IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i22p12437-d676519.html
   My bibliography  Save this article

Road Weather Monitoring System Shows High Cost-Effectiveness in Mitigating Malfunction Losses

Author

Listed:
  • Jingyan Wu

    (Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Saini Yang

    (Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China
    Academy of Disaster Reduction and Emergency Management, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China)

  • Feng Yang

    (Highway Monitoring and Response Center, Ministry of Transport of China, Beijing 100029, China)

  • Xihui Yin

    (Highway Monitoring and Response Center, Ministry of Transport of China, Beijing 100029, China)

Abstract

Understanding the environmental impacts of road networks and the success of policy initiatives is crucial to a country’s socioeconomic development. In this study, we propose a comprehensive approach to quantitatively assessing whether a given response is effective in mitigating the impacts of environmental shocks on roads. Our approach includes factor analysis, direct and indirect loss quantification, and cost-benefit analysis. Using nationwide data on road malfunctions and weather service performance in China, we found that the macro-level indirect economic losses from road malfunctions were more than the direct losses in multiples ranging from 11 to 21, and that information provided by the weather service could reduce losses, with benefits exceeding costs by a ratio of 51. The results of our study provide a quantitative tool as well as evidence of the effectiveness of sustainability investment, which should provide guidance for future disaster mitigation, infrastructure system resilience, and sustainability-building policy-making.

Suggested Citation

  • Jingyan Wu & Saini Yang & Feng Yang & Xihui Yin, 2021. "Road Weather Monitoring System Shows High Cost-Effectiveness in Mitigating Malfunction Losses," Sustainability, MDPI, vol. 13(22), pages 1-13, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12437-:d:676519
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/22/12437/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/22/12437/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Giuseppe Galiano & Laura Moretti, 2021. "Consistency of Urban Roads to Manage Emergencies: Methodology to Identify the Minimum Network with Total Connectivity at Maximum Availability," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    2. 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.
    3. Alises, Ana & Vassallo, Jose Manuel & Guzmán, Andrés Felipe, 2014. "Road freight transport decoupling: A comparative analysis between the United Kingdom and Spain," Transport Policy, Elsevier, vol. 32(C), pages 186-193.
    4. Lu, Huapu & Chen, Mingyu & Kuang, Wenbo, 2020. "The impacts of abnormal weather and natural disasters on transport and strategies for enhancing ability for disaster prevention and mitigation," Transport Policy, Elsevier, vol. 98(C), pages 2-9.
    5. Schweikert, Amy & Chinowsky, Paul & Kwiatkowski, Kyle & Espinet, Xavier, 2014. "The infrastructure planning support system: Analyzing the impact of climate change on road infrastructure and development," Transport Policy, Elsevier, vol. 35(C), pages 146-153.
    6. Yingliang Zhou & Qiwei Jiang & Jin Qin, 2019. "Pre-Disaster Retrofit Decisions for Sustainable Transportation Systems in Urban Areas," Sustainability, MDPI, vol. 11(15), pages 1-18, July.
    7. Laura Moretti & Giuseppe Loprencipe, 2018. "Climate Change and Transport Infrastructures: State of the Art," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    8. Mariacrocetta Sambito & Alessandro Severino & Gabriele Freni & Larysa Neduzha, 2021. "A Systematic Review of the Hydrological, Environmental and Durability Performance of Permeable Pavement Systems," Sustainability, MDPI, vol. 13(8), pages 1-12, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yaning Qiao & Andrew R. Dawson & Tony Parry & Gerardo Flintsch & Wenshun Wang, 2020. "Flexible Pavements and Climate Change: A Comprehensive Review and Implications," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    2. Zhong Fang & Yung-ho Chiu & Tai-Yu Lin & Tzu-Han Chang & Yi-Nuo Lin, 2024. "Analysis of natural disasters and energy efficiency in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(5), pages 10999-11026, May.
    3. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    4. repec:lan:wpaper:1115 is not listed on IDEAS
    5. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    6. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    7. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    8. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    9. Bowlin, W. F., 1995. "A characterization of the financial condition of the United States' aerospace-defense industrial base," Omega, Elsevier, vol. 23(5), pages 539-555, October.
    10. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    11. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    12. Helmi Hammami & Thanh Ngo & David Tripe & Dinh-Tri Vo, 2022. "Ranking with a Euclidean common set of weights in data envelopment analysis: with application to the Eurozone banking sector," Annals of Operations Research, Springer, vol. 311(2), pages 675-694, April.
    13. Khanal, Aditya & Koirala, Krishna & Regmi, Madhav, "undated". "Do Financial Constraints Affect Production Efficiency in Drought Prone Areas? A Case from Indonesian Rice Growers," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230087, Southern Agricultural Economics Association.
    14. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    15. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    16. Bogetoft, Peter & Nielsen, Kurt, 2003. "Yardstick Based Procurement Design In Natural Resource Management," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25910, International Association of Agricultural Economists.
    17. Singer, Marcos & Donoso, Patricio & Poblete, Francisco, 2002. "Semi-autonomous planning using linear programming in the Chilean General Treasury," European Journal of Operational Research, Elsevier, vol. 140(2), pages 517-529, July.
    18. Chai, Naijie & Zhou, Wenliang & Hu, Xinlei, 2022. "Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China," Transport Policy, Elsevier, vol. 125(C), pages 267-288.
    19. Fang, Lei, 2022. "Measuring and decomposing group performance under centralized management," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1006-1013.
    20. Chih-HAI YANG & WU Leah & Hui-Lin LIN, 2010. "Analysis of total-factor cultivated land efficiency in China's agriculture," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 56(5), pages 231-242.
    21. Jinyi Hu, 2023. "Linguistic Multiple-Attribute Decision Making Based on Regret Theory and Minimax-DEA," Mathematics, MDPI, vol. 11(20), pages 1-14, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12437-:d:676519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.