To resolve problems of information asymmetry and low matching efficiency in freight market, a freight resource sharing platform must provide accurate and readily acceptable vehicle-cargo matching results. We study a two-sided matching model, and analyze the impact of suppliers and demanders’ loss aversion on matching results. We find that users’ loss aversion positively influences the accuracy of vehicle-cargo matching. Next, we construct an evolutionary game model and investigate the trend of users’ strategic selection of the matching results recommended by the platform and the factors influencing their selection. Within their respective limits, the platform’s service level, the users’ initial acceptance probability and waiting cost are found to have a positive impact on the evolutionary trend of users’ acceptance of the matching results. The models are verified using numeric analyses. Several suggestions are made for improving platform matching efficiency.

为了解决货运市场中信息不对称和匹配效率低的问题，货运资源共享平台必须提供准确且易于接受的车辆货物匹配结果。我们研究了一个双向匹配模型，并分析了供应商和需求者的损失厌恶对匹配结果的影响。我们发现用户的损失规避积极地影响了车辆与货物匹配的准确性。接下来，我们构建了一个演化博弈模型，并研究了用户对平台推荐的匹配结果进行战略选择的趋势以及影响他们选择的因素。在各自的限制内，平台的服务水平，用户的初始接受概率和等待成本被发现对用户接受匹配结果的演变趋势具有积极影响。使用数值分析验证模型。为提高平台匹配效率提出了一些建议。