ORIGINAL RESEARCH article
Front. Public Health
Sec. Environmental Health and Exposome
Spatio-Temporal Evolution and Influencing Factors of Cultural Heritage Embedded Cultural Tourism Efficiency
Provisionally accepted
- 1Macao Polytechnic University, Macau, Macao, SAR China
- 2Fuzhou University of International Studies and Trade, Fuzhou, China
- 3Lanzhou University of Finance and Economics, Lanzhou, China
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Enhancing the efficiency of cultural tourism serves as a critical catalyst for the synergistic development of culture and the economy. However, existing research has primarily focused on the content of the cultural tourism industry and its coupling coordination relationships, while comparatively little attention has been given to incorporating key resources – such as cultural heritage – into analytical frameworks access efficiency and underlying impact mechanisms. This study introduces an innovative perspective that embeds cultural heritage within the evaluation process. To address the issue of intertemporal and regional comparability, the Super SBM-DEA model is employed to measure the efficiency of cultural heritage-embedded cultural tourism (CHECTE) across 30 Chinese provinces from 2012 to 2022 and identifies its driving factors through Tobit regression. The findings demonstrate that average efficiency exhibits a "declining-rising-declining" pattern over the observed period. Specifically, efficiency decreased to 0.5829 in 2015, reached a peak of 0.8511 in 2019, and then experienced a subsequently decline. During periods of decline, efficient areas contract toward the central and western regions, whereas during periods of improvements, these areas expand into the southwest and southeast. This spatial dynamic reveals a notable departure from traditional regional economic gradients. The central region attained a higher average efficiency of 0.7499 compared to the eastern region of 0.5746, suggesting that the central region derives greater benefits from cultural heritage resources than its eastern counterpart. Tobit regression results reveal that transportation conditions, informatization level, policy environment, higher education, and technological innovation are the key driving factors, with significant regional differences. The eastern region is primarily driven by technological innovation and consumption demand, the central region by the policy environment and informatization, and the western region by transportation conditions and higher education. This study offers theoretical and practical guidance for resource allocation and region-specific cultural tourism policies.
Keywords: Cultural tourism efficiency, Cultural heritage, Super SBM-DEA, Tobitregression, Spatio-temporal evolution
Received: 22 Aug 2025; Accepted: 25 Nov 2025.
Copyright: © 2025 Lin, Zhang, Feng, Lu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Su Lin
Linjie Feng
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