Technology and Health Care 23 (2015) 1–8 DOI 10.3233/THC-140866 IOS Press
1
A model of Occupational Safety and Health Management System (OSHMS) for promoting and controlling health and safety in textile industry S. Manimarana , R. Rajalakshmib and K. Bhagyalakshmia,∗ a Department
of Management of Studies, PSNA College of Engineering and Technology, Tamil Nadu, India b Department of Science and Humanities, Christian College of Engineering and Technology, Oddanchatram, India Received 9 September 2014 Accepted 19 September 2014 Abstract. BACKGROUND: The development of Occupational Safety and Health Management System in textile industry will rejuvenate the workers and energize the economy as a whole. In India, especially in Tamil Nadu, approximately 1371 textile business is running with the help of 38,461 workers under Ginning, Spinning, Weaving, Garment and Dyeing sectors. Textile industry of contributes to the growth of Indian economy but it fails to foster education and health as key components of human development and help new democracies. PURPOSE: The present work attempts to measure and develop OSHMS which reduce the hazards and risk involved in textile industry. Among all other industries textile industry is affected by enormous hazards and risk because of negligence by management and Government. It is evident that managements are not abiding by law when an accident has occurred. Managements are easily deceiving workers and least bothered about the Quality of Work Life (QWL). METHODOLOGY: A detailed analysis of factors promoting safety and health to the workers has been done by performing confirmatory factor analysis, evaluating Risk Priority Number and the framework of OHMS has been conceptualized using Structural Equation Model. The data have been collected using questionnaire and interview method. RESULT: The study finds occupation health for worker in Textile industry is affected not only by safety measure but also by technology and management. CONCLUSION: The work shows that difficulty in identifying the cause and effect of hazards, the influence of management in controlling and promoting OSHMS under various dimensions. One startling fact is existence of very low and insignificance correlation between health factors and outcome. Keywords: Occupational Safety and Health Management System, textile industry, hazards, safety, health, management, technology
∗ Corresponding author: K. Bhagyalakshmi, Department of Management Studies, PSNA College of Engineering and Technology, Dindigul 624622, Tamil Nadu, India. Tel.: +91 9585111044; E-mail: [email protected].
c 2015 – IOS Press and the authors. All rights reserved 0928-7329/15/$35.00
2
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
1. Introduction Textile industry plays a vital role in economic development. Textile industries serve as the catalysts in the process of industrialization and economic growth. Technical progress alone cannot lead to textile industrial development unless technological breakthroughs are put to occupational safety and health by management. It is the management who organizes and puts to use capital, labour and technology. The development of Occupational Safety and Health Management System in textile industry will rejuvenate the workers and energize the economy as a whole. In India, especially in Tamil Nadu approximately 1371 textile business is running with the help of 38,461 workers under Ginning, Spinning, Weaving, and Garment and Dyeing sectors. Textile industry of contributes to the growth of Indian economy but it fails to foster education and health as key components of human development and help new democracies. The present work attempts to measure and develop OSHMS which reduce the hazards and risk involved in textile industry. Among all other industries textile industry is affected by enormous hazards and risk because of negligence by management and Government. It is evident that managements are not abiding by law when an accident has occurred. Managements are easily deceiving workers and least bothered about the Quality of Work Life (QWL). 2. Theoretical framework OHS includes the task, the physical work environment, social environment within the organization, administrative system and relationship between life on and off the job [2]. Also, emphasis has been made in the humanization of work which includes the need to protect the worker from hazards to health and safety [6]. The improvement in OHS has definite potential and scope for improving productivity and overall organizational effectiveness [3,15]. QWL is associated with adequate and fair compensation, safety and healthy working conditions [18]. The favourable condition and environment of employees benefit, employees welfare and management attitudes towards operational workers as well as employees in general [16]. H1: Promoting and controlling Physical hazardous have positive influence on health intention by the management. H2: Promoting and controlling Electrical hazardous have positive influence on health intention by the management. H3: Promoting and controlling Ergonomic hazardous have positive influence on health intention by the management. H4: Promoting and controlling Physiological hazardous have positive influence on health intention by the management. Long working hours, excessive work pressure and handling demanding and unique customers in textile sector has become a take for granted phenomenon in the textile sector. There are many cases that suggest that work life balance assists in retention, productivity and the requirement of good staff [7]. Occupational Health and Safety programs can improve employee morale and organizational effectiveness [10]. Pay, benefits, supervisory style – these extrinsic determinants of management play a major role for OHS as well [17]. H5: As the health intention by the management increases so as the safety measures to control the hazards increases.
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
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Hazards Physical
Demographic Profile
Electrical Health
Safety Result
Ergonomically Management Physiological
Fig. 1. A framework of Occupational Safety and Health Management System (OSHMS).
H6: As the Safety measure adapted by management to control hazards increases so as the future OHS effectiveness and Management role. H7: As the future OHS effectiveness and Management role increases so as the health intention among managers increases. Management has direct impact on human outcomes and it significantly reduces absenteeism, minor accidents, grievances and quits [12]. It is found that employee turnover can be minimized with better OHS and management system [16]. The plan based on participative culture in OHS principles has been found to be more effective than traditionally managed plans [17]. Indian mangers on the meaning of work, the managerial communist assigned higher preferences to psychological rewards compared to monetary rewards [18].
3. Methods 3.1. Population and sample The sample for the study constitutes 465 workers from various sectors of textile industry. The field work has been carried out in the textile company of Dindigul district from January to June 2014. The sample selected for the study consists of workers who had never been aware of Occupational Safety and Health (OHS) related risk and were uneducated. 3.2. Measures The Table 1 illustrates the construct that has been used in the study which is adapted based on the field work and Risk Priority Number (RPN). The study applied Likert 5 point scale for measurement. The scale items for Safety measures were identified from the concepts defined by [14]. Management role in decision making and strategic planning for OHS control and promotion was measured [9]. The health hazards are identified and measured based on field work, the various hazards in Textile industry occupation are categorized into four key components, and the measurements under each of these hazardous
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S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
Construct [Scale Type] Physical hazards [Likert 5 point]
a
Table 1 Measurement scales Item code Item description
RPNa
PH-N1 PH-N2 PH-LHW PH-Dust
10 * 10 * 10 = 1000 7 * 8 * 7 = 392 9 * 10 * 8 = 720 10 * 10 * 9 = 900
PH-Light
I would maintain & lubricate machine to control noise I would consider inverted drive control & silencer I would recommend lifting load with backbone & arms straight I would hold proper housekeeping, Dust collector & cotton dust mask I would maintain proper lighting condition
Electrical hazards [Likert 5 point]
EH-IME EH-HV EH-IMI EH-Moi
I would avoid improper earthing & loose connection I would avoid motor high speed rotating due to high voltage I would ensure that all circuits to be enclosed in a proper circuit I would ensure proper wiring to control
10 * 7 * 9 = 630 10 * 7 * 9 = 630 9 * 10 * 8 = 720 9 * 9 * 8 = 648
Ergonomic hazards [Likert 5]
ErH-WS ErH-Str ErH-Pro
I would elevate uncomfortable work station & height I would avoid improper work & strain I would willfully impose proper working process
9 * 9 * 9 = 729 8 * 9 * 9 = 648 9 * 9 * 9 = 729
Physiological hazards [Likert 5 point]
PH-Int PH-Tar PH-Stre
I would motivate to work properly in machines/technology I would avail achievable possible target I would avoid stress in work
10 * 10 * 9 = 900 10 * 10 * 10 = 1000 9 * 9 * 9 = 729
Health Intention [Likert 5 point]
HI-1 HI-2 HI-3
Using proper silencer, dust collector & lighting condition for better health Using proper circuit & moisture for all circuits control Using proper working condition for ergonomics importance using achievable target setting & counseling for avoid of physiological hazards
Safety measures [Likert 5 point]
SM-1 SM-2 SM-3 SM-4
Identifying hazards Risk estimation Emergency preparedness Safety audit & inspection
Management role [Likert 5 point]
MR-1 MR-2 MR-3
To educate workers to get knowledge about medical rights, legal & social behavior To provide training, housekeeping & safety signs To provide access to hospital & first aid facility
10 * 10 * 9 = 900
RPN – risk priority number.
affect are adapted based on higher RPN number. The RPN is the number that evaluates the risk involved in hazards by multiplying Severity, Probability and Detect ability. RPN = Severity × Probability × Detect ability The health intention of management was derived from OHS in Textile industry dimension of the scale provided by Padmini et al., 2011. Table 2 describes how the variable within each factor in the research has been measured. 4. Validation of the measurement model The Fig. 1 shows how the variable within the factors are validated using confirmatory factor analysis and develops the Occupational Safety and Health Management System (OSHMS) model (Table 2). As stated by Bagozzi et al. [1], to guarantee convergent validity, items with factor loading s that were not significant or below 0.6 and Hatcher [11], those for which the Lagrange multiplier test suggested significant relations over a different factor to the one for which they were indicators were eliminated.
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
5
Table 2 Validation of the final measurement model: Reliability and Covergent validity Variable Physical hazards
Indicator PH-NI PH-Dust PH-Light
Factor loading 0.840∗ 0.873∗ 0.743∗
Robust T-value 12.04 16.99 19.51
CA 0.78
CR 0.74
AVE 0.87
Electrical hazards
EH-IME EH-IMI EH-Mois
0.758∗ 0.732∗ 0.760∗
18.01 19.59 20.86
0.80
0.75
0.87
Ergonomic hazard
ErH-WS ErH-Str ErH-Pro
0.780∗ 0.740∗ 0.753∗
19.03 18.27 20.29
0.67
0.43
0.57
Physiological
PH-Int PH-Tar PH-Stres
0.646∗ 0.600∗ 0.629
16.82 10.67 8.81
0.73
0.81
0.78
Health Intention
HI-1 HI-2 HI-3
0.920∗ 0.701∗ 0.629∗
12.88 14.01 12.04
0.74
0.81
0.80
Safety measures
SM-1 SM-2 SM-3 SM-4
0.646∗ 0.600∗ 0.750∗ 0.758∗
19.59 16.82 20.86 16.82
0.59
0.43
0.67
MR-1 MR-2 MR-3
0.732∗ 0.760∗ 0.740∗
19.05 19.79 18.22
0.57
0.75
0.78
Management role
S-B χ2 (94 df) = 256.41 (p < 0.01); NFI = 0.91; NNFI = 0.90; CFI = 0.95; RMSEA = 0.07 ∗ p < 0.01 AVE, Average Variance Extracted; CA, Cronbach’s α; CR, Composite reliability; RPN, Risk Priority Number = Severity x probability x detect ability.
The reliability of final measurement model is also significant and acceptable as all Cronbach α values and Composite reliability indexes are above the suggested value of 0.7 [4]. No evidence of a lack of discriminate validity is found, either applying the confidence interval criterion or the average variance extracted criterion. Nomological validity is assured as the difference between the measurement model and the theoretical model (structural model) χ2 values is not significant [11].
5. Results The structural model shown in Fig. 1, which was developed after the evaluation of psychometric properties of the measurement scale or instrument, portrays the hypotheses established and estimated. The Structural Equation Model (SEM) was used to test the hypotheses. Steenkamp and Baumgartner highlighted two main advantages of this technique. First, Structural Equation Models allow measurement error to be explicitly incorporated into models and its influence on the degree of fit to be analyzed. Second, unlike multiple regressions, relations between model variables can be studied simultaneously as several dependent variables can be considered in the same model and the same variable can be at the same time an endogenous and exogenous variable regarding the other variables in the model. Raw data screening showed evidence of non-normal distribution (Mardia’s coefficient normalized estimated = 16.5). Although other estimation methods have been developed for use when the normality
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S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
e1
.74
1
Dust
.24 e2 e3
.05 1
.67
I-Earth 1
e6
.32 1 .43
.82
.54 .63
I -isolate
Electrical
.65
.87
Health
Moisture
1
I-work .21 .77
e9
1
.54
e1 .48
. 53 .11
Strain 1
.43 Ergonomicall
.64
Station
.62
e1
.04
1
e5
e1
Physical
Light
.76
e8
.08
1 .35
e4
e7
Noise
1 1 1
Target Personal Financial
.76
.81 .91
Physiological .55
Fig. 2. OSHMS-CFS for promoting and controlling health and safety in textile industry.
assumption does not hold, the recommendation of Chou et al. and Hu et al. of correcting the statistics rather than using a different estimation model has been followed. So, robust statistics will be provided. The empirical estimates for the main effects model are shown in Fig. 2. The results indicate that the data fit our conceptual model acceptably (S-B χ2 = 295.03, p = 0.00; df = 124; RMSEA = 0.055; NNFI = 0.92; NFI = 0.90; CFI = 0.94). Modification indices do not provide any indication of misfit of the structural model, suggesting that there is no need to include any new path between constructs in the model. The result obtained shows that the health intention among managements in textile industry as a tool to control hazards and promote OHS to the workers has a positive influences on the set of variables that at as risk estimators in future OHS measures and Management role or strategic decision making – physical hazards effect on health intention by management (H1: A = 0.613; p < 0.01), electrical hazards effect on health intention (H2: A = 0.133; p < 0.01), ergonomic hazards effect on health intention (H3: A = 0.569; p < 0.01), physiological hazards effect on health intention (H4: A = 0.188; p < 0.01) and the safety measures to control the hazards that effect health intention related activities and process (H5: A = 0.213; p < 0.01). The result also shows how the health intention by the management is highly conditioned by their contribution measured by management role clarity that is providing proper working condition as a health intention by management is not only enough unless management train, educate and create awareness on hazards for effective OHS. Consequently, although health intention by management does not directly influence OHS effectiveness and Management decision, it does activate the other variables that directly influence intention to control and promote OSHMS for workers. As Fig. 2 shows, safety measures adapted by management to control hazards in textile industry influences future OHS effectiveness and management decision, both directly (H6: A = 0.304; p < 0.01) and
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
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through its influence on health intention by management (H5: A = 0.213, p < 0.01) which also has a positive effect on management role (H7: A = 0.284; p = 0.01). These results confirm that the structural model in this study is a valid model to explain the management role in OHS. The question is whether a workers demographic profile can significantly improve it or not. Focusing on two of these demographic variables of the workers, the age as a measure of physical capacity in the health process has a positive and significant impact on OHS effectiveness and management decision (H8: A = 0.611; p < 0.01) and income level of the workers is revealed as crucial to improve the explanatory power of OHS, Income not only directly and positively influences a workers consciousness to live with good health (H9: A = 0.425; p = 0.01) but it also influences the safety measures (H10: A = 622; p < 0.01). 6. Discussion The main contribution of this research lies in proposing and empirically verifying a model that integrates the influence of hazards impact on health intention, safety measures and management role for future OHS effectiveness and management strategic decision making. The indirect influence of health intention by management on future OHS effectiveness and management decision through management role highlights the central role of the health intention by management for occupational health in the textile industries, thus imparting important managerial implications. If a textile company wishes to improve the productivity of workers in addition to quality and cost reduction, it must also take great care to educate workers to get knowledge about medical rights, legal, social behaviour and include elements such as training, house-keeping, safety signs and hospital facilities that promote OHS. Furthermore, this study emphasise the importance of general management policy in the textile industry as the preceding step to growth in OHS, given the central role of management as an antecedent to health intention. The direct and positive influence of age towards obtain OHS effectiveness and management decision confirms similar results obtained in prior studies showing that a positive intention to OHS is a significant predictor of adoption. This result also highlights that management need to be able to do more than just identifying hazards with the various age groups of workers. They should target emergency preparedness and risk estimation towards the much age old workers provide companies with great feedback early in the production process and may be become supporters who will influence workers in educating OHS. 7. Conclusion Targeting OHS has an additional attraction for management. Although it is a proven fact that among other factors OHS and management effectiveness go hand in hand, meaning thereby that there exist a direct relationship between OHS and management effectiveness. Therefore, management are well able to beer cost involved in controlling hazards due to physical, electrical, ergonomic and physiological. Therefore, we can conclude that management develop complex OHS strategies in which achievement of the final objective is preceded by secondarily a set of prior objectives. This result may also have important implications in terms of prohibition of workers by management from hazards. Education and health is always important for quality of work life but in textile industries it appears to be even more so, differentiation in the health intention and management role on OHS being offered thus becomes a significant competitive instrument.
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S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19]
Bagozzi RP, Yi Y. On the evaluation of structural equation models. Journal of Academic Market Science; 1988; 16: 74-94. Beh LS, Uli, Idris K and Silong AD. An analysis of Quality of Work Life and Career-Related variables. American Journal of Applied Sciences; 2006; 12(3): 2151-2159. Buchanan DA and Boddy D. Advanced technology and the quality of work life. Journal of occupation psychology; 1982; 55: 1-11. Churchill GA. A paradigm for developing better measures of marketing constructs. Journal of Market Research; 1979; 16: 64-73. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika; 1951; 16: 297-334. Delamotte Y and Walker KF. Humanization of work and the quality of work life trends and issues. International Institute of Labour studies bulletin; 1974; 11: 3-14. Evans A and Vernon K. Work-Life Balance in Hong Kong: Case Studies. Community Business: 2007. Fisher CD, Schoenfeldt LF and Shaw JB. Human Resources Management. New Delhi: Biztantra; 2004. Hanif, Muzamil et al. (2013). Factors affecting customer satisfaction. International Research Journal of Finance and Economics, (60), 44-52. Hanlon MD and Gladstein DL. Improving the Quality of Work Life in Hospitals: A case study. Hospital Health Service Administration; 1984; 29(5): 94-107. Hatcher, R.D., Jr., Whisner, S.C., Bream, B.R., and Miller, C.F. (2004). Sediments derived from mountain chains do not always land in foredeeps. Volume 36, no.2, p. 92. Havlovic SJ. Quality of Work Life and Human Resource Outcomes. Industrial Relations; 1991; 30(3): 469-479. Newaz MK, Ali T and Akhter I. Employee perception regarding turnover decision in context of Bangladesh Banking Sector. BRAC University Journal; 2007; 4(2): 67-74. Ledford GE and Lawler EE. Quality of work life programs, coordination and productivity. Journal of Contemporary Business; 1982; 11: 93-106. Levitan and Werneke. Worker participation and productivity change: a careful assessment of the available evidence casts doubt on the viability of grafting industrial relations practices from abroad on to the U.S. scene. The monthly labour review;2000. Nazia Maklik. Role of hazards control measure in occupational health and safety in the textile industry of Pakistan; Pakistan Journal of Agricultural Science; 2010; 47(1): 72-76. Padmini DS. Unsafe work environment in garments industries. Journal of Environment Research and Development; 2012; 1(1): 23-27. Skinner SJ and Ivancevich JM. Business for the 21st Century. IRWIN: Homewood; Boston: 2008. Wyatt TA and Wah CY. Perceptions of QWL: A study of Singaporean Employees Development. Research and Practice in Human Resource Management; 2001; 9(2): 59-76.
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1
A model of Occupational Safety and Health Management System (OSHMS) for promoting and controlling health and safety in textile industry S. Manimarana , R. Rajalakshmib and K. Bhagyalakshmia,∗ a Department
of Management of Studies, PSNA College of Engineering and Technology, Tamil Nadu, India b Department of Science and Humanities, Christian College of Engineering and Technology, Oddanchatram, India Received 9 September 2014 Accepted 19 September 2014 Abstract. BACKGROUND: The development of Occupational Safety and Health Management System in textile industry will rejuvenate the workers and energize the economy as a whole. In India, especially in Tamil Nadu, approximately 1371 textile business is running with the help of 38,461 workers under Ginning, Spinning, Weaving, Garment and Dyeing sectors. Textile industry of contributes to the growth of Indian economy but it fails to foster education and health as key components of human development and help new democracies. PURPOSE: The present work attempts to measure and develop OSHMS which reduce the hazards and risk involved in textile industry. Among all other industries textile industry is affected by enormous hazards and risk because of negligence by management and Government. It is evident that managements are not abiding by law when an accident has occurred. Managements are easily deceiving workers and least bothered about the Quality of Work Life (QWL). METHODOLOGY: A detailed analysis of factors promoting safety and health to the workers has been done by performing confirmatory factor analysis, evaluating Risk Priority Number and the framework of OHMS has been conceptualized using Structural Equation Model. The data have been collected using questionnaire and interview method. RESULT: The study finds occupation health for worker in Textile industry is affected not only by safety measure but also by technology and management. CONCLUSION: The work shows that difficulty in identifying the cause and effect of hazards, the influence of management in controlling and promoting OSHMS under various dimensions. One startling fact is existence of very low and insignificance correlation between health factors and outcome. Keywords: Occupational Safety and Health Management System, textile industry, hazards, safety, health, management, technology
∗ Corresponding author: K. Bhagyalakshmi, Department of Management Studies, PSNA College of Engineering and Technology, Dindigul 624622, Tamil Nadu, India. Tel.: +91 9585111044; E-mail: [email protected].
c 2015 – IOS Press and the authors. All rights reserved 0928-7329/15/$35.00
2
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
1. Introduction Textile industry plays a vital role in economic development. Textile industries serve as the catalysts in the process of industrialization and economic growth. Technical progress alone cannot lead to textile industrial development unless technological breakthroughs are put to occupational safety and health by management. It is the management who organizes and puts to use capital, labour and technology. The development of Occupational Safety and Health Management System in textile industry will rejuvenate the workers and energize the economy as a whole. In India, especially in Tamil Nadu approximately 1371 textile business is running with the help of 38,461 workers under Ginning, Spinning, Weaving, and Garment and Dyeing sectors. Textile industry of contributes to the growth of Indian economy but it fails to foster education and health as key components of human development and help new democracies. The present work attempts to measure and develop OSHMS which reduce the hazards and risk involved in textile industry. Among all other industries textile industry is affected by enormous hazards and risk because of negligence by management and Government. It is evident that managements are not abiding by law when an accident has occurred. Managements are easily deceiving workers and least bothered about the Quality of Work Life (QWL). 2. Theoretical framework OHS includes the task, the physical work environment, social environment within the organization, administrative system and relationship between life on and off the job [2]. Also, emphasis has been made in the humanization of work which includes the need to protect the worker from hazards to health and safety [6]. The improvement in OHS has definite potential and scope for improving productivity and overall organizational effectiveness [3,15]. QWL is associated with adequate and fair compensation, safety and healthy working conditions [18]. The favourable condition and environment of employees benefit, employees welfare and management attitudes towards operational workers as well as employees in general [16]. H1: Promoting and controlling Physical hazardous have positive influence on health intention by the management. H2: Promoting and controlling Electrical hazardous have positive influence on health intention by the management. H3: Promoting and controlling Ergonomic hazardous have positive influence on health intention by the management. H4: Promoting and controlling Physiological hazardous have positive influence on health intention by the management. Long working hours, excessive work pressure and handling demanding and unique customers in textile sector has become a take for granted phenomenon in the textile sector. There are many cases that suggest that work life balance assists in retention, productivity and the requirement of good staff [7]. Occupational Health and Safety programs can improve employee morale and organizational effectiveness [10]. Pay, benefits, supervisory style – these extrinsic determinants of management play a major role for OHS as well [17]. H5: As the health intention by the management increases so as the safety measures to control the hazards increases.
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
3
Hazards Physical
Demographic Profile
Electrical Health
Safety Result
Ergonomically Management Physiological
Fig. 1. A framework of Occupational Safety and Health Management System (OSHMS).
H6: As the Safety measure adapted by management to control hazards increases so as the future OHS effectiveness and Management role. H7: As the future OHS effectiveness and Management role increases so as the health intention among managers increases. Management has direct impact on human outcomes and it significantly reduces absenteeism, minor accidents, grievances and quits [12]. It is found that employee turnover can be minimized with better OHS and management system [16]. The plan based on participative culture in OHS principles has been found to be more effective than traditionally managed plans [17]. Indian mangers on the meaning of work, the managerial communist assigned higher preferences to psychological rewards compared to monetary rewards [18].
3. Methods 3.1. Population and sample The sample for the study constitutes 465 workers from various sectors of textile industry. The field work has been carried out in the textile company of Dindigul district from January to June 2014. The sample selected for the study consists of workers who had never been aware of Occupational Safety and Health (OHS) related risk and were uneducated. 3.2. Measures The Table 1 illustrates the construct that has been used in the study which is adapted based on the field work and Risk Priority Number (RPN). The study applied Likert 5 point scale for measurement. The scale items for Safety measures were identified from the concepts defined by [14]. Management role in decision making and strategic planning for OHS control and promotion was measured [9]. The health hazards are identified and measured based on field work, the various hazards in Textile industry occupation are categorized into four key components, and the measurements under each of these hazardous
4
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
Construct [Scale Type] Physical hazards [Likert 5 point]
a
Table 1 Measurement scales Item code Item description
RPNa
PH-N1 PH-N2 PH-LHW PH-Dust
10 * 10 * 10 = 1000 7 * 8 * 7 = 392 9 * 10 * 8 = 720 10 * 10 * 9 = 900
PH-Light
I would maintain & lubricate machine to control noise I would consider inverted drive control & silencer I would recommend lifting load with backbone & arms straight I would hold proper housekeeping, Dust collector & cotton dust mask I would maintain proper lighting condition
Electrical hazards [Likert 5 point]
EH-IME EH-HV EH-IMI EH-Moi
I would avoid improper earthing & loose connection I would avoid motor high speed rotating due to high voltage I would ensure that all circuits to be enclosed in a proper circuit I would ensure proper wiring to control
10 * 7 * 9 = 630 10 * 7 * 9 = 630 9 * 10 * 8 = 720 9 * 9 * 8 = 648
Ergonomic hazards [Likert 5]
ErH-WS ErH-Str ErH-Pro
I would elevate uncomfortable work station & height I would avoid improper work & strain I would willfully impose proper working process
9 * 9 * 9 = 729 8 * 9 * 9 = 648 9 * 9 * 9 = 729
Physiological hazards [Likert 5 point]
PH-Int PH-Tar PH-Stre
I would motivate to work properly in machines/technology I would avail achievable possible target I would avoid stress in work
10 * 10 * 9 = 900 10 * 10 * 10 = 1000 9 * 9 * 9 = 729
Health Intention [Likert 5 point]
HI-1 HI-2 HI-3
Using proper silencer, dust collector & lighting condition for better health Using proper circuit & moisture for all circuits control Using proper working condition for ergonomics importance using achievable target setting & counseling for avoid of physiological hazards
Safety measures [Likert 5 point]
SM-1 SM-2 SM-3 SM-4
Identifying hazards Risk estimation Emergency preparedness Safety audit & inspection
Management role [Likert 5 point]
MR-1 MR-2 MR-3
To educate workers to get knowledge about medical rights, legal & social behavior To provide training, housekeeping & safety signs To provide access to hospital & first aid facility
10 * 10 * 9 = 900
RPN – risk priority number.
affect are adapted based on higher RPN number. The RPN is the number that evaluates the risk involved in hazards by multiplying Severity, Probability and Detect ability. RPN = Severity × Probability × Detect ability The health intention of management was derived from OHS in Textile industry dimension of the scale provided by Padmini et al., 2011. Table 2 describes how the variable within each factor in the research has been measured. 4. Validation of the measurement model The Fig. 1 shows how the variable within the factors are validated using confirmatory factor analysis and develops the Occupational Safety and Health Management System (OSHMS) model (Table 2). As stated by Bagozzi et al. [1], to guarantee convergent validity, items with factor loading s that were not significant or below 0.6 and Hatcher [11], those for which the Lagrange multiplier test suggested significant relations over a different factor to the one for which they were indicators were eliminated.
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
5
Table 2 Validation of the final measurement model: Reliability and Covergent validity Variable Physical hazards
Indicator PH-NI PH-Dust PH-Light
Factor loading 0.840∗ 0.873∗ 0.743∗
Robust T-value 12.04 16.99 19.51
CA 0.78
CR 0.74
AVE 0.87
Electrical hazards
EH-IME EH-IMI EH-Mois
0.758∗ 0.732∗ 0.760∗
18.01 19.59 20.86
0.80
0.75
0.87
Ergonomic hazard
ErH-WS ErH-Str ErH-Pro
0.780∗ 0.740∗ 0.753∗
19.03 18.27 20.29
0.67
0.43
0.57
Physiological
PH-Int PH-Tar PH-Stres
0.646∗ 0.600∗ 0.629
16.82 10.67 8.81
0.73
0.81
0.78
Health Intention
HI-1 HI-2 HI-3
0.920∗ 0.701∗ 0.629∗
12.88 14.01 12.04
0.74
0.81
0.80
Safety measures
SM-1 SM-2 SM-3 SM-4
0.646∗ 0.600∗ 0.750∗ 0.758∗
19.59 16.82 20.86 16.82
0.59
0.43
0.67
MR-1 MR-2 MR-3
0.732∗ 0.760∗ 0.740∗
19.05 19.79 18.22
0.57
0.75
0.78
Management role
S-B χ2 (94 df) = 256.41 (p < 0.01); NFI = 0.91; NNFI = 0.90; CFI = 0.95; RMSEA = 0.07 ∗ p < 0.01 AVE, Average Variance Extracted; CA, Cronbach’s α; CR, Composite reliability; RPN, Risk Priority Number = Severity x probability x detect ability.
The reliability of final measurement model is also significant and acceptable as all Cronbach α values and Composite reliability indexes are above the suggested value of 0.7 [4]. No evidence of a lack of discriminate validity is found, either applying the confidence interval criterion or the average variance extracted criterion. Nomological validity is assured as the difference between the measurement model and the theoretical model (structural model) χ2 values is not significant [11].
5. Results The structural model shown in Fig. 1, which was developed after the evaluation of psychometric properties of the measurement scale or instrument, portrays the hypotheses established and estimated. The Structural Equation Model (SEM) was used to test the hypotheses. Steenkamp and Baumgartner highlighted two main advantages of this technique. First, Structural Equation Models allow measurement error to be explicitly incorporated into models and its influence on the degree of fit to be analyzed. Second, unlike multiple regressions, relations between model variables can be studied simultaneously as several dependent variables can be considered in the same model and the same variable can be at the same time an endogenous and exogenous variable regarding the other variables in the model. Raw data screening showed evidence of non-normal distribution (Mardia’s coefficient normalized estimated = 16.5). Although other estimation methods have been developed for use when the normality
6
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
e1
.74
1
Dust
.24 e2 e3
.05 1
.67
I-Earth 1
e6
.32 1 .43
.82
.54 .63
I -isolate
Electrical
.65
.87
Health
Moisture
1
I-work .21 .77
e9
1
.54
e1 .48
. 53 .11
Strain 1
.43 Ergonomicall
.64
Station
.62
e1
.04
1
e5
e1
Physical
Light
.76
e8
.08
1 .35
e4
e7
Noise
1 1 1
Target Personal Financial
.76
.81 .91
Physiological .55
Fig. 2. OSHMS-CFS for promoting and controlling health and safety in textile industry.
assumption does not hold, the recommendation of Chou et al. and Hu et al. of correcting the statistics rather than using a different estimation model has been followed. So, robust statistics will be provided. The empirical estimates for the main effects model are shown in Fig. 2. The results indicate that the data fit our conceptual model acceptably (S-B χ2 = 295.03, p = 0.00; df = 124; RMSEA = 0.055; NNFI = 0.92; NFI = 0.90; CFI = 0.94). Modification indices do not provide any indication of misfit of the structural model, suggesting that there is no need to include any new path between constructs in the model. The result obtained shows that the health intention among managements in textile industry as a tool to control hazards and promote OHS to the workers has a positive influences on the set of variables that at as risk estimators in future OHS measures and Management role or strategic decision making – physical hazards effect on health intention by management (H1: A = 0.613; p < 0.01), electrical hazards effect on health intention (H2: A = 0.133; p < 0.01), ergonomic hazards effect on health intention (H3: A = 0.569; p < 0.01), physiological hazards effect on health intention (H4: A = 0.188; p < 0.01) and the safety measures to control the hazards that effect health intention related activities and process (H5: A = 0.213; p < 0.01). The result also shows how the health intention by the management is highly conditioned by their contribution measured by management role clarity that is providing proper working condition as a health intention by management is not only enough unless management train, educate and create awareness on hazards for effective OHS. Consequently, although health intention by management does not directly influence OHS effectiveness and Management decision, it does activate the other variables that directly influence intention to control and promote OSHMS for workers. As Fig. 2 shows, safety measures adapted by management to control hazards in textile industry influences future OHS effectiveness and management decision, both directly (H6: A = 0.304; p < 0.01) and
S. Manimaran et al. / OSHMS for promoting and controlling health and safety in textile industry
7
through its influence on health intention by management (H5: A = 0.213, p < 0.01) which also has a positive effect on management role (H7: A = 0.284; p = 0.01). These results confirm that the structural model in this study is a valid model to explain the management role in OHS. The question is whether a workers demographic profile can significantly improve it or not. Focusing on two of these demographic variables of the workers, the age as a measure of physical capacity in the health process has a positive and significant impact on OHS effectiveness and management decision (H8: A = 0.611; p < 0.01) and income level of the workers is revealed as crucial to improve the explanatory power of OHS, Income not only directly and positively influences a workers consciousness to live with good health (H9: A = 0.425; p = 0.01) but it also influences the safety measures (H10: A = 622; p < 0.01). 6. Discussion The main contribution of this research lies in proposing and empirically verifying a model that integrates the influence of hazards impact on health intention, safety measures and management role for future OHS effectiveness and management strategic decision making. The indirect influence of health intention by management on future OHS effectiveness and management decision through management role highlights the central role of the health intention by management for occupational health in the textile industries, thus imparting important managerial implications. If a textile company wishes to improve the productivity of workers in addition to quality and cost reduction, it must also take great care to educate workers to get knowledge about medical rights, legal, social behaviour and include elements such as training, house-keeping, safety signs and hospital facilities that promote OHS. Furthermore, this study emphasise the importance of general management policy in the textile industry as the preceding step to growth in OHS, given the central role of management as an antecedent to health intention. The direct and positive influence of age towards obtain OHS effectiveness and management decision confirms similar results obtained in prior studies showing that a positive intention to OHS is a significant predictor of adoption. This result also highlights that management need to be able to do more than just identifying hazards with the various age groups of workers. They should target emergency preparedness and risk estimation towards the much age old workers provide companies with great feedback early in the production process and may be become supporters who will influence workers in educating OHS. 7. Conclusion Targeting OHS has an additional attraction for management. Although it is a proven fact that among other factors OHS and management effectiveness go hand in hand, meaning thereby that there exist a direct relationship between OHS and management effectiveness. Therefore, management are well able to beer cost involved in controlling hazards due to physical, electrical, ergonomic and physiological. Therefore, we can conclude that management develop complex OHS strategies in which achievement of the final objective is preceded by secondarily a set of prior objectives. This result may also have important implications in terms of prohibition of workers by management from hazards. Education and health is always important for quality of work life but in textile industries it appears to be even more so, differentiation in the health intention and management role on OHS being offered thus becomes a significant competitive instrument.
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