Using Fuzzy AHP and Fuzzy TOPSIS Approaches for Assessing Safety Conditions at Worksites in Construction Industry

Using Fuzzy AHP and Fuzzy TOPSIS Approaches for Assessing Safety Conditions at Worksites in Construction Industry

A. Basahel O. Taylan 

Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia.

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Providing safe workplace conditions is one of the main purposes of a safety management system (SMS) in effective construction companies. Ensuring safe workplace conditions at construction sites depends on different factors, including safety rules, management commitment, safety training, and safe behaviour. The current research aims to establish a method for identifying and evaluating the factors that impact workplace safety conditions at construction sites in Saudi Arabia. The fuzzy analytical hierarchy process (AHP) technique was used to determine and measure the qualitative factor weights affecting workplace safety to assist in the evaluation of multiple concurrent criteria. Hence, the fuzzy AHP technique was used to determine criterion weight. Alternatively, a fuzzy technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model was used to evaluate the performance of companies and rank them according to their safety performance. Based on the results and findings of the presented approaches, four companies were ranked for their overall safety performance. The findings are encouraging and can be used in the construction industry to benchmark the performance of construction companies for their application of safety rules and regulations. The approach also determines the leading companies in terms of best practices and provides information for government inspectors to investigate the priorities identified for inspection.


construction worksites, fuzzy AHP, fuzzy TOPSIS, safety behaviour, safety management, safety procedures, safety training


[1] Vinodkumar, M.N. & Bhasi, M., A study on the impact of management system certification on safety management. Safety Science, 49(3), pp. 498–507, 2011.

[2] Sawacha, E., Naoum, S. & Fong, D., Factors affecting safety performance on construction sites. International Journal of Project Management, 17(5), pp. 309–315, 1999.

[3] van der Molen, H., Koningsveld, E., Haslam, R. & Gibb, A., Ergonomics in building and construction: time for implementation. Applied Ergonomics, 36(4), pp. 387–389, 2005.

[4] Al-Refaie, A., Factors affect companies’ safety performance in Jordan using structural equation modeling. Safety Science, 57, pp. 169–178, 2013.

[5] Ai Lin Teo, E. & Yean Yng Ling, F., Developing a model to measure the effectiveness of safety management systems of construction sites. Building and Environment, 41(11), pp. 1584–1592, 2006.

[6] Goetsch, D.L., Occupational Safety and Health, 4th edn., Upper Saddle River, NJ: Prentice Hall, 2002.

[7] Jannadi, O.A. & Bu-Khamsin, M.S., Safety factors considered by industrial contractors in Saudi Arabia. Building and Environment, 37(5), pp. 539–547, 2002.

[8] Tam, C.M., Tong, T.K.L., Chiu, G.C.W. & Fung, I.W.H., Non-structural fuzzy decision support system for evaluation of construction safety management system. International Journal of Project Management, 20(4), pp. 303–313, 2002.

[9] Ismail, Z., Doostdar, S. & Harun, Z., Factors influencing the implementation of a safety management system for construction sites. Safety Science, 50(3), pp. 418–423, 2012.

[10] Zhou, Z., Goh, Y.M. & Li, Q., Overview and analysis of safety management studies in the construction industry. Safety Science, 72, pp. 337–350, 2015.

[11] Zou, P.X.W. & Sunindijo, R.Y., Skills for managing safety risk, implementing safety task, and developing positive safety climate in construction project. Automation in Construction, 34, pp. 92–100, 2013.

[12] Dağdeviren, M. &Yüksel, İ., Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management. Information Science, 178(6), pp. 1717–1733, 2008.

[13] Taylan, O., Bafail, A.O., Abdulaal, R.M.S. & Kabli, M.R., Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing, 17, pp. 105–116, 2014.

[14] Aguarón, J., Escobar, M.T. & Moreno-Jiménez, J.M., Consistency stability intervals for a judgement in AHP decision support systems. European Journal of Operational Research, 145(2), pp. 382–393, 2003.

[15] Saaty, T.L., Decision Making with Dependence and Feedback: The Analytic Network Process, Pittsburgh: RWS Publications, 2001.

[16] Saaty, T.L., Multi-Criteria Decision Making: The Analytic Hierarchy Process, Pittsburgh: RWS Publications, 1988.

[17] Kaya, T. & Kahraman, C., Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: the case of Istanbul. Energy, 35(6), pp. 2517–2527, 2010.

[18] Lee, G., Jun, K.-S. & Chung, E.-S., Integrated multi-criteria flood vulnerability approach using fuzzy TOPSIS and Delphi technique. Natural Hazards and Earth System Science, 13(5), pp. 1293–1312, 2013.

[19] Buckley, J.J., Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), pp. 233–247, 1985. 0.1016/0165-0114(85)90090-9.

[20] Chang, D., Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), pp. 649–655, 1996.

[21] Antonsen, S., Safety Culture: Theory, Method and Improvement, Farnham, UK: Ashgate Press, 2009.

[22] Noweir, M.H., Alidrisi, M.M., Al-Darrab, I.A. & Zytoon, M.A., Occupational safety and health performance of the manufacturing sector in Jeddah Industrial estate, Saudi Arabia: A 20-years follow-up study. Safety Science, 53, pp. 11–24, 2013.

[23] Zhang, N. & Wei, G., Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Applied Mathematical Modelling, 37(7), pp. 4938–4947, 2013.

[24] Torfi, F., Farahani, R.Z. & Mahdavi, I., Fuzzy MCDM for weight of object’s phrase in location routing problem. Applied Mathematical Modelling, 40(1), pp. 526–541, 2016.

[25] Hatami-Marbini, A. & Tavana, M., An extension of the Electre I method for group decision-making under a fuzzy environment. Omega, 39(4), pp. 373–386, 2011.

[26] Taylan,O., Kaya, D. & Demirbas, A., An integrated multi attribute decision model for compressor selection in petrochemical industry applying fuzzy set theory. Energy conversion & Management, Energy, 117, pp. 501–512, 2016.