Mansi Singh
Department of Mechanical Engineering, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, India.

Viket Saurabh
Department of Mechanical Engineering, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, India.

Sagar Bharti
Department of Mechanical Engineering, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, India.

Anchal Patil
Operations Management & Quantitative Techniques, IMI Delhi, New Delhi, India.

Suchi Dubey
Department of Management, Symbiosis International University, Dubai, United Arab Emirates.

DOI https://doi.org/10.33889/IJMEMS.2026.11.5.094

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Abstract

Food waste in the agricultural sector remains a critical challenge with far-reaching impacts for food security and resource efficiency. In response, digitalization has increasingly been integrated into the Agri-Food Supply Chain (AFSC) to ease these losses. However, before effective digital solutions can be implemented, it is essential to identify and cognize the barriers within the digital AFSC. Only then can meaningful strategies be developed to overcome these obstacles. This study delineates the barriers and consequences of Industry 4.0 technologies in the AFSC through an analysis of current literature and expert perspectives. A total of 18 barriers were identified across the technical, operational, organizational and strategic dimensions. We use both the Matrix of Cross-Impact-Multiplication Applied to a Classification (MICMAC) method and interpretive structural modelling (ISM) to model these barriers. The results suggest that security and privacy concerns, technological immaturity, lack of technological infrastructure, high initial costs, uncertainty in Return On Investment (ROI), and lack of government regulation are the most important driving barriers within the hierarchical structure. Consequently, this research focuses on constraints that have emerged in the digital AFSC. This study serves as a guide for addressing supply chain issues in the Indian agri-food sector amid high demand for agricultural products.

Keywords- Interpretive structural modeling, Fuzzy-MICMAC analysis, Industry 4.0, Agri-food supply chain.

Citation

Singh, M., Saurabh, V., Bharti, S., Patil, A., & Dubey, S. (2026). Barriers to the Adoption of Industry 4.0 Technologies in the Digital Agri-Food Supply Chain. International Journal of Mathematical, Engineering and Management Sciences, 11(5), 2340-2361. https://doi.org/10.33889/IJMEMS.2026.11.5.094.