Integrating Fuzzy Cognitive Mapping and Picture Fuzzy TOPSIS for Long-Term Retail Performance Evaluation
摘要
Efficient performance evaluation holds pivotal importance in the dynamic landscape of the retail sector. This paper presents a methodology that integrates Fuzzy Cognitive Map (FCM) and Picture Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF-TOPSIS) for comprehensive performance measurement. Emphasizing the overarching significance of retail performance assessment in organizational success, this approach begins by acknowledging the multifaceted nature of retail operations. Through FCM, the intricate interrelationships among long-term influential criteria shaping retail performance are identified and elucidated, facilitating a deeper understanding of underlying dynamics. Subsequently, leveraging PF-TOPSIS, retailers are assessed based on identified criteria, while accounting for inherent uncertainties in real-world data. This integrated framework empowers retailers to gain insights into critical performance factors and prioritize strategic actions for sustained success. By offering a holistic perspective that considers both qualitative and quantitative dimensions, our methodology enhances the accuracy and reliability of performance evaluation in the retail domain. Through an application on a company in the tire industry, the effectiveness and applicability of this approach are demonstrated, providing valuable guidance for retail practitioners and researchers navigating the intricacies of performance assessment and strategic decision-making in the retail landscape.