Author
Listed:
- Haifei Wang
- Hassan Zargarzadeh
Abstract
The focus on high-quality development in regional tourism involves not only transforming the previous extensive development model and improving the efficiency of tourism development but also promoting the coordinated development of the tourism industry across different regions. Taking the 21 prefecture-level cities in Guangdong Province as the research object and guided by high-quality development, a tourism efficiency measurement index system that includes carbon emissions as an unexpected output has been established. By comprehensively applying methods such as the Super-SBM model, LISA temporal path, and standard deviation ellipse, this study addresses the neglect of spatial relationships in the existing literature and measures the tourism efficiency of Guangdong’s 21 prefecture-level administrative units from 2009 to 2019, exploring its spatiotemporal evolution and collaborative trends. The results show that during the research period, the average tourism efficiency in Guangdong Province was 0.807, at a medium–high efficiency level. Spatially, the tourism efficiency of the province is composed of a main peak and side peaks, with a general leftward shift of the main peak, a fluctuating decrease in peak height, and an expanding width. The evolution of spatial patterns reveals that regions with similar tourism efficiency in Guangdong tend to be spatially concentrated, with strong local stability and clear spatial dependency in the change process of tourism efficiency. The study’s insights suggest strategies for Guangdong’s tourism sector, advocating for technological innovation, sustainable development practices, and a robust evaluation framework. It emphasizes leveraging regional tourism assets, fostering collaboration, and promoting the “Great Lingnan Tourism Circle†for a balanced industry growth.
Suggested Citation
Haifei Wang & Hassan Zargarzadeh, 2024.
"Spatiotemporal Differences in Regional Tourism Efficiency: An Empirical Study From Guangdong Province, China,"
Complexity, Hindawi, vol. 2024, pages 1-15, November.
Handle:
RePEc:hin:complx:5781877
DOI: 10.1155/2024/5781877
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