IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i22p6187-d283989.html
   My bibliography  Save this article

Numerical Simulation and Spatial Distribution of Transportation Accessibility in the Regions Involved in the Belt and Road Initiative

Author

Listed:
  • Hui Shi

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    These authors contributed equally to this work.)

  • Zhen You

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    These authors contributed equally to this work.)

  • Zhiming Feng

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Yanzhao Yang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

The Belt and Road Initiative (BRI) is a Chinese strategy, proposed to strengthen the connectivity and cooperation among BRI countries. Under this circumstance, many transportation projects are planned to be carried out, which means the transportation accessibility evaluation is of significance in providing valuable suggestions for transportation construction. This research established a global transportation accessibility index (GTAI) model in the BRI region using raster data. Based on its gridded outputs, we conducted classification evaluation, autocorrelation analysis, and a geographical weighted regression model to explore the spatial characteristics of the GTAI distribution and its correlation with population density. The results show that: (1) most countries in Europe and the Middle East, western Russia, and eastern China enjoy high accessibility, while central regions (e.g., Central Asia and western China) have poor access to destinations; (2) the GTAI values are distributed as a spindle, where about 60% areas belong to the middle transportation accessibility region, mapped as a non-significant type; and (3) there is a positive relationship between transportation accessibility and population distribution, but their connection tends to be weaker as socioeconomic development increases. Finally, several policy implementations are provided: (1) give a priority to road or railway construction between China and Central Asian countries; (2) establish an innovative transportation system and introduce advanced technologies to enhance the exchange and cooperation among the BRI countries; (3) improve public transport management in well-developed regions, and introduce talents and strengthen transportation infrastructure construction in developing regions.

Suggested Citation

  • Hui Shi & Zhen You & Zhiming Feng & Yanzhao Yang, 2019. "Numerical Simulation and Spatial Distribution of Transportation Accessibility in the Regions Involved in the Belt and Road Initiative," Sustainability, MDPI, vol. 11(22), pages 1-14, November.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6187-:d:283989
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/22/6187/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/22/6187/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mavoa, Suzanne & Witten, Karen & McCreanor, Tim & O’Sullivan, David, 2012. "GIS based destination accessibility via public transit and walking in Auckland, New Zealand," Journal of Transport Geography, Elsevier, vol. 20(1), pages 15-22.
    2. Chuchu Zhang & Chaowei Xiao & Helin Liu, 2019. "Spatial Big Data Analysis of Political Risks along the Belt and Road," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    3. Xiaorui Zhang & Andong Ren & Lihua Chen & Xianyou Zheng, 2019. "Measurement and Spatial Difference Analysis on the Accessibility of Road Networks in Major Cities of China," Sustainability, MDPI, vol. 11(15), pages 1-15, August.
    4. Shunfeng Song, 1996. "Some Tests of Alternative Accessibility Measures: A Population Density Approach," Land Economics, University of Wisconsin Press, vol. 72(4), pages 474-482.
    5. Jelena M. Andrić & Jiayuan Wang & Ruoyu Zhong, 2019. "Identifying the Critical Risks in Railway Projects Based on Fuzzy and Sensitivity Analysis: A Case Study of Belt and Road Projects," Sustainability, MDPI, vol. 11(5), pages 1-18, March.
    6. Barker, Theresa J. & Zabinsky, Zelda B., 2011. "A multicriteria decision making model for reverse logistics using analytical hierarchy process," Omega, Elsevier, vol. 39(5), pages 558-573, October.
    7. Saghapour, Tayebeh & Moridpour, Sara & Thompson, Russell G., 2016. "Public transport accessibility in metropolitan areas: A new approach incorporating population density," Journal of Transport Geography, Elsevier, vol. 54(C), pages 273-285.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Yaoming & Kundu, Tanmoy & Goh, Mark & Sheu, Jiuh-Biing, 2021. "Multimodal transportation network centrality analysis for Belt and Road Initiative," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    2. Degong Ma & Chun Lei & Farid Ullah & Raza Ullah & Qadar Bakhsh Baloch, 2019. "China’s One Belt and One Road Initiative and Outward Chinese Foreign Direct Investment in Europe," Sustainability, MDPI, vol. 11(24), pages 1-13, December.

    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. Ruqin Yang & Yaolin Liu & Yanfang Liu & Hui Liu & Wenxia Gan, 2019. "Comprehensive Public Transport Service Accessibility Index—A New Approach Based on Degree Centrality and Gravity Model," Sustainability, MDPI, vol. 11(20), pages 1-20, October.
    2. Chandra, Shailesh & Bari, Muhammad Ehsanul & Devarasetty, Prem Chand & Vadali, Sharada, 2013. "Accessibility evaluations of feeder transit services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 47-63.
    3. Mansour, Shawky & Alahmadi, Mohammed & Abulibdeh, Ammar, 2022. "Spatial assessment of audience accessibility to historical monuments and museums in Qatar during the 2022 FIFA World Cup," Transport Policy, Elsevier, vol. 127(C), pages 116-129.
    4. Xingjian Liu, 2020. "Assessing airport ground access by public transport in Chinese cities," Urban Studies, Urban Studies Journal Limited, vol. 57(2), pages 267-285, February.
    5. Frank, Laura & Dirks, Nicolas & Walther, Grit, 2021. "Improving rural accessibility by locating multimodal mobility hubs," Journal of Transport Geography, Elsevier, vol. 94(C).
    6. Ben-Elia, Eran & Benenson, Itzhak, 2019. "A spatially-explicit method for analyzing the equity of transit commuters' accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 31-42.
    7. Xia, Nan & Cheng, Liang & Chen, Song & Wei, XiaoYan & Zong, WenWen & Li, ManChun, 2018. "Accessibility based on Gravity-Radiation model and Google Maps API: A case study in Australia," Journal of Transport Geography, Elsevier, vol. 72(C), pages 178-190.
    8. Ricardo Flores-Fillol & Rosella Nicolini, "undated". "Aerotropolis: an aviation-linked space," Working Papers 283, Barcelona School of Economics.
    9. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.
    10. Chen, Shaopei & Claramunt, Christophe & Ray, Cyril, 2014. "A spatio-temporal modelling approach for the study of the connectivity and accessibility of the Guangzhou metropolitan network," Journal of Transport Geography, Elsevier, vol. 36(C), pages 12-23.
    11. Sadayuki, Taisuke, 2018. "Measuring the spatial effect of multiple sites: An application to housing rent and public transportation in Tokyo, Japan," Regional Science and Urban Economics, Elsevier, vol. 70(C), pages 155-173.
    12. Nerdjes Bennani & Samy Mezhoud, 2023. "Risk assessment of several hazards along railway network using AHP incorporated into GIS," Technium Social Sciences Journal, Technium Science, vol. 39(1), pages 452-464, January.
    13. Jen-Jia Lin & Chi-Hau Chen & Tsung-Yu Hsieh, 2016. "Job accessibility and ethnic minority employment in urban and rural areas in Taiwan," Papers in Regional Science, Wiley Blackwell, vol. 95(2), pages 363-382, June.
    14. Agnieszka Bekisz & Magdalena Kowacka & Michał Kruszyński & Dominika Dudziak-Gajowiak & Grzegorz Debita, 2022. "Risk Management Using Network Thinking Methodology on the Example of Rail Transport," Energies, MDPI, vol. 15(14), pages 1-19, July.
    15. Rafal Stachyra & Kamil Roman, 2021. "Analysis of Accessibility of Public Transport in Warsaw in the Opinion of Users," Postmodern Openings, Editura Lumen, Department of Economics, vol. 12(3), pages 384-403, August.
    16. Ilenia Epifani & Rosella Nicolini, 2013. "On The Population Density Distribution Across Space: A Probabilistic Approach," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 481-510, August.
    17. Lee, Hasik & Park, Ho-Chul & Kho, Seung-Young & Kim, Dong-Kyu, 2019. "Assessing transit competitiveness in Seoul considering actual transit travel times based on smart card data," Journal of Transport Geography, Elsevier, vol. 80(C).
    18. Xuesong Sun & Zaisheng Zhang, 2021. "Coupling and Coordination Level of the Population, Land, Economy, Ecology and Society in the Process of Urbanization: Measurement and Spatial Differentiation," Sustainability, MDPI, vol. 13(6), pages 1-19, March.
    19. Tanya Suhoy & Yotam Sofer, 2019. "Getting to Work in Israel: Locality and Individual Effects," Bank of Israel Working Papers 2019.02, Bank of Israel.
    20. Haji Vahabzadeh, Ali & Asiaei, Arash & Zailani, Suhaiza, 2015. "Reprint of “Green decision-making model in reverse logistics using FUZZY-VIKOR method”," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 334-347.

    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:11:y:2019:i:22:p:6187-:d:283989. 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.