A study on the impact of user behavior in the perspective of multiple regression analysis for the green sharing economy

With the continuous transformation and upgrading of the economy and society and the continuous improvement of people’s income levels, the importance of green consumption in the economy is gradually emerging. In this paper, the article takes the sharing tourism app as an experimental object. First of all, using a multiple regression model to put forward relevant assumptions for research, and with the characteristics of the sharing economy, the characteristics of the sharing tourism APP variables, on the basis of which the theoretical model framework is constructed. The four variables of performance expectation, effort expectation, social factors, and facilitating factors are measured simultaneously across different dimensions. The data obtained from the questionnaire distributed to users using the shared tourism app were modeled and tested using SPSS to ensure the reasonableness of the questionnaire and the validity of the scale data. Finally, the correlation analysis of the obtained data was carried out, and the multiple regression model was used for analysis and robustness test, which concluded that the effort expectation, the willingness to use, and the social influence would affect the behavior of users using the shared tourism APP. The regression coefficients for behavioral influence are 0.216, 0.212, and 0.185, respectively. The results of the study show that in the green sharing economy, users’ behavior will be affected by multiple factors, and there will be instability.