Unlocking Technology Adoption for a Robust Food Supply Chain: Evidence from Indian Food Processing Sector

Vranda Jain, Tavishi Tewary and Badri Narayanan Gopalakrishnan
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Tavishi Tewary: Jaipuria Institute of Management, India
Badri Narayanan Gopalakrishnan: University of Washington, Washington, Seattle, WA, USA

HSE Economic Journal, 2021, vol. 25, issue 1, 147-164

Abstract: This paper pioneers the identification of artificial intelligence (AI) enablers like technology feasibility, sophistication, data integrity, interoperability and perceived benefits that can boost operational efficiency of firms in Indian food processing industry. With the food processing industry contributing significantly to do­mestic gross value added and generating an export earning of close to USD 40 billion from agricultural and processed food exports, the study examines the role of AI in overcoming the existing inefficiencies of firms, particularly the small and medium enterprises (SMEs) involved in food processing. For this, questionnaire wascirculated to 500 respondents comprising of IT and supply chain professionals, managers of food processing companies and academicians working in this do main, of which 341 complete responses were received. These responses were then analysed using PLS–SEM modeling, through which the relationship between AI adoption and operational efficiency of firm was established. The study found a significant relationship between AI adoption and operational efficiency. The R square and Q square values substantiate the predictive power of the model used in the study. The research has significant implications for supply chain professionals as technology adoption would boost resilience, integration and transparency of these firms. The study is also relevant for addressing issues pertaining to food security, employment generation, enhancing industrial output and export growth. Policy makers can also get perspectives on harnessing the benefits of AI technology while creating an enabling environment for different supply chain partners.

Keywords: Supply Chain Management; SMEs; Disruptive Technology; Food Processing Industry; PLS–SEM; India (search for similar items in EconPapers)
JEL-codes: C38 O33 Q16 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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