Modelling Contingent Technology Adoption in Farming Irrigation Communities
Antoni Perello-Moragues (),
Pablo Noriega () and
Manel Poch ()
Additional contact information
Pablo Noriega: http://www.iiia.csic.es/~pablo/
Journal of Artificial Societies and Social Simulation, 2019, vol. 22, issue 4, 1
Abstract:
Of all the uses of water, agriculture is the one that requires the greatest proportion of resources worldwide. Consequently, it is a salient subject for environmental policy-making, and adoption of modern irrigation systems is a key means to improve water use efficiency. In this paper we present an agent-based model of the adoption process —known as "modernisation"— of a community constituted by farmer agents. The phenomenon is approached as a contingent innovation adoption: a first stage to reach a collective agreement followed by an individual adoption decision. The model is based on historical data from two Spanish irrigation communities during the period 1975-2010. Results suggest that individual profits and farm extension (as proxy of social influence) are suitable assumptions when modelling the modernisation of communities in regions where agriculture is strongly market-oriented and water is scarce. These encouraging results point towards the interest of more sophisticated socio-cognitive modelling within a more realistic socio-hydrologic context.
Keywords: Agent-Based Modeling; Innovation Diffusion; Policy-Making; Irrigation Agriculture; Socio-Hydrology (search for similar items in EconPapers)
Date: 2019-10-31
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
https://www.jasss.org/22/4/1/1.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2019-50-3
Access Statistics for this article
More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().