Salita (Johnson Shoyama Graduate School of Public Policy, University of Saskatchewan. Salita is a Master of Public Policy (MPP) student at the Johnson Shoyama Graduate School of Public Policy, University of Saskatchewan. Her MPP dissertation uses an experimental approach to examine farmers' responses to regulatory frameworks governing agricultural big data, focusing on farmers’ trust and willingness to share farm data. Through her research, she is committed to contributing to evidence-based policymaking.) , Dr Yang Yang (Johnson Shoyama Graduate School of Public Policy, University of Saskatchewan. Dr. Yang Yang is an Associate Professor at the Johnson Shoyama Graduate School of Public Policy, University of Saskatchewan. Yang’s research focuses mainly on behavioural economics, food economics, experimental economics, and public policy. Yang has extensive experience in exploring and analyzing the framing effects in science communication, conducting experiments with stated preference methods using survey instruments and behavioral experiments. Yang is also knowledgeable in public finance and financial management issues. She has published in the flagship journals in agricultural economics (American Journal of Agricultural Economics, Journal of Agricultural Economics, Canadian Journal of Agricultural Economics), a top multidisciplinary policy journal (Food Policy), and top public policy/administration journals (Canadian Journal of Political Science, Canadian Public Administration).)
Abstract
Smart farming technologies generate vast amounts of agricultural data, raising concerns among Canadian farmers about data ownership, privacy, and power imbalances. The lack of robust governance frameworks increases farmers’ reluctance to share data and erodes their trust in the system. This study examines how Canadian farmers respond to different governance models – government command and control, farmer cooperatives, and market-based voluntary approaches – focusing on their willingness to engage with big data analytics platforms and trust in various governance structures.
A pre-registered online survey will collect data from 375 Western Canadian grain farmers, incorporating an experimental component where participants will be randomly assigned to one of four conditions: treatment 1 (government command and control governance), treatment 2 (farmer cooperatives), treatment 3 (market-based voluntary association), and a control condition (no information on governance model is provided). Each treatment will describe the governance dimensions, including governance structure, accountability and transparency, ownership and power, benefits, and downsides, according to its specific governance model.
The study will also collect data on socio-demographics, attitudes toward digital technologies, big data platform usage, risk perception, and ambiguity aversion to better understand factors influencing trust and data-sharing behaviour. The survey is currently being finalized, with data collection set to begin in mid-March. Our findings will inform evidence-based policymaking by identifying governance structures that address farmers’ concerns, build trust, and encourage participation in data-driven farm management.