EXPLORING THE DIMENSIONS OF EMPLOYEE RETENTION IN BPO INDUSTRY

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As ia Pacific Jou rnal of Research Vol: I Issue XIV, Jun e 2014

ISSN: 2320-5504, E-ISSN-2347-4793

Page | 61

EXPLORING THE DIMENSIONS OF EMPLOYEE RETENTION IN BPO INDUSTRY

IN KERALA

Dr .G S Gir eesh Kumar , Associate Professor, Department of Commerce,

Nirma College,Muvattupuzha, Kerala

Santhosh C, Assistant Professor, Department of Commerce, EKNM Government College,

Elerithattu, Kasaragod, Kerala

ABSTRACT

The Indian IT-BPO sector has remained as global powerhouse by exhibiting rapid evolution in

terms of expansion of vertical and geographic markets, attraction of new customer segments,

transformation from technology providers to strategic business partners and by offering a

considerably wider spectrum of services over the years. The aggregated revenue from the sector isestimated at USD 95 billion in FY year 2013, growing at 10.2% over FY 2012 with the provision of

direct employment to about three million people. It is expected that the industry will reach USD 106 – 111 billion during FY 2014; a growth of about 13 – 15% over FY 2013 (NASSCOM 2013) . Humanresources are the drivers and principal value-creators of the output of this industry. Therefore,

attracting, training, retaining and motivating employees are the critical success-determinants.

However, retaining talented employees is a serious concern in knowledge based organizations. When

employees leave an organization, they carry with them invaluable tacit knowledge which is often the source of competitive advantage for the business. The present study aims at identifying the major

dimensions of retention in BPO industry in Kerala. A survey instrument was developed for the study to

gather information. The population for this study comprised of employees working in various BPOs in Kerala. A sample size of 240 was chosen by simple random sampling method. Factor Analysis,

Correlation and Regression are used to extract dimensions of employee retention and to know the

influence of these dimensions on employee‟s intention to stay. Out of the dimensions extracted, job support, compensation and recognition are identified as major factors determining the stay of

employees in BPO industry in Kerala.

Key words: Business Process Outsourcing, verticals, retention, compensation, motivation.


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I. INTRODUCTION

The IT-BPO Industry is playing a vital role in India‟s economic growth. It accounts nearly for5.2 percent of the country‟s GDP. Over the last 10 years, this industry has grown at an average annual

rate of 30 percent. The industry is estimated to aggregate revenues of USD 108 billion in FY2013,

with the IT software and services sector (excluding hardware) accounting for USD 95 billion ofrevenues. During this period, direct employment is expected to reach nearly three million, an additionof 188,300 employees, while indirect job creation is estimated at 9.5 million. As a proportion of

national GDP, the sector revenues have grown from 1.2 per cent in FY1998 to nearly 8 per cent inFY2013. Its share of total Indian exports (merchandise plus services) increased from less than 4 per

cent in FY1998 to about 23-25 per cent in FY2013. Export revenues (excluding hardware) are

estimated to gross USD 75.8 billion in FY2013, growing by 10.2 per cent over FY2012, and

contributing nearly 80 per cent of the total IT-BPM revenues (excluding hardware), employing over

2.3 million employees (NASSCOM 2013). Key global megatrends around macroeconomics,demographics, social, environmental, technology and business will present a new set of opportunities

in the form of largely untapped markets and customer segments, which can propel industry revenues to

USD 225 billion by 2020 (NASSCOM 2011). With the whirlpool of opportunities the Indian BusinessProcess Outsourcing sector seems to be on a happy ride.

India has the second largest English-speaking scientific professionals after the US. It is

considered as a knowledge economy with a highly talented technical workforce. Knowledge-workersare the main resource in the ITES/BPO Industry. They add value to their organizations through their

communications skills, high level of education, and domain knowledge. High attrition rate is an

important issue in BPO industry. High attrition not only reduces the efficiency or customersatisfaction, but is also expensive. When the employees move they not only take skills and knowledge

but also trade secrets with them as they typically moved to the competitor‟s organization (Abassi and

Hollman, 2000). According to a recent survey conducted by All India Management association

(AIMA) on CEO‟s and HR managers of different IT organizations, attrition is the second importantissue related to HR department. A global call-centre report (Neale Helen 2004) state that Indian call

centers have the highest employee turnover of 40% against a global average of 20%. Another

benchmarking analysis (Scholl Rebecca 2003) reports that India had the greatest level of call centreagent attrition (38%) and lowest average employee tenure (11 months) in the Asia Pacific Region. It is

very important to retain top talent to promote innovation and creativity which will help organization to

differentiate from its competitors (Peter Cappelli, 2008). .

II. REVIEW OF LITERATURE

There are a few significant studies conducted to analyse the effect of factors of employeeretention on employee intention to stay.

Abhoy (2000), opined that ensuring employee commitment and retaining best talent is the

major challenge in software firms. Agrawal et al (2003) suggested that the work place must be

conducive for learning and at the same time informal, full of fun, excitement and passion so thatemployees can learn, experiment and relieve stress. Gwen et al (2003) concluded that changes that

could be made to make the workplace more challenging and rewarding includes having a more flexiblework environment, more effective communication and more career development and training.

Suryanarayana et al (2003) found that work environment is a significant factor that affect job

satisfaction and work commitment of software professionals. Deepak et al (2012) found that

employees in at a comparatively lower age have a higher propensity to leave the job and lack of safety

among female employees and availability of more career opportunities in the external labour marketare the most significant reasons for employees to leave the organizations. Muhammad Umer et al


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(2011), identified that the variables such as career development, job support, work environment and

work life balance have significant and positive impact on employee stay in BPO industry.

Monis et al (2011) reported that the employee growth and development activities such as

continued education courses, tuition reimbursement, career development skills training, opportunities

for promotion and internal career advancement, coaching, mentoring and leadership development programmes have a positive impact on enhancing employee satisfaction and reducing the possibility ofemployee leaving. Karthikeyan (2010) found that variables like sufficient financial resources,

encouragement by supervisors, effective leadership, efficient feedback system and good relationshipwith colleagues play a significant role in improving organizational climate. Adhinarayanan et al

(2011) found that career growth and compensation are the important causes for increased employee

turnover in companies and employee, employer and supervisor all are responsible for the hike in the

rate of attrition. They strongly recommended for the conduct of an exit interview to realize actual

cause of leaving and to reduce the possibility of future employee turnover.

Shaveta et al (2011) found that as the total cost in association with hiring of employees to fill

the vacancy of the gone out employee is substantial, organizations have to build their own retention

strategies to ensure long-term stay of their best talent. Shefali et al(2012) recommended for theadoption of certain techniques like Muscle Relaxation, Biofeed Back, Meditation, CognitiveRestructuring, Time Management, Employee Assistance rogramme and Employee Wellness

Programme to minimize stress, enhance productivity and to reduce the employee dissatisfaction. A

study by Venugopal et al (2006) revealed that most of the organizational measures to retain talented persons such as rewards, recognition and appreciation, better communication etc. are accepted by the

professionals. Gayathri et al (2012) said that frustration and constant friction with their superiors or

other team members are the real reasons of most employees leaving an organization and identified

mentoring, well equipped safety environment, potential and prospective roles, encouragement andrecognition and competitive compensation as the significant variables that influences employee

retention. Many other studies also supported the same findings [Srikanth et. al. (2006), Chandra

Mohan et. al. (2007), Latha et al (2007), Kanwar (2009), Misra (2007), Prakash (2013), Rakesh(2011), Ramlall (2003), Shah et al (2007), Singh (2005)]

III. RESEARCH PROBLEM

IT-BPO sector has become one of the most significant growth catalysts for the Indianeconomy. However, the sector is facing the challenge of shortage of sufficient competent middle and

top level managers and poor retention rates. Studies on various dimensions have been done in India

and abroad to address the issue pertaining to IT-BPO industry. But, most of the studies limited theirscope on HR practices, employee work-life balance and stress. Assurance of employee retention is a

crucial challenge to any manager. Kerala state is a growing BPO destination in India. The cities like

Thiruvananthapuram and Cochin are growing fastly, especially after the formation of Special

Economic Zones and development of Info Park and Techno Park. It is expected that both these citieswill become Tier II cities in terms of BPO development (at present they are included in the list of Tier

III Cities). As per a recent Nasscom estimation, about 120000 new job opportunities will be created in

IT and ITES sector in 2013. However, huge rate of brain drain and attrition in BPO industry in Kerala badly affects its accelerated growth in our state. Therefore, it is necessary to identify the various

dimensions of employee retention in BPO industry in Kerala in order to ensure long stay of employees

in this sector. Since there are no remarkable studies on this aspect pertaining to Kerala, the present

study is significant to develop employee retention strategies in BPO sector.


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IV. RESEARCH OBJECTIVESThe present study is based on the following specific objectives:-

1. To identify various dimensions of employee retention in BPO industry in Kerala.

2. To study the interrelationship between dimensions of retention on employee intention to stay.

V. RESEARCH MODEL AND HYPOTHESES

Figure 1 The Proposed Research Model

Independent Variables Dependent Variable

Job Support & Recognition

Compensation & Career

Growth

Organizational Culture Intention To Stay

Work-Compatibility Factors

Autonomy & Independence

To have a disciplined guidance to the enquiry, the following hypotheses were formulated and

tested:

H1. The „ Job Support and Recognition‟ dimension of employee retention has a positive effect on

employee intention to stay.

H2. The „Compensation and Career Growth‟ dimension of employee retention has a positive effecton employee intention to stay.

H3. The „Organizational Culture‟ dimension of employee retention has a positive effect on


H4. The „Work Compatibility Factor ‟ dimension of employee retention has a positive effect on


H5. The „ Autonomy and Independence‟ dimension of employee retention has a positive effect on



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VI. RESEARCH METHODOLOGYThe study mainly depends on primary data which have been collected from a sample of 240

respondents in Kerala. The samples were identified randomly from the middle level and lower level

employees working in various BPOs in Kerala. The data are collected by using a pre-drafted and pre-tested Questionnaire. Pre-drafted questionnaire was tested among 60 respondents and necessary

modifications were made. The final questionnaire was delivered among 290 respondents and collected240 partly/completely filled questionnaires. The data collected have been analyzed by using variousstatistical and mathematical techniques. Descriptive statistical tools like mean, standard deviations,

correlations were applied for the study. Regression Analysis has been used to study the

interrelationship between variables.

VII. ANALYSIS AND INTERPRETATION OF DATA

A. Measur es Chosen for the Study

On the basis of exhaustive literature and the pilot study done, total of 22 factors were chosen

for the study. The respondents were asked to rate these factors on a 5 point Likert scale ranging from 1to 5, 5 being Strongly Agree and 1 being Strongly Disagree . Table 1 enlists all the 22 factors, the

codes assigned together with their mean and standard deviation.

Table: 1: Measures of Retention Chosen for the Study with Mean and SD

Sl.No.

CodeNo.

Measures N Mean S.D

1 RT 1I am satisfied with the level autonomyassociated with my position

240 2.85 1.016

2 RT 2 I have the freedom I need to do my job. 232 3.14 1.227

3 RT 3A good social environment is prevailing in myorganization.

240 3.48 1.074

4 RT 4 All the departments in my organization areworking with harmony without conflicts.

240 3.05 1.178

5 RT 5 My boss congratulates me for doing a good job. 240 3.32 1.220

6 RT 6My boss ensures that people who do a good jobare recognized and appreciated.

232 3.27 1.080

7 RT 7My boss provided adequate amount coachingand mentoring.

240 3.27 1.049

8 RT 8 My boss provides me with challenging work. 240 3.05 1.009

9 RT 9My boss give me feedback on regular basis onmy performance.

240 3.05 1.192

10 RT 10My boss involves me in decisions that affect my

job.240 3.27 1.198

11 RT 11I am satisfied with the support I receive frommy boss.

236 3.36 .990

12 RT 12My boss listens my personal and officialconcerns.

240 3.00 .993

13 RT 13My organization considers valuable suggestionsof the employees.

240 2.85 1.095

14 RT 14I am doing something that is considered reallyworthwhile.

240 3.13 .765


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15 RT 15Management is genuinely interested inemployee ideas on how to improve our services.

240 3.27 .930

16 RT 16My job gives me a feeling of personalaccomplishment and self-esteem.

240 3.20 .793

17 RT 17My organization goes out of its way to makesure that employees enjoy their work as well as

their family.

240 3.03 .950

18 RT 18People at this organization are paid fairlyaccording to their job performance.

240 2.55 1.299

19 RT 19I feel that the existing system of grantingincrement is quite effective.

240 2.98 1.399

20 RT 20I believe my career aspirations can achieved atthis organization.

240 2.72 1.144

21 RT 21The organization takes a supportive role in mycareer development.

240 3.13 .923

22 RT 22I feel that I shall be able to continue and growwith this organization.

240 2.75 1.061

B. Descriptive Statistics

Table 2: Descriptive Statistics

Sl. No. Factor Name MeanStd.

DeviationN

1 Job Support and Recognition 3.20 1.084 240

2 Compensation and Career Growth 2.90 1.116 240

3 Organizational Culture 3.06 1.090 240

4 Work-Compatibility Factor 3.12 0.872 240

5 Autonomy and Independence 3.14 0.996 240

It is clear from table 2 that job support and recognition has the highest mean of 3.20 stating thatmost of the respondents consider this factor to be responsible for their stay.

C. KMO and Bartlett’s Test

The Kaiser-Meyer-Olkin test was done to measure the homogeneity of variables and Bartlett'stest of sphericity was done to test for the correlation among the variables used. Table 3 shows the

values.

Table 3: KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .792

Bartlett's Test of SphericityApprox. Chi-Square 4416.268

df. 231

Sig .000


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The KMO value for the instrument was 0.792 and hence the factor analysis is appropriate forthe given data set. Bartlett‟s test of sphericity chi-square statistics is 4416.268, which shows the 22

statements are correlated and hence the instrument was accepted for further study.

D. Factor Analysis

Since the factors of retention were large in number and were inter-related, Factor Analysis wasdone to extract and club the factors responsible for attrition. Principal Component Analysis was usedfor extraction and Varimax for rotation. As per the Kaiser criterion, only factors with eigenvalues

greater than 1 were retained (Kaiser H. F 1960). Five factors in the initial solution have eigenvalues

greater than 1. Together, they account for almost 76% of the variability in the original variables. Table

4 shows initial eigenvalues of the factors and Table 5 shows the rotation matrix.

Table 4: Total Variance Explained

Component Initial Eigenvalues

Extraction Sums of SquaredLoadings

Rotation Sums of SquaredLoadings

Total

% of

Variance

Cumulative % Total

% ofVariance

Cumulative % Total

% of

Variance

Cumulative %

dimensi

on0

1 6.578 29.900 29.900 6.578 29.900 29.900 5.719 25.996 25.996

2 4.300 19.545 49.445 4.300 19.545 49.445 4.207 19.121 45.117

3 2.356 10.710 60.155 2.356 10.710 60.155 2.625 11.934 57.051

4 2.163 9.831 69.986 2.163 9.831 69.986 2.257 10.259 67.310

5 1.287 5.851 75.836 1.287 5.851 75.836 1.876 8.526 75.836

6 .790 3.590 79.426

7 .662 3.009 82.435

8 .587 2.670 85.105

9 .534 2.427 87.532

10 .482 2.193 89.725

11 .457 2.076 91.801

12 .305 1.388 93.189

13 .285 1.297 94.486

14 .249 1.131 95.617

15 .227 1.033 96.650

16 .200 .909 97.559

17 .158 .717 98.276

18 .128 .584 98.86019 .095 .433 99.294

20 .058 .265 99.559

21 .055 .251 99.810

22 .042 .190 100.000

Extraction Method: Principal Component Analysis.


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Table 5: Rotated Component Matrix

Component

1 2 3 4 5

Rt 12 .870 .151 -.114 .014 -.045Rt 9 .854 -.053 .244 -.241 .148

Rt 15 .819 -.256 .113 .143 .097Rt 8 .819 -.235 .276 -.131 .166

Rt 10 .791 .078 .111 -.435 -.004

Rt 11 .789 .138 .115 .248 .081Rt 13 .781 -.067 -.058 .039 .345

Rt 14 .662 .177 .236 .168 .335

Rt 26 .050 .905 .123 .173 -.049

Rt 25 .132 .855 -.170 .044 -.153Rt 28 -.011 .844 .220 -.023 .042

Rt 19 -.162 .809 -.049 -.088 .191Rt 27 -.217 .763 -.263 -.112 .236Rt 24 .269 .649 .014 .530 -.117

Rt 1 .186 -.086 .769 .145 -.189

Rt 6 .102 .161 .733 -.275 .336

Rt 17 -.058 .045 .719 .241 .248Rt 5 .421 -.156 .687 -.076 .166

Rt 23 .111 .041 -.072 .873 -.064

Rt 21 -.187 .000 .214 .788 .089

Rt 2 .326 -.052 .177 -.048 .774Rt 18 .222 .130 .120 .031 .771

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.Rotation converged in 6 iterations.

The factors extracted for further study are shown in Table 6. These 5 factors that were

ultimately extracted included factors which have loadings more than .6. Such factors were referred toas dimensions of retention in the further analysis. The table is followed by the explanation of all these

five dimensions.


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Table 6: Dimensions of Retention Extracted from Factor Analysis

Factor No. Item Code Loading Factor Name

1

RT 5 0.819

Job Support & Recognition

(JSR)

RT 6 0.854RT 7 0.791

RT 8 0.789

RT 9 0.87

RT 10 0.781

RT 11 0.662

RT 12 0.819

2

RT 15 0.809

Compensation & Career Growth

(CCG)

RT 18 0.649

RT 19 0.855

RT 20 0.905

RT 21 0.763

RT 22 0.844

3

RT 1 0.769

Organizational Culture

(OC)

RT 3 0.687

RT 4 0.733

RT 13 0.719

4RT 16 0.788 Work Compatibility Factor

(WCF)RT 17 0.873

5 RT 2 0.774 Autonomy and Independence(AI)RT 14 0.771

The factor analysis has identified the following fi ve dimensions of employee retention:

Factor 1: The name given to this factor is Job Support & Recogni tion . This factor consists of eightvariables which contribute 29.90 percent variation. The variables are: Congratulation by boss for

doing good work with factor loading of .819; recognition and appreciation of performance with factor

loading of .854; provision of good coaching and mentoring with factor loading of .791; challenging

work with factor loading of ..789; Performance feedback on regular basis with factor loading of .870;

involvement in decision making with factor loading of .781; support received from boss with factorloading of .662 and caring on employee personal and official concerns with factor loading of .819. The

above are the most important factors which contribute to enhance internal motivation in employeesworking BPO industry in Kerala. Many studies supported this finding. [Karthikeyan (2010), Bhaduri

(2008), Beardwell et al (2007), Gaiduk (2009), Budhwar (2006)].

Factor 2: This factor is named as Compensation & Career Growth . This factor includes six variables

which contribute 19.545 percent variation. The variables are: genuineness in management‟s interest inemployee ideas to improve service performance with factor loading of .809; payment according to job


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performance with factor loading of .649; effectiveness of existing system of granting increment withfactor loading of .855; belief in achievement of career aspirations with factor loading of .0.905;

organization‟s role to support career development with factor loading of .763; ability to continue and

grow with the organization with factor loading of .844. This result was substantiated by many previousstudies [Drucker, Anil Kumar (2007), Ryan et al. (2007), (Rosser, 2004)].

Factor 3: The name given to this factor is organizational culture . This factor consists of fourvariables which contribute 10.71 percent variation. The variables are: autonomy associated with position with factor loading of .769; prevalence of good social environment with factor loading of

.687; harmony between departments with factor loading of .733 and consideration of valuable

suggestions of employees feeling of respect in job with factor loading of .719. Many studies

substantiated this finding [(Grebner S (2003), Semmer (2007), Dormann (2002)].

Factor 4: The name given to this factor is work-compatibil ity factors . This factor consists of two

variables which contribute 9.831 percent variation. The variables are: job‟s ability to create feeling ofaccomplishment and self-esteem with factor loading of .788; and organization assuring work-life

balance of employees with factor loading of .873. This result was substantiated by many previous

studies [Wickramasinghe et al. (2010), Budhwar et al. (2006), Mehta et al. (2006), Greenhaus

(1974), Kohli (1978), Inkson (1985)].

Factor 5: The name given to this factor was autonomy & independence . This factor consists of two

variables which contribute 5.851 percent of variation. The variables are: availability of desired

freedom in doing the job with factor loading of .774 and enjoyment on doing work which is

worthwhile with factor loading of .771.

E. Mul tiple Regression M odel

There are many reasons for the stay of employees in an organization. All these factors are

grouped and a five factor model is constructed. Employee intention to stay is determined by these

dimensions of retention. Multiple Regression Analysis has been carried out here to study the

association between employee intention to stay and dimensions of retention.E.1. Dimensions of Retention – Independent Variables

Independent variables for the analysis are various dimensions of retention extracted from thefactor analysis. These five dimensions are: job support & recognition, compensation & career growth,

organizational culture, work-compatibility factor and autonomy & independence. Employee intention

to stay is determined y these dimensions of retention.

E.2. Intention to Stay – Dependent Variable

Employee intention to stay is determined by the dimensions extracted from factor analysis.Four statements are included in the instrument to measure intention to stay and the respondents

responded to each statement on five point Likert Scale with “Strongly Agree” dictating the highest

level of satisfaction (Score of 5), “Strongly Disagree” as the highest level of dissatisfaction ( Score of

1). The actual scores are collected, summated, averaged and compared across different groups to drawmeaningful conclusions. The item code, item mean and standard deviation are presented in Table 7.


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Table 7: Measures of Intention to Stay Chosen for the Study with Mean and SD

Sl. No.Item

CodeItem N

Mea

n

Std.

Deviatio

n

1 Stay1 This company is able to retain quality employees. 240 2.60 .972

2 Stay2

I see myself working for this organization threeyears from now.

240 2.43 1.298

3 Stay

3

Even I had another job offer that paid more than the

present one, I‟d stay here.

232 2.90 1.244

4 Stay

4

I am not bothered about alternative employment in

any other organization.

240 3.03 1.050

E.3. Validity and ReliabilityThe validity of the instrument and scales was assessed by face validity and content

validity. To ensure face validity, the research instrument was presented to experienced HR professionals working in major BPOs in Kerala to comment up on the appropriateness of the

instrument and scales to achieve the proposed objectives. On the basis of feedback necessary

refinements were made in the questionnaire to make it ready for final research. The content validitywas examined through review of most relevant previous empirical and theoretical literatures in the

field of employee retention and a pilot study by presenting the questionnaire among 60 sample BPO

employees. The reliability of the redrafted research instrument was assessed on the basis of

Cronbach‟s alpha co-efficient [Sekaran, U.(2003)].

Table 8: Reliability - Co-efficient- Cronbach’s alpha

Retention DimensionsNo. of

Items

Cronbach’s

alpha

Job Support & Recognition 8 0.930


Growth

6 0.889

Organizational Culture 4 0.756

Work-Compatibility Factor 2 0.697

Autonomy & Independence 2 0.684

Overall RetentionDimensions

22 0.749

Intention to Stay

(dependent)

4 0.762

E.4. Correlation Analysis

The next step involved is computing the correlations between the independent variables and thedependent variable in order to find out the relationship between the two. There should be correlations

between the dependent variable and the independent variables to precede further analysis. Table 9

shows the correlations along with significant values.


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Table 9: Correlations

JSR CCG OC WCF AI STAY

JSR PearsonCorrelation

1 .019 .361 -.050 .471 .210

Sig. (2-tailed) .781 .000 .454 .000 .002 N 228 228 228 228 228 220

CCG PearsonCorrelation

.019 1 -.039 .127 .043 .510

Sig. (2-tailed) .781 .546 .049 .515 .000 N 228 240 240 240 232 232

OC PearsonCorrelation

.361 -.039 1 .065 .395 .145

Sig. (2-tailed) .000 .546 .314 .000 .027 N 228 240 240 240 232 232

WCF PearsonCorrelation

.050 .127 .065 1 -.031 .146

Sig. (2-tailed) .454 .049 .314 .641 .026 N 228 240 240 240 232 232

AI PearsonCorrelation

.471 .043 .395 -.031 1 .361

Sig. (2-tailed) .000 .515 .000 .641 .000 N 228 232 232 232 232 224

STAY PearsonCorrelation

.210 .510 .145 .146 -.361 1

Sig. (2-tailed) .002 .000 .027 .026 .000

N 220 232 232 232 224 232

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

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

E.5. Regression Assumptions

The basic assumptions of parametric statistical tests such as regression should be carefullyfollowed for reliable findings. As per the methodologies recommended by well known researchers

(Hair et al (1998), the analysis of residuals provides the best information about regression model‟s

errors which are used to examine the regression analysis assumptions. They are as follows: (1) The

assumption of Normal distribution -tested using Shapiro-Wilk which reveals that standardised errorsare normally distributed since all P values are above .05. (The null hypothesis is that errors are

normally distributed). (2) Multi collinearity assumption-tested using VIF (Variance Inflation Factor)

and tolerance. If VIF is more than 5 and tolerance less than .20, there is problem of Multi collinearity

[(Hair et al (1998)]. Here all variables pass this acid test. (3) The independent errors assumption – which is tested with Durbin Watson statistic. If the value of the test is between 1 and 3, this

assumption is met. The value for the present research is 1.897 which is ideal in all respects.

E.6. Regression Model

The regression model used for the present study is:

Y = a + b1 X1+ b2 X2+ b3 X3+ b4 X4 + b5 X5....................................................... (1)


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Where: Y= Intention to Stay (Dependent Variable),a= Constant,

X1, X2, …………X5 = Dimensions of Retention (Independent Variables),

[X1 = „Job support & Recognition‟, X2 = „Compensation & Career Growth‟, X3 = „OrganizationalCulture‟, X4 = „Work -compatibility Factor‟, X5 = „Autonomy & Independence‟.]

b1, b2 ……………b5= Beta values of independent variables.

The stepwise regression model is carried out which provided 3 models as shown in Table 10.

Table 10: Model Summary

Model

R R Square

Adjusted R

Square

Std. Error of

the Estimate

Durbin-

Watson

1 .464a .215 .212 2.90527

2 .523 .273 .267 2.80202

3 .536c .288 .278 2.78087 1.897

a. Predictors: (Constant), CCG b. Predictors: (Constant), CCG, JSR

c. Predictors: (Constant), CCG, JSR, WCF

d. Dependent Variable: STAY

The first model with „compensation and career growth‟ gave an r 2

value of .215. In the secondmodel, by adding the dimension „job support and recognition‟, the predictive power of the model (r

2)

improved to .273. In the last model, by adding „work -compatibility factor‟ with the dimensions

„compensation and career growth‟ and „job support and recognition‟ the predictive power of the modelincreased to .288. Therefore, the improved model explains 29 percent of the variation in the dependent

variable by the 3 independent variables.

Model Sum of

Squares df

Mean

Square F Sig.

1 Regression 504.390 1 504.390 59.758 .000a

Residual 1840.047 218 8.441

Total 2344.436 219

2 Regression 640.704 2 320.352 40.802 .000

Residual 1703.732 217 7.851

Total 2344.436 219

3 Regression 674.056 3 224.685 29.054 .000c

Residual 1670.381 216 7.733

Total 2344.436 219

a. Predictors: (Constant), CCG, b. Predictors: (Constant),CCG, JSR, c.

Predictors: (Constant), CCG, JSR, WCF, d. Dependent Variable: STAY


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ANOVA table shows that all the 3 models are statistically significant at 99 percent confidence

level.

Table 12: Coefficients

ModelUnstandardized

Coefficients

Standardized

Coefficients

t Sig.

CollinearityStatistics

B Std. Error Beta

Toleranc

e VIF

1 (Constant)

8.847 .654 13.522 .000

CCG .280 .036 .464 7.730 .000 1.000 1.000

2 (Constant

)

11.582 .910 12.721 .000

CCG .290 .035 .480 8.269 .000 .996 1.004

JSR .114 .027 .242 4.167 .000 .996 1.004

3 (Constant

)

10.137 1.140 8.888 .000

CCG .280 .035 .464 7.996 .000 .979 1.021

JSR .113 .027 .240 4.172 .000 .996 1.004

WCF .252 .121 .120 2.077 .039 .983 1.017

Dependent Variable: STAY

The standardized Beta Coefficients of the 3 dimensions which are statistically significant is

shown in table 12. The strongest predictor is „compensation and career growth‟ since its beta value is

highest with .464 which is statistically significant at 1 percent level. The next predictor is „job supportand recognition‟ with the beta value of .242 which is also significant at 1 percent level. The dimension

„work -compatibility factor‟ has also significant relation with the dependent variable as the beta value

of .120 is also statistically significant at 5 percent level of significance.Hypotheses (1), (2) and (4) are accepted since all of the three dimensions of retention have

positive effect on employee intention to stay. The other attributes such as organizational culture and

autonomy and independence have no positive effect on employee intention to stay and hence,

hypotheses (3), and (5) are rejected. BPOs should give due significance to compensation & careergrowth, job support & recognition and work-compatibility factor to ensure the long stay of their

employees.

Therefore, the validated regression model is as follows:

Intention to Stay = 10.137 + .464 (CCG) + .240 (JSR) + .120 (WCF).

Thus, compensation and career growth, job support and recognition and work-compatibilityfactor are the strongest predictors of variations of employee intention to stay in BPO industry inKerala.


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Figure 2: Relationship framework of the dimensions of attrition

Independent Variables Dependent Variable


Growth .464

Job Support & Recognition.240

Intention to Stay (r2

= .29)

.120

Work-Compatibility Factors

VIII. CONCLUSION

The main aim of this research study was to identify the major dimensions of employeeretention in BPO industry in Kerala and also to study the interrelationship between these dimensions

and employee intention to stay. The essence of the proposed study was the identification of strongest

predictors of the dimensions of retention on employee intention to stay. The multiple regressionanalyses findings indicate that there is a positive and significant relationship between compensation &

career growth, job support & recognition and work-compatibility factor and the employee intention to

stay in BPO organizations. The findings indicate that, based on beta values and significance,

„compensation and career growth‟ is the most influential dimension (predictor) of the BPO employee

intention to stay. The previous research and our research advocated that a BPO unit providing goodcompensation package and career development opportunities, will able to retain its valuable

employees for a long period of time. Based on the beta values and significance, the second strongestdimension of employee retention is „job support and recognition‟. This finding provides a strong

support to the HR literature review that advocated that a BPO organization which gives recognition

and appreciation to the good work of their employees and extending support to them in work will gaintheir faith and confidence and is able to retain them. Also, based on the beta values and significance,

the third strongest dimension of employee retention is „work -compatibility factor‟. The finding

suggests that the organization should consider the personal feelings of the employees while designing

work schedules. The management has to develop sound human relations strategies to motivate theiremployees to ensure their long stay in the organization. This is observed that the employees are ready

to stay in the organization if they are provided with fair pay, career advancement opportunities, job

support, recognition and appreciation on work and balancing of their work and life.

IX. RESEARCH CONTRIBUTION

This research is thought to have contributed to the BPO employee retention literature in three

aspects. First, from an academic standpoint, this research has fulfilled some gaps that emerged fromthe literature that needed more empirical study especially in a state like Kerala. Secondly, this research

is the first empirical study that investigated the relationship between retention dimensions and

employee intention to stay in BPO industry in Kerala. Thirdly, the research findings can be utilized by


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the BPO professionals and management as valuable inputs to design effective HR policies and

strategies so that they can ensure the long stay of their talented, valuable employees.

X. LIMITATIONS AND FUTURE RESEARCH

Although this research achieved its objectives, limitations and future research are outlined. The

study is done on a general way without concentrating on specific BPO verticals. Future research can be done on the employee retention dimensions on specific BPO verticals. Another limitation is thatthis study includes only five dimensions of employee retention in BPO industry in Kerala. A good area

of research in the future is to find out if there are more dimensions of employee retention that

influence the stay of BPO employees. In this study only job related variables are considered for theanalysis. Future research can aim to find out the relationship between the demographic variables of the

respondents such as, age, sex, marital status, tenure, education etc. and employee intention to stay

along with job related variables. The present study is confined to lower and middle level BPO

professionals. Future research can study the influence of these dimensions on the stay of top level BPO

professionals.

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EXPLORING THE DIMENSIONS OF EMPLOYEE RETENTION IN BPO INDUSTRY

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