STRUCTURAL EQUATION MODELING ANALYSIS USING SMART PLS TO ASSESS THE OCCUPATIONAL HEALTH AND SAFETY (OHS) FACTORS ON WORKERS’BEHAVIOR

Main Article Content

Viswanadham Silaparasetti
G.V.R. Srinivasarao
Firdouse Rahman Khan

Keywords

Construction, Occupational Health and Safety, Workers behavior, Smart PLS.

Abstract

Purpose: The study aims to examine and evaluate the impact of five Occupational Health and Safety (OHS) factors, i.e., Commitment of management, Communication, Training & Education, Health Care and Policies in predicting construction workers’ behavior in construction projects of Oman.

Design/methodology/approach: A questionnaire was designed, and data was collectedon arandom sampling basis. Two hundred and fifty-twosamples were collected, and the data was analyzed using Smart PLS -Structural Equation Modeling (SEM) technique.

Findings: The study shows thatCommitment of management, Communication, and Training &Educationplays a pivotal role in inspiring the construction workers to improve their perception towards Health and Safety behavior. These factors help in theclear-cut understanding of safety issues and aid in skills development and increase capabilities. All the factors influence the sustainable positive OHS results. 

Research limitations/Implications: The present study covers only the construction workers. Entire stakeholdersinvolved in construction project (contractors, clients, and consultants) canbe includedfor further studies. 

Social Implications: The study will help to improve the Health and Safety practices in the construction industry and expected to bring in more awareness among workers, which will inevitably bring in a culture of safe behavior. The ultimate result will be asubstantial reduction or elimination in safety-relatedincidents, which helps all the stakeholders (Contractors, Clients and Consultants).

Originality/Value: Only a very few have examined the impact of Occupational Health and Safety factors on the workers’ behavior, and usage of SmartPLS is a novel idea, and it is a first-hand study of its kind.

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References

1. Akter, S., D’Ambra, J. and Ray, P. (2011), “Trustworthiness in Health Information Services: An Assessment of a Hierarchical Model with Mediating and Moderating Effects Using Partial Least Squares (PLS),” Journal of The American Society for Information Science and Technology, Volume. 62, Issue.1, pp.100–116.

2. Comrey, A. L. (1973), “A first course in factor analysis,” Academic Press, New York, ISBN 13: 9780121835507, New York.

3. Chin, W. (1998), “The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.),” Modern Methods for Business Research, Lawrence Erlbaum Associates Publisher, Mahwah, New Jersey, pp. 295-336.

4. Chin, W., Marcolin, B.L., and Newsted, P.R. (2003), “A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo simulation study and an electronic mail emotion/adoption study,” Information Systems Research, Volume. 14, Issue. 2, pp. 189-217.

5. Fornell, C. and J. Cha (1994), “Partial Least Squares,” Advanced Methods of MarketingResearch, R. P. Bagozzi (ed.), Oxford, Basil Blackwell Ltd, pp. 52-78.

6. Efron, B., and Tibshirani, R.J. (1993), “An introduction to the bootstrap,” New York:Chapman Hall. ISBN-13: 978-0412042317.

7. Fornell, C. and Larcker, D. F. (1981), “Evaluating structural equitation models withunobservable variables and measurement errors,” Journal of Marketing Research, Volume.18, Issue. 1, pp. 39–50.

8. Gilkey, D.P., Puerto, C.L.D., Keefe, T., Bigelow, P., Herron, R., Rosecrance, J. and Chen, P. (2012), “Comparative Analysis of Safety Culture Perceptions among Home Safe Managers and Workers in Residential Construction,” Journal of construction engineering and management, Volume. 138, Issue. 9, pp. 1044-1052 available at http://doi.org/10.1061/(ASCE)CO.1943-7862.0000519

9. Ganah, A. and John, G.A. (2015), “Integrating Building Information Modelling and Health and Safety for Onsite Construction,” Safety and Health at Work, Volume. 6, Issue. 1, pp. 39-45.

10. Gefen, D., Straub, D., and Boudreau, M. (2000), “Structural equation modeling techniques and regression: Guidelines for research practice,” Communications of the Association for Information Systems, Volume. 7, Issue. 7, pp. 1–78.

11. Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R.E. (2010), “Multivariate data analysis,”7th ED., Pearson, ISBN-10-0138132631, Upper Saddle River, NJ.

12. Hair, J.F., Sarstedt, M., Ringle, C.M., and Mena, J.A. (2011), “An assessment of the use of partial least squares structural equation modeling in marketing research,” Journal of the Academy of Marketing Science, Volume. 40, Issue. 3, pp. 414–433, available athttp://dx.doi.org/10.1007/s11747-011-0261-6

13. Hamid, A.R.A., Majid, M.A. and Singh, B. (2008), “Causes of accidents at construction sites,” Malaysian Journal of Civil Engineering, Volume. 20, Issue. 2, pp. 242-259.

14. Hecker, S. and Goldenhar, L. (2013), “Understanding Safety Culture and Safety Climate in Construction: Existing Evidence and a Path Forward,” Literature Review Summary for Safety Culture/Climate Workshop June 11-12, 2013 Washington, DC. pp. 1-210.

15. Henderson, D., Sheetz, S.D., and Trinkle, B. S. (2012), “The determinants of inter-organizational and internal in-house adoption of XBRL: A structural equation model,” International Journal of Accounting Information Systems,Volume. 13, Issue. 2, pp. 109–140, available athttp://dx.doi.org/10.1016/j.accinf.2012.02.001

16. Hinze, J.M., Matthew, H.A.M. and Baud, K. (2013), “Construction-Safety Best Practices and Relationships to Safety Performance,”Journal of construction engineering and management, Volume. 139, Issue. 10, pp. 1-8.

17. Hulland, J. (1999), “Use of partial least squares (PLS) in strategic management research: A review of four recent,” Strategic Management Journal,
Volume. 20, Issue. 2, pp. 195-204.

18. Jin, R. and Chen, Q. (2013), “Safety culture Effects of Environment, Behavior & Person,” Professional Safety, pp. 60-70. www.asse.org

19. Kim, H., Lee, H., Park, M., and Choi, B. (2013), "Automated Information Retrieval for Hazard Identification in Construction Sites," Proceedings of the ASCE International Workshop on Computing in Civil Engineering. Los Angeles, CA, pp.897-904.

20. Lay, A.M., Saunders, R., Lifshen, M., Breslin, F.C., Lamontagne, A.D., Tompa, E. and Smith, P.M. (2017), “The relationship between occupational health and safety vulnerability and workplace injury,” Safety Science, Volume. 94, pp. 85–93.https://doi.org/10.1016/j.ssci.2016.12.021

21. Lee, C. K.,and Jaafar, Y. (2012), “Prioritization of Factors Influencing Safety Performance on Construction Sites: A Study Based on Grade Seven (G7) Main Contractors,” Perspective, Volume. 57, Issue. 2, pp. 6-12, available http://doi.org/10.7763/IPEDR.2012.V57.2

22. Lee, Y.J. and Lee, D. (2015), “Factors Influencing Learning Satisfaction of Migrant Workers in Korea with E-Learning-Based Occupational Safety and Health Education,” Safety and Health at Work, Volume. 6, Issue. 3, pp. 211-217.

23. Litwin, M. S. (1995), “How to measure survey reliability and validity,” Sage, Thousand Oaks, CA.ISBN-0-8039-5704-1.

24. Materna, B.L., Harrington, D., Scholz, P., Payne, S.F., Stubbs, H.A., Hipkins, K., Merideth, E., Kisech, L., Lomax, G., Coyle, P. and Uratsu, C. (2002), “Results of an intervention to improve lead safety among painting contractors and their employees”,American journal of industrial medicine, Volume.41, Issue. 2, pp. 119-130.http://do.org/10.1002/ajim.10034

25. Nordlof, H., Wiitavaara, B., Winblad, U., Wijk, K., and Westerling, R. (2015), “Safety culture and reasons for risk-taking at a large steel manufacturing company: Investigating the worker perspective,” Safety Science, Volume. 73, pp. 126–135.https://doi.org/10.1016/j.ssci.2014.11.020

26. Priyadarshani, K., Karunasena, G. and Jayasuriya, S. (2013), “Construction Safety Assessment Framework for Developing Countries: A Case Study of Sri Lanka,” Journal of Construction in Developing Countries, Volume.18, Issue.1, pp. 33–51.

27. Puerto, C.L.D.,and Gilkey, D.(2014), “Injuries Among Construction Workers: An Exploratory Study,”50th ASC Annual International Conference Proceedings,Blacksburg, Virginia March 26-28, 2014, pp. 1-8.

28. Ringle, C.M., Wende, S. and Becker, J.M. (2015). SmartPLS 3. Bönningstedt: SmartPLS, Available at http://www.smartpls.com

29. Sawacha, E. (1999), “Factors affecting safety performance on construction sites,” International Journal of Project Management, Volume. 17, Issue.5, pp. 309-315.

30. Shikdar, A.A., and Sawaqed, N.M. (2003), “Worker productivity and occupational health and safety issues in selected industries,” Computers & Industrial Engineering, Volume.45, Issue. 4, pp. 563-572.

31. Silaparasetti, V., Srinivasarao, G.V.R. and Khan, F.R. (2017), “Social Entrepreneurship: Impact of Occupational Health and Safety (OHS) Factors on Workers’ Behavior in Construction Sectors in Oman,” International Journal of Management, Innovation & Entrepreneurial Research, Volume. 3, Issue. 1, pp. 12-22, available athttps://doi.org/10.18510/ijmier.2017.312

32. Tenenhaus, M., Vinzi, V.E., Chatelin, Y.M., and Lauro, C. (2005), “PLS path modeling Computational Statistics and Data Analysis,” Volume. 48, issue. 1, pp. 159-205.

33. U.S. Bureau of Labor Statistics (2016),"National Census of Fatal Occupational Injury in 2015,”U.S. Department of Labor, USDL-16-2304 pp. 1-11 available athttps://www.bls.gov/news.release/pdf/cfoi.pdf

34. Wamuziri, S. (2008), “Improving safety performance in construction through cultural change,” 24th Annual ARCOM Conference, 1-3 September 2008, Cardiff, UK, Association of Researchers in Construction Management, pp. 1103-111.