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. e-mail:scdas@sify.com, 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.

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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 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 LITERATUREThomas 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 co-workers. 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

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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. 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

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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:1KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .836Bartlett's Test of Sphericity Approx. Chi-Square 1.873E3

df 253Sig. .000

3. EMPIRICAL RESULTS & DISCUSSIONS3.1: 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 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

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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 2006-07 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.

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

100

200

300

400

500

600

Figure I: Indian Sugar Statistics

Production (Lakh Tonnes) 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 %)

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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 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. No.

Variable Categories No. of Employees

Percentage

1. Nature of Organization

Private 270 75Cooperative 90 25

2. Nature of Employment

Permanent 150 50Seasonal 150 50

3. Work Experience 1-5 Yrs 21 5.85-10 Yrs 60 16.710-15 Yrs 86 23.915-20 Yrs 97 26.920 and above 96 26.7

4. Monthly Income Below Rs. 10,000 139 38.610,000-20,000 177 49.220,000 and above 44 12.2

5. Education Below High school 14 3.9High school Pass 35 9.7Intermediate 51 14.2Graduation 156 43.3Post-Graduation 48 13.3Others 56 15.6

6. Age Below 30 Yrs 26 7.230-40 Yrs 88 24.440-50 Yrs 148 41.150 and above 98 27.2

7. Job Position Clerical 93 25.8Accounting 51 14.2Administration 18 5.0Managerial 27 7.5Sales and Marketing 11 3.1Technical 152 42.2Others 8 2.2

Source: Primary Data

3.3: Correlation Matrix

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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.

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Factors LF SF HF WC

WF SI SS RC

RS TR UR RT AT AR NA WS

JS PP AB PB

TS

SU

PA

Lighting Facilities (LF)

1

Safety Measures (SF)

.394** 1

Health Facilities (HF)

.121* .284**

1

Physical Working Condition (WC)

.251** .331**

.449** 1

Welfare Facilities (WF)

-.254** -.070 -.008 -.109*

1

Supervisor’s Interference (SI)

.011* -.050 -.022* -.119*

-.039 1

Supervisor’s Support (SS)

.365** .333**

.201** .239* -.120* -.119*

1

Relationship with Colleagues (RC)

.227** .152**

-.033 .086* -.160** -.052 .203**

1

Relationship with Superiors (RS)

.354** .297**

.049 .133* -.191** -.099 .265**

.254**

1

Treating Respects (TR)

.337** .263**

.075 .153**

-.139** -.007*

.152* .238**

.090 1

Union- Management Relations (UR)

.208** .369**

.080 .091* -.037 -.042 .147* .194**

.110* .285**

1

Role of Trade Union (RT)

.270** .312* .203* .234**

-.106* -.149*

.209**

.159**

.176**

.295**

.467** 1

Adequate Training (AT)

.270** .369**

.263** .199**

-..089** .016 .216**

.046

.207**

.073 .182** .259** 1

Additional Responsibility (AR)

.272** .086* .078 .066* .096* -.116*

.162 .064

.005 .085 .163** .090 .255** 1

Necessary Authority (NA)

.354** .341**

.079 .204* ..200** -.063 .303**

.110*

.212**

.220**

.177** .294** .323**. .239**

1

Work Schedule (WS)

-.094 .030**

.032 .007**

.013 .007 -.031 .017

.000 .002 -.024 -.041* .057 .003 -.023 1

Job Security .325** .42 .279** .22 -.179** -.007 .27 .05 .18 .24 .225** .326** .401** .060 .30 -.14 1

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(JS) 2** 9** 6** 5 9** 0** 4** 0*

Pay Package (PP)

.297** .442**

.220** .142**

-.148** .012 .240**

.107*

.190**

.185**

.289** .320** .344** .152**

.277**

-.053 .510**

1

Adequate Bonus (AB)

-131* -.057 .012 -.039 .020* -.009 -.049 -.026

-.050

-.092 -.063* -.153* -.113 .100 -.074 .006* -.108 -.014 1

Performance based Promotion (PB)

.262** .367**

.254** .168**

-.048* -.050 .260**

.095*

.215**

.072 .224** .313** .418** .134* .260**

.136* .366**

.455**

-.019 1

Team Spirit (TS)

.282** .265**

.087 .166**

-.163** .090 .142* .204**

.211**

.185**

.183** .224** .221** .089 .359**

-.009 .301**

.258**

-.212** .249**

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Skill Utilization (SU)

.170** .150**

.026 .100* -.094* .066 .078 .136*

.068 .089 .120* .073 .137** .186**

.038 -.058 .167**

.098 -.012 .062

.103*

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Perceived Abilities (PA)

.176** -.087 .048 .750*

-.066+ -.040 .086 .106*

.181**

.033 -.020 .080 .137** .249**

.067 .006 .093* .042 .040 .092

.136*

.192**

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

Table- 3: Correlation Matrix of Quality of Work Life

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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 CommunalitiesThe 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: 4Communalities

Factors Statements Variables Initial

Extraction

Mean

S.D

1.Workin

g Environ

ment Factor

1. The lighting facility within the mill is sufficient to work.

Lighting Facilities (LF) 1.000 .542 4.00 .910

2. The quality of safety measures adopted by the organization.

Safety Measures (SF) 1.000 .524 2.22 .908

3. The health facilities in the mill are not good.

Health Facilities (HF) 1.000 .723 2.66 1.319

4. I am not satisfied with the working condition

Physical Working

1.000 .703 2.99 1.267

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provided by the organization.

Condition (WC)

5. The quality of welfare facilities in your organization.

Welfare Facilities (WF) 1.000 .562 1.74 1.156

6. My supervisor interferes in the given work.

Supervisor’s Interference (SI)

1.000 .622 1.99 .853

2.Relatio

nal Factor

7. I receive adequate support from my supervisor.

Supervisor’s Support (SS) 1.000 .474 3.88 1.057

8.The relationship with our colleagues is good

Relationship with colleagues (RC)

1.000 .497 4.44 .736

9. The relationship with our superiors is good.

Relationship with superiors (RS)

1.000 .603 4.14 .900

10. I am not treated with respect in the organization.

Treating Respects (TS) 1.000 .528 3.64 1.230

11. How are union-management relations in your organization?

Union- Management Relations (UR)

1.000 .657 2.95 1.178

12.Trade union plays a major role to protect the workers interest.

Role of Trade Union (RT) 1.000 .570 2.81 1.228

13.I receive adequate training to do my job well.

Adequate Training (AT) 1.000 .571 3.16 1.418

3.Job

Factor

14.I am ready to take additional responsibility with my job.

Additional Responsibility (AR)

1.000 .654 3.63 1.178

15. I have necessary authority to do my job well.

Necessary Authority (NA) 1.000 .554 3.55 1.145

16.Which of the best describe your usual work schedule

Work Schedule (WS) 1.000 .816 1.37 .889

17. How satisfied are you with your overall job security?

Job Security (JS) 1.000 .615 2.36 .986

4.Financi

al Factor

18. Are you satisfied with your pay package?

Pay Package (PP) 1.000 .628 2.16 1.277

19. Do you get adequate bonus beside your salary.

Adequate Bonus (AB) 1.000 .698 1.34 .474

20. Promotion is strictly linked to performance and seniority.

Performance based Promotion (PB)

1.000 .600 2.82 1.418

5.Impact factor

21. How satisfied you are with your team spirit.

Team spirit (TS) 1.000 .511 3.97 .977

22. I am fully able to use my skill in the present

Skill Utilization

1.000 .727 4.27 .912

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position. (SU)23. I am confident of my abilities to succeed of my work.

Perceived Abilities (PA) 1.00 .716 4.44 .791

Extraction Method: Principal Component AnalysisRotation 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: 5Total Variance Explained

FACTOR

Initial Eigen Values Extraction Sums of Squared

Rotation Sums of Squared loadings

Total

% of Varian

ceCumulati

ve%Total

% of Varianc

eCumulati

ve %Total

% of Varian

ceCumulativ

e %

1 5.346 23.243 23.243 5.34

6 23.243 23.443 3.425

14.890 14.890

2 1.603 6.968 30.211 1.60

3 6.968 30.211 1.886

8.202 23.092

3 1.485 6.459 36.670 1.48

5 6.459 36.670 1.858

8.079 31.171

4 1.264 5.495 42.165 1.26

4 6.495 42.165 1.605

7.239 38.410

5 1.206 5.242 47.407 1.20

6 5.242 47.407 1.561

6.787 45.197

6 1.555 5.023 52.430 1.15

5 5.023 52.430 1.370

5.955 51.152

7 1.097 4.769 57.199 1.09

74.769 57.199 1.28

35.580 56.732

8 1.040 4.253 61.722 1.04

04.523 61.722 1.14

84.990 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

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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: 6Rotated Component Matrix

VariablesFactor

1 2 3 4 5 6 7 8

1.Lighting Facilities (LF) .315 .496 .191 .177 .098 .251 .082 -.2242.Safety Measures (SF) .584 .312 .202 .029 .205 .043 -.015 -.0133. Health Facilities (HF) .780 -.076 .022 .022 .316 -.070 -.025 .0544.Physical Working Condition (WC) .083 .147 .100 .079 .794 .120 .117 -.0285.Welfare Facilities (WF) .552 .365 .221 .002 .222 .158 -.015 .0336.Supervisor’s Interference (SI) .149 -.166 -.078 .400 -.175 .136 -.702 -.0257.Supervisor’s Support (SS) .282 .494 .028 -.007 .223 .019 .288 -.1298.Relationship with colleagues (RC) -.080 .613 .398 .154 -.084 -.028 -.046 .1529.Relationship with superiors (RS) .220 .736 -.069 .041 -.007 .066 .029 .03310.Respects .044 .202 .669 .008 .096 .130 -.053 -.09711.Union- Management Relations (UR)

.262 -.038 .755 .031 -.061 -.008 .106 .037

12.Role of Trade Union (RT) .303 .034 .607 -.013 .188 .179 .201 -.00713.Adequate Training (AT) .661 -.013 -.043 .162 .119 .225 .168 .11214.Additional Responsibility (AR) .224 -.128 .094 .418 -.111 -.016 .626 .01415.Necessary Authority (NA) .424 .204 .086 -.005 -.045 .383 .395 -.142

16.Work Schedule (WS) .035 .008 -.021 -.020 .028 .017 -.010 .90117.Job Security (JS) .655 .084 .173 .072 .196 .024 -.083 -.31418. Pay Package (PP) .739 .088 .231 -.001 .006 -.075 -.048 -.11419.Adequate Bonus (AB) .078 .013 -.085 .080 -.075 -.817 .063 -.03620.Performance based Promotion (PP)

.704 .119 .064 .002 .076 -.005 .085 .271

21. Team spirit (TS) .327 .193 .149 .145 -.033 .562 -.080 -.00922.Skill Utilization (SU) .048 .039 .139 .826 .064 -.006 -.108 -.07823.Perceived Abilities (PA) .040 .157 -.109 .812 .048 .019 .114 .045

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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).

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

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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.

Table: 7Summary of Factors of QWL

Factors (Factorial

Mean)

Variables Loadings

Eigen

value

% of Variance

Cumulative % of

Variance

Cronbach’s

alpha

1. Job and Working Environm

ent Dimensio

ns(2.641)

Safety measures (SM)

.584

5.349

14.890 14.980 .790

Health facilities (HF)

.780

Welfare facilities (WF)

.552

Adequate training (AT)

.661

Necessary authority (NA)

.424

Job security (JS)

.655

Pay package (PP)

.739

Performance based promotion (PBP)

.709

2. Human

Relations Dimensio

ns(4.115)

Lighting facilities (LF)

.496

1.603

8.202 23.092 .605Supervisory support (SS)

.494

Relationship with Colleagues (RC)

.613

Relationship with superiors (RS)

.736

3. Industrial

Treating respects (TR)

.669

Union management

.755

15

Relations Dimensio

ns(3.133)

relationships (UR)

1.485

8.079 31.171 .615

Role of trade union (RT)

.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 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.

Table: 8A Regression Model SummaryModel R R square Adjusted R Square Significanc

e F ChangeF Sig.

1 .552a .425 .411 .000 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: 8BCoefficient

Model - 1

Unstandardized

Coefficient

Standardized

Coefficient

t Sig.

CollinearityStatistics

B Std. Error

Beta Tolerance

VIF

Constant .784 .206 -- 3.813

.000

-- ---

Safety measures

.094 .071 .068 4.326

.186

.631 1.584

Health .062 .042 .064 1.46 .14 .845 1.183

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facilities 1 5Welfare facilities

.105 .072 .075 1.464

.144

.623 1.604

Adequate training

.007 .043 .008 .168 .867

.693 1.444

Necessary authority

.070 .050 .063 -1.40

1

.162

.803 1.245

Performance based Promotion

.178 .044 .200 4.055

.000

.677 1.4777

Pay package .206 .052 .208 3.984

.000

.603 1.658

Job security .382 .065 .298 5.861

.000

.635 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 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

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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.

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.

18

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 Karnataka. New Delhi: Anmol Publications Pvt. Ltd.

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.

Mirvis, P.H. and Lawler, E.E. (1984). Accounting for the Quality of Work Life. Journal of Occupational Behavior. 5. 197-212.

19

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 Review, Stanford: Stanford Graduate School of Business, Fall.

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 Science and Quality Management Vol 3..

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, The quality of working life, The Free Press, New York.

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.

20

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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