Residents' participation in rural tourism and interpersonal trust in tourists: The mediating role of residents' perceptions of tourism impacts

Interpersonal trust is a critical psychological factor that reveals the quality of resident-tourist relationship in tourism destinations. However, residents' positive attitudes toward tourists are gradually taken for granted, with research on residents' psychological tendency (i.e., interpersonal trust) in providing tourism services and creating mutually beneficial resident-tourist interaction lagging behind. Based on interpersonal relationship theory and social exchange theory, this study employed a sequential mixed-methods design to examine the formation of interpersonal trust in tourists during resident participation in rural tourism. The dimensions of resident participation (i.e., decision-making, economic, and social participation) and the conceptual model were first identified through qualitative analysis. Subsequently, through the PLS-based structural equation modeling using a sample of 469 residents from Jiuzhai Valley, China, the study suggested that economic and social participation were instrumental in shaping residents' cognitive and affective trust in tourists both directly and indirectly through residents' perceived benefits of tourism. This study offers implications for academia and destination management to promote sustainable tourism development and social harmony against the crisis of trust between residents and tourists caused by the COVID-19 pandemic.

ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19.

As a large agricultural country, China's vegetable prices affect the increase in production and income of farmers and the daily life of urban and rural residents and influence the healthy development of Chinese agriculture. 51,567 vegetable price data of 2020 are analyzed to determine the factors that influence vegetable price fluctuations in two dimensions (vertical and horizontal) in the special context of the COVID-19, and an ARIMA model of short-term price prediction is then employed and evaluated. Based on the factors affecting vegetable prices, the results of the model are further examined. Finally, pertinent suggestions are made for the development of the local vegetable industry in the post-epidemic era.