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A new approach for vehicle-health system measurement by network data envelopment analysis and an application in the USA

Author

Listed:
  • Ruchuan Zhang

    (Shandong School of Development, Shandong University)

  • Aijun Li

    (Shandong School of Development, Shandong University)

  • Davo Ayuba Dahoro

    (Shandong School of Development, Shandong University)

Abstract

Public health and climate change mitigation are strongly related to the efficiency of a unified vehicle-health system. To date, however, the existing DEA studies have not incorporated a robust set of transportation and public health indicators to evaluate the performance of the vehicle-health system. Our approach maps the relationship between transportation and health indicators in a network DEA framework. In addition, this study develops a new methodological framework for identifying stage priorities for decision-makers, peer evaluation and an understanding of the effects of policy in a comprehensive vehicle-health production system. This study empirically evaluates indicators of vehicle use and their effects on public health for each US state. The main conclusions are summarized: First, the network DEA and cross-efficiency network DEA models have significant methodological differences, highlighting the importance of model selection for empirical analysis. Second, US states exhibit enormous disparities in their prior strategies. The relative weights of the vehicle use stage and health outcomes stage confirm differing levels of importance attached to either stage. Third, group heterogeneity and technology inequality are observed among US states. Both intra-group and inter-group inequalities drive technology inequality. Moreover, considerable heterogeneity exists in the intra-group decomposition of the overall efficiency Theil index among the three network DEA models. Finally, promoting a safe and integrated transportation network improves vehicle-health performance, implying that strategic transportation policies hold significant potential for improving public health.

Suggested Citation

  • Ruchuan Zhang & Aijun Li & Davo Ayuba Dahoro, 2024. "A new approach for vehicle-health system measurement by network data envelopment analysis and an application in the USA," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(6), pages 14693-14727, June.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:6:d:10.1007_s10668-023-03213-0
    DOI: 10.1007/s10668-023-03213-0
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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. Chen, Yao & Liang, Liang & Zhu, Joe, 2009. "Equivalence in two-stage DEA approaches," European Journal of Operational Research, Elsevier, vol. 193(2), pages 600-604, March.
    3. Chen, Chialin & Zhu, Joe & Yu, Jiun-Yu & Noori, Hamid, 2012. "A new methodology for evaluating sustainable product design performance with two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 221(2), pages 348-359.
    4. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    5. Chen, Chailin & Cook, Wade D. & Imanirad, Raha & Zhu, Joe, 2020. "Balancing Fairness and Efficiency: Performance Evaluation with Disadvantaged Units in Non-homogeneous Environments," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1003-1013.
    6. Panagiotis Mitropoulos, 2021. "Production and quality performance of healthcare services in EU countries during the economic crisis," Operational Research, Springer, vol. 21(2), pages 857-873, June.
    7. Simone Schenkman & Aylene Bousquat & Maria Paula Ferreira, 2022. "Efficiency Analysis in Brazil’s Sao Paulo State Local Unified Health System (SUS): From Gender-Ethnicity-Power Inequities to the Dissolution of Health Effectiveness," IJERPH, MDPI, vol. 19(5), pages 1-22, March.
    8. 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.
    9. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    10. Beata Gavurova & Kristina Kocisova & Jakub Sopko, 2021. "Health system efficiency in OECD countries: dynamic network DEA approach," Health Economics Review, Springer, vol. 11(1), pages 1-25, December.
    11. Xu, Chong & Wang, Bingjie & Chen, Jiandong & Shen, Zhiyang & Song, Malin & An, Jiafu, 2022. "Carbon inequality in China: Novel drivers and policy driven scenario analysis," Energy Policy, Elsevier, vol. 170(C).
    12. Li, Haitao & Chen, Chialin & Cook, Wade D. & Zhang, Jinlong & Zhu, Joe, 2018. "Two-stage network DEA: Who is the leader?," Omega, Elsevier, vol. 74(C), pages 15-19.
    13. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    14. Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2019. "Cross-efficiency evaluation in data envelopment analysis based on prospect theory," European Journal of Operational Research, Elsevier, vol. 273(1), pages 364-375.
    15. Yang, Guo-liang & Yang, Jian-bo & Liu, Wen-bin & Li, Xiao-xuan, 2013. "Cross-efficiency aggregation in DEA models using the evidential-reasoning approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 393-404.
    16. Porter, J.M. & PhD, S.L. & Bryan, S.J. & Arseniadis, K. & Caldwell, L.P. & Corso, P.S. & Lee, J.M. & Davis, M., 2018. "Law accommodating nonmotorized road users and pedestrian fatalities in Florida, 1975 to 2013," American Journal of Public Health, American Public Health Association, vol. 108(4), pages 525-531.
    17. Hwang, Shiuh-Nan & Chen, Chialin & Chen, Yao & Lee, Hsuan-Shih & Shen, Pei-Di, 2013. "Sustainable design performance evaluation with applications in the automobile industry: Focusing on inefficiency by undesirable factors," Omega, Elsevier, vol. 41(3), pages 553-558.
    18. Lim, Dong-Joon, 2016. "Inverse DEA with frontier changes for new product target setting," European Journal of Operational Research, Elsevier, vol. 254(2), pages 510-516.
    19. Lee, Hsuan-Shih, 2021. "Efficiency decomposition of the network DEA in variable returns to scale: An additive dissection in losses," Omega, Elsevier, vol. 100(C).
    20. Kao, Chiang, 2018. "A classification of slacks-based efficiency measures in network data envelopment analysis with an analysis of the properties possessed," European Journal of Operational Research, Elsevier, vol. 270(3), pages 1109-1121.
    21. See, Kok Fong & Md Hamzah, Nurhafiza & Yu, Ming-Miin, 2021. "Metafrontier efficiency analysis for hospital pharmacy services using dynamic network DEA framework," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
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