Document Type : Original Article
Authors
1
PhD Student of Industrial Management, Department of Management, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran
2
Department of Industrial Management, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran
3
Assistant professor of operations and supply chain management ,Pennsylvania state university. USA
10.22075/mmsd.2025.37975.1003
Abstract
Background and Objectives: In today's turbulent and competitive environment, resilience is recognized as a strategic advantage for organizational survival and achieving sustainable development. Various industries, in pursuit of resilience, align themselves with technological advancements by implementing fundamental transformations. The emergence of advanced technologies in the field of logistics, particularly warehousing, can play a significant role in enhancing industrial resilience. This study aims to develop an analytical model to examine the impact of the factors of smart warehouses on industrial resilience.
Materials and Methods: In the first phase, a comprehensive review of theoretical literature and credible academic sources led to the identification of 13 key factors of smart warehouses. Then, using the Fuzzy Delphi technique and expert surveys in the field of logistics and warehousing across various industries, the significance of each factor was assessed, and 11 factors were ultimately validated. In the next phase, the Fuzzy DEMATEL method was employed to analyze the relationships among the factors, determine their degree of influence and interaction, and model the causal structure to examine the role of warehouse smartification in enhancing industrial resilience.
Results: The findings revealed that three factors—mechanization, required new infrastructures, and information management—exert the greatest influence on other factors and are identified as key drivers of warehouse smartification. At the same time, these factors are also the most affected by others, placing them at the core of systemic interactions. Any improvement or deficiency in these areas may trigger significant ripple effects across the system. According to the analysis, industry structure, human resource skills, mechanization, and infrastructural needs possess the greatest driving force over the remaining variables and are identified as primary catalysts in the system. Since the industry structure exhibits the highest level of unidirectional impact—exerting change without being altered in return—it can be concluded that the characteristics and foundational requirements of industries form the essential basis for any decision-making concerning smartification.
Conclusion: The results showed, that developing human capabilities and aligning organizational frameworks with technological advancements are vital pillars of success on the path to smart warehousing. Given that industrial resilience under critical conditions demands intelligent and responsive systems, the insights from this study can serve as a practical guide for decision-makers, logistics managers, and warehouse system designers in implementing smart technologies effectively. In addition, the proposed analytical model offers a scientific framework for assessing organizational preparedness for change and enhancing operational flexibility, providing a foundation for future policymaking in the field of intra logistics at industries.
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