Enhancing Tourist Satisfaction: A Study on Sample Selection Methods
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Abstract
Tourist satisfaction evaluation is one of the key issues of tourism management research, and it can also provide important decision-making references for the development of the tourism service industry and service providers. Based on the micro-data of tourism during China’s National Day Golden Week, this article surveys tourist satisfaction with a tourist attraction. The statistical treatment of the sample selection problem is carried out based on obtaining the sample data. Based on the classical regression, the Heckman model, the Switch model, and the treatment effect model for the statistical treatment of sample selection are compared and studied. From the methodological perspective, the study finds that the statistical method after processing the sample selection problem confirms the absolute positive correlation between tourist income and tourist satisfaction; classical regression does not apply to the analysis of micro cross-section data; the standard Heckman model is less adaptable than the other two methods in dealing with sample selection. On this basis, according to the results of empirical analysis, it is suggested that personalized and differentiated tourism services should be provided according to the different identities of tourists to improve their satisfaction.
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