A Decision Support System for Strategic Business Location Selection Using the TOPSIS Method

Abstract

The rapid growth of urbanization and business competition has increased the complexity of strategic business location selection, which involves multiple and often conflicting criteria such as cost, accessibility, market potential, and infrastructure availability. Traditional decision-making approaches are frequently subjective and lack systematic evaluation, leading to inconsistent and suboptimal location choices. To address this problem, this research is motivated by the need for an objective, transparent, and computationally efficient decision-making tool that can support practitioners, particularly small and medium-sized enterprises, in selecting optimal business locations. This study proposes a Decision Support System based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate and rank alternative business locations using both benefit and cost criteria. The main contribution of this research lies in the integration of a well-established multi-criteria decision-making method into a practical, web-based system that emphasizes usability, interpretability, and real-world applicability. The proposed system was evaluated through a case study involving multiple candidate locations, and the results demonstrate that the system is able to generate consistent and logical rankings aligned with expert judgment. Sensitivity analysis further confirms the robustness of the decision outcomes with respect to variations in criteria weights. Future work will focus on enhancing the proposed system by incorporating uncertainty-handling techniques, spatial analysis, and intelligent learning mechanisms to further improve decision accuracy and adaptability in dynamic business environments.