With the prosperous development of e-commerce live streaming, many logistics companies have also begun to expand their live streaming business, leveraging their advantages in logistics to sell green agricultural products through live streaming. However, some quality issues have emerged during the sales process. This phenomenon is not only detrimental to the sustainable development of the business model, but also affects the sales of green agricultural products. In view of this, we first construct a tripartite evolutionary game model with logistics enterprises, farmers, and consumers as the main subjects based on prospect theory, and analyze the game behavior and evolutionary game stability strategies of each subject in turn. Secondly, numerical simulation analysis will be conducted on the relevant risk coefficients, as well as the three party benefit parameters, cost parameters, and coupling parameters. Finally, feasible suggestions are proposed for green agricultural products in e-commerce live streaming. The research results show that: (1) The impact of agricultural product quality inspection level on green agricultural products is not a simple linear relationship, but there are different threshold intervals; (2) Smaller logistics companies are more inclined to choose consignment strategies, while larger logistics companies are more inclined to adopt resale strategies; (3) When the quality inspection level of logistics enterprises is certain, penalty losses do not have a significant impact on farmers’ strategic choices; (4) The lower the cost of loss avoidance, risk aversion coefficient, and the right to know of agricultural products, the higher the risk preference coefficient and the degree of concern for green agricultural products, which is more conducive to the evolution of the three parties to an ideal stable state.

Industry–University–Research (IUR) networks are vital for knowledge sharing and collaborative innovation, yet existing network research largely ignores the maintenance cost of inter-organizational ties, which creates persistent theoretical tension between social capital theory (advocating dense connections) and structural hole theory (advocating sparse non-redundant ties). This study constructs a simulation model integrating barter knowledge exchange and multi-dimensional relational maintenance cost loss and systematically simulates the evolution of average knowledge stock (AKS) under regular, small-world and random network structure. The simulation results show that there exists a stable optimal node degree range of 20–40 for IUR actors, which is robust against changes in network scale, initial knowledge endowment and relational cost coefficients. Under moderate technological complexity, small-world networks realize the highest efficiency of knowledge accumulation; when technological complexity rises to a high level, regular networks with local agglomeration advantages become more efficient. This study supplements a cost-based analytical perspective to reconcile the contradiction between two core network theories and provides preliminary simulation evidence for the contingent design of IUR collaborative networks. From a practical perspective, the findings offer reference for adaptive governance of IUR alliances to balance relational costs and knowledge gains and further respond to the United Nations Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure). Limitations of this simulation-based analysis are clearly acknowledged in the discussion section.