FACTORS AFFECTING QUALITY OF WORK LIFE: EMPIRICAL EVIDENCE
FROM INDIAN SUGAR MILLS
Author: Dr. S C Das, Associate Professor
Organization: Faculty of Commerce, Banaras Hindu University, Varanasi-5, India. email:[email protected], Cell: +91-9415624673.
1. INTRODUCTION
Work is central to human existence, providing the necessities for life, sources of identity,
opportunities for achievement, and determining standing within the larger community. Therefore, Quality of
work life (QWL) has evolved as an important aspect, which affects an organizational efficiency and
productivity (Gorden, Judith R. 1987). The term “Quality of Work Life” has appeared in Research Journals
and Press in USA only in 1970’s introduced by Louis Davis. From 1980 onwards QWL was increasingly
placed on employee centered productivity programs. In the mid 1990s till today faced with challenges of
economize and corporate restructuring, QWL is reemerging where employees are seeking out more meaning
where rising educational levels and occupational aspirations in today’s slow economic growth and reduced
opportunities for advancement, naturally, there are rising concerns for QWL and for career and personal life
planning.
‘Quality of work life’ (QWL) has different meanings of different peoples, some consider it industrial
democracy or codetermination with increased employee participation in the decision making process. For
others, particularly managers and administrators, the term denotes improvement in the psychological aspects
of work to improve productivity. Unions and workers interpret it as more equitable sharing of profits, job
security and healthy and humane working conditions. Others view it as improving social relationships at
workplace through autonomous workgroups. Finally, others take a broader view of changing the entire
organizational climate by humanizing work, individualizing organizations and changing the structural and
managerial systems. According to Chan, and Einstein, (1990) people conceive QWL as a set of methods;
such as autonomous work groups, job enrichment and high involvement aimed at boosting the satisfaction
and productivity of workers. QWL reflects a concern for people’s experience at work, their relationship with
other people, their work setting and their effectiveness on the job. With the increasing levels of development,
the working environment has also become more competitive. However, the concept of QWL included other
aspects that affect employees' job satisfaction and productivity and these aspects are, reward systems, physical
work environment, employee involvement, rights and esteem needs (Cummings and Worley, 2005).
Walton (1973) suggested eight major conceptual areas for understanding quality of work life. These were
adequate and fair compensation, safe and healthy working conditions, development of human competencies,
growth and security, social integration, constitutionalization and total life space and social reliance.
According to Guest (1979), “quality of working life is a generic phrase that covers a person’s feelings about
every dimension of work including economic rewards and benefits, security, working conditions,
organizational and interpersonal relationship”. In the same vein Heskett, Sasser and Schlesinger (1997)
define QWL as the feelings that employees have towards their jobs, colleagues and organizations that ignite a
chain leading to the organizations’ growth and profitability. A good feeling towards their job means the
employees feel happy doing work which will lead to a productive work environment. This definition provides
an insight that the satisfying work environment is considered to provide better QWL. The recent definition
by Serey (2006) on QWL is quite conclusive and best meet the contemporary work environment. The
definition is related to meaningful and satisfying work. It includes (i) an opportunity to exercise one’s talents
and capacities, to face challenges and situations that require independent initiative and self-direction; (ii) an
activity thought to be worthwhile by the individuals involved; (iii) an activity in which one understands the
1
role the individual plays in the achievement of some overall goals; and (iv) a sense of taking pride in what one
is doing and in doing it well. This issue of meaningful and satisfying work is often merged with discussions of
job satisfaction, and believed to be more favorable to QWL.
2. REVIEW OF LITERATURE
Thomas Wyatt and Chat Yue Wah (2001) examined the perception of QWL with a sample size of
332 managerial executives. Results from Factor analysis suggest four dimensions which are named favourable
work environment, personal growth and autonomy, nature of job and stimulating opportunities and coworkers. The overall findings support the conceptualizations of factors involved in perception of QWL. Rice
(1985) emphasized the relationship between work satisfaction and Quality of people’s lives. He contended
that work experiences and outcomes can affect person’s general Quality of life, both directly and indirectly
through their effects on family interactions, leisure activities and levels of health and energy. Karrir and
Khurana (1996) found significant correlations of quality of work life of managers from three sectors of
industry viz., Public, Private and Cooperative, with some of the background variables (education qualification,
native/migrant status, income level) and with all of the motivational variables like job satisfaction and job
involvement. Singh (1983) conducted studies in chemical and textile factories in India that were designed to
improve the Quality of Work Life by reorganizing the work and introducing participatory management.
Bhatia and Valecha (1981) studied the absenteeism rates of textile factory and recommended that closer
attention should be paid to improve the Quality of Work Life. Kavoussi (1978) compared the unauthorized
absenteeism rates in two large textile factories and recommended that closer attention be paid for improving
the Quality of Work Life. Ritti (1970) in his study found that lack of opportunity to perform meaningful
work is at the root of frustration among engineers and who have more autonomy at workplace feel more
satisfied with their work life. In a study, Sirota (1973) found that underutilization of worker’s skill and
abilities cause low Quality of Work Life and suggested job enrichment programme to correct the problems of
worker’s skill and abilities. Hackman and Oldham (1976) observed psychological growth needs as crucial
determinant of Quality of working life. Several such needs were identified; Skill variety, Task Identity, Task
significance, Autonomy and Feedback. They concluded that fulfillment of these needs plays an important role
if employees are to experience high quality of working life. Mirvis and Lawler (1984) found in their study
that Quality of working life was related with satisfaction with wages, hours and working conditions,
describing the “essentials of a good quality of work life” as; safe work environment, equitable wages, equal
employment opportunities and opportunities for advancement. Baba and Jamal (1991) listed what they
described as typical indicators of quality of working life, including: job satisfaction, job involvement, work
role ambiguity, work role conflict, work role overload, job stress, organizational commitment and turn-over
intentions. Baba and Jamal also explored reutilization of job content, suggesting that this facet should be
investigated as part of the concept of quality of working life. Various other studies conducted on quality of
work life include employment conditions, employment security, income adequacy, profit sharing, equity and
other rewards, employee autonomy, employee commitment, social interaction, self- esteem, self- expression,
democracy, employee satisfaction, employee involvement, advancement, relations with supervisors and peers
and job enrichment ( Chander and Singh, 1993).
2.1 Research Gap
The work on QWL had begun in India four decade ago with differences in the social, cultural,
political and economic spheres. Most of the work in Indian setting dealt with the QWL in theoretical and
descriptive framework, or mostly in an action research context to bring about some desirable change in the
design of work system. No specific studies have been conducted to understand factor affecting quality of
work life that is working towards the development of sugar industry. Moreover, it is difficult to best
conceptualize the QWL elements (Seashore, 1975). This study examines the reasons behind what employees
perceive about quality of working-life experiences employed by mill owners in India which ranks first in sugar
consumption and second in sugar production in world but its share in global sugar trade is below 3%.
2
2.2. Purpose
The study has two fold objectives firstly to test the factors influencing on quality of work life of
employees in the select sugar mills in India and finally, to understand the impact of identified variables of
QWL on job satisfaction.
2.3. Research Design
The study is exploratory in nature based on structured questionnaire with 360 respondents complying
sampling adequacy (Yamane, 1967) in the ratio of 1:3 among cooperative and private sugar mills employees
selected through proportionate stratified random sampling technique have been collected from 12 sugar mills
in the state of Uttar Pradesh (UP) of India. The most common assessment of QWL is the individual attitudes
(Loscocco and Roschelle, 1991) and questionnaire survey is arguably the most common technique in
management research (Veal, 2005). Four dimensions or components namely working environment,
relational, job and financial aspects including 23 statements were considered based on the literature review
(Walton, 1975; Havlovic 1991; Sadique 2003; Royuela, Tamayo & Suriñach 2007; Islam & Siengthai
2009; Dixon & Sagas, 2007; Sinha and Sayeed, 1980; Karla and Gosh,1984; Carlson, 1978 ) for
achieving the objectives of the study. Questionnaire survey method was used to gather primary data.
Secondary data were collected from research studies, books, various published journals, magazines websites
and online articles. The adequacy of the data is evaluated on the basis of the results of Kaiser-Meyer-Olkin
(KMO) measures of sampling adequacy and Bartlett’s test of Sphericity (homogeneity of variance). The KMO
measure of sampling adequacy is .836, indicating that the present data are suitable for Factor Analysis.
Similarly, Bartlett’s test sphericity is significant (p<0.001), indicating significant correlation exists between the
variables to proceed with the analysis. The Bartlett’s test statistic is approximately distributed and it may be
accepted when it is significant at p<0.05 (Table-1).
Table:1
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett's Test of Sphericity
Approx. Chi-Square
.836
1.873E3
df
253
Sig.
.000
3. EMPIRICAL RESULTS & DISCUSSIONS
3.1: Industry Structure
India is the second largest producer of sugarcane next to Brazil (accounting 15% of the world’s
sugar production). The sub-tropical region (Uttar Pradesh) contributes almost 60% of India’s total sugar
production, while the balance comes from the tropical region, mainly from Tamil Nadu, Karnataka,
Maharashtra and Madhya Pradesh. Sugar industry is one of the oldest industries in India which played a very
dominant role in the development of the rural areas. The industry covers around 7.5% of total rural
population and provides employment to more than 5 Lakh rural people. About 4.5 Crores farmers are
engaged in sugarcane cultivation in India (Devaraja, 2009). The geographical and historical factors contribute
largely to the establishment and development of sugar industry in Uttar Pradesh. But they have many
3
problems and difficulties in the production and marketing of sugar due to non availability of quality sugar
cane, high cost of production, low price of sugar etc. The industry has also shortage of technical skill, modern
machinery and effective government assistance. The most important problems namely working conditions,
compensation with workload determination caused lot of strain on the relationship between employees and
employers. Among six major sugar producing states, the sugar firms of Uttar-Pradesh (UP) and Maharashtra
are contributing about 27.06 percent and 30.12 percent, respectively to the total sugar production of India
(Ray, 2012).The Indian sugar industry is marked by co-existence of different ownership and management
structures since the beginning of the 20th century. At one extreme, there are privately owned sugar mills in
Uttar Pradesh that procure sugarcane from nearby cane growers. At the other extreme, there are cooperative
factories owned and managed jointly by farmers, especially in the western state of Gujarat and Maharashtra.
There are state owned factories in both the states and state-managed cooperatives in Uttar Pradesh. Sugar is
India’s second largest agro-processing industry, with around 490 operating mills as of SY 2010-11 (Figure 1).
Over the years the sugarcane and sugar production fluctuated noticeably. The production of sugar in India
increased substantially from 185.19 lakh tonnes in sugar year (SY) 2000-01 to 283.64 lakh tonnes in SY 200607 and decreased to 243.94 lakh tonnes in SY 2010-11(Figure 1) particularly due to the onslaught of drought
and white woolly aphid in major sugar producing states like Maharashtra, Tamil Nadu and Karnataka
resulting in a fall in sugarcane production, delayed payment of cane price and closure of some sugar mills.
The Indian sugar industry comprises about 20 percent of sugar mills and 15 percent of sugar production of
the world. The sugar industry’s contribution, to the Indian economy is presently enormous with its total
turnover of 12 billion US Dollars per year (Directorate of Sugar, 2006).
In the era of globalization, sugar industry needs more competitive edge which can be given by way of
modernization, enhancing productivity, and manufacturing excellent quality sugar at competitive prices. It
needs quality management at every level of activity to enhance its performance. The need of the hour is to
liberalize industry from clutches of unprofessional people. New sugar units should be set up taking into
consideration sugarcane availability. The study would be useful in understanding the formulation of suitable
workplace policies by the sugar producers and mill owners, so that overall performance of the industry as well
as performance of employees can be developed.
Figure I: Indian Sugar Statistics
600
500
400
300
200
100
0
2001
2002
2003
2004
2005
2006
Production (Lakh Tonnes)
2007
2008
2009
2010
2011
No. of Sugar Mills in Operation
3.2 Analysis of Socio-Economic Background: It is discernible from Table I that the largest majority of the
sample respondents i.e. 75 % is belongs to private sector and rest of the (25%) from cooperative sector.
Further the ratio between permanent and seasonal employees was same. As far as employees experience is
concerned, it is found that the largest majority of the sample employees (26.9 %) had employee experience of
10-15 years followed by 26.7% more than 20 years indicating that employees had longer attachment with their
workplaces. The majority of the respondent’s (49.2%) monthly income is Rs. 10,000 to 20,000 (INR) and
12.2% of them earnings above Rs. 20,000. Education- wise it is discernible that the largest majority of the
4
employees are graduates (43.3%) followed by intermediate and post graduates. It is also apparent that the
largest majority of the sample respondents i.e. 41.1 % are between 40-50 age groups which were followed in
by the age group of 50 and above years (27.2 %), 30-40 years (24.4 %), 21-30 and below 30 years (7.2%). It is
to be noted that majority of employees selected for the study is technical staffs i.e., 42.2% and rest of the
staffs are clerical, accounting, administration and managerial cadre.
Table: 2 Demographic Factor wise Classification of respondents (Employees)
S.
Variable
No.
1.
Nature of Organization
2.
Nature of Employment
3.
Work Experience
4.
Monthly Income
5.
Education
6.
Age
7.
Job Position
Categories
Private
Cooperative
Permanent
Seasonal
1-5 Yrs
5-10 Yrs
10-15 Yrs
15-20 Yrs
20 and above
Below Rs. 10,000
10,000-20,000
20,000 and above
Below High school
High school Pass
Intermediate
Graduation
Post-Graduation
Others
Below 30 Yrs
30-40 Yrs
40-50 Yrs
50 and above
Clerical
Accounting
Administration
Managerial
Sales and Marketing
Technical
Others
No. of Employees
Percentage
270
90
150
150
21
60
86
97
96
139
177
44
14
35
51
156
48
56
26
88
148
98
93
51
18
27
11
152
8
75
25
50
50
5.8
16.7
23.9
26.9
26.7
38.6
49.2
12.2
3.9
9.7
14.2
43.3
13.3
15.6
7.2
24.4
41.1
27.2
25.8
14.2
5.0
7.5
3.1
42.2
2.2
Source: Primary Data
3.3: Correlation Matrix
A correlation matrix (Table: 3) is a lower triangle matrix showing the simple correlations( r) between
all possible pairs of variables included in the analysis. The diagonal elements, which are all 1, are omitted. The
correlation coefficient value ranges from 0.10 to 0.29 is considered weak, from 0.30 to 0.49 is considered
medium and from 0.50 to 1.00 is considered strong (Wei et. al. 2009 and Noordin and Sadi, 2010). Twenty
three variables have been entered in the Pearson Correlation Coefficient matrix to understand the factorability
and multicollinearity.
5
Table- 3: Correlation Matrix of Quality of Work Life
Factors
Lighting Facilities
(LF)
Safety Measures
(SF)
Health Facilities
(HF)
Physical Working
Condition (WC)
Welfare Facilities
(WF)
Supervisor’s
Interference (SI)
Supervisor’s
Support (SS)
Relationship with
Colleagues (RC)
Relationship with
Superiors (RS)
Treating Respects
(TR)
UnionManagement
Relations (UR)
Role of Trade
Union (RT)
Adequate Training
(AT)
Additional
Responsibility
(AR)
Necessary
Authority (NA)
Work Schedule
(WS)
Job Security (JS)
Pay Package (PP)
Adequate Bonus
(AB)
Performance
based Promotion
(PB)
Team Spirit (TS)
Skill Utilization
(SU)
Perceived Abilities
(PA)
LF
SF
HF
WC
WF
SI
SS
RC
RS
TR
UR
RT
AT
AR
NA
WS
JS
PP
AB
PB
TS
SU
PA
1
.394**
1
.121*
.284**
1
.251**
.331**
.449**
1
-.254**
-.070
-.008
-.109*
1
.011*
-.050
-.022*
-.119*
-.039
1
.365**
.333**
.201**
.239*
-.120*
-.119*
1
.227**
.152**
-.033
.086*
-.160**
-.052
.203**
1
.354**
.297**
.049
.133*
-.191**
-.099
.265**
.254*
.337**
.263**
1
*
.075
.153**
-.139**
-.007*
.152*
.238*
.090
1
.110*
.285**
1
.176**
.295**
.467**
1
*
.208**
.369**
.080
.091*
-.037
-.042
.147*
.194*
*
.270**
.312*
.203*
.234**
-.106*
-.149*
.209**
.159*
*
.270**
.369**
.263**
.199**
-..089**
.016
.216**
.046
.207**
.073
.182**
.259**
1
.272**
.086*
.078
.066*
.096*
-.116*
.162
.064
.005
.085
.163**
.090
.255**
1
.354**
.341**
.079
.204*
..200**
-.063
.303**
.110*
.212**
.220**
.177**
.294**
.323**.
.239**
1
-.094
.030**
.032
.007**
.013
.007
-.031
.017
.000
.002
-.024
-.041*
.057
.003
-.023
1
.325**
.422**
.279**
.229**
-.179**
-.007
.276**
.055
.189**
.240**
.225**
.326**
.401**
.060
.304**
-.140*
1
.297**
.442**
.220**
.142**
-.148**
.012
.240**
.107*
.190**
.185**
.289**
.320**
.344**
.152**
.277**
-.053
.510**
1
-131*
-.057
.012
-.039
.020*
-.009
-.049
-.026
-.050
-.092
-.063*
-.153*
-.113
.100
-.074
.006*
-.108
-.014
1
.262**
.367**
.254**
.168**
-.048*
-.050
.260**
.095*
.215**
.072
.224**
.313**
.418**
.134*
.260**
.136*
.366**
.455**
-.019
1
.282**
.265**
.087
.166**
-.163**
.090
.142*
.204*
.211**
.185**
.183**
.224**
.221**
.089
.359**
-.009
.301**
.258**
-.212**
.249*
.170**
.150**
.026
.100*
-.094*
.066
.078
.136*
.068
.089
.120*
.073
.137**
.186**
.038
-.058
.167**
.098
-.012
.062
.103*
1
.176**
-.087
.048
.750*
-.066+
-.040
.086
.106*
.181**
.033
-.020
.080
.137**
.249**
.067
.006
.093*
.042
.040
.092
.136*
.192**
*
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)
1
*
6
1
The first variable of lighting facilities under physical working condition is positively correlated with
18 variables listed in table-3 and found significant at .01 level. Safety measures found significant r with fifteen
variables at .01 or .05 level. Health facilities shows weak and few cases moderate correlation ( r ) with eight
variables and significant at .05 or .01 level. Working condition found strong correlation with perceived abilities
whereas rest cases of correlation coefficient lays less than .29 shows weak correlation and found significant at
.05 or .01 level. The variables of welfare facilities projects negative correlation with thirteen variables and all
are significant at their respective level. Supervisory interference shows very weak correlation (r ≤ .29) and
found to be significant at .01 level. Supervisors support and relationship with colleagues found significant r
with the rest of select variables. Relationship with superiors and treating respects projects week correlation
with ten variables and found significant at .05 or .01 level. Union management relationship shows significant
correlation coefficient (r) with majority of variables. Rest of variables namely role of trade union , adequate
training, additional responsibility, necessary authority, work schedule, job security, pay package, adequate
bonus, performance based promotion, team spirit, skill utilization and perceived abilities projects week or
moderate correlation which is found to be significant at 0.05 or 0.01 level. Field (2005) indicated that
multicollinearity may arise if correlation coefficient is found to be more than 0.80. But in the table the
highest correlation is 0.625, hence there is no existence of multicollinearity in measuring the quality of
work life factor.
3.4: Extraction Communalities
The extraction communalities are useful as these are obtained using the extracted factors. Extraction
communalities for a variable give the total amount of variance in that variable, explained by all the factors.
The higher the value of communality for a particular variable after extraction, higher is its amount of variance
explained by the extracted factors. In Table: 4, the rows indicate the various components taken care of to
examine the factor analysis of the study. There are 23 variables under various factors comes into act. Fourth
column denotes that what will be the total weight of each of the components if there is only one component.
The fifth column denotes that in presence of all the components what will be the weight of all the
components individually. Further, table: 4 show the mean and SD scores of 23 variables independently.
Table: 4
Communalities
Factors
1.
Working
Environme
nt Factor
2.
Relational
Factor
Statements
1. The lighting facility within the
mill is sufficient to work.
2. The quality of safety measures
adopted by the organization.
3. The health facilities in the mill
are not good.
4. I am not satisfied with the
working condition provided by
the organization.
5. The quality of welfare facilities
in your organization.
6. My supervisor interferes in the
given work.
7. I receive adequate support
from my supervisor.
8.The relationship with our
colleagues is good
9. The relationship with our
superiors is good.
10. I am not treated with respect
in the organization.
Variables
Lighting Facilities
(LF)
Safety Measures
(SF)
Health Facilities
(HF)
Physical Working
Condition (WC)
Welfare Facilities
(WF)
Supervisor’s
Interference (SI)
Supervisor’s Support
(SS)
Relationship with
colleagues (RC)
Relationship with
superiors (RS)
Treating Respects
(TS)
7
Initial
Extraction
Mean
S.D
1.000
.542
4.00
.910
1.000
.524
2.22
.908
1.000
.723
2.66
1.319
1.000
.703
2.99
1.267
1.000
.562
1.74
1.156
1.000
.622
1.99
.853
1.000
.474
3.88
1.057
1.000
.497
4.44
.736
1.000
.603
4.14
.900
1.000
.528
3.64
1.230
11. How are union-management
relations in your organization?
3.
Job
Factor
4.
Financial
Factor
5.
Impact
factor
12.Trade union plays a major
role to protect the workers
interest.
13.I receive adequate training to
do my job well.
14.I am ready to take additional
responsibility with my job.
15. I have necessary authority to
do my job well.
16.Which of the best describe
your usual work schedule
17. How satisfied are you with
your overall job security?
18. Are you satisfied with your
pay package?
19. Do you get adequate bonus
beside your salary.
20. Promotion is strictly linked
to performance and seniority.
21. How satisfied you are with
your team spirit.
22. I am fully able to use my skill
in the present position.
23. I am confident of my abilities
to succeed of my work.
UnionManagement
Relations (UR)
Role of Trade Union
(RT)
Adequate Training
(AT)
Additional
Responsibility (AR)
Necessary Authority
(NA)
Work Schedule (WS)
Job Security (JS)
Pay Package (PP)
Adequate Bonus
(AB)
Performance based
Promotion (PB)
Team spirit (TS)
Skill Utilization
(SU)
Perceived Abilities
(PA)
1.000
.657
2.95
1.178
1.000
.570
2.81
1.228
1.000
.571
3.16
1.418
1.000
.654
3.63
1.178
1.000
.554
3.55
1.145
1.000
.816
1.37
.889
1.000
.615
2.36
.986
1.000
.628
2.16
1.277
1.000
.698
1.34
.474
1.000
.600
2.82
1.418
1.000
.511
3.97
.977
1.000
.727
4.27
.912
1.00
.716
4.44
.791
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization
3.5: Variance Analysis
In Table 5 summarizes the total variance explained by the FA solution and gives an indication about
the number of useful factors. This table has three parts. The first part, titled Initial Eigen values gives the
variance explained by all the possible factors. There are a total of 23 factors, which is same as the number of
variables entered into the FA. The first column under initial eigenvalues gives the eigenvalues for all the possible
factors in a decreasing order. This is followed by the variance as a percentage of all the variance and
cumulative variance. From this table it can be seen that the cumulative value of the first eight attributes
become approximately 62%. That means the eight factors are so powerful to overpower the rest of the
factors. It can be observed only the factors with Eigen values greater than 1 were considered significant and
all the factors with Eigen values less than 1 were considered insignificant and discarded.
Table: 5
Total Variance Explained
F
A
C
T
O
R
1
Initial Eigen Values
Extraction Sums of Squared
Rotation Sums of Squared
loadings
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative %
5.346
23.243
23.243
5.346
23.243
23.443
3.425
14.890
14.890
8
2
3
4
5
6
7
8
1.603
1.485
1.264
1.206
1.555
1.097
1.040
6.968
6.459
5.495
5.242
5.023
4.769
4.253
30.211
36.670
42.165
47.407
52.430
57.199
61.722
1.603
1.485
1.264
1.206
1.155
1.097
1.040
6.968
6.459
6.495
5.242
5.023
4.769
4.523
30.211
36.670
42.165
47.407
52.430
57.199
61.722
1.886
1.858
1.605
1.561
1.370
1.283
1.148
8.202
8.079
7.239
6.787
5.955
5.580
4.990
23.092
31.171
38.410
45.197
51.152
56.732
61.722
3.6: Factor Loadings: Table-6 shows the factor loadings are used to measure the correlation between
variables and the factors. A loading close to 1 indicates strong correlation between a variable and the factor,
while a loading close to zero indicates weak correlation. The factors are rotated with the used of Varimax with
Kaiser Normalization rotation method and Principal Component Analysis (PCA) method for factor
extraction. Only those factors whose are greater than .40 are used for interpretation purpose.
Table: 6
Rotated Component Matrix
Factor
Variables
1.Lighting Facilities
(LF)
2.Safety Measures
(SF)
3. Health Facilities
(HF)
4.Physical Working
Condition (WC)
5.Welfare Facilities
(WF)
6.Supervisor’s
Interference (SI)
7.Supervisor’s
Support (SS)
8.Relationship with
colleagues (RC)
9.Relationship with
superiors (RS)
10.Respects
11.UnionManagement
Relations (UR)
12.Role of Trade
Union (RT)
13.Adequate
Training (AT)
14.Additional
Responsibility (AR)
15.Necessary
Authority (NA)
16.Work Schedule
(WS)
17.Job Security (JS)
18. Pay Package (PP)
1
2
3
4
5
6
7
8
.315
.496
.191
.177
.098
.251
.082
-.224
.584
.312
.202
.029
.205
.043
-.015
-.013
.780
-.076
.022
.022
.316
-.070
-.025
.054
.083
.147
.100
.079
.794
.120
.117
-.028
.552
.365
.221
.002
.222
.158
-.015
.033
.149
-.166
-.078
.400
-.175
.136
-.702
-.025
.282
.494
.028
-.007
.223
.019
.288
-.129
-.080
.613
.398
.154
-.084
-.028
-.046
.152
.220
.736
-.069
.041
-.007
.066
.029
.033
.044
.202
.669
.008
.096
.130
-.053
-.097
.262
-.038
.755
.031
-.061
-.008
.106
.037
.303
.034
.607
-.013
.188
.179
.201
-.007
.661
-.013
-.043
.162
.119
.225
.168
.112
.224
-.128
.094
.418
-.111
-.016
.626
.014
.424
.204
.086
-.005
-.045
.383
.395
-.142
.035
.008
-.021
-.020
.028
.017
-.010
.901
.655
.084
.173
.072
.196
.024
-.083
-.314
.739
.088
.231
-.001
.006
-.075
-.048
-.114
9
19.Adequate Bonus
(AB)
20.Performance
based Promotion
(PP)
21. Team spirit (TS)
22.Skill Utilization
(SU)
23.Perceived
Abilities (PA)
.078
.013
-.085
.080
-.075
-.817
.063
-.036
.704
.119
.064
.002
.076
-.005
.085
.271
.327
.193
.149
.145
-.033
.562
-.080
-.009
.048
.039
.139
.826
.064
-.006
-.108
-.078
.040
.157
-.109
.812
.048
.019
.114
.045
3.7: Catell’s Scree Test: It involves plotting each of the Eigen values of the factor and inspecting the plot to
find a pint at which the shape of the curve changes direction and become horizontal. Catell recommends
retaining all factors above the eblow, or break in the plot all these factors contribute the most to the
explanation of the variance in the data set (Catell, 1966). Figure: 2 shows a sharp break in sizes of eigenvalues
which results in a change in the slope of the plot from steep to shallow. It can be observed that the slope of
the Scree plot changes from steep to shallow after the first eight factors. This suggests that a eight-factor
solution may the right choice.
Figure-2: Scree Plot
3.8: Factors of Quality of Work Life
The various factors and the subsequent variables, along with their reliability alpha and factorial mean
values are integrated in table -7. The factor analysis contains 23 statements encompassed with five dimensions
(Table-4 and 5) which explained for 62% of total variance. To see the internal consistency of the scale,
Cronbach’s alpha reliability analysis has been conducted of the newly created factors. It may be noted in
table-7 that only three factors internal consistency greater than .6 (significant) and accordingly rest of five
factors have been removed. The newly constructed factors have been renamed as
I. Job and Working Environment Dimensions (8 items)
II. Human Relation Dimensions (4 items) and
III. Industrial Relations Dimensions (3 items).
10
Job and working environment dimension is the first and most important factor on which eight
statements are loaded and it explains 14.89% of variance with Eigen value of 5.349. Human Relation
Dimensions is the second highest factor loading in quality of work life, it explains 8.2% of variance with the
Eigen value of 1.603. Industrial Relations Dimensions have rigorous impact on QWL which loaded with
three statements and jointly explains 8.079% of variance with the Eigen value 1.485. It to be noted that only
fifteen statements have been finally selected keeping in view the reliability coefficient of the scale.
Factors
(Factorial
Mean)
1.
Job and
Working
Environment
Dimensions
(2.641)
2.
Human
Relations
Dimensions
(4.115)
3.
Industrial
Relations
Dimensions
(3.133)
Variables
Safety measures
(SM)
Health facilities
(HF)
Welfare facilities
(WF)
Adequate training
(AT)
Necessary
authority (NA)
Job security (JS)
Pay package (PP)
Performance
based promotion
(PBP)
Lighting facilities
(LF)
Supervisory
support (SS)
Relationship with
Colleagues (RC)
Relationship with
superiors (RS)
Treating respects
(TR)
Union
management
relationships (UR)
Role of trade
union (RT)
Table: 7
Summary of Factors of QWL
Loadings Eigen
% of
value
Variance
Cumulative %
of Variance
Cronbach
’s alpha
.584
.780
.552
.661
5.349
14.890
14.980
.790
1.603
8.202
23.092
.605
1.485
8.079
31.171
.615
.424
.655
.739
.709
.496
.494
.613
.736
.669
.755
.607
3.9: Multiple Linear Regression Analysis
Out of three factors identified in factor analysis, job and working environment to be considered
more powerful since it projects maximum variance. In order to test the impact of eight different variables of
11
job and working environment on job satisfaction, multiple linear regression analysis has been employed. All
eight variables are considered as independent variable and the job satisfaction is assumed as dependent
variable, which are presented in table 8A.
Model
R
1
.552a
Table: 8A Regression Model Summary
R square
Adjusted R Square Significance
F Change
.425
.411
.000
F
Sig.
32.370
0.000
a. Predictors: Constant, Safety measures, Health facilities, Welfare facilities, Adequate training, Authority,
promotion, Pay package, and job security.
b. Dependent Variable: Job satisfaction
Table 8A reveals the value of Adjusted R2 .411, which indicates that 41% of variation on job
satisfaction is explained by eight underlying variables of quality of work life. It can be seen from table: 8B that
only three independent variables are positively related with the quality of work life of employees in sugar
industry. Job security having highest beta coefficient of 0.298 and t value of 5.861 is statistically significant at
1% level. Pay package is positively correlated with the job satisfaction and statistically found to be significant
at 1% level. Performance based promotion another important factor of quality of work life has significant
affect on job satisfaction and makes statistically difference at 1% level.
Table: 8B
Coefficient
Unstandardized
Standardized
Collinearity
Coefficient
Coefficient
Statistics
Model - 1
t
Sig.
B
Std. Error
Beta
Tolerance
VIF
Constant
Safety measures
Health facilities
Welfare facilities
Adequate
training
Necessary
authority
Performance
based
Promotion
Pay package
Job security
.784
.094
.062
.105
.007
.206
.071
.042
.072
.043
-.068
.064
.075
.008
3.813
4.326
1.461
1.464
.168
.000
.186
.145
.144
.867
-.631
.845
.623
.693
--1.584
1.183
1.604
1.444
.070
.050
.063
.162
.803
1.245
.178
.044
.200
1.401
4.055
.000
.677
1.4777
.206
.382
.052
.065
.208
.298
3.984
5.861
.000
.000
.603
.635
1.658
1.574
4: SUMMARY AND CONCLUSIONS
Prior to factor analysis, Cronbach’s Alpha for all select 23 statements is found to be .83 which shows
the high internal consistency (Nunnally, 1978; Freitas and Rodrigues, 2005) of the scale. To decide whether to
continue with the rest of the dimensions, principal component analysis was conducted with varimax rotation.
The study identified eight factors have an Eigen values over 1 and they have account for about 62% of
variance in data, out of which three factors comprising 15 statements renamed as (i) Job and working
12
environment (JWE) dimensions, (ii) Human relations (HR) and (ii) Industrial relations (IR) dimensions have
been found valid. Job and working environment dimensions is the first and most important factor on which
eight statements (Performance based Promotion, Pay Package, Job Security, Adequate training, Safety
measures, Welfare facilities, Health facilities, and Necessary authority) are loaded and it explains 15% of
variance with the Eigen value of 5.35. The reliability alpha coefficient of internal consistency (.79) strongly
evidence that the item comprising factor 1 produce a reliable scale. Rest of two factors i.e., human relations
and industrial relations dimensions has not been considered, since their internal consistency coefficient and
percentage of variance lesser than factor 1. Multiple linear regression analysis shows that 41% of variation on
job satisfaction is explained by eight identified variable and is statistically significant at 1% level. Job security
having highest beta coefficient 0.298 and t- value of 5.861 is statistically significant at 1% level.
The main focus of the study was to identify useful variable which affects quality of work life with
limited number of statements and to measure the impact of select variables on job satisfaction. Social
innovation can be defined as new responses to pressing social demands, which affect the process of social
interactions. It is aimed at improving human wellbeing (J. Cloutier ,2003). The Stanford Social Innovation Review
(Phills et al. 2008) defines social innovation as ‘a novel solution to a social problem that is more effective,
efficient, sustainable, or just than existing solutions and for which the value created accrues primarily to
society as a whole rather than private individuals. According to Stiglitz commission it is about developing
innovative solutions and new forms of organisation and interactions to tackle social issues. The study
concludes that quality of work life in India at infant stage whereas there is a huge opportunities to adopt
social innovation in workplace development structure. In order to improve competitiveness and productivity
it is desirable to address workplace and social innovation in multiple shape namely flexible ways of
organizing, modern employment relations, external collaboration, participatory adopted changes in an
organization’s practice of managing very scientifically in European way by the Indian policy makers, and
mill owners. Finally, talents and competencies of HR play a significant role in the building of a social
innovation.
ACKNOWLEDGEMENTS
I express my deep sense of gratitude to the Chairman, University Grants Commission, New Delhi, India for
providing me financial assistance to conduct a survey on “Quality of Working Life in Uttar Pradesh”, India .
I am very much thankful to Mr. Anil Kumar Gope (Research Assistant) for his support of gathering primary
data from different sugar mills of Uttar Pradesh, India. Finally, my deepest regards to all of early writers of
QWL, because without their knowledge supportive, it is not possible to generate idea of the present research.
My hearty thanks to different organizers of the “Research Methodology Workshop” in India for imparting
me knowledge about different tools and techniques of statistics used in the present research.
REFERENCES
Baba, VV and Jamal, M (1991). Routinisation of job context and job content as related to employees quality of
working life: a study of psychiatric nurses. Journal of organizational behaviour. 12. 379-386.
Bhatia, S. K. and G. K. Valencia (1981) A Review of Research Findings on Absenteeism, Indian Journal of Industrial
Relations, 17(2), 1234.
Cartell R B (1966). The Shree test for number of factors. Multivariate Behavioral Research, 1, 254-276.
Chan, C.H. and Einstein, W.O. (1990). Quality of Work Life (QWL): What can unions do? SAM Advanced
Management Journal, 55, 17-22.
13
Chander, Subash and Singh, parampal (1983). Quality of work life in a University: An Empirical Investigation‖,
Management and Labour Studies, 18(2), 97-101.
Carlson, C (1978). General Motor’s quality of work life efforts. Personnel 55(4): 11-23.
Directorate of Sugar (2006). Revitalization of Sugar Industry, Department of Food and Public Distribution,
Ministry of Food, Consumer Affairs and Public Distribution, GOI, Krishi Bhavan, New Delhi.
Danna, K. & Griffin, R. W. (1999). Health and well-being in the workplace: A review and synthesis of the
literature. Journal of Management, 25, 357-384.
Freitas, A.L.P., Rodrigues, S.G. (2005). A availacao da confiabilidade de questionnaeio: Uma
analyse utilizando o
coefficient alpha de cronbanch.in: Simiposio de Engenharia de Producao, 12, 2005, Bauru. Proceeding bauru:
UNESP, 2005.
Field, A (2005). Discovering statistics using SPSS, 2nd edn, Sage Publication, London.
Gorden, J. R. (1987). A Diognastic Approach to Organizational Behaviour. 651-663.
Deveraja, T.S, (2009). Financial Performance of Agro-based Industries. The case study of sugar industry in
Delhi: Anmol Publications Pvt. Ltd.
Karnataka.
New
Dixon, M. and Sagas, M. (2007). The relationship between organizational support, work family conflict, and the job-life
satisfaction of university coaches. Research Quarterly for Exercise and Sport, 78, 236-247.
Guest, R.H. (1979).Quality of work life-learning from Tarry Town. Harvard Business Review. 57, 76-87.
Hackman J & Oldham G (1974). The Job Diagnostic Survey. New Haven: Yale University
Havlovic, SJ (1991). Quality of Work Life and Human Resource Outcomes, Industrial Relations, vol. 30, no. 3, pp.
469-479.
Islam, MZ & Siengthai, S (2009). “Quality of work life and organizational performance: Empirical evidence from
Dhaka Export Processing Zone‟, paper presented to ILO Conference on Regulating for Decent Work,
Geneva.
Heskett, J.L., Sasser, W.E., J.R and L.A., Schlesinger, (1997). The service profit chain. New York: The Free Press.
J. Cloutier (2003). ‘Qu’est-ce que l’innovation sociale?’, Discussion paper CRISES, Université du Québec à
Montréal (http://www.crises. uqam.ca/cahiers/ET0314.pdf).
Karrir, N. and Khurana (1996) A Quality of work life of managers in Indian industry, Journal of the Indian Academy
of Applied Psychology, 22(12), 1926.
Kalra Satish Kumar and Gosh, Sadana (1984). Quality of Work Life: A Study of Associated Factors. Indian Journal
of Social Work, XIV.3.
Kavoussi, N. (1978). The Effects of Unsatisfactory Working Condition on the Epidemology of Unauthorised
Absenteeism in an old textile factory, Journal of Human Ecology, September, 7(1), 8187.
Loscocco, KA & Roschelle, AR (1991). Influences on the quality of work and non-work life: two decades in
review. Journal of Vocational Behavior, 39(2), 182–225.
14
Mirvis, P.H. and Lawler, E.E. (1984). Accounting for the Quality of Work Life. Journal of Occupational Behavior.
5. 197-212.
Noordin, MF & Sadi, AHMS (2010). ‘Adoption of Mobile Commerce in Malaysia: An Exploratory Study on
Extension of Theory of Planned Behavior’, Business Analyst, 31(1), 115-150.
Nunnally, J.C. (1978). Psychometric Theory. New York: McGraw Hill.
Phills, J. A. J., K. Deiglmeier and D. T. Miller (2008). Rediscovering Social Innovation, Social Innovation
Stanford: Stanford Graduate School of Business, Fall.
Review,
Royuela, V, Tamayo, JL, Suriñach, J (2007). The institutional vs. the academic definition of the quality of work
life. What is the focus of the European Commission? ‟ Research Institute of Applied Economics, Working
Papers 2007/13, AQR-IREA Research Group, University of Barcelona, Geneva.
Ray Sarbapriya (2012). Reviewing Performance of Indian Sugar Industry: An Economic Analysis Food
and Quality Management Vol 3..
Science
Sinha, P & Sayeed O.B. (1980). Measuring Quality of Working Life: Development of an Inventory. Indian Journal of
Social Work, 41: 219-26.
Rice, R. W.(1985). Organizational Work and the Perceived Quality of Life towards a Conceptual Model, Academy of
Management Review, 10(2), 296-310.
Ritti, R. R.(1970). Underemployment of Engineers, Industrial Relations, 9(4), 437452.
Serey, T.T., (2006). Choosing a Robust Quality of Work Life, Business Forum, 27(2), 7-10.
Singh, J. P.(1983). QWL Experiments in India: Trials and Triumphs, Abhigyan, (Fall).
Veal, A.J (2005). Questionnaire survey in business research methods: A managerial approach, Pearson Education
Australia, Sydney.
Seashore SE (ed.) (1975). Defining and measuring the quality of working life, L.E. Davis A.B. Cherns,
quality of working life, The Free Press, New York.
The
Sadique, Z (2003). Quality of Work Life among White Collar and Blue Collar Employees.Journal of the Institute of
Bangladesh Studies, 26, 169-174.
Sirota, D.(1973). Production and Service Personnel and Job Enrichment, Work Study, 22(1), 915.
Walton, R. (1973). Quality of Work life Indicators- Prospects and Problems- A Portigal Measuring the Quality of
working life, 57-70, Ottawa.
Walton, RE (1975), Criteria for Quality of Working Life.
Wei, TT, Govindan M, Alain YC, Keng-Boon O & Seetharam A (2009). ‘What drives Malaysian m-commerce
adoption? An empirical analysis’, Industrial Management & Data Systems, 109 (3) 370 – 388.
Wyatt, T.A. and Wah, C.Y. (2001). Perceptions of QWL: A study of Singaporean Employees Development,
Research and Practice in Human Resource Management, 9(2), 59-76.
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