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Influence of Chinese economic fluctuations on tourism efficiency in national scenic areas

Author

Listed:
  • Fangdong Cao

    (Nanjing Normal University, China)

  • Zhenfang Huang

    (Nanjing Normal University, China)

  • Cheng Jin

    (Nanjing Normal University, China)

  • Min Xu

    (Nanjing Normal University, China)

Abstract

This article measures and calculates tourism efficiency in Chinese national scenic areas. In order to analyse the characteristics of multi-scale fluctuations, the empirical mode decomposition (EMD) and wavelet decomposition methods are adopted. Specific Chinese national scenic areas are divided into several zones, with conclusions provided about the impact of economic fluctuations on their tourism efficiency. The results are as follows. The tourism efficiency of Chinese national scenic areas overall is not high; most have not yet reached data envelopment analysis (DEA) optimization; and the quasiperiodicity of scenic areas’ tourism efficiency mainly fluctuates between 2.42 and 9.67 years. Owing to the effects of extraneous factors, the significance of pure technical efficiency declined, which illustrates that economic development could promote technological progress, but technological progress is not a sufficient and necessary condition of economic development; studies of different periods show that a downward economic fluctuation will also facilitate technological improvement and promotion, which is the embodiment of the inverse periodicity of technological progress.

Suggested Citation

  • Fangdong Cao & Zhenfang Huang & Cheng Jin & Min Xu, 2016. "Influence of Chinese economic fluctuations on tourism efficiency in national scenic areas," Tourism Economics, , vol. 22(5), pages 884-907, October.
    • Handle: RePEc:sae:toueco:v:22:y:2016:i:5:p:884-907
    DOI: 10.5367/te.2015.0463
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    References listed on IDEAS

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    Cited by:

    1. Gaojun Zhang & Jinfeng Wu & Bing Pan & Junyi Li & Minjie Ma & Muzi Zhang & Jian Wang, 2017. "Improving daily occupancy forecasting accuracy for hotels based on EEMD-ARIMA model," Tourism Economics, , vol. 23(7), pages 1496-1514, November.
    2. Hongwei Liu & Chenchen Gao & Henry Tsai, 2024. "Spatial spillover and determinants of tourism efficiency: A low carbon emission perspective," Tourism Economics, , vol. 30(3), pages 543-566, May.
    3. Vatsa, Puneet, 2020. "Comovement amongst the demand for New Zealand tourism," Annals of Tourism Research, Elsevier, vol. 83(C).
    4. Dan Xue & Xianzong Li & Fayyaz Ahmad & Nabila Abid & Zulqarnain Mushtaq, 2022. "Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    5. Vatsa, Puneet, 2021. "Seasonality and cycles in tourism demand—redux," Annals of Tourism Research, Elsevier, vol. 90(C).
    6. Yongcuomu Qu & Ziqiong Zhang & Yanchao Feng & Xiaorong Cui, 2021. "How Do Chinese National Scenic Areas Affect Tourism Economic Development? The Moderating Effect of Time-Limited Rectification," IJERPH, MDPI, vol. 18(21), pages 1-11, November.
    7. Pengfei Zhang & Hu Yu & Mingzhe Shen & Wei Guo, 2022. "Evaluation of Tourism Development Efficiency and Spatial Spillover Effect Based on EBM Model: The Case of Hainan Island, China," IJERPH, MDPI, vol. 19(7), pages 1-21, March.
    8. Guang Chu & Liangjian Yang & Jinhe Zhang & Tian Wang & Yingjia Dong & Zhangrui Qian, 2024. "Navigating the Efficiency Landscape: A Data Envelopment Analysis of Tourist Resorts in Jiangsu Province for Optimized Socio-Economic Benefits," Sustainability, MDPI, vol. 16(4), pages 1-21, February.

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