Integrated Analysis of Industry 4.0 Technologies in Warehouse Management of Chain Stores Based on the BWM-TOPSIS Technique
Keywords:
Analysis, Industry 4, 0 Technologies, Warehouse Management, Chain Stores, BWM–TOPSISAbstract
In the era of the Fourth Industrial Revolution, the retail industry is facing extensive technological transformations and sustainability challenges. Chain stores, as the main actors in this industry, require transformation in their warehousing processes in order to enhance operational efficiency while also responding to environmental and social requirements. Within such a framework, the selection and implementation of Industry 4.0 technologies require precise analysis from the perspectives of organizational capability and strategic attractiveness. Therefore, the main objective of this study is to provide an integrated analysis of Industry 4.0 technologies in warehouse management of chain stores based on the BWM-TOPSIS technique. In this research, an introduction was first presented to introduce the subject, followed by a review of the relevant theoretical foundations and previous studies. Subsequently, the procedure for implementing the research methodology was explained. During the research process, the main criteria were extracted through a survey of experts, and a set of linguistic expressions proposed by specialists was utilized for the integrated analysis and evaluation of Industry 4.0 technologies in warehouse management of chain stores with respect to each criterion. These qualitative expressions were converted into corresponding numerical values, and in the final stage, multi-criteria decision-making methods, including BWM and TOPSIS, were employed to identify and rank the influencing factors. The findings indicate that the interval estimation BWM-TOPSIS method is used to enhance decision-makers’ ability to identify indicators that may mislead high-risk decisions or inefficiently influence them. This capability enables secondary or unnecessary factors to be eliminated from the decision-making process, thereby improving decision-making accuracy and efficiency. One of the key advantages of the interval estimation BWM-TOPSIS method lies in its ability to decompose complex decision-making problems into manageable components and create a hierarchical structure that clarifies the relationships among individual indicators. This structured approach assists decision-makers in achieving a comprehensive understanding of the decision-making process and facilitates the targeted elimination of inefficient indicators. The results demonstrate that the designed indicator system for the implementation of Industry 4.0 technologies in warehouse management of chain stores was screened using the interval estimation BWM-TOPSIS method. Consequently, technical innovation and waste management were eliminated, whereas the remaining indicators were retained.
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Copyright (c) 2025 Amirmohammad Shirani, Mansour Momeni (Author); Fatemeh Saghafi
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