Data_ AI applied in Smart Tourism

Description

Four hundred twenty-nine available questionnaires were collected that meet the sample size to conduct structural equation modeling and the other multivariate analysis. The samples include 196 males (45.7%) and 233 females (54.3%). Most respondents have a bachelor’s degree (78.3%) and are aged from 19 to 40 (92.7%). Students account for the majority of occupations (39.4%), followed by workers/employees (33.8%), public institution staff (18.2%), and civil servants (3.3%). The sample distribution aligns with the visit distribution of general smart tourism attractions without bias. There are two worksheets in the excel file. One is the questionnaire items, the other one is the data.

Steps to reproduce

Data were collected on a platform with a majority population database providing functions equivalent to Amazon Mechanical Turk. The study applied a clustering random sampling approach to select tourists who have traveled to smart tourism attractions covering twenty-two provinces in China.

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