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The Interaction and Sustainable Efficiency Between Tourism Systems and the Energy–Economy–Environment System: A Novel Parallel Network Super-Efficiency Slacks-Based Measure Model

Author

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  • Zhijian Chen

    (College of Transportation & Communications, Shanghai Maritime University, Shanghai 201306, China
    Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518057, China)

  • Jiqiang Zhao

    (Zhejiang Province Key Think Tank, Institute of Ecological Civilization, Zhejiang A&F University, Hangzhou 311300, China
    School of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China)

  • Xinqiang Chen

    (Logistics Science and Engineering Research Institute, Shanghai Maritime University, Shanghai 201306, China)

Abstract

Sustainable tourism entails balancing economic growth, environmental protection, and energy utilisation. However, the current interactive dynamics between urban agglomeration tourism systems and the energy–economy–environment (EEE) system, as well as the sustainable efficiency of the tourism–energy–economy–environment (TEEE) system, remain unclear. For the first time, this study employs a super-efficiency network slacks-based measure (SE-NSBM) model to interact with tourism and EEE systems, proposing a novel network structure that includes feedback variables. To validate the proposed model, this study evaluated the efficiency of the TEEE system and its subsystems in the Yangtze River Delta urban agglomeration (YRDUA) from 2016 to 2020. The study revealed significant variations in the efficiency of the TEEE, tourism, and EEE systems among cities in the YRDUA, with a discernible downward trend. The TEEE and tourism systems exhibit relatively weak coping capabilities when faced with significant unforeseen events, highlighting the urgent need to strengthen system resilience. The results also demonstrate that the new model effectively resolves the issue of efficiency overestimation in the TEEE system observed in traditional models, which tend to overestimate actual efficiency by 3%. The novel model and empirical results offer decision-makers new perspectives and practical insights into formulating sustainable tourism policies.

Suggested Citation

  • Zhijian Chen & Jiqiang Zhao & Xinqiang Chen, 2024. "The Interaction and Sustainable Efficiency Between Tourism Systems and the Energy–Economy–Environment System: A Novel Parallel Network Super-Efficiency Slacks-Based Measure Model," Sustainability, MDPI, vol. 16(23), pages 1-21, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:23:p:10520-:d:1533652
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    1. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    5. Zhao, Jiqiang & Wu, Xianhua & Guo, Ji & Gao, Chao, 2022. "Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model," Applied Energy, Elsevier, vol. 325(C).
    6. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    7. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    8. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    9. Feng, Chenpeng & Chu, Feng & Ding, Jingjing & Bi, Gongbing & Liang, Liang, 2015. "Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA," Omega, Elsevier, vol. 53(C), pages 78-89.
    10. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "DEA-like models for the efficiency evaluation of hierarchically structured units," European Journal of Operational Research, Elsevier, vol. 154(2), pages 465-476, April.
    11. Chen, Shanshan & Zhang, Ruchuan & Li, Peiwen & Li, Aijun, 2023. "How to improve the performance of China's energy-transport-economy-environment system: An analysis based on new strategy parallel-series input-output data envelopment analysis models," Energy, Elsevier, vol. 281(C).
    12. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    13. Rajinder Kaur & Jolly Puri, 2024. "Analysing cost-effectiveness in dynamic network DEA: a directional distance function approach," Operational Research, Springer, vol. 24(4), pages 1-31, December.
    14. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
    15. Song, Malin & Li, Hui, 2019. "Estimating the efficiency of a sustainable Chinese tourism industry using bootstrap technology rectification," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 45-54.
    16. 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.
    17. Duras, Toni & Javed, Farrukh & Månsson, Kristofer & Sjölander, Pär & Söderberg, Magnus, 2023. "Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data," Energy Economics, Elsevier, vol. 120(C).
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