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Measurement of Tourism Ecological Efficiency and Analysis of Influencing Factors under the Background of Climate Change: A Case Study of Three Provinces in China’s Cryosphere

Author

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  • Yubin Wu

    (School of Accounting, Lanzhou University of Finance and Economics, Lanzhou 730020, China)

  • Feiyang He

    (School of Accounting, Lanzhou University of Finance and Economics, Lanzhou 730020, China)

  • Zhujun Sun

    (School of Accounting, Lanzhou University of Finance and Economics, Lanzhou 730020, China)

  • Yongyu Wang

    (School of Statistics and Data Science, Lanzhou University of Finance and Economics, Lanzhou 730020, China)

Abstract

Against the backdrop of climate change and the “dual carbon” goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as “climate change, carbon emission constraints, and cryospheric resources” into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment.

Suggested Citation

  • Yubin Wu & Feiyang He & Zhujun Sun & Yongyu Wang, 2024. "Measurement of Tourism Ecological Efficiency and Analysis of Influencing Factors under the Background of Climate Change: A Case Study of Three Provinces in China’s Cryosphere," Sustainability, MDPI, vol. 16(14), pages 1-24, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:6085-:d:1436509
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    References listed on IDEAS

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    1. Quariguasi Frota Neto, J. & Walther, G. & Bloemhof, J. & van Nunen, J.A.E.E. & Spengler, T., 2009. "A methodology for assessing eco-efficiency in logistics networks," European Journal of Operational Research, Elsevier, vol. 193(3), pages 670-682, March.
    2. Gössling, Stefan & Peeters, Paul & Ceron, Jean-Paul & Dubois, Ghislain & Patterson, Trista & Richardson, Robert B., 2005. "The eco-efficiency of tourism," Ecological Economics, Elsevier, vol. 54(4), pages 417-434, September.
    3. Kytzia, Susanne & Walz, Ariane & Wegmann, Mattia, 2011. "How can tourism use land more efficiently? A model-based approach to land-use efficiency for tourist destinations," Tourism Management, Elsevier, vol. 32(3), pages 629-640.
    4. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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