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

HSE Economic Journal Pub Date : 2021-01-01 DOI:10.17323/1813-8691-2021-25-1-147-164

Vranda Jain, Tavishi Tewary, B. Gopalakrishnan

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引用次数: 9

Abstract

This paper pioneers the identification of artificial intelligence (AI) enablers like technology feasibility, sophistication, data integrity, interoperability and per ceived 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.

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解锁技术采用稳健的食品供应链:来自印度食品加工部门的证据

本文率先确定了人工智能(AI)的推动因素，如技术可行性、复杂性、数据完整性、互操作性和预期效益，这些因素可以提高印度食品加工业公司的运营效率。鉴于食品加工业对国内总增加值做出了重大贡献，并从农产品和加工食品出口中创造了近400亿美元的出口收入，该研究考察了人工智能在克服企业，特别是参与食品加工的中小型企业(SMEs)现有效率低下方面的作用。为此，我们向500名受访者发放了问卷，其中包括IT和供应链专业人士、食品加工公司经理和从事该行业的院士，其中341份完整回复。然后使用PLS-SEM模型分析这些响应，通过该模型建立人工智能采用与企业运营效率之间的关系。该研究发现，人工智能的采用与运营效率之间存在显著关系。R平方和Q平方值证实了研究中使用的模型的预测能力。该研究对供应链专业人员具有重要意义，因为技术的采用将提高这些公司的弹性、整合和透明度。这项研究也与解决与粮食安全、创造就业、提高工业产出和出口增长有关的问题有关。政策制定者还可以了解如何利用人工智能技术的好处，同时为不同的供应链合作伙伴创造有利的环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

HSE Economic Journal Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)

CiteScore

1.10

自引率

0.00%

发文量

期刊介绍： The HSE Economic Journal publishes refereed papers both in Russian and English. It has perceived better understanding of the market economy, the Russian one in particular, since being established in 1997. It disseminated new and diverse ideas on economic theory and practice, economic modeling, applied mathematical and statistical methods. Its Editorial Board and Council consist of prominent Russian and foreign researchers whose activity has fostered integration of the world scientific community. The target audience comprises researches, university professors and graduate students. Submitted papers should match JEL classification and can cover country specific or international economic issues, in various areas, such as micro- and macroeconomics, econometrics, economic policy, labor markets, social policy. Apart from supporting high quality economic research and academic discussion the Editorial Board sees its mission in searching for the new authors with original ideas. The journal follows international reviewing practices – at present submitted papers are subject to single blind review of two reviewers. The journal stands for meeting the highest standards of publication ethics.