Impact of Task-Technology Fit on Improving the Performance of Meituan Application

Abstract

In this paper, the impact of task-technology fit (TTF) on improving the performance of Meituan app is explored. Nowadays, with broad research scope, the research on TTF covers many fields, and it is found to be applicable to many fields. However, few scholars have researched about performance from the perspective of TTF. Therefore, with the help of the structural equation model (SEM), attitudes have been empirically verified and analyzed to build a structural model involving TTF, attitudes, user behavior, and performance in this paper. The results showed that the fit degree of task technology significantly affects the performance of Meituan app positively, and attitudes positively affect the user behavior of Meituan app users. Moreover, the two factors directly affect the performance of Meituan app, among which the user behavior of Meituan app users positively affects its performance. In addition, suggestions, such as continuously optimizing users’ feedback and giving users positive responses in terms of user experience, have been proposed, so that they will continue using the application (app).