Abstract
Intense market competition, changes in demand structure and acceleration in the technological developments have led companies to offer innovative and technology driven solutions in order to have competitive advantage and to survive in the market. In this aspect, tech-centers offering technological & innovative engineering solutions, and providing customized services to the needs of the companies, have taken attentions of academicians and practitioners. In this study, a tech-center location evaluation problem having a strategic and complex structure on the success and performance of the engineering companies, is analyzed. By considering inherent uncertainties and lack of information in the multi-criteria & multi-expert based tech-center location selection problem, the fuzzy set theory as a tool of artificial intelligence is employed. In the study, one of the recently proposed fuzzy sets namely Spherical fuzzy sets are used to handle uncertainty in a better way by incorporating a larger domain. According to the best knowledge of the authors, it is the first study concentrating on tech-centers and employing an integrated interval-valued Spherical fuzzy Analytic Hierarchy Process (AHP) & MULTIMOORA methodology to solve location selection problem of a tech-center. In the study, a novel defuzzification function is also presented. In the application section, a case of a company planning to launch a tech-center is analyzed. Moreover, sensitivity analysis is applied to test the applicability and robustness of the method. The results of the proposed multi-expert Spherical fuzzy methodology are also compared with the results of AHP & MULTIMOORA methodology utilizing interval-valued intuitionistic fuzzy sets.
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“The datasets generated during and/or analysed during the current study are not publicly available due to privacy concerns and policies of the company but are available from the corresponding author on reasonable request.”
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Otay, İ. Tech-center location selection by interval-valued spherical fuzzy AHP based MULTIMOORA methodology. Soft Comput 27, 10941–10960 (2023). https://doi.org/10.1007/s00500-023-08082-3
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DOI: https://doi.org/10.1007/s00500-023-08082-3