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QUALITY OF WORK LIFE METRICS AS A PREDICTOR OF JOB
SATISFACTION & ORGANIZATIONAL COMMITMENT: A STUDY WITH
SPECIAL REFERENCE TO INFORMATION TECHNOLOGY INDUSTRY
Dr. M. SWAPNA
Principal, Ramaiah Institute Of Business Studies,
Bangalore E-Mail: [email protected]
ABSTRACT
Information Technology (IT) industry in India is playing a very important role in
putting India on the global map. This industry has become one of the most significant
growth catalysts for the Indian economy. It has today become a growth engine for the
economy, contributing substantially to increase in the GDP, urban employment and
exports, to achieve the vision of a powerful and resilient India. Indian firms, across all
other sectors, largely depend on the IT service providers to make their business
processes efficient and streamlined. NASSCOM expects the IT services sector in India
to grow by 13-14 per cent in 2013-14 and to touch US$ 225 billion by 2020.
The major strength of IT industry lies in its human resources. Human resources play a
pivotal role in the success of the IT industry. Today’s IT industry concentrates on its so
called intellectual capital for enhancing its growth. They make the employees
committed and satisfied through providing a satisfactory quality of work life. QWL in
IT industry influences job satisfaction, job involvement and organizational commitment
to a greater extent as compared to other industry.
KEYWORDS
Information Technology, Work Life Metrics, Quality, Job Satisfaction, Organizational
Commitment.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 115 Volume 6, Issue No. 1, Jan. – June 2016
INTRODUCTION
Information Technology (IT) industry in India is playing a very important role in
putting India on the global map. This industry has become one of the most significant
growth catalysts for the Indian economy. It has today become a growth engine for the
economy, contributing substantially to increase in the GDP, urban employment and
exports, to achieve the vision of a powerful and resilient India. Indian firms, across all
other sectors, largely depend on the IT service providers to make their business
processes efficient and streamlined. NASSCOM expects the IT services sector in India
to grow by 13-14 per cent in 2013-14 and to touch US$ 225 billion by 2020.
The major strength of IT industry lies in its human resources. Human resources play a
pivotal role in the success of the IT industry. Today’s IT industry concentrates on its so
called intellectual capital for enhancing its growth. They make the employees
committed and satisfied through providing a satisfactory quality of work life. QWL in
IT industry influences job satisfaction, job involvement and organizational commitment
to a greater extent as compared to other industry.
STATEMENT OF THE PROBLEM
The topic chosen for the study is “Quality of Work Life Metrics as a Predictor of Job
Satisfaction & Organizational Commitment: A Study with Reference to Information
Technology Industry”. Today, most of the IT companies have realised that QWL
improves employee motivation, job performance, organizational commitment and
productivity.
Most of the research conducted in the field of the quality of work life has focused on
increasing employees’ motivation to work harder and produce more, fostering loyalty
and creating more effective organizations. Past studies have concentrated on reducing
or eliminating costs involved in absenteeism and the subsequent loss in revenue, for the
benefit of the organization. At the same time, investigations have given attention to
guaranteeing job security, better remuneration and a safer work environment for
employees.
In an article entitled Strategic approaches to work/life balance in Work life Report
(2000), mention is made of organizations, which have taken a strategic, systematic
approach to addressing work/life issues. Such organizations were able to report
significant business gains, such as greater retention, increased productivity,
commitment and customer service and reduced absenteeism.
In 2010 Normala and Daud investigated the relationship between quality of work life
and organizational commitment amongst employees in Malaysian firms and say that the
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 116 Volume 6, Issue No. 1, Jan. – June 2016
quality of work life of employees is an important consideration for employers interested
in improving employee’s job satisfaction and commitment.
There are number of studies which focused on the QWL as variable, movement,
construct and as an outcome. But only few studies had identified the essential
components of quality of working life. From the past studies it is also found that no
study pinpointed QWL as a predictor of job satisfaction and organizational
commitment in the IT industry. Hence this is a pioneer attempt by the researcher. It is
also stressed that this study will bring lot of benefits to IT industry as it will pave the
way for increasing job satisfaction and organizational commitment. Hence the
emergence of this study.
OBJECTIVES OF THE STUDY
The study is undertaken with the following objectives:
To examine the level of employees quality of work life, organizational
commitment and job satisfaction in information technology industry.
To analyse quality of work life as a predictor of employees job satisfaction &
organizational commitment in information technology industry.
To investigate whether quality of work life, Job satisfaction & employee
commitment is effective irrespective of the demographical characteristics of
employees like age, gender, marital status and work experience levels.
To elicit the impact of quality of work life on job satisfaction and organizational
commitment.
SCOPE OF THE STUDY
For the purpose of this study, the researcher concentrates on the top three Indian IT
companies namely TCS, Infosys and Wipro only. Other IT companies are not covered
for this study.
Of the four metros of India, which are also one of the biggest in the world, Bangalore is
one city whose name is being taken by corporate and multinational companies all over
the world. The IT infrastructure of Bangalore is amazing and world class. Every year,
Bangalore exports over 18,000 crore rupees worth Software. Bangalore is an
opportunity galore for employees and employers, and especially entrepreneurs.
It is a much known fact that most of the IT companies in and around the globe are
housed in Bangalore, in areas that are named as Software Technology Park of India
(STPI), Electronics City, International Tech Park of Bangalore (ITPB).
This study will highlight the relationship that exists in QWL, job satisfaction and
commitment among information technology professionals in Bangalore city.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 117 Volume 6, Issue No. 1, Jan. – June 2016
This study will benefit both the company and the society by providing the necessary
benefits associated with QWL and job satisfaction and organizational commitment.
This study also throws light on the important QWL dimensions upon which the
companies shall concentrate on for having a better quality of work life.
RESEARCH METHODOLOGY
Type of the Study
The type of study undertaken for this research is of descriptive type, where the QWL
metrics as a predictor of job satisfaction and organizational commitment prevailing in
IT industry was analyzed in depth. Three IT Companies are taken as the case units.
TOOLS USED
Tools used in this study for the collection of data were the well designed questionnaire
developed by LEIDEN and Meyer and Allen. The independent variable quality of work
life is measured using Leiden QWL scale using the 59 items questionnaire which was
constructed to assess work characteristics from two influential occupational stress
models, the Job Demand Control Support model (Johnson & Hall, 1988; Johnson,
1989; Karasek & Theorell, 1990) and the Michigan model (Caplan, Cobb, French, van
Harrison & Pinneau, 1975).
The dependent variable in this study is employees Organizational Commitment. The
overall organizational commitment is measured using the 18-item Revised
questionnaire developed by (Meyer, Allen and Smith 2004), designed to measure.
Affective commitment, Normative commitment and Continuance commitment. The
dependent variable job satisfaction is measured in the independent variable QWL as an
outcome measure.
Although the Leiden Quality of Work Life Questionnaire consists of 12 work
characteristics or dimensions, for this research it was only decided to use the first
eleven. This was because the twelfth factor job satisfaction is considered to be an
outcome variable of QWL.
PILOT TESTING
A well designed questionnaire was administered among 40 respondents in the top three
IT companies TCS, Infosys and Wipro as per NASSCOM survey 2012. The
Cronbach’s Alpha value for reliability of the instruments QWL, organizational
commitment and job satisfaction were 0.876, 0.824 & 0.897 respectively. The results
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 118 Volume 6, Issue No. 1, Jan. – June 2016
from ANOVA signify that there exists a relationship between QWL and employee’s
organizational commitment.
The R Square value 0.609 indicates that the model is fit for estimation. From Pearson
correlation the items Hazardous Exposure, Job Insecurity and Physical Exertion
reported negative correlation with organizational commitment which indicated inverse
relationship and all other items indicate positive relationship. Finally the questionnaire
was subject to lot of modifications as suggested by the experts. Then the questionnaire
was corrected and revised to prove the reliability and validity of the information
collected.
Methods of Collecting Data
The researcher collected both primary and secondary data for the purpose of the study.
Primary data was collected with a well defined questionnaire whereas the secondary
data was collected with the help of journals, company reports, NASSCOM survey,
company press releases, library and websites etc.
SAMPLING DESIGN
Method of Sampling
For the purpose of collection of data the researcher had used convenience sampling
method for arriving at the reliability and validity of the data collected.
Sample Size
Among the 4113 operational executives the researcher had chosen 410 employees from
the total population belonging to each company. The following table shows the sample
size of each company chosen.
Table 1: Sample Size Chosen for the Study
Company Operational Executives Total
Population
SAMPLE SIZE Total 410
Respondents
TCS 1652 165
INFOSYS 1235 123
WIPRO 1226 122
FRAMEWORK OF ANALYSIS
This study adopted the following variables for analyzing QWL metrics as a predictor of
job satisfaction and organizational commitment.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 119 Volume 6, Issue No. 1, Jan. – June 2016
Independent Variable-The independent variable is quality of work life (Leiden QWL
scale).
Dependent Variable- The dependent variables in this study are Job Satisfaction and
organizational commitment, where job satisfaction is an outcome variable of Quality of
Work life.
Demographic Variables-Gender, Age, Total Years of Experience and Marital Status.
STATISTICAL TECHNIQUES USED
The researcher made use of mean, standard deviation for each item. The researcher also
adopted correlations to find out whether there exists inter correlation among the various
dimensions.
The researcher carried out an Analysis of variance to determine the impact of
demographic variables on QWL, organizational commitment and job satisfaction. The
researcher adopted regression model to find out the linear relationship between the
QWL dimensions and organizational commitment dimensions.
It was also the interest of the researcher to find out the impact/influence of QWL on
organizational commitment and job satisfaction. To find out the extent of impact the
researcher carried out a PATH ANALYSIS using AMOS software.
RELIABILITY SCORE
The reliability of the instrument is tested and the alpha value obtained for QWL (0.90),
organizational commitment (0.91) and job satisfaction (0.94). These values are higher
than the acceptable lower limit of 0.6 according to Nunnally.J.C (1978).
Table 2: Reliability Score Of The Instrument
Cronbach’s Alpha Value for Dimensions and Variables Alpha
Skill Discretion .87
Decision Authority .82
Task Control .91
Work And Time Pressure .98
Role Ambiguity .94
Physical Exertion .78
Hazardous Exposure .80
Job Insecurity .92
Lack Of Meaningfulness .91
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 120 Volume 6, Issue No. 1, Jan. – June 2016
Supervisor Social Support .97
Co-Workers Social Support .83
Quality Work Life .90
Affective .89
Continuance .91
Normative .94
Organizational Commitment .91
Job Satisfaction .94
LIMITATIONS OF THE STUDY
The study is not free from limitations.
This study is restricted to only Indian IT companies whereas international
companies operating in India is not considered.
As always time is limiting factor this study suffers from time constraint.
The measurement of this study was subjective based on their personal
experiences so it is purely based on individual experience and perception in
the company.
This study does have source bias for both dependent and independent
variables.
OPERATIONAL DEFINITIONS
Operational Executives: This includes the programmers, system analyst, data base
managers, software testers, network administrators and software developers (software
engineers).
Quality of Work Life: It insists on the nature of work and work characteristics and the
worker’s relationship with the organization.
Job Satisfaction: It encompasses the ultimate satisfaction that an individual exercises
in the organization.
Organizational Commitment: This indicate the attachment to the organization,
characterized by an intention to remain in it; an identification with the values
and goals of the organization; and a willingness to exert extra effort on its
behalf.
Skill Discretion refers to task variety and the extent to which the job challenges one’s
skills.
Decision Authority refers to the freedom of decision-making over one’s work.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 121 Volume 6, Issue No. 1, Jan. – June 2016
Task Control refers to the flexibility that one has in ones work.
Work and Time Pressure refers to ones workload and time pressure.
Role Ambiguity refers to not knowing what ones tasks are and also not knowing what
is expected from oneself.
Physical Exertion refers to the extent that one’s work requires physical effort.
Hazardous Exposure refers to the extent that one is being exposed to dangerous tools,
equipment and machinery.
Job Insecurity refers to uncertainty about one’s job.
Lack of Meaningfulness refers to whether one’s work is worthwhile doing.
Social Support Supervisor refers to the support that is provided by ones supervisor
Social Support Colleagues refer to instrumental and emotional support provided by
colleagues.
RESEARCH HYPOTHESIS
In determining QWL, job satisfaction and organizational commitment the focus was
laid on demographic variables and determinants which showed a significant
difference. Thus the following null hypothesis was formulated.
H1: There is no significant difference in quality of work life across the
demographic variables like age, gender, marital status and work experience
level of the respondents.
H2: There is no significant difference in organizational commitment
across the demographic variables like age, gender, marital status and work
experience level of the respondents.
H3: There is no significant difference in job satisfaction across the
demographic variables like age, gender, marital status and work experience
level of the respondents.
H4: There is no correlation between all the twelve dimensions of QWL and
organizational commitment.
H5: There is no linear relationship existing between Skill Discretion, Decision
Authority, Task Control, Work and Time Pressure, Role Ambiguity, Physical
Exertion, Hazardous Exposure, Job Insecurity, Lack Of Meaningfulness,
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 122 Volume 6, Issue No. 1, Jan. – June 2016
Supervisor Social Support, Co-Workers Social Support on Affective
dimension.
H6: There is no linear relationship existing between Skill Discretion, Decision
Authority, Task Control, Work and Time Pressure, Role Ambiguity, Physical
Exertion, Hazardous Exposure, Job Insecurity, Lack of Meaningfulness,
Supervisor Social Support, Co-Workers Social Support on Continuance
dimension.
H7: There is no linear relationship existing between Skill Discretion, Decision
Authority, Task Control, Work And Time Pressure, Role Ambiguity,
Physical Exertion, Hazardous Exposure, Job Insecurity, Lack Of
Meaningfulness, Supervisor Social Support, Co-Workers Social Support on
Normative dimension.
H8: There is no linear relationship existing between Skill Discretion, Decision
Authority, Task Control, Work and Time Pressure, Role Ambiguity, Physical
Exertion, Hazardous Exposure, Job Insecurity, Lack of Meaningfulness,
Supervisor Social Support, Co-Workers Social Support on Job Satisfaction.
H9: There is no linear relationship existing between Skill Discretion, Decision
Authority, Task Control, Work and Time Pressure, Role Ambiguity, Physical
Exertion, Hazardous Exposure, Job Insecurity, Lack of Meaningfulness,
Supervisor Social Support and Co-Workers Social Support on
organizational commitment index.
H10: There is no significant relationship between organizational commitment and
job satisfaction.
H11: There is no impact/influence of quality of work life on organizational
commitment.
H12: There is no impact/influence of quality of work life on job satisfaction.
FINDINGS AND SUGGESTIONS
After fine tuning the data collected, the results were summarized in the analysis and
interpretation chapter v .On proper scrutiny of the analysis and interpretation it was
very obvious that QWL was found to be significantly correlated with the job
satisfaction and organizational commitment.
The findings and suggestions are summarized below.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 123 Volume 6, Issue No. 1, Jan. – June 2016
The statistics results showed that the QWL had an overall mean score of 3.41, for
organizational commitment it showed 3.97 and for job satisfaction it showed 3.54.
This results indicates that there exists a moderate status of QWL, organizational
commitment and job satisfaction in the study organization.
Table 3: Mean score of the QWL Dimensions
S. No. DIMENSIONS MEAN SCORE
1 Skill discretion 3.90
2 Decision authority 3.47
3 Task control 3.69
4 Work and time pressure 3.47
5 Role ambiguity 3.68
6 Physical exertion 3.02
7 Hazardous exposure 2.70
8 Job insecurity 2.92
9 Lack of meaningfulness 3.52
10 Supervisor social support 3.52
11 Co-workers social support 3.64
From the above table it is evident that the dimensions hazardous exposure and job
insecurity indicate a low status. The mean score of affective commitment is 3.80,
continuance commitment is 3.93 and normative commitment is 4.17 which indicate
good status of organizational commitment in the organization. The mean score of job
satisfaction is 3.54 which indicate moderate status.
Hence it can be concluded that the companies need to focus more on the areas like
hazardous exposure and job security which requires significant attention. On the other
hand skill discretion is found to be high which indicate that the respondents have a
challenging work environment.
Findings from Analysis Of Variance
The researcher carried out an ANOVA to check whether there exist significant
differences with demographic variables (gender, age, marital status and work
experience level) and their perception towards QWL, job satisfaction and
organizational commitment.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 124 Volume 6, Issue No. 1, Jan. – June 2016
Table 4: ANOVA for Gender
FACTORS GENDER N Mean Std. Deviation F Sig.
Quality of Work Life
Male 174 3.35 0.30
16.94 0.00* Female 236 3.45 0.19
Total 410 3.41 0.25
Organization
Commitment
Male 174 3.87 0.53
6.32 0.01* Female 236 4.05 0.80
Total 410 3.97 0.70
Job Satisfaction
Male 174 3.40 0.48
27.94 0.00* Female 236 3.63 0.41
Total 410 3.54 0.46
*: Significant at 5% level
From the above values, it is obvious that the significance values for
QWL(0.00),organizational commitment(0.01) and job satisfaction (0.00) is less than
0.05, hence the null hypothesis is rejected and therefore it can be concluded that there
exists a significant differences in gender and their perception towards QWL, job
satisfaction and organizational commitment.
Hence it is suggested that companies shall frame HR policies based on the gender, so
that a good QWL can be established to enhance job satisfaction and organizational
commitment.
Table 5: ANOVA for Age Group
FACTORS AGE N Mean Std. Deviation F Sig.
Quality of Work
Life
20-25 yrs 144 3.28 0.12
104.72 0.00*
26-30 123 3.48 0.28
31-35 123 3.39 0.14
40+ 21 4.03 0.00
Total 410 3.41 0.25
Organization
Commitment
20-25 yrs 144 4.10 0.67
35.36 0.00*
26-30 123 4.20 0.75
31-35 123 3.50 0.47
40+ 21 4.53 0.20
Total 410 3.97 0.70
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 125 Volume 6, Issue No. 1, Jan. – June 2016
Job Satisfaction
20-25 yrs 144 3.45 0.48
3.86 0.01*
26-30 123 3.63 0.51
31-35 123 3.52 0.39
40+ 21 3.67 0.00
Total 410 3.54 0.46
* Significant at 5% level
From the above values, it is obvious that the significance values for
QWL(0.00),organizational commitment(0.00) and job satisfaction (0.01) is less than
0.05, hence the null hypothesis is rejected and therefore it can be concluded that there
exists a significant differences among the Age groups and their perception towards
QWL, job satisfaction and organizational commitment.
Hence it is found that, higher the age group showed higher status of QWL,
organizational commitment and job satisfaction.
Table 6: ANOVA for Marital Status
FACTORS GENDER N Mean Std. Deviation F Sig.
Quality of Work
Life
Single 164 3.26 0.17
124.42 0.00* Married 246 3.51 0.24
Total 410 3.41 0.25
Organizational
Commitment
Single 164 3.91 0.63
2.51 0.11 Married 246 4.02 0.75
Total 410 3.97 0.70
Job Satisfaction
Single 164 3.31 0.40
78.22 0.00* Married 246 3.68 0.43
Total 410 3.54 0.46
* Significant at 5% level
From the above values, it is obvious that the significance values for QWL (0.00) and
job satisfaction (0.00) is less than 0.05, hence the null hypothesis is rejected and
therefore it can be concluded there exists a significant differences in the marital status
of the respondents and their perception towards QWL and Job satisfaction. But in case
of organizational commitment the significance value (0.11) is greater than 0.05, hence
null hypothesis is accepted and can be concluded that irrespective of marital status
organizational commitment remains the same.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 126 Volume 6, Issue No. 1, Jan. – June 2016
Therefore it is found that employees, who are matured enough irrespective of their
marital status, are prone to have higher commitment in the Organization.
Table 7: ANOVA for Work Experience Levels
FACTORS WORK EXP. N Mean Std. Deviation F Sig.
Quality of Work
Life
1 to 2 years 103 3.36 0.20
34.18 0.00*
2 to 3 144 3.30 0.19
3 to 4 41 3.46 0.00
4 plus years 123 3.56 0.30
Total 410 3.41 0.25
Organizational
Commitment
1 to 2 years 103 4.05 0.85
19.87 0.00*
2 to 3 144 4.09 0.55
3 to 4 41 3.22 0.34
4 plus years 123 4.03 0.67
Total 410 3.97 0.70
Job Satisfaction
1 to 2 years 103 3.67 0.35
19.31 0.00*
2 to 3 144 3.46 0.54
3 to 4 41 3.90 0.10
4 plus years 123 3.39 0.41
Total 410 3.54 0.46
* Significant at 5% level
From the above values, it is observed that the significance values for QWL (0.00),
organizational commitment(0.00) and job satisfaction (0.00) is less than 0.05, hence the
null hypothesis is rejected and therefore it can be concluded that there exists a
significant differences in the work experience level and their perception towards QWL,
job satisfaction and organizational commitment. Therefore it can be concluded that all
three variables vary on the situational basis, depends on the case.
Correlation Analysis
The researcher adopted Pearson’s correlation to find the correlation among the
dimensions. Positive correlation indicates positive relationship and negative correlation
indicated inverse relationship that is if one variable increases whereas the other variable
decreases. The results are as follows:
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 127 Volume 6, Issue No. 1, Jan. – June 2016
Table 8: Correlation Analysis
FACTORS Job
Satisfaction Affective Continuance Normative
Organization
Commitment
Skill Discretion -.272** 0.036 .138** .196** .127**
Decision Authority .145** .183** 0.037 -0.011 .116**
Task Control .128** .256** .122** .302** .286**
Work And Time Pressure .219** .417** .245** .395** .448**
Role Ambiguity .393** -0.066 0.039 -0.003 -0.027
Physical Exertion .133** -.186** -.526** -0.042 -.286**
Hazardous Exposure .137** -.128** -.601** -.229** -.336**
Job Insecurity -.204** -0.01 -.358** -.194** -.179**
Lack Of Meaningfulness .134** .122** .491** .222** .296**
Supervisor Social Support .625** .452** .219** .369** .452**
Co-Workers Social
Support .002 .260** .585** .549** .512**
From the above table it is clear that the dimensions used in the questionnaire such as
decision authority, task control, work and time pressure, Lack of Meaningfulness,
Supervisor Social Support, Co-Workers Social Support are found positively correlated
with job satisfaction, affective, continuance, normative and over all organizational
commitment. The other dimensions having negative correlations are as follows:
Skill Discretion: Its correlations with Continuance, Normative and Organization
Commitment were found to be positive and significant (at 1% level). With Job
Satisfaction, its correlation was found to be negative and significant (at 1%
level).which indicates that challenging work environment reduces job
satisfaction.
Physical Exertion: Its correlation with Job Satisfaction was found to be positive
and significant (at 1% level). With Affective, Continuance and Organization
Commitment, its correlations were found to be negative and significant (at 1%
level).which implies that if physical effort increases then organizational
commitment decreases.
Hazardous Exposure: Its correlation with Job Satisfaction was found to be
positive and significant (at 1% level). With the remaining four dimensions, its
correlations were found to be negative and significant (at 1% level).It implies
that higher the hazardous exposure decreases organizational commitment.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 128 Volume 6, Issue No. 1, Jan. – June 2016
Job Insecurity: With Job Satisfaction, Continuance, Normative and
Organization Commitment, its correlations were found to be negative and
significant (at 1% level).This is a very important point to be noted where if job
insecurity increases that ultimately job satisfaction and organizational
commitment decreases.
From the above correlation statistics it can be concluded that the companies need to
focus more on the aspects like skill discretion, physical exertion, hazardous exposure
and job insecurity to have a better satisfaction and committed employees.
Table 9: Partial correlation for organizational commitment index, QWL and Job
satisfaction
OCI QWL Job Satisfaction
OCI 1.000 .190** .130**
QWL .190** 1 .348**
Job Satisfaction .130** .348** 1
* Significant at 5% level
Table 10: Partial Correlation Holding Job Satisfaction Constant
Control Variable OCI QWL
Job Satisfaction
1.000 .156**
.156** 1
* Significant at 5% level
From the above table it is clear that Pearson correlation coefficients were computed
among the three variables, namely, organizational commitment index, quality of work
life and job satisfaction. The results of these correlational analyses indicated that all
three variables were positively correlated with one another. The Pearson’s correlation
between organizational commitment index and quality of work life was 0.190
(significant at 1% level), and the Pearson’s correlation between organizational
commitment index and job satisfaction was 0.130 (significant at 1% level).Finally, the
Pearson’s correlation between quality of work life and job satisfaction was 0.348
(significant at 1% level).
A partial correlation was then computed between organizational commitment index,
quality of work life, holding constant or controlling for job satisfaction. The results
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 129 Volume 6, Issue No. 1, Jan. – June 2016
suggest that organizational commitment index is positively correlated to quality of
work life (Pearson’s correlation of 0.156, significant at 1% level), when controlling for
job satisfaction.
Regression Analysis
The researcher carried out regression analysis to check the linear relationship between
independent variable (Skill Discretion, Decision Authority, Task Control, Work and
Time Pressure, Role Ambiguity, Physical Exertion, Hazardous Exposure, Job
Insecurity, Lack Of Meaningfulness, Supervisor Social Support and Co-Workers Social
Support) and dependent variables (Affective, Continuance and Normative
Commitment). The results are presented as follows:
Table 11: Linear Relationship between Independent and Dependent Variables
S. No Dimensions Correlation Coefficient Value
(R)
1 QWL dimensions on Affective Commitment 0.711
2 QWL dimensions on Continuance Commitment 0.780
3 QWL dimensions on Normative Commitment 0.692
From the above table values it can be concluded that there exist a linear relationship
between QWL dimensions and organizational commitment dimensions which indicate
that any given change in QWL dimension or dimensions will always produce a
corresponding change in organizational commitment dimensions. So if the company
intends to have more committed employees then the better choice is through better
QWL.
Structural Equation Modeling
It is of interest for the researcher to apply structural equation modeling (SEM) .Model
that is proposed for the study is shown below in the diagram #, model specification
which indicates the independent variable QWL and the dependent variables
organizational commitment and job satisfaction.
Quality of work life dimensions are treated as independent variables which comprises
11 variables such as Skill Discretion , Decision Authority , Task Control , Work and
Time Pressure ,Role Ambiguity , Physical Exertion , Hazardous Exposure , Job
Insecurity , Lack of Meaningfulness , Supervisor Social Support and Co-Workers
Social Support. Organization commitment and job satisfaction are treated as dependent
variables. The given hypothesis is likely to prove in the study.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 130 Volume 6, Issue No. 1, Jan. – June 2016
Figure 1: Model Proposed For The Study
Figure 2: Model Drawn Through Path Analysis
.24
.50
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 131 Volume 6, Issue No. 1, Jan. – June 2016
Table 12: SEM Values
Squared Multiple Correlations: (Group number 1 - Default model)
PAMETER Observed Value Recommended Value
CMIN/DF 2.947 2.5 – 4.5
RMR 0.056 0.05 To 0.08 (Hu and Bender, 1999)
GFT 0.934 >0.9 (Hooper et al. 2008)
CFI 0.904 > 0.9 (Hooper et al. 2008)
TLI 0.901 >0.9 (Hooper et al. 2008)
KMSEA >0.087 .08 to 1.0 (MacCallum et al. 1996
PATH ANALYSIS
From the Diagram, it is found that QWL has impact on Organization commitment and
Job satisfaction, the standardized coefficient of model is, .87 and .50 respectively and
subsequently the R square is .75 and .24 for model respectively. The CR values for the
relationships among QWL and Organization commitment was found significant, with
CR values above 1.96. Thus the model is considered plausible.
SUGGESTIONS
Though it a collective analysis of top three Indian IT companies it opens up new
message for all the Indian IT companies to understand the importance of QWL which is
one of the important aspect to have a better committed employees with good job
satisfaction. Any organization can be successful only if it has a committed employee
base. Moreover the study projects such dimensions that increase QWL, organizational
commitment and job satisfaction. Following are the suggestions made by researcher
considering the data analysis and results.
It is suggested by the researcher that organization should frame policies by
considering the demographic factors like age, gender, marital status, etc to make
the policies more customized to the individual employee to have a better QWL,
organizational commitment and job satisfaction.
It is suggested by the researcher that the top three information technology
companies TCS, Infosys and Wipro need to focus more on job security which
requires significant attention. The respondents irrespective of not losing their
job or not faced such situation in the past still have an insecure feeling towards
their job. This insecure feeling will make the employees to be more alert; on the
other hand losing their individuality. But the IT industry requires knowledge
workers for better performance.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 132 Volume 6, Issue No. 1, Jan. – June 2016
The dimension skill discretion is negatively correlated with job satisfaction.
Hence it is recommended that the companies should take steps to provide
challenging work environment that will make the employees to accept in a
positive manner which will subsequently increase job satisfaction. This will
relatively resolve the negative correlation between skill discretion and job
satisfaction in the long run. Ultimately if the employee is not able to enjoy or
accept the challenging work environment his commitment towards the
organization will drop.
The suggestions drawn from the partial correlation is that, even when job
satisfaction was held constant QWL influences organizational commitment,
where it is to be noted that QWL is a major factor that has a significant impact
on organizational commitment.
It is also suggested by the researcher that the companies should have flexible
organizational practices to reduce physical exertion or effort.
From the results of PATH analysis it is strongly recommended that critical care
should be taken by the companies in developing the dimensions of QWL which
will directly influence job satisfaction and organizational commitment.
It is also recommended that the companies should also find and implement
methods to develop QWL as it was found to predict organizational commitment
and job satisfaction.
The study provided an insight into the dimensions required for effective QWL,
organizational commitment and job satisfaction.
The difference in demographic characteristics reveals that organizations policy
should be more specific to suit the individual employee.
Hereby this study is also useful for foreign invested organizations that operate
in India to select the QWL, organizational commitment and job satisfaction
activities suitable for Indian context.
As India is the hub for IT for its talented workforce and the availability of resources,
high productivity can be facilitated by increasing QWL, organizational commitment
and job satisfaction.
DIRECTION FOR FURTHER RESEARCH
Having found that QWL dimensions leads to organizational commitment and
job satisfaction further research can focus on how and why it influences.
Further insight on other factors that contribute to organizational commitment
can be studied.
Quantitative studies on QWL are highly required in Indian context.
Sector specific studies could also be carried out for the extension of such
effectiveness-based research.
The complementing feature of QWL on organizational commitment and job
satisfaction could be analyzed.
Quality Of Work Life Metrics As A Predictor Of Job Satisfaction & Organizational Commitment: A Study With Special Reference To Information Technology Industry
– Dr. M. Swapna
Namex International Journal of Management Research 133 Volume 6, Issue No. 1, Jan. – June 2016
Multidisciplinary approach on QWL, organizational commitment and job
satisfaction could be studied.
The congruence and link between QWL and productivity could be analyzed.
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