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

Movin Sequeira (), Anders Adlemo () and Per Hilletofth ()
Additional contact information
Movin Sequeira: Jönköping University
Anders Adlemo: Jönköping University
Per Hilletofth: Jönköping University

Operations Management Research, 2023, vol. 16, issue 1, No 9, 164-191

Abstract: 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.

Keywords: Decision-making; Fuzzy-AHP; Fuzzy-TOPSIS; Manufacturing relocation; Offshoring; Reshoring (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12063-022-00284-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:opmare:v:16:y:2023:i:1:d:10.1007_s12063-022-00284-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/12063

DOI: 10.1007/s12063-022-00284-6

Access Statistics for this article

Operations Management Research is currently edited by Jan Olhager and Scott Shafer

More articles in Operations Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().