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Modeling Farmers’ Adoption Potential to New Bioenergy Crops: An Agent-Based Approach

  • SUNY Buffalo
  • Oak Ridge National Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternatives to these especially in the form of biofuels, fuels derived from bioenergy crops. This paper aims to determine farmers’ potential adoption rates of newly introduced bioenergy crops with a specific example of carinata in the state of Georgia. The determination is done using an agent-based modeling technique with two principal assumptions—farmers are profit maximizer and they are influenced by neighboring farmers. Two diffusion parameters (traditional and expansion) are followed along with two willingness (high and low) scenarios to switch at varying production economics to carinata and other prominent traditional field crops (cotton, peanuts, corn) in the study region. We find that a contract prices around $9, $8 and $7 can be a viable option for encouraging farmers to adopt carinata in low, average, and high profit conditions, respectively. Expansion diffusion (that diffuses all over the geographical area), rather than centered to the few places like traditional diffusion at the early stage of adoption in conjunction with higher willingness conditions influences higher adoption rates in the short-term. As such, the model can be used to understand the behavioral economics of carinata in Georgia and beyond, as well as offering a potential tool to study similar bioenergy crops.

Original languageEnglish
Title of host publicationProceedings of the 2022 Conference of The Computational Social Science Society of the Americas -
EditorsZining Yang, Santiago Núñez-Corrales
PublisherSpringer Science and Business Media B.V.
Pages63-75
Number of pages13
ISBN (Print)9783031375521
DOIs
StatePublished - 2023
EventAnnual conference of the Computational Social Science Society of the Americas, CSSSA 2022 - Santa Fe, Mexico
Duration: Oct 27 2022Oct 30 2022

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

ConferenceAnnual conference of the Computational Social Science Society of the Americas, CSSSA 2022
Country/TerritoryMexico
CitySanta Fe
Period10/27/2210/30/22

Keywords

  • Adoption
  • Agent-based modeling
  • Bioenergy crops
  • Farming

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