Factoral influences on workers' job-satisfaction in Kolkata leather units.

Bose, Indranil ; Mudgal, R.K.

Introduction

The leather and leather products industry is one of India's oldest manufacturing industries that catered to the international market right from the middle of the nineteenth century, the demand for its products being both domestic as well as international right from the beginning. About 46 per cent of the production in the sector is exported and it ranks eighth in the list of India's top export earning industries and contributes roughly Rs. 10,000 crores per annum, i.e., about 4 per cent to export earnings. The sector accounts for 2.5 per cent of the global leather-related trade of Rs. 387,200 crores. An estimated 15 per cent of total purchase of leading global brands in footwear, garments, leather goods & accessories, in Europe, and 10 percent of global supply is outsourced from India. Therefore, the dynamics of the industry has been shaped to a large extent by export orientation from colonial times. The sector is dominated by small-scale firms although there also exists a significant number of medium and large sized firms in all segments of the industry. The industry is concentrated in several leather clusters in four or five distinct locations in the country, with each cluster containing a wide variety of enterprise forms and organizational structure. To be more specific, the major production centers of leather and leather products are located at Chennai, Ambur, Ranipet, Vaniyambadi, Trichy, Dindigul in Tamil Nadu, Kolkata in West Bengal, Kanpur and Agra in U.P., Calendar in Punjab, Delhi, Hyderabad in Andhra Pradesh, Bangalore in Karnataka and Mumbai in Maharashtra. Tamil Nadu is the biggest leather exporter (40%) of the country and its share in India's output on leather products is 70% (Report of Council of Leather Exports, CLE 2005). With the growing scope of GLP (Globalization, Liberalization and Privatization) job satisfaction of the workers has emerged as an issue of research interest as the issues of quality improvement, competency building, technology adaptation and even the environmental norms compliance are causing deeper impacts on the morale of the workers of the organized leather sector leading to the problems of job-insecurity, role ambiguity etc.

Labour Scenario in Leather Industry

The leather industry is labour intensive and is concentrated in the small and cottage industry sectors. While leather shoes and uppers are concentrated in large scale units, the sandals and chappals are produced in the household and cottage sector. The leather industry employs about 2.5 million people (www.indiastat. com/ Oct, 2009). The industry is also one with strong links with the social structure through caste and community. Thus a large number of people engaged in the industry (entrepreneurs as well as workers) are even today from traditional leatherworking castes (belonging to the lower castes in the caste hierarchy) and the Muslim community. Due to the age of the industry and its links with the social structure, the organizational structure that has emerged is a very complex one that contains within it elements of continuity with traditional structures as well as those that represent a break with them. The processes in the footwear making include last making, pattern cutting, clicking, sewing, assembling and finishing. There is no gender selectivity in child labour. Adults earn wages that are only marginally higher than what the children earn. Irrespective of the experience, skill and family size and requirements the wage payment system remains insensitive and relatively inelastic. Children contribute 20 to 40 per cent of the family income. The labour in the leather industry is defined by the caste location (www.laboubur eau.nic.in/ Nov.2009).

While market forces predominantly govern all other aspects of the industry, the labour is drawn exclusively from the most downtrodden section. As heads of 60 per cent of the households are engaged in leather work, the leather sector study establishes the incidence of child labour in leather flaying as an intergenerational phenomenon. Women are also employed in large numbers in Indian leather industry and are making important contribution to the national economy as well as to exports. Women are involved in large numbers, especially in footwear production in Athani (Karnataka), Rajasthan, Agra (UP) and Chennai, Ambur, Ranipet and Vaniambadi (Tamil Nadu). Their entry into productive work has helped considerably in improving their household situation. With the 'take off' of the footwear industry, especially in the last 20 years and the rapid rise of exports, women's employment has increased. The leather industry has been designated as a hazardous industry under the Factory Act 1948, and has a mandatory requirement of formal approvals for expansion. It has been observed that formal units expand and set up illegal units, where the bulk of women workers, especially dalit women are found. Women are not documented as 'workers' in any official records. Therefore, they are not legally entitled to any compensations or benefits. These women are recruited through contractors and are engaged in all stages of the tanning process. Their tasks are time consuming, backbreaking and the most hazardous.

West Bengal's leather industry employs over 200,000 people. As far as working conditions of West Bengal leather industries are concerned, Bata India Ltd. (BIL), Taj Leather Works (TLW) and a few other units like Khadims etc. are the exception. In addition to salubrious working conditions, BIL's workers enjoy subsidized housing, medical facilities and numerous other benefits. TLW has modern machines with devices to prevent accidents and injuries to workers. In contrast, working conditions in the tanneries and the leather manufacturing units are generally appalling and there is scant regard for workers' safety or health. However, with the shifting of large number of leather industry organizations to newly built Calcutta Leather Complex (CLC) near Bantala, which is spread over across 1100 acres of land with all modern infrastructure and technical amenities about 50000 directly employed workers and about 150000 indirectly dependent work-force are enjoying better working conditions than their counterparts working in traditional concentrations (Kashyap 1997).

Composition of work-force in both traditional and modern leather organizations are divided into following categories:

I) Regular and irregular workers under the direct company payroll.

II) Irregular work-force under the control of the contractors as well as under company payroll (but as a casual worker).

Literature Review

The term "Job-Satisfaction" has been defined by many from different perspectives. All such definitions aim to emphasize on one aspect, namely employee's expectation from the job and how well his expectations are fulfilled by the organization. This sort of need fulfilment becomes important to keep the organization march towards higher levels of progress without any friction. Bullock (1952) is of the view that 'Job-satisfaction is an attitude which results from a balancing and summation of many likes and dislikes experienced in connection with job'. Thus, the level of job satisfaction in a way rests on the facilities available in an organization, work climate and punishment and reward system that are prevalent. A more popular definition of job satisfaction, which is cited by many scholars, is by Locke (1969). According to him, job satisfaction is "a pleasurable or positive emotional state resulting from the appraisal of one's job or job-experience". Dayal and Saiyadain (1970) cited that achievement , work-life , recognition , advancement and responsibility were the top five factors. Pestonjee (1991) goes still further and opines that job-satisfaction is the summation of employee's feelings in four important areas such as job, management, social relations and personnel adjustment. Two of these areas encompass factors directly connected with the job but which are presumed to have a bearing on job-satisfaction.

Methodology

The universe of the study included all those employees who have been working in different leather units of Calcutta Leather Complex (CLC). For selection of the sample, a multi-stage approach of sampling was followed. At the first stage, a list of all the forward integrated tannery cum product making units located at CLC was prepared and of these units six specific units were selected randomly on the basis of convenient sampling. At the next stage, a list of all regular employees working in these units was prepared with the administrative staff of the units. At the third stage, the 25% of regular employees from each organization were selected in proportion to employees working in the organization. Thus a total sample of 150 regular workers (including supervisory staffs) was finally selected. The process took about four months (October 2009-January 2010) to complete. Table 1 shows the base data on the surveyed establishments.

The study is based mainly on the primary data collected from employees with the help of a well-drafted, pre-tested and structured questionnaire. Factor analysis approach has been applied on the response of 150 regular workers to identify the factors which determine employees' satisfaction in order to condense the information covered under a number of original variables into a smaller set of dimensions (factors) with minimum loss of information. To have more clarity in factor solution and reduce the inaccuracies, varimax method of rotation of factors was used. However, before applying factor analysis, the data adequacy tests for factor analysis were carried out, calculation matrix was computed and enough correlations were found for the purpose of factor analysis. The value of Kaiser-Meyer-Okin measure of sample adequacy (KMO) was calculated. Overall measure of sample adequacy has been found to be 0.780. This is supposed to be very large and significant in its own strength. It supports that the sample was good enough for factor analysis. The test value of Bertlett's Test of Sphericity has also been applied to confirm adequacy of available data for factor analysis to be carried out for the research progress.

Findings

Extracting of factors has been the foremost important task in the process of data analysis. Here the method of principal component analysis was used for the purpose of extracting factors. The number of such factors has been decided on the basis of latent root criteria, where it is assumed that eight values greater than 1. The factors having loadings 0.45 or higher (ignoring the signs) have been considered very significant while factors having loadings 0.40 or higher (ignoring signs) have been considered important and factors with loadings 0.30 or higher (ignoring signs) have been considered. The results have been obtained through Orthogonal Rotation with Varimax and all factor loadings 0.40 or higher (ignoring signs) have been retained. The factors have been restricted to eleven statements (Table 2) for rotation purposes in order to condense the available data through survey.

From the above table it has been observed that the factors like cordial relations and congenial working environment are supposed to be the most important with maximum percentage of variance (15.54%). It is to be mentioned here that nine out of thirty seven statements have been loaded under this factor. Moreover, all the nine statements have been found to be highly correlated with the factor. Table 3 reveals the factors associated with respective dimensions and statements. Moreover, these three trends have been identified under eleven sub-factors as the most influential factors towards job-satisfaction extracted together stands for 78.318.

On the basis of factorial composition of the job-satisfaction as specified in the above table, some basic findings have been derived.

1. Cordial relations & Congenial work environment has been identified as the most important factor (factor 1) among all the factors of employee satisfaction in the study, in which total nine sub-factors have been included.

2. Among the sub-factors under the factor of Cordial relations & Congenial work environment, highest factor loading (.769) has been attached with the first sub-factor, i.e. physical working condition.

3. Growth prospects has emerged as the last important factor of influence on the satisfaction of the regular workers of the leather industry.

It can be concluded from the above table that eleven factors, which have been extracted together stands for 78.32 percent of variance explained by the information contained in the fraction matrix. The percentage of variance explained by factor one to eleven are as 15.540, 13.549, 10.045, 9.035, 6.753, 5.691, 5.002, 3.688, 3.413, 3.045 , 2.538 (Table 2). To what extent, the forces / factors are responsible for determining the satisfaction level of the regular workers / employees of the surveyed leather organizations has been revealed in Table 2. This has been further segregated into respective sub-factors along with the factorial loadings (strength of emphasis) as presented in the Table 3. Not surprisingly, many sub-factors have been identified to be common in many factors due to their individual importance at multi-dimension levels. For example, S10 (Smooth interdepartmental communication flow) has been identified to be relevant to factor 1 (Cordial relations and Congenial work environment) and factor 9 (career development and internal communication). Likewise, some other sub-factors viz. S 15 (My contribution is in the line of company's mission) has the multi-dimensional relevance to factor 1 and factor 4. This list might be little longer, but the main revelation from such findings can be not so difficult to presume. It can be said that though there has been nearly forty six sub-factors related to eleven main factors of job-satisfaction dimension measurement as per the current study, yet as good as about ten sub-factors are present in more than one main factor as per the findings. Therefore, it can be said that few sub-factors are so important in influencing the main factors of job-satisfaction, their contribution can provide fundamental direction in identifying the trends of workers satisfaction as per the study.

Recommendations

From the above analysis, following general trends can be identified as the effectiveness criteria of determining job-satisfaction level among the regular workers in the leather industry in Kolkata:

* 5 "I" s (information, involvement orientation, independence, increased recognition, increased visibility) can be the most important ingredients of determining workers job-satisfaction.

* Personal growth opportunities and professional development within the organization (in terms of skill improvement etc.) are also high priority factors of job-satisfaction as per the study.

* Well defined career paths give the workers a clarity of the career vision causing higher satisfaction with the current employment.

* Work-life balance or the recognition of the social needs is another important factor of job satisfaction.

* Proper rewarding is also required for enhanced satisfaction.

References

Bullock , R.P.(1952), Social Factors Related to Job-satisfaction, Research Monograph, No.70, Ohio State University, cited in Pestonjee, D.M. (1991), Motivation and Job-satisfaction, MacMillan India Ltd., New Delhi.

Dayal, I & Saiyadain (1970), "M.S. Cross-cultural Validation of Motivation -Hygiene Theory", Indian journal of Industrial Relations, 6: 171-83

Indian Leather Sector Network Report, Sector Overview and SWOT Analysis (2000), New Delhi,

Kashyap, Subas Chandra (1997), Indian Leather Industry: Growth, Productivity and Export Performance, Purana Books, New Delhi

Locke, E .A. (1969), "What Is Job-satisfaction, Organizational Behaviour and Human Performance", cited in Pestonjee, D.M.(1991), Motivation and Job-satisfaction, Mac Millan India Ltd., New Delhi.

Pestonjee , D.M. (1991), Motivation and Job-satisfaction, MacMillan India Ltd., New Delhi.

Report of Council of Leather Exports (CLE), (2005).

Sen, Sunanda & Dasgupta, Byasdeb (2009), Unfreedom and Waged Work: Labour in India's Manufacturing Industry, Sage Publications India Pvt. Ltd, New Delhi

www.indiastat.com/ Oct, 2009

www.laboubureau.nic.in/ Nov., 2009

Indranil Bose & R.K. Mudgal

Indranil Bose is Assistant Professor, Department of Management Studies, Lal Bahadur Shastri Institute of Management and Technology, Bareilly, Uttar Pradesh, Pin-243001, E-mail : sentindranil@gmail.com. R.K.Mudgal is Registrar & Professor, Teerthanker Mahaveer University, Moradabad 244001. E-mail: registrar@tmu.ac.in Table 1 Base Data on the Researched Organizations Name of the unit Total workforce Total regular workforce including the regular (including supervisory and irregular workers staffs) as on 15th (as on 15th Jan,2010) Jan, 2010 Lup young tannery (LYT) 286 102 RahamaniaEnterprise (RE) 272 91 Agarwal Fabricators (AF) 276 106 Kolkata Leather Factory (KLF) 216 72 B N Agarwal Associates (BNA) 384 128 Leather Hut (LH) 293 101 Total 1727 600 Name of the unit Total surveyed regular workers (approx. 25% of the total regular work-force) Lup young tannery (LYT) 25 RahamaniaEnterprise (RE) 23 Agarwal Fabricators (AF) 27 Kolkata Leather Factory (KLF) 18 B N Agarwal Associates (BNA) 32 Leather Hut (LH) 25 Total 150 Table 2 Orthogonal Rotation with Varimax F1 F2 F3 F4 F5 F6 v.2.1.1 0.128 -0.11 -0.012 -0.038 0.253 -0.057 v.2.1.2 0.146 -0.039 -0.249 0.106 0.519 0.07 v.2.1.3 0.238 -0.264 0.001 0.112 0.229 -0.106 v.2.1.4 0.164 -0.068 -0.048 0.032 -- 0.074 v.2.1.1 -- -0.367 0.17 0.076 0.545 0.021 v.2..2..2 -- -0.3 0.12 0.365 0.104 0.125 v 2..2.3 0.033 -0.145 0.027 0.022 0.245 0.097 v 2..3.1 0.341 -0.108 0.206 -0.226 0.705 0.181 v 2..3.2 0.637 0.018 -0.116 -0.319 0.253 0.156 v2..3..3 0.45 -0.032 0.227 -0.236 0.188 0.1777 v 2.4.1 -- 0.048 0.015 0.119 0.038 0.252 v 2.4.2 0.003 0.12 -0.137 0.216 -0.06 0.824 v 2.4.3 -- -0.01 0.004 0.047 0.399 0.634 v 2.5.1 0.17 0.018 0.119 0.136 0.043 0.648 v 2.5.2 0.467 -0.034 -0.167 0.445 0.123 0.203 v 2.5.3 0.134 0.068 0.259 -0.048 -- 0.541 v 2.6.1 -- -0.248 0.025 -0.06 -- 0.106 v 2.6.2 0.327 -0.001 0.043 -0.022 -- -0.061 v 2.6.3 0.55 0.221 0.329 0.111 -- -0.001 v 2.6.4 0.084 -0.043 -0.149 -0.187 0.064 -0.026 v2.7.1 -- -0.248 0.11 0.087 0.685 -0.203 v .2.7.2 0.114 -0.042 -0.15 0.722 0.071 0.254 v .2.8.1 0.733 0.042 -0.025 0.073 -- 0.09 v 2.8.2 0.769 -0.13 0.226 -0.057 0.305 -0.11 v 2.8.3 0.768 0.101 -0.09 -0.068 -- -0.017 v 2.8.4 0.044 -0.018 0.885 0.186 -- -0.054 v 2.8.5 0.258 0.026 0.31 0.411 -0.12 -0.19 v 2.9.1 0.68 -0.062 -0.067 0.341 -- 0.074 v 2.9.2 0.23 -0.273 0.535 0.079 0.214 -0.016 v 2.9.3 -- 0.085 0.386 0.825 -- 0.055 v 2.9.4 0.623 0.265 -0.264 0.364 0.032 -0.001 v 2.10.1 -- 0.327 0.752 -0.277 -- 0.123 v 2.10.2 0.134 0.722 0.05 -0.364 -- 0.158 v 2.11.1 -- 0.343 0.249 0.059 -0.03 -0.33 v 2.11.2 0.182 0.912 -0.103 0.088 0.033 -0.076 v 2.11.3 -- 0.88 0.209 0.093 -- -0.001 v 2.11.4 -- 0.878 0.008 0.036 -- 0.126 Percentage 15.54 13.549 10.045 9.035 6.753 5.691 Cumulative 15.54 29.089 39.133 48.168 54.92 60.611 F7 F8 F9 F10 F11 v.2.1.1 0.8 -0.019 -0.048 0.054 0.001 v.2.1.2 0.035 0.262 0.011 0.4 0.152 v.2.1.3 -0.008 -0.101 0.269 0.703 0.153 v.2.1.4 -0.076 0.223 -.0008 0.806 -0.057 v.2.1.1 0.467 0.196 0.136 -- -0.15 v.2..2..2 -0.431 0.183 -0.344 0.195 0.218 v 2..2.3 -0.142 0.721 -0.322 0.137 -0.161 v 2..3.1 0.095 -0023 -0.027 -- -0.083 v 2..3.2 0.32 0.007 -0.051 0.237 -0.167 v2..3..3 -0.019 -0.23 0.606 0.026 0.039 v 2.4.1 0.034 0.042 0.788 0.198 0.05 v 2.4.2 0.016 0.007 0.052 0.164 -0.15 v 2.4.3 0.275 -0.151 0.13 -- 0.064 v 2.5.1 -0.052 0.106 0.433 -- 0.224 v 2.5.2 0.19 -0.001 0.069 0.136 0.323 v 2.5.3 -0.325 0.297 0.116 0.269 0.144 v 2.6.1 -0.093 0.009 0.292 -- 0.729 v 2.6.2 0.315 -0.127 -0.264 -0.197 0.712 v 2.6.3 -0.201 -0.008 -0.111 0.176 0.081 v 2.6.4 0.174 0.749 0.172 0.121 0.109 v2.7.1 0.233 0.244 0.129 0.066 -0.043 v .2.7.2 -0.025 -0.075 0.056 0.056 -0.073 v .2.8.1 -0.104 0.364 -0.176 -- 0.102 v 2.8.2 0.088 -0.105 0.184 -0.03 0.003 v 2.8.3 0.25 0.038 0.079 0.409 0.179 v 2.8.4 0.025 -0.042 0.083 -- 0.089 v 2.8.5 -0.469 -0.072 0.097 0.071 0.428 v 2.9.1 0.007 0.347 0.374 0.03 -0.065 v 2.9.2 0.093 0.401 0.352 -- 0.097 v 2.9.3 -0.064 -0.057 -0.024 -- -0.016 v 2.9.4 -0.091 -0.243 0.027 0.12 -0.151 v 2.10.1 -0.026 -0.202 -0.079 -- -0.118 v 2.10.2 -0.227 -0.058 -0.026 -- -0.08 v 2.11.1 0.593 0.22 0.194 -- 0.011 v 2.11.2 -0.062 -0.174 0.065 -- 0.001 v 2.11.3 0.174 -0.087 0.063 -0.02 0.015 v 2.11.4 -0.003 0.106 -0.07 -- -0.166 Percentage 5.002 3.688 3.413 3.045 2.538 Cumulative 65.613 69.302 72.715 75.76 78.318 Communalities v.2.1.1 0.743 v.2.1.2 0.623 v.2.1.3 0.802 v.2.1.4 0.758 v.2.1.1 0.78 v.2..2..2 0.731 v 2..2.3 0.782 v 2..3.1 0.771 v 2..3.2 0.799 v2..3..3 0.8 v 2.4.1 0.75 v 2.4.2 0.815 v 2.4.3 0.738 v 2.5.1 0.761 v 2.5.2 0.665 v 2.5.3 0.751 v 2.6.1 0.744 v 2.6.2 0.815 v 2.6.3 0.629 v 2.6.4 0.718 v2.7.1 0.79 v .2.7.2 0.646 v .2.8.1 0.745 v 2.8.2 0.821 v 2.8.3 0.826 v 2.8.4 0.841 v 2.8.5 0.804 v 2.9.1 0.86 v 2.9.2 0.785 v 2.9.3 0.871 v 2.9.4 0.767 v 2.10.1 0.909 v 2.10.2 0.795 v 2.11.1 0.816 v 2.11.2 0.933 v 2.11.3 0.906 v 2.11.4 0.851 Percentage Cumulative Note: Bold numbers show the high significance level of respective sub-factors under each factors as they are the loadings of 0.45 or over. F1 = Factor 1, F2 = Factor 2, F3 = Factor 3, F4 = Factor 4, 10 = F5 = Factor 5, F6 = Factor 6, F7 = Factor 7 , F8 = Factor 8, F9 = Factor 9, F Factor 10, F11 = Factor 11 (For dimensions under each factor, the Table-3 can be referred) . Table 3 Factors Responsible for Respective Dimensions and Strategies Factor number Factorial dimensions Sub-factors Factor 1 Cordial relations & Congenial work environment S24 S25 S23 S28 S9 S31 S19 S10 *** S15 * Factor 2 Training and Fringe benefits S35 S36 S37 S33 Factor 3 Workload and orientation S26 S32 S29 Factor 4 Valued by company and Work-life balance S30 S22 S15 * S27 ** Factor 5 Team-based task sharing and distributive corporate planning S8 S21 S5 S2 Factor 6 Scope of learning and autonomy in decision-making S12 S14 S11 S16 Factor 7 Overall company policy S1 S34 S27 ** S5 * S6 Factor 8 Adequacy of compensation S20 S7 S29* Factor 9 Career Development and internal communication S11 S10 *** S14 * Factor 10 Fair Management decision S4 S3 S25 * S2 * Factor 11 Growth prospects S17 S18 S27 ** Factor number Statements Factor 1 Working conditions are satisfactory Performance deadlines are realistic Current job is secured Fair treatment by Supervisor Commitment made by employer is fulfilled My input is important for decision making I am valued by the company Smooth inter-departmental communication flow My contribution is in the line of company's mission. Factor 2 Vacation is satisfactory Sick leave is satisfactory Satisfied with health care Ongoing training facility is adequate Factor 3 Reasonable work-load Initial training is adequate Supervisor is fair in employee treatment Factor 4 Work-related issues are effectively handled by the supervisor. Minimum internal politics My contribution is in the line of company's mission. Work-life balance is satisfactory Factor 5 Corporate communication is transparent Team-working towards shared corporate goal Quality is preferred than quantity Task-distribution is based on corporate planning Factor 6 Adequate opportunities to learn and grow Autonomy in decision making Scope of upgrading skill with the current role Adequate materials and equipments are provided Factor 7 Effective leadership Company's overall benefit package is satisfactory Work-life balance is satisfactory Quality is preferred than quantity Individual creativity is encouraged Factor 8 Salary is commensurate with the job-responsibility Every possible monetary support is provided for effective delivery Supervisor is fair in employee treatment Factor 9 Career path is clearly defined in the unit Smooth inter-departmental communication flow Autonomy in decision making Factor 10 Management does not "say one thing and do another" Management does not play favorites Performance deadlines are realistic Task-distribution is based on corporate planning Factor 11 Performance is monetarily compensated Performance is recognized by promotion Work-life balance is satisfactory *** shows smooth inter-departmental communication flow (S10) ** shows work-life balance (S27) * shows performance management practice (through S2-task distribution, S25-realistic performance deadlines, S14-autonomy in decision making, S29-Fair supervisory style, S5-quality performance, S15-company mission oriented performance) etc. Table 4 Factor Loadings of Each of the Sub-Factors and the Percentage of Variance of Each Main Factor) Factor number Percentage of Sub-factors Sub-factor variance loadings Factor 1 15.54 S24 .769 S25 .768 S23 .733 S28 .680 S9 .637 S31 .623 S19 .550 S10 .467 S15 * .450 Factor 2 13.549 S35 .912 S36 .880 S37 .878 S33 .722 Factor 3 10.040 S26 .855 S32 .752 S29 .535 Factor 4 9.035 S30 .825 S22 .722 S15 * .445 S27 ** .411 Factor 5 6.735 S8 .705 S21 .685 S5 .545 S2 .519 Factor 6 5.691 S12 .824 S14 .648 S13 .634 S16 .541 Factor 7 5.002 S1 .800 S34 .593 S27 * .469 S5 * .467 S6 .431 Factor 8 3.6888 S20 .749 S7 .721 S29 * .401 Factor 9 3.413 S11 .788 S10 .606 S14 * .433 Factor 10 3.045 S4 .806 S3 .703 S25 * .409 S2 * .400 Factor 11 2.538 S17 .729 S18 .712 S27 ** .428 *** shows smooth inter-departmental communication flow (S10) ** shows work-life balance (S27) * shows performance management practice (through S2-task distribution, S25-realistic performance deadlines, S14-autonomy in decision making, S29-Fair supervisory style, S5-quality performance, S15-company mission oriented performance) etc.