Original Article

Development and Validation of a Model for HSE Management Performance Assessment Based on the Resilience Engineering Approach (A Case Study in a Car Manufacturing Company)


The performance evaluation of HSE based on updated analytical models such as Resilience Engineering particularly in automotive industries is crucial. This research aims to develop the evaluation of the HSE management performance model and incorporate Resilience Engineering principles with the emphasis on a futuristic approach rather than a retrospective one, as well as focusing on strengths issues instead of weaknesses in an organization. This study, as a cross-sectional analysis, carried out in an automotive industry. Four Resilience components were chosen based on the Hollnagel theory as the RE contribution factors. Then, using an expert panel, the main and sub-indices of environmental health safety indices were evaluated and validated via CVI and CVR method. In the consecutive step, the validated indices were made in the format of the questionnaire and finally compiled through the analytical results of the mentioned questionnaire. According to the resilience engineering factors weight were determined that the highest impact for the safety component and the least effect on the monitoring component. In the case of health, experience has the highest impact where prediction comes with the least impact; in the environmental dimension, prediction has the highest impact and monitoring has the least effect relevant to the explanation of the structures. Overall, for HSE performance management, forecasting and monitoring in the aspect of environmental dimension have the highest effect (0/18) and the lowest effect (0/07). In the current study, the performance of HSE management in three dimensions of safety, health and environment as well as four factors including forecasting, response, experience acquisition and monitoring that are derived from data-driven theory research approach is studied in the automotive industry. Based on the analysis results, health (0/40), safety (0/37) and the environment (0/33) have the highest impact in the formation of HSE performance management, respectively. On the other hand, these dimensions cover almost all aspects of HSE (R=1) in its measurement.

1- Omidvar M, Mazloumi A, Mohammad fam I, Rahimi foroushani A, Niroumand F.: organitional safety assessment based on resilience engineerineg inccluing Fuzzy AHP for presenting a model in OiL and gas industry 1395
2- Tavana M, Zareinejad M, Di Caprio D, Kaviani MA. An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics. Applied Soft Computing.2016; 40:544-57.
3. Gunasekaran A., Bharatendra K. R., Griffin M. "Resilience and Competitiveness of small and medium size enterprises: An empirical research", International Journal of Production Research, (2011) 49 (18):5489-5509
4. Haimes YY. On the Complex Definition of Risk: A Systems-Based Approach. Risk Analysis. 2009; 29(12):1647-54.
5. Labaka L., Hernantes J., Sarriegi J.M. "A holistic framework for building Critical infrastructure resilience", Technological Forecasting & Social Change, (2016) 103:21-33
6 -ThirdProgress Report, June2007 Sidney Dekker & Erik Hollnagel Resilience Engineering: New directions for measuring and maintaining safety in complex systems)
7. Wreathall J. Properties of resilient organizations: an initial view. In: Hollande E, Woods D, Leveson N, editors. Resilience Engineering: Concepts and Precepts. Aldershot, UK: Ashgate 2006
8 - Lee A., Vargo J., Seville E. "Developing a tool to measure and compare (2013)
9. Azadeh A, Zarrin M. Evaluating the Impacts of Resilience Engineering on Health, Safety, Environment, and Ergonomics Factors by Z-Number Cognitive Map in a Large Petrochemical Plant. Safety and Health at Work.2015.
10- Borekci, D., Rofcanin, Y., & Sahin, M. Effects of organizational culture and organizational resilience over subcontractor riskiness. (2014)
11. Hollnagel E, Woods DD, Leveson N. Resilience engineering: Concepts and precepts. Surrey (UK): Ashgate; 2007.
12- Bhamra, R., Dani, S., & Burnard, K. Resilience: the concept, a literature review and future
Directions. International Journal of Production Research, (2011) 49(18), 5375-5393
13. Dijkstra A, editor Resilience engineering and safety management systems in aviation. Second Symposium of the Resilience Engineering Network; 2007; Paris: L’Ecole de Mines De
14. Shirali GA, Ebrahipour V, Mohammad salahi L. Proactive Risk Assessment to Identify Emergent Risks using Functional Resonance Analysis Method (FRAM): A Case Study in an Oil Process Unit. Iran Occupational
Health Journal. 2013; 10(6):33-46.
15. Shirali GA, Mohammadfam I, Ebrahimipour V. A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry. Reliability Engineering & System Safety. 2013; 119:88-94.
16. Carvalho PVR, dos Santos IL, Gomes JO, Borges MRS. Micro incident analysis framework to assess safety and resilience in the operation of safe critical systems: A case study in a nuclear power plant. Journal of Loss Prevention in the Process Industries. 2008; 21(3):277-86.
17. Woods DD. Four concepts for resilience and the implications for the future of resilience engineering. Reliability Engineering & System Safety. 2015; 141:5-9.
18. Vugrin ED, Warren DE, Ehlen MA. A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane. Process
Safety Progress. 2011; 30(3):280-90.
19. Jeffcott SA, Ibrahim JE, Cameron PA. Resilience in healthcare and clinical handover. Quality & safety in health care. 2009; 18(4):256-60.
20. Grecco CHS, Vidal MCR, Santos IJAL, Carvalho PVR. A method to assess safety and resilience in radiopharmaceuticals production process. Work. 2012; 41(Supplement 1):5839-43.
21. Francis R, Bekera B. A metric and frameworks for resilience analysis of engineered and infrastructure systems. Reliability Engineering & System Safety. 2014; 121:90-103.
22. Azadeh A, Salehi V, Ashjari B, Saberi M. Performance evaluation of integrated resilience engineering actors by data envelopment analysis: The case of a petrochemical plant. Process Safety and Environmental Protection. 2014; 92(3):231-41.
23- AdeL A, GhoLamzadeh R, Ghanvati M (1391), Route-structuraL modeling In management, Negah Danesh publications.
24- Hair et al, Adel A, A GhoLamzadeh R, Modeling – structuraL equations of Least squres (1395), Negah Danesh publications.
25. Chin, W. W. The partial least squares approach to structural equation modelling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). New Jersey: Lawrence Erlbaum. (1998).
26. Chin, W. W. How toWrite Up and Report PLS Analyses. In: V. Esposito Vinzi, W. Chin, J. Hensler, and H. Wold (Eds.,) Handbook of partial least squares, (pp. 655–690). (2010).
27. Cohen, J. Statistical power analysis for the behavioral sciences. Hillside, NJ: L. Erlbaum Associates. (1988).
28. Efron, B., & Tibshirani, R. J. An introduction to the bootstrap. New York: Chapman and Hall. (1993).
29. Fornell, C., & Bookstein, F. L. Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19, 440–452. (1982).
30. Haenlein, M., & Kaplan, A. M. A beginner’s guide to partial least squares analysis. Understanding Statistics, 3(4), 283–297. (2004).
31. Hair, J.F., Ringle, C.M., Sarstedt, M. PLS-SEM: Indeed, a Silver Bullet, Journal of Marketing Theory and Practice, vol. 19, no. 2, pp. 139–151. (2011).
32. Pugesek, B. H., Tomer, A., & von Eye, A. Structural Equation Modeling. Cambridge University Press. (2003).
33. Tenenhaus, M., Vinzi, V. E., Chatelinc, Y. M. and Lauro, C. PLS path modeling, Computational Statistics & Data Analysis, 48, 159 – 205. (2005).
34. Wetzels, M., Odekerken-Schroder, G., van Oppen, C., Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly 33 (1), 177e195. 2009.
35. Barroso, C., Carrion, G. C., & Roldan, J. L. Applying maximum likelihood and PLS on different sample sizes: studies on SERVQUAL model and employee behavior model. In V. Esposito Vinzi, W. Chin, J. Henseler, & H. Wang (Eds.), Handbook Partial Least Squares. Berlin: Springer. (2010).
36. Reinartz, W., Haenlein, M., Henseler, J. An empirical comparison of the efficacy of covariance-based and variance-based SEM, Intern. J. of Research in Marketing Vol. 26 PP. 332–344. (2009).
37. Tenenhaus, M. Component-based Structural Equation Modelling, Total Quality Management & Business Excellence, Volume 19, Issue 7-8, PP. 871-886. (2008).
38. Diamantopoulos, A., Riefler, P., Roth K.P. “Advancing Formative Measurement Models,” Journal of Business Research, 61 (12), 1203–1218. (2008)
39. Henseler, J., Ringle, C. M., Sinkovics, R. R.: The use of partial least squares path modeling in international marketing, in: Sinkovics, R. R., Ghauri, P. N. (eds.), Advances in International Marketing, Vol. 20, Bingley 2009, pp. 277–320.
IssueVol 12 No 4 (2020) QRcode
SectionOriginal Article(s)
Performance Evaluation Resilience Engineering Safety Health Environment HSE Automotive Industry

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How to Cite
Ahmadvand A, Arjmandi R, Mohammadi A, Mirzahosseini SA. Development and Validation of a Model for HSE Management Performance Assessment Based on the Resilience Engineering Approach (A Case Study in a Car Manufacturing Company). Int J Occup Hyg. 2020;12(4):289-309.