Understanding the Effects of Social Value Orientations in Shaping Regulatory Outcomes through Agent-Based Modeling: An Application in Organic Farming

Abstract

Within existing regulatory scholarship, limited attention is given to whether and how mesolevel, or group, characteristics shape compliance. We advance understanding of meso-level regulatory dynamics by assessing how the composition of regulated groups shapes overall compliance levels within a regulated system, as well as compliance trends among system participants. Specifically, we employ agent-based modeling as a tool suited to understanding emergent behaviors to assess how variation in the social value orientations of farmers participating in the United States' voluntary organic farming regulatory program may shape aggregate and subgroup compliance. We also assess how variation in sanctioning shapes compliance outcomes, shedding light on the interaction between participant motivation and sanctioning mechanisms. We conclude that, for compliance outcomes, the former is more decisive than the latter. e modeling exercise draws on an institutional grammar coding of regulatory design, survey, and interview data. In addition to reporting findings from the modeling exercise in the context of the organic farming regulatory domain, the paper offers insights about leveraging diverse forms of data to inform agent-based modeling, which is particularly appropriate for studying institutional (e.g., policy) and related behavioral dynamics in any governed setting.

Understanding the Emergence of Computational Institutional Science: A Review of Computational Modeling of Institutions and Institutional Dynamics

“…Over time, various approaches have been developed and engaged for the purpose of analyzing institutions and better understanding their effects of behavior; these include frameworks like the Institutional Analysis and Development (IAD) Framework (Ostrom 2005; and the Social-Ecological Systems (SES) Framework (Ostrom 2009;McGinnis and Ostrom 2014) and tools such as the Institutional Grammar (Crawford and Ostrom 1995;. Existing research notes the potential of computational methodologies (e.g., agentbased modeling, text analysis) to complement existing approaches to institutional analysis (e.g., Ghorbani et al 2013;Pieper et al 2023;Siddiki and Frantz 2022) and scholars have increasingly leveraged these methods for such institutional inquiries (e.g., Olivier and Schlager 2022;Rice et al 2021;Siddiki and Frantz 2023;Vannoni 2022).…”