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Understanding Technology Adoption Through System Dynamics Modeling: Implications For Agribusiness Management

Author

Listed:
  • Fisher, Donna K.
  • Norvell, Jonathan
  • Sonka, Steven T.
  • Nelson, Mark J.

Abstract

This work demonstrates the utility of sophisticated simulation tools in aiding agribusiness managers' decision making. The system dynamics model developed here provides insight into the use of such models to evaluate potential adoption rates and diffusion patterns of yield mapping and monitoring technologies. The model allows for comparative analyses of the possible effects of different profit assumptions on adoption and diffusion.

Suggested Citation

  • Fisher, Donna K. & Norvell, Jonathan & Sonka, Steven T. & Nelson, Mark J., 2000. "Understanding Technology Adoption Through System Dynamics Modeling: Implications For Agribusiness Management," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 3(3), pages 1-16.
  • Handle: RePEc:ags:ifaamr:34477
    DOI: 10.22004/ag.econ.34477
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    References listed on IDEAS

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    1. Michael Boehlje, 1999. "Structural Changes in the Agricultural Industries: How Do We Measure, Analyze and Understand Them?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(5), pages 1028-1041.
    2. Madhu Khanna & Onesime Faustin Epouhe & Robert Hornbaker, 1999. "Site-Specific Crop Management: Adoption Patterns and Incentives," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 21(2), pages 455-472.
    3. Sterman, John., 1994. "Learning in and about complex systems," Working papers 3660-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.
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    Cited by:

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    2. Dizyee, Kanar & Baker, Derek & Rich, Karl M., 2017. "A quantitative value chain analysis of policy options for the beef sector in Botswana," Agricultural Systems, Elsevier, vol. 156(C), pages 13-24.
    3. Tanure, Soraya & Nabinger, Carlos & Becker, João Luiz, 2013. "Bioeconomic model of decision support system for farm management. Part I: Systemic conceptual modeling," Agricultural Systems, Elsevier, vol. 115(C), pages 104-116.
    4. Soraya Tanure & Carlos Nabinger & João Luiz Becker, 2015. "Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(6), pages 658-671, November.
    5. Jonas Fernando Petry & Sabrina Arcanjo Sebastião & Erik Garcia Martins & Paulo Berti de Azevedo Barros, 2019. "Innovation and the Diffusion of Technology in Agriculture in Floodplains in the State of Amazonas," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 23(5), pages 619-635.
    6. Grabowski, Philip & Schmitt Olabisi, Laura & Adebiyi, Jelili & Waldman, Kurt & Richardson, Robert & Rusinamhodzi, Leonard & Snapp, Sieglinde, 2019. "Assessing adoption potential in a risky environment: The case of perennial pigeonpea," Agricultural Systems, Elsevier, vol. 171(C), pages 89-99.
    7. Robert Yawson & Jennifer Kuzma, 2010. "Systems Mapping of Consumer Acceptance of Agrifood Nanotechnology," Journal of Consumer Policy, Springer, vol. 33(4), pages 299-322, December.
    8. Francesca Varia & Dario Macaluso & Ida Agosta & Francesco Spatafora & Giovanni Dara Guccione, 2021. "Transitioning towards Organic Farming: Perspectives for the Future of the Italian Organic Wine Sector," Sustainability, MDPI, vol. 13(5), pages 1-15, March.

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