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Coupling coordination analysis with data-driven technology for disaster–economy–ecology system: an empirical study in China

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Abstract

Nowadays, frequent meteorological disasters that cause huge economic losses and ecological damages have swept the world. Thus, research investigates how to overcome the adverse impacts of storm debris flow by exploring sustainable interaction among disaster, economy, and ecology. To achieve this goal, the study analyzes coupling coordination for disaster–economy–ecology system through data-driven technology named Scrapy engine. To be specific, a comprehensive index system of disaster–economy–ecology is established. Accordingly, a projection pursuit method is used to reduce the dimensions of data involved in the system. Then, an integrated weighting method of interval-valued hesitant fuzzy entropy and maximum deviation of weight is utilized. For further analysis of the internal laws in disaster–economy–ecology system, a coupling coordination model based on order preference by similarity to ideal solution is proposed. Moreover, a back-propagation artificial neural network is designed to identify the key influencing factors in disaster–economy–ecology system. Finally, an empirical study is carried out using the panel data related to storm debris flow of 31 provincial areas in China within 11 years to illustrate the study. The study results show that the overall sustainable development of disaster, economy, and ecology in China does not achieve an ideal status. Various measures based on local conditions are required to improve the imbalanced development of disaster–economy–ecology system in different areas of China. At last, strategic suggestions for sustainable development of disaster–economy–ecology system are provided.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 71801135), the Natural Science Foundation of Jiangsu Province (Grant No. BK20180792), the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No. 19YJC630063), the Sichuan Science and Technology Program (Grant No. 2020YJ0365 and 2020JDR0209), the Chengdu Science and Technology (Grant No. 2019-RK00-00311-ZF), and the Chengdu Philosophy and Social Science Planning Research Funds (Grant No. 2019L12).

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Authors and Affiliations

  1. College of Architecture and Urban-Rural Planning, Sichuan Agricultural University, Dujiangyan, 611830, China

    Lu Gan, Yuanyuan Wang & Wen Jiang

  2. School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China

    Yusheng Wang

  3. LeBow College of Business, Drexel University, Philadelphia, PA, 19104, USA

    Lu Gan, Benjamin Lev & Wenjing Shen

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  1. Lu Gan
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  6. Wen Jiang
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Correspondence to Yusheng Wang or Wen Jiang.

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Gan, L., Wang, Y., Wang, Y. et al. Coupling coordination analysis with data-driven technology for disaster–economy–ecology system: an empirical study in China. Nat Hazards 107, 2123–2153 (2021). https://doi.org/10.1007/s11069-021-04787-6

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