共享经济相关的商业应用和研究非常火热。但是，共享平台中常常由于供需不平衡而使得平台运作效率下降。目前学术界关注的重点是经济杠杆方法（尤其是价格）在供需平衡以及共享服务使用中的调节机理和效果。有研究表明，这种机制运作下，供给侧和需求侧的波动难以避免。考虑到消费者和服务供给者在共享平台上驻留时间的分布差异，本项目引入海量消费者数据，在深入挖掘消费者平台系统复用行为和平台产品消费行为的基础上，提出将消费者行为预测结果引入到共享运作机制分析中，进而提高平台的运作效率的新思路。该方向的研究成果可以在技术创新、理论分析和产业应用上有潜在价值。

Commercial application of and research on sharing economy has attracted a lot of attention. However, imbalance between supply and demand in sharing platforms often leads to reduced operational efficiency of these platforms. The extant literature pays much attention to adjusting mechanisms and effects of economic leverage (especially prices) in balancing supply and demand and using sharing services. But, some research reveals that supply-side or demand-side fluctuations cannot be avoided via the economic leverage. Considering the distributional difference of staying time between consumers and sharing service providers on a sharing platform, this project introduces massive consumers’ data and implements data mining of consumers’ revisiting behaviors of sharing platforms and buying behaviors of platform’s products. Based on those result, this project proposes a new framework which incorporates the forecast of consumers’ behaviors into the analysis of sharing operational mechanism to further improve operational efficiency of sharing platforms. This framework has full potentials in technological innovation, theoretical analysis, and industrial application.