Abstract
This paper seeks to calibrate the dynamic policy-induced adoption/diffusion of an agri-environmental beneficial technology. The paper develops an agent-based model to integrate the adoption problem into a complex farmer adoption decision-making system involving different components (e.g., GIS environment, agents, network, production and adoption, policy). Based on the model, a case on cost-effectiveness evaluation of a hypothetical agricultural extension (AE) program is exemplified in this study to explain how this model can support the agri-environmental policy design. As a result, farmers’ adoption decision-making under the influence of the AE program can be brought forward to an average ten-year ahead with a higher upper boundary of ultimate adoption rate than no policy scenario. Furthermore, this study presents simulated policy evaluation from different participation rates of the AE program to compare policy effects and thus assess their cost-effectiveness. The comparison results imply that a higher participation rate does not positively increase the performance of the AE program. Our ex-ante agent-based modeling (ABM) simulation method can be applied in agri-environmental policy design, evaluation, and long-term policy monitor. In addition, the model provides a flexible quantitative tool to predict farmers’ policy-induced adoption decision-making and outcomes in a future period. We also introduce potential improvements to extend the inherent farmers’ adoption behavior algorithm, computing capability, and model validation for future research.
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Data Availability
RePast package with data and code is released on the GitHub repository: https://github.com/Sunran2017/GIS-based-ABM-of-technology-adoption
Notes
RePast (Recursive Porous Agent Simulation Toolkit) was originally developed by researchers from the Social Science Computing Research Center of the University of Chicago and was subsequently extended by Argonne National Laboratory as a packaged software infrastructure (North et al. 2013).
Tile Drainage Area (Ontario GeoHub): https://geohub.lio.gov.on.ca/datasets/tile-drainage-area.
Controlled Drainage (Ontario GeoHub): https://geohub.lio.gov.on.ca/datasets/4b2e0e3cdd0f48f0a832e568629daf56.
Individuals File, Census of Population (Public Use Microdata Files): https://www150.statcan.gc.ca/n1/en/catalogue/98M0001X.
Prophet: https://facebook.github.io/prophet/.
The estimated costs consider annual extension activities (6 to 8 occurrences) of $5,000-$7,500 per seminar, or $48,500 for a part-time contract offering regional service.
\(lp\_\mathrm{solve}\) reference guide: http://lpsolve.sourceforge.net/5.5/; \(lp\_\mathrm{solve}\) was initially developed by Michel Berkelaar at the Eindhoven University of Technology and extended to a Java interface made by Juergen Ebert (University of Koblenz–Landau, Germany).
Statistical tests were based on production and operation variables. The model can output a dynamic farm dataset for V &V, which can be reproduced by code package.
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Acknowledgements
We would like to thank Dr. Chandra A. Madramootoo of McGill University for providing biophysical data regarding environmental performance of BWMPs and Mariela Marmanillo for providing financial analysis data BWMPs. We would also like to thank Weicheng Qian, Bo Pu for their helpful review in code and acknowledge helpful comments from all anonymous reviewers.
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Sun, R., Nolan, J. & Kulshreshtha, S. Agent-based modeling of policy induced agri-environmental technology adoption. SN Bus Econ 2, 101 (2022). https://doi.org/10.1007/s43546-022-00275-6
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DOI: https://doi.org/10.1007/s43546-022-00275-6