With both cost and safety taken into account in the context of the life-threatening COVID-19 pandemic globally, rural tourism is expected to be the top choice for Chinese residents for relaxation and enhancing parent-child relationships. In this paper, a structural equation (SEM) model was proposed to compare risk knowledge, risk perception, risk aversion attitudes and behavioral intentions towards rural tourism. According to the empirical results, there was a large proportion of tourists showing preference for rural tourism recently. Potential participants in rural tourism paid most attention to the performance realization and time cost of scenic spots, while the psycho-social risk posed by COVID-19 had little impact. The inherent risk nature of risk aversion attitudes made knowledge of the pneumonia risk less effective in reducing tourists’ intentions, while knowledge of the pneumonia risk was more effective in alleviating the risk perception that potential tourists have towards rural tourism. With regard to travel intention and recommendation intention of rural tourism, the negative impacts of risk aversion attitude were more considerable compared to risk perception. Meanwhile, the parallel mediating effect of risk perception and risk aversion attitude in rural tourism needed to be taken into consideration together.

Focusing on urban–rural development issues, this paper analyzes the necessity of coordinated development between the narrowing gap and integral development. An overall urban– rural development dynamic model aimed at two major objectives is pointed out. A principal component analysis (PCA)—Grey Entropy measurement model is proposed to evaluate urban–rural coordination from economic development, social security, public services, and environmental quality perspectives. In this model, principal component analysis (PCA) was used to extract the components that explained overall urban–rural coordination. This model was then combined with Grey Entropy to measure the level of urban–rural development coordination. By establishing a scientific measurement model, the coordination value of the rural and urban areas was effectively calculated from a comprehensive perspective, including subsystems and static and dynamic coordination values. Finally, the model was applied to Sichuan Province as an example to show its effectiveness in measuring urban–rural coordination.