earticle

영어

The aim of this study is to explore the key antecedent condition combinations that influence the impact of AI technology on the deep and sustainable development of tourism and cultural resources through qualitative comparative analysis (QCA) methods. We set strict analysis criteria and consider geographical differences to analyze the impact of different combinations of conditions on the results. In terms of research methodology, we use group analysis techniques to identify three different patterns of antecedent condition combinations. These patterns reveal that factors such as industrial structure, government policies, market demand and enterprise R&D investment are driving the indepth development of tourism and cultural resources by AI technology. The results of the study show that the value added rate of the secondary industry, local financial expenditures in specific areas, the consumption index, and the input of R&D personnel in industrial enterprises are the key factors influencing the in-depth development of tourism and cultural resources by AI technology. These factors show variability in different regions, but have relative stability in general. The significance of the study is to provide theoretical support and empirical evidence for the innovation of AI technology on the in-depth development of tourism and cultural resources, which will help policy makers to formulate more targeted policy measures and promote the sustainable development of AI technology on the in-depth development of tourism and cultural resources.