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How to promote universities’ research and development into green agricultural products – A tripartite evolutionary game analysis

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Listed:
  • Lin Xiong
  • Luyao Chang
  • Yiyi Luo
  • Hansheng Wu
  • Yuchao Wang
  • Huile Jin

Abstract

Research into green agricultural products significantly enhances the sustainable development of China’s agriculture. These products ensure food safety, meet quality demands, reduce pollution, and advance agricultural green transformation. Utilising evolutionary game theory, this study analyses the interactions among the government, universities, and consumers in the research and development (R&D) on green agricultural products. Results show that under specific conditions, strategic interactions evolve toward stable states: (1,1,0) or (1,1,1). Secondly, critical factors affecting universities’ R&D demonstrate threshold effects. Third, government incentive measures have a significant impact on the R&D willingness of universities and the choices of consumers drives the enthusiasm of universities in making R&D decisions. Policy effectiveness and the outcomes of universities’ R&D subsequently constrain consumer choices. Short-term government incentives are crucial for promoting universities’ green agricultural R&D. Long-term sustainability, however, requires integrating market-driven incentives with government policies to sustain universities’ R&D strategies. This work offers theoretical and practical guidance for governmental policy-making, universities’ R&D strategies, and the upgrading of consumer behaviour. These findings critically support agriculture’s green and sustainable development.

Suggested Citation

  • Lin Xiong & Luyao Chang & Yiyi Luo & Hansheng Wu & Yuchao Wang & Huile Jin, 2026. "How to promote universities’ research and development into green agricultural products – A tripartite evolutionary game analysis," PLOS ONE, Public Library of Science, vol. 21(2), pages 1-29, February.
    • Handle: RePEc:plo:pone00:0342240
    DOI: 10.1371/journal.pone.0342240
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    References listed on IDEAS

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    1. Chiara Bersani & Ahmed Ouammi & Roberto Sacile & Enrico Zero, 2020. "Model Predictive Control of Smart Greenhouses as the Path towards Near Zero Energy Consumption," Energies, MDPI, vol. 13(14), pages 1-17, July.
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