Farmer characteristics and decision-making: A model for bioenergy crop adoption. (1st November 2021)

• Record Type: Journal Article
• Authors: Burli, Pralhad H.; Nguyen, Ruby T.; Hartley, Damon S.; Griffel, L. Michael; Vazhnik, Veronika; Lin, Yingqian
• Is Part Of: Energy. Volume 234(2021)
• Publication Date: 2021-11-01
• Subjects: Agent-based model -- Bioenergy -- Crop residue -- Energy crops -- Adoption; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.121235
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry. Highlights: Farmer adoption rates vary widely for crop residues and energy crops. Social networks and market structure influence adoption for both feedstocks. Information dissemination has a positive impact for energy crop adoption. Combining interventions can accelerate farmer adoption substantially.