird, fourth and fifth position respectively to make thepatients feel satisfied.

Table No. 2: Results of Cronbach’s Alpha

Dimension No. of items

Cronbach's Alpha

Tangibility 10 0.778 Reliability 10 0.872 Responsiveness 10 0.731 Assurance 10 0.725 Empathy 10 0.849

From the above table no.2, it can be seen that Cronbach’salpha is higher than 0.70 which indicates a high levelof internal consistency for the scale in all the selecteddimension of SERVQUAL model with this presentstudy.

Table No. 3: Chi-Square

Factors N Chi Square

(Asymp. Sig.)

Null Hypothesis

T1 100 0.00 Rejected T2 100 0.00 Rejected T3 100 0.028 Rejected T4 100 0.00 Rejected T5 100 0.00 Rejected T6 100 0.005 Rejected T7 100 0.00 Rejected T8 100 0.00 Rejected T9 100 0.00 Rejected T10 100 0.00 Rejected R1 100 0.00 Rejected R2 100 0.00 Rejected R3 100 0.00 Rejected R4 100 0.11 Accepted R5 100 0.01 Rejected R6 100 0.00 Rejected R7 100 0.00 Rejected R8 100 0.00 Rejected R9 100 0.00 Rejected

R10 100 0.00 Rejected RS1 100 0.00 Rejected RS2 100 0.00 Rejected RS3 100 0.00 Rejected RS4 100 0.00 Rejected RS5 100 0.00 Rejected RS6 100 0.00 Rejected RS7 100 0.00 Rejected RS8 100 0.028 Rejected RS9 100 0.005 Rejected RS10 100 0.00 Rejected A1 100 0.00 Rejected A2 100 0.00 Rejected A3 100 0.00 Rejected A4 100 0.00 Rejected A5 100 0.00 Rejected A6 100 0.00 Rejected A7 100 0.00 Rejected A8 100 0.00 Rejected A9 100 0.00 Rejected A10 100 0.00 Rejected E1 100 0.00 Rejected E2 100 0.00 Rejected E3 100 0.00 Rejected E4 100 0.00 Rejected E5 100 0.00 Rejected E6 100 0.00 Rejected E7 100 0.00 Rejected E8 100 0.00 Rejected E9 100 0.00 Rejected E10 100 0.00 Rejected

The results of Chi-square explains that in all the abovecases null hypothesis is rejected except in R4 (Reportsare accurate) which indicates that there is a significantdifference in the perception of patients regarding selecteddimensions of SERVQUAL model in SDMH hospital.

FINDINGS AND SUGGESTIONSFindings

On the basis of the study the major findings are:-

• The patients of SDMH are found satisfied (4.42)with the cleanliness at the entry and exit in thehospital.

• The patients of the hospital are found satisfiedwith the system of waiting to meet the doctors inthe hospital (4.44).

Perception of Patients Regarding Service Quality Dimensions : An Empirical Study of Santokba Durlabji Memorial Hospital, Jaipur

( 85 )

• The patients are found satisfied with theavailability of the staff in the hospital premises(4.39).

• The patients are found satisfied with the pre andpost treatment services provided by the hospital(4.19).

• The patients of the SDMH are found satisfiedwith the treatment information provided by thedoctors (4.29).

Suggestions

• Pathology lab must be situated in the hospitalpremises for the convenience of the patients.

• Treatment provided by the hospital should beaffordable for all kind of patients.

• Administration should properly solve theproblems of the patients.

• Life insurance proposals must be available in thehospital for the patients.

• Nurses must be polite so that patients feel morerelaxed and satisfied.

CONCLUSION

The results of the study shows that patients of SDMHare most satisfied with the Tangibility i.e. physicalfacilities provided by the hospital as it has maximummean score (4.2570). The Hospital staff’s willingness tohelp patients i.e. responsiveness with mean score(4.0110) is playing the second leading role in providingsatisfaction to the patients. The Empathy, Reliabilityand Assurance with mean score of 4.0800, 3.8530 and3.2100 holds third, fourth and fifth position respectivelyto make the patients feel satisfied. In table no.2, it canbe seen that Cronbach’s alpha is higher than 0.70which indicates a high level of internal consistency forthe scale in all the selected dimension of SERVQUALmodel with this present study. The results of Chi-square explains that in all the cases null hypothesis isrejected except in R4 which indicates that there is asignificant difference in the perception of patientsregarding selected dimensions of SERVQUAL model inSDMH hospital.

LIMITATIONS

• Humans have tendency to behave artificiallywhen they know that they are being observed.So, the patients upon whom the research iscarried may behave artificially when they areaware that they are being observed.

• An inability to answer research questions by thepatients of the hospital.

• The study may have some common limitations ofa subjective research.

• The problem of imperfections of data and theintricacy involved in the statistical analysis arein a way inevitable in all such behavioral scienceresearch.

• The conclusions are only exploratory andsuggestive in nature.

REFERENCES

Andaleeb, S. S. (2000). “Public and private hospitals inBangladesh: service quality and predictors of hospitalchoice”. Health Policy and Planning, Vol. 15, No. 1, PP.95–102.

Anirban Chakraborty, Sonal G Rawat, Susheel Chhabra(2009), “Enhancing service Quality in Hospitals: MiningMultiple Data sources”, International Journal of InformationCommunication Technologies and Human Development,Volume 1, Issue 4, PP 58-71.

Annamalai Solayappan , Dr. Jothi Jayakrishnan , SethuVelmani (2011), “Quality Measurement for HospitalServices”, International Conference on Information andFinancial Engineering, Volume 12, PP 246-250.

Arun kumar G, Dr. S.J Manjunath, Chethan K.C (2012),The paper titled “Service Quality at Hospital – A Studyof Apollo Hospital in Mysore”, Volume 4, Issue 1, PP.1-7.

Dr. D. Selcen Aykac, Dr. Serkan Aydin, Dr. Metin Ates,Dr. Ayse Tansel Cetin (2007), “Effects of service qualityon customer satisfaction and customer loyalty: Marmrauniversity Hospital”, Journal of business and management,Volume 4, Issue 1, PP 1-11.

Dr. Mamta Brahmbhatt, Dr. Narayan Baser, Prof. NisargJoshi (2011), “Adapting the SERVQUAL scale to Hospitalservices: An Empirical investigation of patient’s perception


( 86 )

of service quality, International Journal of MultidisciplinaryResearch, Volume 1 Issue 8, PP 27-42.

Fethi Calisir, Cigdem Altin Gumussoy, Ayse ElvanBayraktaroglu and Burcu Kaya (2012), “Effects of ServiceQuality Dimensions on Customer Satisfaction and ReturnIntention in Different Hospital Types”, InternationalConference on Industrial Engineering and OperationsManagement Istanbul, Turkey, Volume 12, PP 3-6.

Figen Yesilada and Ebru Direktor (2010), “Health careservice quality: A comparison of public and private hospitals”,African Journal of Business Management, Volume 4 Issue 6, PP. 962-971.

Hanjoon Lee, Linda M. Delene, Mary Anne Bunda,Chankon Kim (2000), “Methods of Measuring Health-CareService Quality”, Journal of Business Research, Volume 48,PP 233–246.

Johan de Jager and Therese du Plooy (2011), “TangibleService-Related Needs of Patients in Public Hospitals inSouth Africa”, International Research Symposium in ServiceManagement Yogyakarta, INDONESIA, Volume 1 Issue 2,PP 26 – 30.

Parasuraman, A., zeithaml, V.A., & Berry, L.L. (1998).SERVQUAL: “A Multiple-Item scale for measuring consumerperceptions of service quality”. Journal of retailing, Vol.64(1), pp. 12-40.

Sulieman Ibraheem Shelash Al-Hawary (2012), “Healthcare services quality at private hospitals, from patients’perspective: A comparative study between Jordan and SaudiArabia”, African Journal of Business Management , Volume6 Issue 22, PP. 6516-6529.

Zahra Khamda, Nazanin Pilevari (2013), “Presenting aModel to Rank Hospital Wards on the Base of ServiceQuality Case Study: An Iranian Hospital” , Volume (3)1 ,PP. 807-817.

Dr. Ankita JainAssociate Professor


Varsha ChoudharyResearch Scholar


Perception of Patients Regarding Service Quality Dimensions (An Empirical Study of Santokba Durlabji Memorial Hospital, Jaipur)

Relative Importance of the Organisational Factors Capable of ...

Documents