Seeds of Cross-Sector Collaboration: A Multi-Agent Evolutionary Game Theoretical Framework Illustrated by the Breeding of Salt-Tolerant Rice

• Published in: Agriculture (Basel) Vol. 14; no. 2; p. 300
• Main Authors: Chen, Yusheng, Sun, Zhaofa, Wang, Yanmei, Ma, Ye, Yang, Weili
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2024
• Subjects: Agricultural cooperatives; Agricultural development; Agricultural research; Agricultural sciences; Algorithms; Asymmetry; breeding; Case studies; China; Climate change; Collaboration; collaborative innovation; Computer simulation; DDE; delay differential equation (DDE); Differential equations; Empirical analysis; Evolution; evolutionary game; Food security; Food supply; Game theory; Industrial research; Innovations; Mathematical analysis; Mathematical models; Multiagent systems; Nitrous oxide; Numerical analysis; Ordinary differential equations; Participation; Plant breeding; Product development; Public sector; R&D; Research & development; Research facilities; Research institutions; Rice; Salinity tolerance; Salt; salt-tolerant rice; Salts; Seed industry; Seeds; Simulation; Simulation methods; Stability analysis; Subsidies; Sustainability; Sustainable agriculture; Sustainable development; System theory; China
• ISSN: 2077-0472; 2077-0472
• DOI: 10.3390/agriculture14020300

In the context of global food security and the pursuit of sustainable agricultural development, fostering synergistic innovation in the seed industry is of strategic importance. However, the collaborative innovation process between seed companies, research institutions, and governments is fraught with challenges due to information asymmetry and bounded rationality within the research and development phase. This paper establishes a multi-agent evolutionary game framework, taking the breeding of salt-tolerant rice as a case study. This study, grounded in the theories of information asymmetry and bounded rationality, constructs a two-party evolutionary game model for the interaction between enterprises and research institutions under market mechanisms. It further extends this model to include government participation, forming a three-party evolutionary game model. The aim is to uncover the evolutionary trends in collaborative behavior under various policy interventions and to understand how governments can foster collaborative innovation in salt-tolerant rice breeding through policy measures. To integrate the impact of historical decisions on the evolution of collaborative innovation, this research employs a delay differential equation (DDE) algorithm that takes historical lags into account within the numerical simulation. The stability analysis and numerical simulation using the DDE algorithm reveal the risk of market failure within the collaborative innovation system for salt-tolerant rice breeding operating under market mechanisms. Government involvement can mitigate this risk by adjusting incentive and restraint mechanisms to promote the system’s stability and efficiency. Simulation results further identify that the initial willingness to participate, the coefficient for the distribution of benefits, the coefficient for cost sharing, and the government’s punitive and incentivizing intensities are crucial factors affecting the stability of collaborative innovation. Based on these findings, the study suggests a series of policy recommendations including enhancing the initial motivation for participation in collaborative innovation, refining mechanisms for benefit distribution and cost sharing, strengthening regulatory compliance systems, constructing incentive frameworks, and encouraging information sharing and technology exchange. These strategies aim to establish a healthy and effective ecosystem for collaborative innovation in salt-tolerant rice breeding. While this research uses salt-tolerant rice breeding as a case study, the proposed cooperative mechanisms and policy suggestions have universal applicability in various agricultural science and technology innovation scenarios, especially when research meets widespread social needs but lacks commercial profit drivers, underscoring the essential role of government incentives and support. Consequently, this research not only contributes a new perspective to the application of evolutionary game theory in agricultural science and technology innovation but also offers empirical backing for policymakers in advancing similar collaborative innovation endeavors.