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Application of the grey TOPSIS method to assess and select a contractor in terms of occupational safety management

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Języki publikacji
EN
Abstrakty
EN
The objective of the article is to analyze the possibility of using the gray TOPSIS method to evaluate and select a contractor due to specific criteria regarding occupational health and safety management (OHSM). The choice of contractor is a problem for the decision-maker to make decisions based on many criteria, and most often, these criteria are very diverse, both quantitative and qualitative. The gray TOPSIS method is based on the use of a measure of the relative distance from the best solution, constituting the pattern, and from the worst solution, constituting the anti-pattern, to sort the solutions, using the Grey System Theory. To evaluate and select the contractor, 12 different criteria were used, describing the key areas of OHSM for the decision-maker. The criteria and their weights were selected taking into account the nature of the work planned to be carried out by the company ordering the work. Z-10 annual reports on working conditions in a given year submitted by enterprises to the Central Statistical Office, expert assessments and occupational health and safety procedures provided by five potential contractors were used as sources of information. The research confirmed that the use of gray numbers as part of the TOPSIS method allows the ranking of potential contractors from the point of view of selected criteria and the selection of the company that best meets the assumed occupational health and safety management criteria.
Wydawca
Rocznik
Strony
93--102
Opis fizyczny
Bibliogr. 22 poz., tab.
Twórcy
autor
  • Czestochowa University of Technology, Poland
Bibliografia
  • 1. Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., Ignatius, J., 2012. A state-of the-art survey of TOPSIS applications, Expert System Applied, 39, 13051-13069, DOI: 10.016/j.eswa.2012.05.056
  • 2. Blank, V.L.G., Andersson, R., Linden, A., Nilsson, B.C., 1995. Hidden accident rates an patterns in the Swedish mining industry due to involvement of contractor workers, Safety Science, 21(1), 23-35, DOI:10.1016/0925-7535(95)00004-6
  • 3. Chai, J., Liu, J.N., Ngai, E.,W., 2013. Application of decision-making techniques in supplier selection: a systematic review of literature, Expert systems with Applications, 40(10), 3872-3885, DOI: 10.1016/j.eswa.2012.12.040
  • 4. Clarke, S., 2003. The contemporary workforce, implications for organisational safety culture, Personnel Review, 32(1), 40-57, DOI: 10.1108/ 00483480310454718
  • 5. De Boer, L., Labaro, E., Morlacchi, P., 2001. A review of methods supporting supplier selection, European Journal of Purchasing & Supply Management, 7(2), 75-89, DOI: 10.1016/S0969-7012(00)00028-9
  • 6. Deng, J.L.,1982. Control problems of grey systems, Systems & Control Letters, 1(5), 288-294, DOI: 10.1016/S0167-6911(82)80025-X
  • 7. Deng, J.L.,1982. Control problems of grey systems, Systems & Control Letters, 1(5), 288-294, DOI: 10.1016/S0167-6911(82)80025-X
  • 8. Ho, W., Xu, X., Dey, P.K., 2010. Multi-criteria decision making approaches for supplier evaluation and selection: a literature review, European Journal of Operational Research, 202(1), 16-24, DOI: 10.1016/j.ejor.2009.05.009
  • 9. Jain, V., Sangaiah, A.K., Sakhuja, S., Thoduka, N., Aggarwal, R., 2016. Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive Industry, Neural Computing and Applications, 1(1), 1-10, DOI: 10.1007/s00521-016-2533-z
  • 10. Li, G.D., Yamaguchi, D., Nagai, M., 2007. A grey-based decision- making approach to the supplier selection problem, Mathematical and Computer Modelling, 46(3), 573-581, DOI: 10.1016/j.mcm.2006.11.021
  • 11. Liu, S., Yang, Y., Forrest, J., 2016. Grey Data Analysis. Methods, Models and Applications, Springer Science+Business Media Singapore.
  • 12. Holubová, V., 2016. Integrated Safety Management Systems. Polish Journal of Management Studies, 14(1), 106-118, DOI: 10.17512/pjms.2016.14.1.10
  • 13. Hon, C.K.H., Chan, A.P.C., Wong, F.K.W., 2010. Analysis for the causes of accidents of repair, maintenance, alteration and addition works in Hong Kong, Safety Science, 7 48), 894-901, DOI: 10.1016/j.ssci.2010.03.013
  • 14. Hwang, C.L., Yoon, K., 1981. Multiple Attribute Decision Making Methods and Applications, Springer, Berlin Heidelberg.
  • 15. Klimecka-Tatar, D., Niciejewska, M., 2016. The OHS management system in the small-sized production company, Production Engineering Archives, 13(4), 49-52, DOI: 10.30657/pea.2016.13.11
  • 16. Kochan, T.A., Smith, M., Wells, J.C., Rebitzer, J.B., 1994. Human resource strategies and contingent workers: the case of safety and health in the petrochemical industry, Human Resource Management, 33(1), 55-77, DOI: 10.1002/hrm.3930330105
  • 17. Niciejewska, M., Kiriliuk, O., 2020. Occupational health and safety management in small size enterprises, with particular emphasis on hazards identification, Production Engineering Archives, 26(4), 195-201, DOI: 10.30657/pea.2020.26.34
  • 18. Opricovic, S., Tzeng, G.H., 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156, DOI: 10.1016/S0377-2217(03)00020-1
  • 19. Quinlan, M., Mayhew, C., 2000. Precarious Employment, work re-organisation and the fracturing of OHS management, [in:] Frick K., Jensen P.L., Quinlan M., Wilthagen T. (Eds.) Systematic Occupational Health and Safety Management: Perspectives on an International Development, Pergamon, Amsterdam, pp.175-198
  • 20. Salminen, S., 1995. Serious occupational accidents in the construction industry, Construction Management and Economics, 13(4), 299-306, DOI: 10.1080/01446199500000035
  • 21. Tabor, J., 2018, A grey- based Decision-making Approach to the improvement of OHS Management System, Polish Journal of Management Studies, 18(1), DOI: 10.17512/pjms.2018.18.1.29
  • 22. Woźny, A., 2020. Selected problems of managing work safety - case study, Production Engineering Archives, 26(3), 99-103, DOI: 10.30657/pea.2020.26.20
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e9a98c95-3bb5-46fe-804b-a1f94cb50f46
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