Research on Tourist Satisfaction Improvement Path Based on Multiple Regression Analysis in Tourism Management

As the core service object of the tourism industry, tourists' satisfaction with a tourist destination is an important influencing factor for the sustainable development of the tourism industry there. This paper proposes a set of tourist satisfaction index system containing a total of 20 secondary indicators from five perspectives: feeling experience, emotional experience, thinking experience, action experience, and association experience. And set the satisfaction of tourists' experience as the dependent variable, and 5 level 1 indicators as the independent variables. At the same time, IPA analysis was selected as the method of measuring tourist satisfaction, factor analysis as the method of testing the reliability and validity of the indicator system, and multiple linear regression prediction model as the method of analyzing the intrinsic relationship between the dependent indicator and multiple independent indicators. Taking K scenic spot as the experimental object, the potential relationship between dependent and independent variables is analyzed based on sample data. Among them, emotional experience has the greatest positive effect on tourist satisfaction, with a regression coefficient of 1.677. Accordingly, in tourism management, the emotional experience of tourists should be the first consideration, and the overall satisfaction should be promoted by providing a good emotional experience.