Investigation of Effective Indicators in the Implementation of Industry 4.0 Technologies for Improving Warehousing Operations in Chain Stores
Keywords:
Effective Indicators, Implementation, Industry 4, Warehousing, Chain StoresAbstract
The aim of this study is to investigate the effective indicators in the implementation of Industry 4.0 technologies for improving warehousing operations in chain stores. This research is classified as an analytical–software-based study. The study is cross-sectional in nature. In terms of purpose, it is applied research. From the spatial perspective, it is a field study, and the temporal scope of the research is 2025. Since the m-TISM model within the MICMAC technique framework was employed in this study, the statistical population and sample consisted of 15 managers, warehouse management experts, and specialists in the fields of information technology and artificial intelligence, selected through a census method. In this study, convenience sampling was used. The required data were collected using a pairwise comparison questionnaire and analyzed through MICMAC software. The findings obtained from the conducted analyses indicate that multiple indicators should be considered in warehouse management. When applying technology in warehouse management for chain stores, a defined and context-specific indicator system should be established for this domain. This section introduces an implementation indicator system encompassing six critical dimensions: technical, economic, environmental, safety, managerial, and supervisory dimensions. This comprehensive indicator system includes six primary indicators, which are divided into 20 secondary indicators. The results demonstrate that investment cost (economic), operational cost (economic), expected return (economic), personnel safety (safety), pollution control (environmental), and the use of specialized integrated warehouse operations management software (managerial) are among the key indicators for implementing Industry 4.0 technologies to improve warehousing operations in chain stores. A high success rate in exploration is associated with an increased probability of identifying relevant resources, which enhances the implementation of Industry 4.0 technologies. The availability and effectiveness of the required technology are evaluated to ensure that the implementation achieves the research objectives.
References
Brown, W. L., Johnson, O., & Wilson, G. (2024). The Impact of 5G Technology on Retail Marketing and Supply Chain Operations. https://doi.org/10.20944/preprints202407.2073.v1
Fu, H., He, L., Ju, X., & Liu, Y. (2023). Research on Digital Transformation of New Retail Enterprises Based on AI+RPA. Advances in Economics Management and Political Sciences, 28(1), 250-258. https://doi.org/10.54254/2754-1169/28/20231340
Guo, T., & Palaoag, T. D. (2023). Artificial Intelligence Driven E-Commerce Business Model Under New Retail Environment. https://doi.org/10.4108/eai.2-12-2022.2328056
Gupta, M., & Jauhar, S. K. (2023). Digital Innovation: An Essence for Industry 4.0. Thunderbird International Business Review, 65(3), 279-292. https://doi.org/10.1002/tie.22337
Gupta, R., Usman, M., Kashid, P. V., Mohan, M. L., Gaidhani, V. A., & Ghuge, M. A. R. (2025). Artificial Intelligence and IoT in Retail Marketing: Innovations in Smart Stores and Personalized Shopping. Artificial Intelligence, 5(2). https://www.researchgate.net/profile/Mohammed-Usman-30/publication/390740662
Hrouga, M., & Sbihi, A. (2023). Logistics 4.0 for Supply Chain Performance: Perspectives From A retailing Case Study. Business Process Management Journal, 29(6), 1892-1919. https://doi.org/10.1108/bpmj-03-2023-0183
Kandarkar, P. C., & Ravi, V. (2024). Investigating the Impact of Smart Manufacturing and Interconnected Emerging Technologies in Building Smarter Supply Chains. Journal of Manufacturing Technology Management, 35(5), 984-1009. https://doi.org/10.1108/jmtm-11-2023-0498
Karthikeyan, K. S., & Nagaprakash, T. (2023). Prioritizing IoT-driven Sustainability Initiatives in Retail Chains: Exploring Case Studies and Industry Insights. Eai Endorsed Transactions on Internet of Things, 10. https://doi.org/10.4108/eetiot.4628
Khan, N., Solvang, W. D., Yu, H., & Rolland, B. E. (2024). Towards the Design of a Smart Warehouse Management System for Spare Parts Management in the Oil and Gas Sector. Frontiers in Sustainability, 5. https://doi.org/10.3389/frsus.2024.1426089
Maheshwari, P., Kamble, S., Kumar, S., Belhadi, A., & Gupta, S. (2023). Digital Twin-Based Warehouse Management System: A theoretical toolbox for Future Research and Applications. The International Journal of Logistics Management, 35(4), 1073-1106. https://doi.org/10.1108/ijlm-01-2023-0030
Mashayekhy, Y., Babaei, A., Yuan, X.-M., & Xue, A. (2022). Impact of Internet of Things (IoT) on Inventory Management: A Literature Survey. Logistics, 6(2), 33. https://doi.org/10.3390/logistics6020033
Mayounga, A. (2022). Industry 4.0: The Tenets of the Next Generation of Supply Chain Management. https://doi.org/10.5772/intechopen.102979
Mithas, S., Chen, Z. L., Saldanha, T., & Silveira, A. D. O. (2022). How Will Artificial Intelligence and Industry 4.0 Emerging Technologies Transform Operations Management? Production and Operations Management, 31(12), 4475-4487. https://doi.org/10.1111/poms.13864
Nazir, H., & Fan, J. (2024). Revolutionizing Retail: Examining the Influence of Blockchain-Enabled IoT Capabilities on Sustainable Firm Performance. Sustainability, 16(9), 3534. https://doi.org/10.3390/su16093534
Nguyen, M. D., Yeon, K. T., Rudzki, K., Nguyen, H. P., & Pham, N. D. K. (2023). Strategies for Developing Logistics Centres: Technological Trends and Policy Implications. Polish Maritime Research, 30(4), 129-147. https://doi.org/10.2478/pomr-2023-0066
R., M. M., & Keserwani, H. (2024). Impact of Technology on Various Facets of the Fashion Industry. International Journal for Multidisciplinary Research, 6(2). https://doi.org/10.36948/ijfmr.2024.v06i02.15845
Raja, R., & Venkatachalam, S. (2024). Technological Features of Warehouse Operations in Third Party Logistics Services in Tamilnadu. 133, Ruthramathi-509. https://doi.org/10.15405/epsbs.2024.05.42
ran, Y. D., & Öztürkoğlu, Ö. (2022). Key Performance Measures and Digital-Era Technologies in Warehouses. Operations and Supply Chain Management an International Journal, 193-204. https://doi.org/10.31387/oscm0490340
Ranjan, J., & Kadam, S. (2025). Analysis of Customer satisfaction, Service Quality and Scope of Knowledge Sharing in Retail Branch Banking of Small and Medium Enterprises in India. https://ijmec.org.in/index.php/ijmec/article/view/139
Raza, Z., Haq, I. U., & Muneeb, M. (2023). Agri-4-All: A Framework for Blockchain Based Agricultural Food Supply Chains in the Era of Fourth Industrial Revolution. IEEE Access, 11, 29851-29867. https://doi.org/10.1109/access.2023.3259962
Rodchenko, V., & Prus, Y. (2023). Digital Technologies in Logistics and Supply Chain Management. Facta Universitatis Series Economics and Organization, 191. https://doi.org/10.22190/fueo230517012r
Schmidt, D. C., Butturi, M. A., & Sellitto, M. A. (2023). Opportunities of Digital Transformation in Post-Harvest Activities: A Single Case Study of an Engineering Solutions Provider. Agriengineering, 5(3), 1226-1242. https://doi.org/10.3390/agriengineering5030078
Schmidt, I., Morris, D. R., Thomas, A., & Manning, L. (2022). Smart Systems: The Role of Advanced Technologies in Improving Business Quality, Performance and Supply Chain Integration. Standards, 2(3), 276-293. https://doi.org/10.3390/standards2030020
Shi, T., Lee, S. J., & Li, Q. (2023). Smart Supply Chain Management in Business Education: Reflection on the Pandemics. Decision Sciences Journal of Innovative Education, 22(1), 19-32. https://doi.org/10.1111/dsji.12303
Sivasankari, M. (2025). Artificial Intelligence in Retail Marketing: Optimizing Product Recommendations and Customer Engagement. Jier, 5(1). https://doi.org/10.52783/jier.v5i1.2105
ThiPham, X. (2024). Improving the Digital Transformation Capacity of Vietnam's Retail Businesses. Global Academic Journal of Economics and Business, 6(01), 1-8. https://doi.org/10.36348/gajeb.2024.v06i01.001
Yu, M., & Su, K. (2025). Dynamic Pricing for Ship-From-Store Omnichannel Retailers: A Globalized Robust Optimization Approach. Ima Journal of Management Mathematics, 37(1), 149-180. https://doi.org/10.1093/imaman/dpaf034
Zhao, D., & Smirnova, E. A. (2023). The Evolution of a Symbiotic Ecosystem of Chinese E-Commerce Retail Logistics in the Post-Covid-19 Epidemic Era. SHS Web of Conferences, 166, 01015. https://doi.org/10.1051/shsconf/202316601015
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Copyright (c) 2026 Amirmohammad Shirani, Mansour Momeni (Author); Fatemeh Saghafi

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