Provide a Model for Improving Work Safety Value Using Fuzzy Performance Indicators: A Case Study of Small Scale Power Plant
Abstract
The purpose of this study is to provide a model to improve safety value, according to productivity indicators in manufacturing industries. In most studies, the cost of each damage has often been used for the calculation of the safety-related costs in the workplace, and this important issue is still neglected despite the high impact of job productivity loss due to occupational accidents. hence, on the present etude, the multi-criteria decision-making (MCDM) method has been used to present a model to improve the safety value according to the proposed solutions. The results showed that among the studied criteria, capital productivity had the most impact and holding classes and training courses for the workforce, according to the studied criteria was identified as the most appropriate solution to improve the value of safety
Keywords
References
Snashall D. Occupational health in the construction industry. Scandinavian journal of work, environment & health. 2005 1:5-10.
International Labor Organization. Safety in numbers: pointers for the global safety at work. Geneva, 2003.
International Labor Organization (ILO). Safety and health at work. Available at:
http://www.ilo.org/global/topics/safety-and-health-at-work/lang--en/index.htm.
Gardner D. Barriers to the implementation of management systems: lessons from the past. Quality Assurance. 2000,8(1):3-10.
Reason J. Managing the risks of organizational accidents. Routledge; 2016 Jan 29.
HR Z. Epidemiological evaluation of fatal occupational accidents and estimation of related human costs in Tehran.
Jørgensen K. One taxonomy for occupational accidents. A systematic description of causal relations.
Haas EJ, Yorio P. Exploring the state of health and safety management system performance measurement in mining organizations. Safety science. 2016,1;83:48-58.
Cheng MM, Humphreys KA. Managing strategic uncertainty: The diversity and use of performance measures in the balanced scorecard. Managerial Auditing Journal. 2016 Apr 4.
Tappura S, Sievänen M, Heikkilä J, Jussila A, Nenonen N. A management accounting perspective on safety. Safety science. 2015;71:151-59.
Danziger SK, Danziger S, Seefeldt KS, Shaefer HL. From welfare to a work-based safety net: An incomplete transition. Journal of Policy Analysis and Management. 2016;35(1):231-38.
Monem R, Saeidi M. The safety-related cost engineering in work environments from the management accounting approach and using modern performance measurement Systems. Management Accounting. 2016 Dec 21;9(31):11-31.
Oddone E, Imbriani M. Pleural mesothelioma: Case-report of uncommon occupational asbestos exposure in a small furniture industry. International journal of occupational medicine and environmental health. 2016 May 1;29(3):523.
Jallon R, Imbeau D, de Marcellis-Warin N. A process mapping model for calculating indirect costs of workplace accidents. Journal of safety research. 2011 Oct 1;42(5):333-44.
Rikhardsson PM, Impgaard M. Corporate cost of occupational accidents: an activity-based analysis. Accident Analysis & Prevention. 2004;36(2):173-82.
Peloza J, Falkenberg L. The role of collaboration in achieving corporate social responsibility objectives. California Management Review. 2009;51(3):95-13.
Aaltonen M, Oinonen K, Kitinoja JP, Saari J, Tynkkynen M, Virta H. Costs of occupational accidents-effects of occupational safety on company business a research and development project. Scientific. 2006 Aug 30:47.
Brief A, of Conduct C, Bribery A, Mix, P, Plagiarism C, Chart P.F, Form I, Flowchart P.C, Form P.V, Form C.A. and Agreement S.I. Corporate Social Responsibility. Issues, 2015.
Ibarrondo-Dávila MP, López-Alonso M, Rubio-Gámez MC. Managerial accounting for safety management. The case of a Spanish construction company. Safety science. 2015;79:116-25.
Gunarathne N, Samudrage D, Wijesinghe DN, Lee KH. Fostering social sustainability management through safety controls and accounting. Accounting Research Journal. 2016 Jul 4.
Christensen HB, Floyd E, Liu LY, Maffett M. The real effects of mandated information on social responsibility in financial reports: Evidence from mine-safety records. Journal of Accounting and Economics. 2017;64(2-3):284-04.
Burnett S, Vlok, P.J. A simplified numerical decision-making methodology for physical asset management decisions.South African Journal of Industrial Engineering, 2014;25(1):162-75.
Zadeh L.A. Fuzzy sets. In Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A Zadeh. 1996:394-32).
Fattahi R, Khalilzadeh M. Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety science. 2018;102:290-00.
Junior FR, Osiro L, Carpinetti LC. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing. 2014 ;21:194-209.
Hwang C.L, Yoon K. Methods for multiple attribute decision making. In multiple attribute decision making. 1981 Springer;58-191
Yoon K. A reconciliation among discrete compromise solutions. J ournal of the Operational Research Society. 1987; 38(3), 277-86.
Hwang C.L, Lai Y.J, Liu T.Y. A new approach for multiple objective decision making. Computers & operations research. 1993; 20(8):889-99.
Chen C.T. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems. 2000;114(1):1-9.
Şengül Ü, Eren M, Shiraz SE, Gezder V, Şengül AB. Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable energy. 2015 Mar 1;75:617-25.
Ervural BC, Zaim S, Demirel OF, Aydin Z, Delen D. An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews. 2018;82:1538-50.
Bilbao-Terol A, Arenas-Parra M, Cañal-Fernández V, Antomil-Ibias J. Using TOPSIS for assessing the sustainability of government bond funds. Omega. 2014 1;49:1-7.
Tavana M, Keramatpour M, Santos-Arteaga FJ, Ghorbaniane E. A fuzzy hybrid project portfolio selection method using data envelopment analysis, TOPSIS and integer programming. Expert Systems with Applications. 2015;42(22):8432-44.
Walczak D, Rutkowska A. Project rankings for participatory budget based on the fuzzy TOPSIS method. European Journal of Operational Research. 2017;260(2):706-14.
de Almeida AT, de Almeida JA, Costa AP, de Almeida-Filho AT. A new method for elicitation of criteria weights in additive models: Flexible and interactive tradeoff. European Journal of Operational Research. 2016;250(1):179-91.
Marichal J.L, Roubens, M. Determination of weights of interacting criteria from a reference set. European journal of operational Research. 2000;124(3): 641-50.
Takeda E, Yu P.L. Assessing priority weights from subsets of pairwise comparisons in multiple criteria optimization problems. European journal of operational research.1995;86(2):315-31.
Choo E.U, Schoner B, Wedley W.C. Interpretation of criteria weights in multicriteria decision making. Computers & Industrial Engineering. 1999;37(3):527-41.
Choo EU, Wedley WC. A common framework for deriving preference values from pairwise comparison matrices. Computers & Operations Research. 2004;31(6):893-08.
Kularatne FC, Mariotti M. Mark-up pricing in South African industry, Article presented at The Royal Economic. In Society Annual Conference, April 5–7, 2004, held at the University of 2004.
Hulten CR, Dean ER, Harper M. New Developments in Productivity Analysis. Vol. 63, university of Chicago press, Chicago, USA.
Denison EF. Estimates of productivity change by industry: an evaluation and an alternative. Brookings Inst Press; 1989.
Amiri M, hadinejad F. Evaluation and Analysis of Productivity Indices in Manufacturing Industries Using Primatical Technique. Productivity management.2015;9(35):7-38.
Enflo K, Kander A , Schön L. Electrification and energy productivity. Ecological Economics. 2009;68(11):2808-17.
Lee CH, Leem CS. An empirical analysis of issues and trends in manufacturing productivity through a 30-year literature review. South African Journal of Industrial Engineering. 2016;27(2):147-59.
Ratnasingam J, Ark CK, Mohamed S, Liat LC, Ramasamy G, Senin AL. An analysis of labor and capital productivity in the Malaysian timber sector. BioResources. 2017;12(1):1430-46.
Sauian MS, Kamarudin N, Rani RM. Labor productivity of services sector in Malaysia: Analysis using input-output approach. Procedia Economics and Finance. 2013;7:35-41.
Koch MJ, McGrath RG. Improving labor productivity: Human resource management policies do matter. Strategic management journal. 1996;17(5):335-54.
Du K, Lin B. International comparison of total-factor energy productivity growth: A parametric Malmquist index approach. Energy. 2017;118:481-88.
Weber CM, Yang J. Organizational learning and capital productivity in semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing. 2014;27(3):316-26.
Martínez‐Caro E, Cegarra‐Navarro JG. The impact of e‐business on capital productivity: An analysis of the UK telecommunications sector. International Journal of Operations & Production Management. 2010 Apr 27.
Zhang Q, Sun Z, Wu F, Deng X. Understanding rural restructuring in China: The impact of changes in labor and capital productivity on domestic agricultural production and trade. Journal of Rural Studies. 2016 Oct 1;47:552-62.
Raouf A. Improving capital productivity through maintenance. International Journal of Operations & Production Management. 1994 Jul 1.
Argilés-Bosch JM, Martí J, Monllau T, Garcia-Blandón J, Urgell T. Empirical analysis of the incidence of accidents in the workplace on firms’ financial performance. Safety science. 2014;70:123-32.
Yılmaz M, Kanıt R. A practical tool for estimating compulsory OHS costs of residential building construction projects in Turkey. Safety science. 2018;101:326-31.
Yılmaz M, Yıldız S, Kanıt R. İş kazalarının işgörenlere göre nedenlerinin şantiye ölçeğinde belirlenmesi. 5inci İşçi Sağlığı ve İş Güvenliği Sempozyumu. 2015:1-2.
Iranian Journal of Health, Safety and Environment e-ISSN: :2345-5535 Iran university of Medical sciences, Tehran, Iran