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- Sequeira, Movin, et al.
(författare)
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A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions
- 2023
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Ingår i: Operations Management Research. - : Springer. - 1936-9735 .- 1936-9743. ; 16, s. 164-191
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
- Sequeira, Movin
(författare)
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Decision support for multi-criteria evaluation of manufacturing reshoring decisions
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Reshoring decisions in the manufacturing sector have received increasing attention due to their potential to improve overall quality, flexibility, or reduce risk. Contemporary events such as the pandemic and the supply crisis have made manufacturing reshoring decisions a timely and important topic to study. Particularly, the decision support deserves attention as there is limited knowledge on tools for reshoring decisions. The purpose of this study is to investigate the feasibility of decision support for reshoring decisions. The purpose is addressed through three research questions (RQ). The first question (RQ1) is “What criteria should be considered in evaluating a manufacturing reshoring decision?” and should guide companies in identifying factors in a reshoring decision. The second one (RQ2) is “How do decision-makers reason with respect to criteria in manufacturing reshoring decisions?” and describes the importance of the identified criteria that come into play during the decision. The third one (RQ3) is “How can the criteria be modeled in decision-support tools for evaluating manufacturing reshoring decisions?” and explores the feasibility of decision support. The research methods involve systematic literature review, multiple case study, modeling, and archival research. The findings show that reshoring is a multi-criteria decision with cost, quality, and delivery time criteria are considered to be more important (high weight) than sustainability criteria (low weight). The reasoning is manifested by inference rules pertaining to the important criteria. Multi-criteria decision-making techniques such as fuzzy inference, AHP, fuzzy-AHP and fuzzy-TOPSIS are feasible for evaluating manufacturing reshoring decisions. While these techniques rely on decision-makers’ ability to specify weights and rules, rule mining is used to extract rules from large datasets. This research contributes through increased knowledge regarding the criteria, reasoning, and modeling of reshoring decisions. Furthermore, the research extrapolates on the theories that are required to move forward when investigating this topic. For practitioners, this research develops tools that can be used in different stages of the decision-making process. For society, the support tools mean making rational decisions on reshoring rather than emotional or politically motivated ones.
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