Retail Store Evaluation under Multiple Criteria in Thailand: A TOPSIS-Based Framework with Robustness Testing
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Abstract
The retail sector faces increasing complexity in evaluating store performance due to evolving market dynamics, competitive saturation, and digital disruption. To address these challenges, this study proposes a multi-criteria evaluation framework based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), enhanced with robustness testing. The framework integrates five dimensions—market potential, accessibility and visibility, competitive intensity, customer experience, and financial performance—to provide a comprehensive assessment of retail stores in Thailand. This study aims to develop and validate a structured, data-driven approach that assists retail managers in prioritizing investments and allocating resources under uncertainty. Five retail stores were analyzed using expert-derived weights, and two robustness tests (±10% weight perturbation and Leave-One-Criterion-Out) confirmed the stability of the ranking. The results demonstrate that Store D consistently outperforms others, supported by strong accessibility, customer satisfaction, and financial indicators. The analysis also highlights clear differentiation between mid-tier and underperforming stores, offering managerial insights for resource allocation and strategic repositioning. The novelty of this research lies in extending MCDM applications to retail store evaluation with integrated robustness analysis in the Thai context. The findings contribute both theoretically, by enhancing methodological rigor, and practically, by providing an actionable decision-support tool for retail management.
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