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A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

Author

Listed:
  • Movin Sequeira

    (Jönköping University)

  • Anders Adlemo

    (Jönköping University)

  • Per Hilletofth

    (Jönköping University
    University of Gävle)

Abstract

Manufacturing relocation decisions are complex because they involve combinations of location modes like offshoring or reshoring, and governance modes like insourcing or outsourcing. Furthermore, the uncertainty involved in the decision-making process makes it challenging to reach a right-shoring decision. This study presents a hybrid fuzzy-AHP-TOPSIS model to support generic relocation decisions. Industry experts were involved in a pairwise comparison of the competitive priorities’ decision criteria. A meta-synthesis of empirical studies is used to generate theoretical relocation scenarios. The presented hybrid model is used to rank the relocation scenarios in order to identify the most pertinent alternative. The resiliency of the solution is presented through a sensitivity analysis. The results indicate that the proposed hybrid model can simultaneously handle all the main relocation options involving governance modes. Based on the input data in this study, the competitive priorities criteria quality, time and cost are shown to have a strong impact, whereas the sustainability criterion has a weak impact on the choice of relocation option. The research presented in this paper contributes to the research field of manufacturing relocation by demonstrating the suitability of the hybrid fuzzy-AHP-TOPSIS model for relocation decisions and the resilience of the results. Furthermore, the research contributes to practice by providing managers with a generic relocation decision-support model that is capable of simultaneously handling and evaluating various relocation alternatives.

Suggested Citation

  • Movin Sequeira & Anders Adlemo & Per Hilletofth, 2023. "A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions," Operations Management Research, Springer, vol. 16(1), pages 164-191, March.
    • Handle: RePEc:spr:opmare:v:16:y:2023:i:1:d:10.1007_s12063-022-00284-6
    DOI: 10.1007/s12063-022-00284-6
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