IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v111y2022i1d10.1007_s11069-021-05046-4.html
   My bibliography  Save this article

Accessing performance of transport sector considering risks of climate change and traffic accidents: joint bounded-adjusted measure and Luenberger decomposition

Author

Listed:
  • Xiaodong Chen

    (Sichuan Agricultural University)

  • Anda Guo

    (Sichuan Agricultural University)

  • Jiahao Zhu

    (Sichuan Agricultural University)

  • Fang Wang

    (Sichuan Agricultural University)

  • Yanqiu He

    (Sichuan Agricultural University)

Abstract

Green transformation of energy use in China’s transport sector will promote sustainable development in the country. This paper extends the Bounded-adjusted Measure and Luenberger indicators to detect the performance of China’s inland transport sector across 2006–2015. In the framework, the climate change and traffic accident risks are taken as undesirable outputs. In addition, source-specific and variable-specific decomposition are proposed for investigating the sources of inefficiency and productivity, and quantifying the contributions of climate change and traffic accident risks. This paper opens up the “black box” of technological progress, identifying the different channels (i.e., quantity and time-dimensions) through which affect economic growth. Therefore, policymakers can find out the most effective pathway to boost productivity growth and mitigate climate change and traffic accident risks in the transport sector, which are ignored in the conventional framework. Empirical results indicate great variances exist among 30 provinces in inefficiency scores, productivity change, and technological progress. Hence, classified regulations help to tackle this issue. We clustered 30 provinces into 4 groups according to their technological progress along quantity and time-dimensions. Variable-wise, CO2 emission-reduction and civil vehicle gains promote the TFP gains most. Also, we verify that economic development and environmental regulations can coordinate to promote the sustainable development of the transport sector.

Suggested Citation

  • Xiaodong Chen & Anda Guo & Jiahao Zhu & Fang Wang & Yanqiu He, 2022. "Accessing performance of transport sector considering risks of climate change and traffic accidents: joint bounded-adjusted measure and Luenberger decomposition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 115-138, March.
  • Handle: RePEc:spr:nathaz:v:111:y:2022:i:1:d:10.1007_s11069-021-05046-4
    DOI: 10.1007/s11069-021-05046-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-05046-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-021-05046-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Miao, Zhuang & Chen, Xiaodong & Baležentis, Tomas, 2021. "Improving energy use and mitigating pollutant emissions across “Three Regions and Ten Urban Agglomerations”: A city-level productivity growth decomposition," Applied Energy, Elsevier, vol. 283(C).
    2. Fleisher, Belton & Li, Haizheng & Zhao, Min Qiang, 2010. "Human capital, economic growth, and regional inequality in China," Journal of Development Economics, Elsevier, vol. 92(2), pages 215-231, July.
    3. Seufert, Juergen Heinz & Arjomandi, Amir & Dakpo, K. Hervé, 2017. "Evaluating airline operational performance: A Luenberger-Hicks-Moorsteen productivity indicator," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 52-68.
    4. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    5. 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.
    6. Li, Tao & Yang, Wenyue & Zhang, Haoran & Cao, Xiaoshu, 2016. "Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China," Transport Policy, Elsevier, vol. 45(C), pages 66-76.
    7. Lisann Krautzberger & Heike Wetzel, 2012. "Transport and CO 2 : Productivity Growth and Carbon Dioxide Emissions in the European Commercial Transport Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 53(3), pages 435-454, November.
    8. Tian, Yihui & Zhu, Qinghua & Lai, Kee-hung & Venus Lun, Y.H., 2014. "Analysis of greenhouse gas emissions of freight transport sector in China," Journal of Transport Geography, Elsevier, vol. 40(C), pages 43-52.
    9. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation," Energy Economics, Elsevier, vol. 33(2), pages 292-303, March.
    10. William Cooper & Jesús Pastor & Fernando Borras & Juan Aparicio & Diego Pastor, 2011. "BAM: a bounded adjusted measure of efficiency for use with bounded additive models," Journal of Productivity Analysis, Springer, vol. 35(2), pages 85-94, April.
    11. Boussemart, Jean-Philippe & Ferrier, Gary D. & Leleu, Hervé & Shen, Zhiyang, 2020. "An expanded decomposition of the Luenberger productivity indicator with an application to the Chinese healthcare sector," Omega, Elsevier, vol. 91(C).
    12. Pilli-Sihvola, Karoliina & Aatola, Piia & Ollikainen, Markku & Tuomenvirta, Heikki, 2010. "Climate change and electricity consumption--Witnessing increasing or decreasing use and costs?," Energy Policy, Elsevier, vol. 38(5), pages 2409-2419, May.
    13. Hao, Han & Geng, Yong & Li, Weiqi & Guo, Bin, 2015. "Energy consumption and GHG emissions from China's freight transport sector: Scenarios through 2050," Energy Policy, Elsevier, vol. 85(C), pages 94-101.
    14. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    15. Monios, Jason, 2019. "Geographies of governance in the freight transport sector: The British case," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 295-308.
    16. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang & Vardanyan, Michael & Zhu, Ning, 2019. "Decomposing banking performance into economic and credit risk efficiencies," European Journal of Operational Research, Elsevier, vol. 277(2), pages 719-726.
    17. Liu, Hongwei & Wu, Jie & Chu, Junfei, 2019. "Environmental efficiency and technological progress of transportation industry-based on large scale data," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 475-482.
    18. Wang, Changjian & Miao, Zhuang & Chen, Xiaodong & Cheng, Yu, 2021. "Factors affecting changes of greenhouse gas emissions in Belt and Road countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    19. Zhang, Guoxing & Deng, Nana & Mou, Haizhen & Zhang, Zhe George & Chen, Xiaofeng, 2019. "The impact of the policy and behavior of public participation on environmental governance performance: Empirical analysis based on provincial panel data in China," Energy Policy, Elsevier, vol. 129(C), pages 1347-1354.
    20. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    21. Liu, Shiyong & Triantis, Konstantinos P. & Sarangi, Sudipta, 2010. "A framework for evaluating the dynamic impacts of a congestion pricing policy for a transportation socioeconomic system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(8), pages 596-608, October.
    22. Saeedi, Hamid & Behdani, Behzad & Wiegmans, Bart & Zuidwijk, Rob, 2019. "Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 66-86.
    23. Shuai Shao, Zhenbing Yang, Lili Yang, and Shuang Ma, 2019. "Can China's Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    24. Chang, Víctor & Tovar, Beatriz, 2017. "Metafrontier analysis on productivity for West Coast of South Pacific terminals," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 118-134.
    25. Cohen, Tom & Jones, Peter, 2020. "Technological advances relevant to transport – understanding what drives them," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 80-95.
    26. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    27. Mahmoudi, Reza & Shetab-Boushehri, Seyyed-Nader & Hejazi, Seyed Reza & Emrouznejad, Ali & Rajabi, Parisa, 2019. "A hybrid egalitarian bargaining game-DEA and sustainable network design approach for evaluating, selecting and scheduling urban road construction projects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 161-183.
    28. Oh, Dong-hyun & Heshmati, Almas, 2010. "A sequential Malmquist-Luenberger productivity index: Environmentally sensitive productivity growth considering the progressive nature of technology," Energy Economics, Elsevier, vol. 32(6), pages 1345-1355, November.
    29. Ilmakunnas, Pekka & Miyakoshi, Tatsuyoshi, 2013. "What are the drivers of TFP in the Aging Economy? Aging labor and ICT capital," Journal of Comparative Economics, Elsevier, vol. 41(1), pages 201-211.
    30. Chen, Xiaodong & Wu, Ge & Li, Ding, 2019. "Efficiency measure on the truck restriction policy in China: A non-radial data envelopment model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 140-154.
    31. Wang, W.W. & Zhang, M. & Zhou, M., 2011. "Using LMDI method to analyze transport sector CO2 emissions in China," Energy, Elsevier, vol. 36(10), pages 5909-5915.
    32. Gehringer, Agnieszka, 2015. "Uneven effects of financial liberalization on productivity growth in the EU: Evidence from a dynamic panel investigation," International Journal of Production Economics, Elsevier, vol. 159(C), pages 334-346.
    33. Oum, Tae Hoon & Pathomsiri, Somchai & Yoshida, Yuichiro, 2013. "Limitations of DEA-based approach and alternative methods in the measurement and comparison of social efficiency across firms in different transport modes: An empirical study in Japan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 57(C), pages 16-26.
    34. Mahdiloo, Mahdi & Ngwenyama, Ojelanki & Scheepers, Rens & Tamaddoni, Ali, 2018. "Managing emissions allowances of electricity producers to maximize CO2 abatement: DEA models for analyzing emissions and allocating emissions allowances," International Journal of Production Economics, Elsevier, vol. 205(C), pages 244-255.
    35. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models," Energy Economics, Elsevier, vol. 34(6), pages 1854-1863.
    36. Cullinane, Kevin & Ji, Ping & Wang, Teng-fei, 2005. "The relationship between privatization and DEA estimates of efficiency in the container port industry," Journal of Economics and Business, Elsevier, vol. 57(5), pages 433-462.
    37. Pettersson, Fredrik & Westerdahl, Stig & Hansson, Joel, 2018. "Learning through collaboration in the Swedish public transport sector? Co-production through guidelines and living labs," Research in Transportation Economics, Elsevier, vol. 69(C), pages 394-401.
    38. Kannan, Ramachandran & Hirschberg, Stefan, 2016. "Interplay between electricity and transport sectors – Integrating the Swiss car fleet and electricity system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 514-531.
    39. Venturini, Francesco, 2015. "The modern drivers of productivity," Research Policy, Elsevier, vol. 44(2), pages 357-369.
    40. Miao, Zhuang & Baležentis, Tomas & Shao, Shuai & Chang, Dongfeng, 2019. "Energy use, industrial soot and vehicle exhaust pollution—China's regional air pollution recognition, performance decomposition and governance," Energy Economics, Elsevier, vol. 83(C), pages 501-514.
    41. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, September.
    42. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    43. Huang, Fei & Zhou, Dequn & Wang, Qunwei & Hang, Ye, 2019. "Decomposition and attribution analysis of the transport sector’s carbon dioxide intensity change in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 343-358.
    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. Miao, Zhuang & Chen, Xiaodong, 2022. "Combining parametric and non-parametric approach, variable & source -specific productivity changes and rebound effect of energy & environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Chu, Junfei & Shao, Caifeng & Emrouznejad, Ali & Wu, Jie & Yuan, Zhe, 2021. "Performance evaluation of organizations considering economic incentives for emission reduction: A carbon emission permit trading approach," Energy Economics, Elsevier, vol. 101(C).
    3. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    4. Miao, Zhuang & Chen, Xiaodong & Baležentis, Tomas, 2021. "Improving energy use and mitigating pollutant emissions across “Three Regions and Ten Urban Agglomerations”: A city-level productivity growth decomposition," Applied Energy, Elsevier, vol. 283(C).
    5. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    6. Wang, Changjian & Miao, Zhuang & Chen, Xiaodong & Cheng, Yu, 2021. "Factors affecting changes of greenhouse gas emissions in Belt and Road countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    7. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    8. Justas Streimikis & Zhuang Miao & Tomas Balezentis, 2021. "Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 576-589, January.
    9. Rashidi, Kamran & Cullinane, Kevin, 2019. "Evaluating the sustainability of national logistics performance using Data Envelopment Analysis," Transport Policy, Elsevier, vol. 74(C), pages 35-46.
    10. Juan Aparicio & Magdalena Kapelko & Juan F. Monge, 2020. "A Well-Defined Composite Indicator: An Application to Corporate Social Responsibility," Journal of Optimization Theory and Applications, Springer, vol. 186(1), pages 299-323, July.
    11. Evelin Krmac & Mozhgan Mansouri Kaleibar, 2023. "A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(4), pages 817-881, December.
    12. Zhong Fang & Hua Bai & Yuriy Bilan, 2019. "Evaluation Research of Green Innovation Efficiency in China’s Heavy Polluting Industries," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    13. 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.
    14. Tianbo Tang & Jianxin You & Hui Sun & Hao Zhang, 2019. "Transportation Efficiency Evaluation Considering the Environmental Impact for China’s Freight Sector: A Parallel Data Envelopment Analysis," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    15. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    16. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    17. Yu, Yang & Li, Shuangqi & Sun, Huaping & Taghizadeh-Hesary, Farhad, 2021. "Energy carbon emission reduction of China’s transportation sector: An input–output approach," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 378-393.
    18. Henriques, C.O. & Chavez, J.M. & Gouveia, M.C. & Marcenaro-Gutierrez, O.D., 2022. "Efficiency of secondary schools in Ecuador: A value based DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    19. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    20. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.

    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:spr:nathaz:v:111:y:2022:i:1:d:10.1007_s11069-021-05046-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.