Development of a new trapezoidal fuzzy AHP-TOPSIS hybrid approach for manufacturing firm performance measurement


GRANULAR COMPUTING, vol.6, no.4, pp.915-929, 2021 (Journal Indexed in ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.1007/s41066-020-00238-y
  • Title of Journal : GRANULAR COMPUTING
  • Page Numbers: pp.915-929
  • Keywords: Performance measurement, Manufacturing firms, Trapezoidal fuzzy numbers, Fuzzy analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS), OPERATIONS MANAGEMENT, DYNAMIC CAPABILITIES, MEASUREMENT MODEL, SYSTEM


This study develops a multi-level hierarchical performance measurement model to measure a manufacturing firm's overall performance score by grading its success levels in critical operations and combining them. Linking overall performance score to local grades of a manufacturing firm in critical operations requires placement of manufacturing goals in the performance measurement model. The relative importance scores of the components at any level in the multi-level performance measurement model with respect to each component belonging to the immediately above level are determined using the fuzzy analytic hierarchy process (FAHP) method. The relative importance scores of the components are combined with success grades in seventeen pre-determined critical operations to obtain overall performance scores for manufacturing firms using the technique for order preference by similarity to ideal solution (TOPSIS) approach. In this study, scorecards are developed to guide scoring in each critical operation by checking levels of success in terms of practices, infrastructures, investments and actions. The developed performance measurement approach provides a structured decision-making environment with the scorecards and fixed hierarchy. Furthermore, the developed approach is more comprehensive in representing important issues necessary for obtaining realistic overall performance scores. For example, fuzzy numbers take into account vagueness (uncertainties) in the assignment of scores. Another advantage identified by the users is that the developed decision hierarchy can be adapted to new sectors or decision environments by adding new components or removing existing ones using the same overall structure and calculation steps.