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

Author

Listed:
  • Vranda Jain

    (Jaipuria Institute of Management, India)

  • Tavishi Tewary

    (Jaipuria Institute of Management, India)

  • Badri Narayanan Gopalakrishnan

    (University of Washington, Washington, Seattle, WA, USA)

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.

Suggested Citation

  • Vranda Jain & Tavishi Tewary & Badri Narayanan Gopalakrishnan, 2021. "Unlocking Technology Adoption for a Robust Food Supply Chain: Evidence from Indian Food Processing Sector," HSE Economic Journal, National Research University Higher School of Economics, vol. 25(1), pages 147-164.
    • Handle: RePEc:hig:ecohse:2021:1:6
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    Citations

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    Cited by:

    1. Pellegrini, Giustina & de Mattos, Camila Silva & Otter, Verena & Hagelaar, Geoffrey, 2022. "Exploring how EU agri-food SMEs approach technology-driven business model innovation," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 26(3), December.
    2. Ahmed Zainul Abideen & Veera Pandiyan Kaliani Sundram & Jaafar Pyeman & Abdul Kadir Othman & Shahryar Sorooshian, 2021. "Food Supply Chain Transformation through Technology and Future Research Directions—A Systematic Review," Logistics, MDPI, vol. 5(4), pages 1-24, November.

    More about this item

    Keywords

    Supply Chain Management; SMEs; Disruptive Technology; Food Processing Industry; PLS–SEM; India;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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