Development of a multi-level performance measurement model for manufacturing companies using a modified version of the fuzzy TOPSIS approach
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This paper aims to develop a comprehensive hierarchical performance measurement model. The proposed model not only determines a manufacturing company’s overall performance within its industry but also obtains its strengths and weaknesses in critical activities. It lets one to combine a company’s performance scores in seventeen critical activities with important industry-specific objectives to obtain a single overall performance score by using a 4-Point Fuzzy Scale and a modified fuzzy version of the Technique for Order Preference by Similarity to Ideal Solution approach. The calculated overall performance scores provide a ranking order among manufacturing companies within their industry. In addition, it also enables each company to compare its performance in critical activities with respect to other companies in its industry. Furthermore, the performance measurement model has the capability to determine what a company should do to improve its performance in critical activities. This paper provides an example to illustrate the application of the proposed model.
KeywordsPerformance measurement Manufacturing companies Multi-criteria decision making (MCDM) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- Banker RD, Potter G, Schroeder RG (1993) Reporting manufacturing performance measures to workers: an empirical study. J Manag Acc Res 5:33–53Google Scholar
- Banks RL, Wheelwright SC (1979) Operations versus strategy—trading tomorrow for today. Harvard Bus Rev 57(3):112–120Google Scholar
- Epstein MJ, Manzoni J (1997) The balanced scorecard and tableau de board, Translating strategy into action. Manag Account 8:28–36Google Scholar
- Fitzgerald L, Johnston R, Brignall TJ, Silvestro R, Voss C (1991) Performance measurement in service businesses. The Chartered Institute of Management Accountants, LondonGoogle Scholar
- Fry TD, Cox JF (1989) Manufacturing performance; local versus global measures. Prod Inven Manag J 30(2):52–56Google Scholar
- Hall RW (1983) Zero inventories. Dow, Jones-Irwin, HomewoodGoogle Scholar
- Hayes RH, Abernathy WJ (1980) Managing our way to economic decline. Harvard Bus Rev 62:95–101Google Scholar
- Hayes RH, Garvin DA (1982) Managing as if tomorrow mattered. Harvard Bus Rev 60(3):70–79Google Scholar
- Hayes RH, Wheelwright SC (1984) Restoring our competitive edge: competing through manufacturing. Wiley, New YorkGoogle Scholar
- Ic YT (2012) Development of a credit limit allocation model for banks using an integrated fuzzy TOPSIS and linear programming. Expert Syst Appl 39(2012):5309–5316Google Scholar
- IFAC (1998) International management accounting practice statement: management accounting concepts. International Federation of Accountants, New YorkGoogle Scholar
- Kagioglou M, Cooper R, Aouad G (2001) Performance management in construction: a conceptual framework. Constr Manag Econ 19(85):95Google Scholar
- Kaplan RS (1983) Measuring performance: a new challenge for managerial accounting research. Acc Rev 18(4):686–705Google Scholar
- Kaplan RS, Norton DP (1992) The balanced scorecard—measures that drive performance. Harvard Bus Rev 70(1):71–79Google Scholar
- Lynch RL, Cross KF (1991) Measure up – the essential guide to measuring business performance. Mandarin, LondonGoogle Scholar
- Matsui Y(2002) An empirical analysis of quality management in Japanese manufacturing companies. In: Proceedings of the seventh annual meeting of the asia-pacific decision sciences institute, APDSI, pp 1–18Google Scholar
- Melnyk SA, Davis EW, Spekman RE, Sandor J (2010) Outcome-driven supply chains. MIT Sloan Manag Rev 51(2):33–38Google Scholar
- Moullin M (2003) Defining performance measurement. Perspect Perform 2(2):3Google Scholar
- Schroeder RG, Flynn BB (2001) High performance manufacturing: global perspectives. Wiley, New YorkGoogle Scholar
- Skinner W (1974) The decline, fall and renewal of manufacturing. Indus Eng 52(5):32–38Google Scholar
- Teece DJ (2009) Dynamic capabilities and strategic management: organizing for innovation and growth. Oxford University Press, OxfordGoogle Scholar