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02-05-2020 | Research Article-Systems Engineering | Issue 8/2020

Arabian Journal for Science and Engineering 8/2020

Hybrid Multicriteria Group Decision-Making Method for Offshore Location Selection Under Fuzzy Environment

Journal:
Arabian Journal for Science and Engineering > Issue 8/2020
Author:
Mehmet Şahin

Abstract

Offshoring has been commonly adopted by organizations in developed countries, which relocate their business activities to low-cost countries to achieve cost-saving, improved flexibility, and greater effectiveness. Manufacturing offshoring has been a crucial business decision impacting the performance and ultimate survival of companies. For this reason, the selection of offshore locations is a strategically important decision involving various conflicting factors, which makes it a typical multicriteria decision-making (MCDM) problem. In this study, twenty-five alternative countries are ranked according to thirty-two conflicting criteria. In this regard, the fuzzy analytic hierarchy process is used to obtain the weights of each criterion. The evaluations of three decision-makers are considered. A comparative analysis of evaluating offshore locations using five MCDM methods—preference-ranking organization method for enrichment evaluation, vise kriterijumska optimizacija i kompromisno resenje, weighted sum method, elimination and choice translating reality, and technique for order of preference by similarity to the ideal solution—is performed by using real data collected from various reliable sources. An illustrative case is implemented to validate the effectiveness of the proposed approach. The outcomes of the proposed models are compared to each other and the list of leading offshoring countries from the statistical institutions. A sensitivity analysis is performed to minimize subjectivity, as the outcome of the ranking methods heavily depends on the criteria weights. The results indicate that all the proposed methods can be utilized for the problem, and greater weight should be given to the accessibility and labor criteria groups.

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