Evolutionary game analysis of stakeholders’ decision-making behavior in agricultural data supply chain

Abstract

The significance of agricultural information sharing in fostering agricultural development cannot be overstated. This practice plays a pivotal role in disseminating cutting-edge agricultural technologies, cultivation methods, and pest control strategies, empowering farmers with valuable knowledge to enhance crop yield and quality. Moreover, it aligns with government objectives of resource sharing and addressing gaps, contributing to the advancement of agricultural modernization and the development of the industry chain. Despite its inherent benefits, the practical implementation of agricultural information sharing faces challenges. Stakeholders engaged in information sharing often prioritize individual benefits, potentially leading to a decline in agricultural information quality and the inefficient use of experimental resources. To confront this issue, the present research establishes a three-party evolutionary game model comprising an agricultural product data sharing platform, agricultural data providers, and agricultural data consumers. Leveraging dynamic system theory, the model analyzes the evolutionary stable strategies of stakeholders and investigates the critical factors influencing the strategic choices of these three parties. Experimental findings underscore the pivotal role of participants’ initial strategies, regulatory intensity, reward and punishment mechanisms, and information feedback in shaping stakeholder decision-making behavior. Implementation of measures such as heightened scrutiny of information on the sharing platform and fostering consumer trust in data emerges as imperative for enhancing system stability. These actions are essential for constructing an efficient and reliable information-sharing ecosystem, thereby facilitating the sustainable development of modern agriculture.