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Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications

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  • Madhu Khanna

Abstract

The digital transformation of agriculture is enabling the collection of vast amounts of geo‐referenced information about growing conditions within the field and facilitating the automated implementation of spatially varying input applications. This has the potential to increase production efficiency, reduce overapplication of inputs, lower input waste and pollution, and improve farm profitability. We discuss the pathways by which digital agricultural technologies have the potential to affect crop management, and current trends and patterns of adoption of digital technologies. We provide insights from the technology adoption literature on the factors that can be expected to influence the adoption of emerging digital technologies and the findings from the empirical literature on the determinants of adoption of these types of technologies. We conclude with a discussion of the design of policy incentives to induce the adoption of digital technologies cost‐effectively, the challenges in implementing such policies and the opportunity that digital technologies offer for addressing these challenges.

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  • Madhu Khanna, 2021. "Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1221-1242, December.
    • Handle: RePEc:wly:apecpp:v:43:y:2021:i:4:p:1221-1242
    DOI: 10.1002/aepp.13103
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    2. Guo, Bingnan & Feng, Yu & Lin, Ji, 2023. "Digital inclusive finance and digital transformation of enterprises," Finance Research Letters, Elsevier, vol. 57(C).
    3. Xiaoxu Zhang & Xinyu Du, 2023. "Industry and Regional Peer Effects in Corporate Digital Transformation: The Moderating Effects of TMT Characteristics," Sustainability, MDPI, vol. 15(7), pages 1-22, March.
    4. McFadden, Jonathan & Njuki, Eric & Griffin, Terry, 2023. "Precision Agriculture in the Digital Era: Recent Adoption on U.S. Farms," USDA Miscellaneous 333550, United States Department of Agriculture.
    5. Wang, Tong & Jin, Hailong & Sieverding, Heidi L. & Rao, Xudong & Miao, Yuxin & Kumar, Sandeep & Redfearn, Daren & Nafchi, Ali, 2022. "Understanding farmer perceptions of precision agriculture profitability in the U.S. Midwest," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322502, Agricultural and Applied Economics Association.
    6. Madhu Khanna & Shady S. Atallah & Saurajyoti Kar & Bijay Sharma & Linghui Wu & Chengzheng Yu & Girish Chowdhary & Chinmay Soman & Kaiyu Guan, 2022. "Digital transformation for a sustainable agriculture in the United States: Opportunities and challenges," Agricultural Economics, International Association of Agricultural Economists, vol. 53(6), pages 924-937, November.
    7. Rachel Opitz & Philippe De Smedt & Victorino Mayoral-Herrera & Stefano Campana & Marco Vieri & Eamonn Baldwin & Carolina Perna & Daniele Sarri & Jeroen Verhegge, 2023. "Practicing Critical Zone Observation in Agricultural Landscapes: Communities, Technology, Environment and Archaeology," Land, MDPI, vol. 12(1), pages 1-20, January.
    8. Ndekwa, Alberto Gabriel & Kalugendo, Elizeus & Sood, Kiran & Grima, Simon, 2023. "An Analysis of Agribusiness Digitalisation Transformation of the Sub-Saharan African Countries Small-Scale Farmers' Production Distribution," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 4(3), September.
    9. Wang, Tong & Jin, Hailong & Sieverding, Heidi & Kumar, Sandeep & Miao, Yuxin & Rao, Xudong & Obembe, Oladipo & Mirzakhani Nafchi, Ali & Redfearn, Daren & Cheye, Stephen, 2023. "Understanding farmer views of precision agriculture profitability in the U.S. Midwest," Ecological Economics, Elsevier, vol. 213(C).

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