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How data analytics is transforming agriculture

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  • Pham, Xuan
  • Stack, Martin

Abstract

Two discussions about the interaction between data analytics and competitive analysis have been taking place in the past decade: one focusing on micro-level firm capabilities and the other on macro-level industry competitiveness. We seek to integrate the micro- and macro-level analyses via the lenses of firms in agricultural input markets. Agriculture is undergoing a tremendous transformation in the collection and use of data to inform smarter farming decisions. Precision agriculture has brought a heightened degree of competition for input supply firms, forcing greater interactions among friends and foes.

Suggested Citation

  • Pham, Xuan & Stack, Martin, 2018. "How data analytics is transforming agriculture," Business Horizons, Elsevier, vol. 61(1), pages 125-133.
    • Handle: RePEc:eee:bushor:v:61:y:2018:i:1:p:125-133
    DOI: 10.1016/j.bushor.2017.09.011
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    Cited by:

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    7. Ioannis Margaritis & Michael Madas & Maro Vlachopoulou, 2022. "Big Data Applications in Food Supply Chain Management: A Conceptual Framework," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    8. Antonio Manuel Ciruela-Lorenzo & Ana Rosa Del-Aguila-Obra & Antonio Padilla-Meléndez & Juan José Plaza-Angulo, 2020. "Digitalization of Agri-Cooperatives in the Smart Agriculture Context. Proposal of a Digital Diagnosis Tool," Sustainability, MDPI, vol. 12(4), pages 1-15, February.
    9. repec:mth:jas888:v:6:y:2018:i:4:p:84-97 is not listed on IDEAS
    10. Jennifer Clapp & Sarah-Louise Ruder, 2020. "Precision Technologies for Agriculture: Digital Farming, Gene-EditedCrops, and the Politics of Sustainability," Global Environmental Politics, MIT Press, vol. 20(3), pages 49-69, August.
    11. Luis Ruiz-Garcia & Patricia Sanchez-Guerrero, 2022. "A Decision Support Tool for Buying Farm Tractors, Based on Predictive Analytics," Agriculture, MDPI, vol. 12(3), pages 1-26, February.
    12. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. Divya Suresh & Abhishek Choudhury & Yinjia Zhang & Zhiying Zhao & Rajib Shaw, 2024. "The Role of Data-Driven Agritech Startups—The Case of India and Japan," Sustainability, MDPI, vol. 16(11), pages 1-17, May.
    14. Kosior, Katarzyna, 2020. "Economic, Ethical and Legal Aspectsof Digitalization in The Agri-Food Sector," Problems of Agricultural Economics / Zagadnienia Ekonomiki Rolnej 311227, Institute of Agricultural and Food Economics - National Research Institute (IAFE-NRI).
    15. Václav Novák & Petr Šařec & Kateřina Křížová & Petr Novák & Oldřich Látal, 2021. "Potential Impact of Biostimulator NeOsol and Three Different Manure Types on Physical Soil Properties and Crop Status in Heavy Soils Conditions," Sustainability, MDPI, vol. 14(1), pages 1-15, December.
    16. Paul B. Hegedus & Bruce Maxwell & John Sheppard & Sasha Loewen & Hannah Duff & Giorgio Morales-Luna & Amy Peerlinck, 2023. "Towards a Low-Cost Comprehensive Process for On-Farm Precision Experimentation and Analysis," Agriculture, MDPI, vol. 13(3), pages 1-20, February.
    17. Njomane, Linda & Telukdarie, Arnesh, 2022. "Impact of COVID-19 food supply chain: Comparing the use of IoT in three South African supermarkets," Technology in Society, Elsevier, vol. 71(C).
    18. Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael, 2022. "The perils of working with big data, and a SMALL checklist you can use to recognize them," Business Horizons, Elsevier, vol. 65(4), pages 481-492.
    19. Jingmei Gao & Zahid Sarwar, 2024. "How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?," Information Technology and Management, Springer, vol. 25(3), pages 283-304, September.

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