Hybrid BWM–VIKOR Evaluation under PLTS Conditions for the Application of Industry 4.0 Technologies in Retail Management with Emphasis on Warehouse Systems

Abstract

Traditional warehousing methods not only fail to meet current requirements but also lead to increased operational errors, product waste, and reduced productivity. In recent decades, the retail industry has undergone significant transformations in technology, consumer behavior, and supply chain structures. The emergence of the Fourth Industrial Revolution (Industry 4.0) has created unprecedented opportunities for optimizing operational processes. In this context, warehouse management within the complex and multi-branch structure of chain stores, as one of the critical pillars of the supply chain, plays a key role in achieving productivity, flexibility, and customer satisfaction. Therefore, the aim of this study is to evaluate a hybrid BWM–VIKOR approach under PLTS conditions for the application of Industry 4.0 technologies in retail management, with an emphasis on warehouse systems. This study is categorized as an analytical–survey research. Given the application of the VIKOR and BWM techniques, the statistical population and sample consist of 10 experts in retail management with extensive experience, as well as specialists in Industry 4.0 technologies, selected through a census approach. Purposeful sampling is employed in this research. Data collection methods include both library research (articles, journals, books, and theses) and field studies (pairwise comparison questionnaires). The findings indicate that this study introduces a hybrid model to enhance decision-making efficiency. The limitations associated with subjective absolutism in single subjective weighting methods are reduced by this model, and the logical consistency of evaluation results is improved. Furthermore, the use of PLTS ensures the accuracy of evaluation data. In the domain of warehouse management, this hybrid model represents an advanced approach to multi-criteria decision-making (MCDM) that balances subjective judgments with objective data, thereby increasing the robustness and validity of decision-making. By reducing biases and improving overall performance, this method supports more informed and balanced decision-making. The results demonstrate that the model for implementing Industry 4.0 technologies in warehouse management of chain stores, developed in this study using the BWM–VIKOR method, has practical value for future decision-making evaluations regarding Industry 4.0 technologies in warehouse management of chain stores. The integration of the BWM–VIKOR approach into Industry 4.0 implementation processes is recognized as an advanced analytical tool that can enhance strategic planning and operational efficiency. This model provides a comprehensive understanding of the indicators, enabling chain store managers to develop effective warehouse management strategies and ultimately ensuring readiness and resilience in modern and intelligent warehousing systems.