Optimizing Location Selection for Foreign Trade Intelligence Centres Using Spherical Fuzzy Methods

Abstract

This investigation focuses on a vital research topic that has significant research gaps in the literature, such as the selection of locations for foreign trade intelligence centres, which have a critical role in a country's development, a country's development and export capabilities. Previous studies have primarily addressed site selection in the context of manufacturing industries and retail outlets, focusing on strategies, and often ignored the unique requirements of foreign trade intelligence operations. This study solves the problem by considering the requirements of an innovative and integrated decision-making approach developed in the context of foreign trade intelligence centres, while at the same time filling the relevant research gap. The proposed model provides a mathematical form by extending Delphi management with spherical fuzzy sets to highlight influential evaluation criteria, as well as providing an integrated decision-making model extended with spherical fuzzy numbers to assess alternatives and determine rankings. Ten primary evaluation criteria are established to present a set of criteria for the authorities. The importance level of the criteria and assessments of alternatives for these criteria are aggregated spherical fuzzy numbers. A mixed integer non-linear multi-objective mathematical model is developed for the previous stages' outputs and different parameters. The results of the empirical application in Turkey show that Mersin is the most suitable alternative due to its attractive government incentives and strong commercial vitality compared to other options. The robustness checks verified the model's validity and reliability, proving a consistent decision-making tool for decision-makers and policymakers in the context of systematic decision-making.