Using Big Data and Empirical Analysis to Optimize The Decision-Making of Smart City Tourism Logistics Service System

Abstract

As an emerging service industry, tourism logistics can affect the response of the city's major business operators. Tourism cities can improve logistics services through system optimization, so as to achieve operator satisfaction. This research uses urban big data, through data collection, questionnaire survey, empirical analysis using SPSS and Amos software, etc., to explore the components of tourism logistics service quality and its relationship with the satisfaction of tourism destination operators. The results show that tourism logistics service quality and its dimensions have a positive impact on the satisfaction of tourism destination operators, and consumer emotion and consumer cognition play a partial mediating role in the impact of tourism logistics service quality on operator satisfaction.