Offshoring Location Decision in Fuzzy Environment
Offshoring location selection is a crucial decision for firms in terms of competitiveness, flexibility, productivity, and profitability. Determining an efficient and appropriate location for offshoring has been a substantial multicriteria decision-making (MCDM) problem. Considering that the outcome...
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| Language: | English |
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Kyrgyz Turkish Manas University
2024-06-01
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| Series: | MANAS: Journal of Engineering |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/3413896 |
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| author | Mehmet Şahin |
| author_facet | Mehmet Şahin |
| author_sort | Mehmet Şahin |
| collection | DOAJ |
| description | Offshoring location selection is a crucial decision for firms in terms of competitiveness, flexibility, productivity, and profitability. Determining an efficient and appropriate location for offshoring has been a substantial multicriteria decision-making (MCDM) problem. Considering that the outcome of an MCDM method alone can be misleading, a novel hybrid approach is presented in this study. Thus, five MCDM methods are utilized to solve the problem, and the results of four MCDM methods are integrated to assure an optimal offshoring location. A Fuzzy-AHP (analytical hierarchy process) integrated with the technique for order preference by similarity to ideal solution (TOPSIS), additive ratio assessment (ARAS), elimination et choix traduisant la realité (ELECTRE), and weighted sum method (WSM) methodology is proposed for the appraisal and selection of the optimal offshoring location. In this context, fifteen alternative locations are determined based on the attractiveness of the locations in terms of offshoring. Fuzzy-AHP is implemented to analyze the problem's structure and find the weights of the quantitative and qualitative criteria. Consistency tests are implemented to assess the quality of inputs of an expert. Then, TOPSIS, WSM, ARAS, and ELECTRE are used to evaluate and rank the candidate locations and present a comparative analysis. By considering fifteen countries and using real data, offshoring location selection is conducted through the proposed methodology. Moreover, sensitivity analysis is made to diminish the subjectivity and assess the robustness of the techniques. The results demonstrated that giving more weights to the labor characteristics and proximity to market criteria might improve the quality of the best offshoring country index. |
| format | Article |
| id | doaj-art-c7b024bf8a8f46d087cf33d7cc3dd84b |
| institution | Kabale University |
| issn | 1694-7398 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Kyrgyz Turkish Manas University |
| record_format | Article |
| series | MANAS: Journal of Engineering |
| spelling | doaj-art-c7b024bf8a8f46d087cf33d7cc3dd84b2025-02-03T11:47:34ZengKyrgyz Turkish Manas UniversityMANAS: Journal of Engineering1694-73982024-06-011218810310.51354/mjen.13617361437Offshoring Location Decision in Fuzzy EnvironmentMehmet Şahin0https://orcid.org/0000-0001-7078-7396ISKENDERUN TECHNICAL UNIVERSITYOffshoring location selection is a crucial decision for firms in terms of competitiveness, flexibility, productivity, and profitability. Determining an efficient and appropriate location for offshoring has been a substantial multicriteria decision-making (MCDM) problem. Considering that the outcome of an MCDM method alone can be misleading, a novel hybrid approach is presented in this study. Thus, five MCDM methods are utilized to solve the problem, and the results of four MCDM methods are integrated to assure an optimal offshoring location. A Fuzzy-AHP (analytical hierarchy process) integrated with the technique for order preference by similarity to ideal solution (TOPSIS), additive ratio assessment (ARAS), elimination et choix traduisant la realité (ELECTRE), and weighted sum method (WSM) methodology is proposed for the appraisal and selection of the optimal offshoring location. In this context, fifteen alternative locations are determined based on the attractiveness of the locations in terms of offshoring. Fuzzy-AHP is implemented to analyze the problem's structure and find the weights of the quantitative and qualitative criteria. Consistency tests are implemented to assess the quality of inputs of an expert. Then, TOPSIS, WSM, ARAS, and ELECTRE are used to evaluate and rank the candidate locations and present a comparative analysis. By considering fifteen countries and using real data, offshoring location selection is conducted through the proposed methodology. Moreover, sensitivity analysis is made to diminish the subjectivity and assess the robustness of the techniques. The results demonstrated that giving more weights to the labor characteristics and proximity to market criteria might improve the quality of the best offshoring country index.https://dergipark.org.tr/tr/download/article-file/3413896offshoringdecision makingfuzzy-ahplocation selectioncomparative analysis. |
| spellingShingle | Mehmet Şahin Offshoring Location Decision in Fuzzy Environment MANAS: Journal of Engineering offshoring decision making fuzzy-ahp location selection comparative analysis. |
| title | Offshoring Location Decision in Fuzzy Environment |
| title_full | Offshoring Location Decision in Fuzzy Environment |
| title_fullStr | Offshoring Location Decision in Fuzzy Environment |
| title_full_unstemmed | Offshoring Location Decision in Fuzzy Environment |
| title_short | Offshoring Location Decision in Fuzzy Environment |
| title_sort | offshoring location decision in fuzzy environment |
| topic | offshoring decision making fuzzy-ahp location selection comparative analysis. |
| url | https://dergipark.org.tr/tr/download/article-file/3413896 |
| work_keys_str_mv | AT mehmetsahin offshoringlocationdecisioninfuzzyenvironment |