IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v70y2018icp123-130.html
   My bibliography  Save this article

Congestion impacts of shopping using vehicle tracking data

Author

Listed:
  • Wadud, Zia
  • Chen, Danlei

Abstract

Shopping and retail trade play an important role in the economy, yet shopping activities and associated on-street parking and disruptions to traffic could substantially contribute to congestion in the megacities of the developing and emerging countries. This research investigates and quantifies the effects of shopping and related road-side frictions and disruptions on congestion in a city. We make use of minute by minute GPS tracking data of vehicles and a unique policy of different shopping closure days in different areas of the city, which allows the separation of shopping related congestion effects from commute and other effects. Results show that average speed increased by 18.5% on weekdays when shopping centres were closed. The differences in speed in the different zones can also be qualitatively related with the density of shopping centres in those zones.

Suggested Citation

  • Wadud, Zia & Chen, Danlei, 2018. "Congestion impacts of shopping using vehicle tracking data," Journal of Transport Geography, Elsevier, vol. 70(C), pages 123-130.
  • Handle: RePEc:eee:jotrge:v:70:y:2018:i:c:p:123-130
    DOI: 10.1016/j.jtrangeo.2018.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692317307639
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.jtrangeo.2018.05.001?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
    ---><---

    References listed on IDEAS

    as
    1. Schmöcker, Jan-Dirk & Fonzone, Achille & Quddus, Mohammed & Bell, Michael G.H., 2006. "Changes in the frequency of shopping trips in response to a congestion charge," Transport Policy, Elsevier, vol. 13(3), pages 217-228, May.
    2. Orit Rotem-Mindali & Jesse Weltevreden, 2013. "Transport effects of e-commerce: what can be learned after years of research?," Transportation, Springer, vol. 40(5), pages 867-885, September.
    3. Jing Li & Pingyu Zhang & Kevin Lo & Meng Guo & Mark Wang, 2015. "Reducing Carbon Emissions from Shopping Trips: Evidence from China," Energies, MDPI, vol. 8(9), pages 1-15, September.
    4. Choudhury, Charisma F. & Ayaz, Sayeeda Bint, 2015. "Why live far? — Insights from modeling residential location choice in Bangladesh," Journal of Transport Geography, Elsevier, vol. 48(C), pages 1-9.
    5. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    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. Waitt, Gordon & Stanes, Elyse, 2022. "Reactivating commuter cycling: COVID-19 pandemic disruption to everyday transport choices in Sydney, Australia," Journal of Transport Geography, Elsevier, vol. 98(C).
    2. Royal, Diane & Roseman, Sharon R., 2021. "Co-passengering and the gendering of a mobile ferry space," Journal of Transport Geography, Elsevier, vol. 92(C).

    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. Lee, Richard J. & Sener, Ipek N. & Mokhtarian, Patricia L. & Handy, Susan L., 2017. "Relationships between the online and in-store shopping frequency of Davis, California residents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 40-52.
    2. Ni, Linglin & Wang, Xiaokun (Cara) & Zhang, Dapeng, 2016. "Impacts of information technology and urbanization on less-than-truckload freight flows in China: An analysis considering spatial effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 12-25.
    3. Kunbo Shi & Long Cheng & Jonas De Vos & Yongchun Yang & Wanpeng Cao & Frank Witlox, 2021. "How does purchasing intangible services online influence the travel to consume these services? A focus on a Chinese context," Transportation, Springer, vol. 48(5), pages 2605-2625, October.
    4. Huiran Han & Kai Yang & Chengfeng Yang & Gang Yang & Lingyi Xu, 2022. "Influence and Mechanism of a Multi-Scale Built Environment on the Leisure Activities of the Elderly: Evidence from Hefei City in China," IJERPH, MDPI, vol. 19(15), pages 1-24, July.
    5. Wenping Liu & Chenlu Dong & Weijuan Chen, 2017. "Mapping and Quantifying Spatial and Temporal Dynamics and Bundles of Travel Flows of Residents Visiting Urban Parks," Sustainability, MDPI, vol. 9(8), pages 1-15, July.
    6. Feipeng Guo & Linji Zhang & Zifan Wang & Shaobo Ji, 2022. "Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    7. Zhao, Pengxiang & Kwan, Mei-Po & Qin, Kun, 2017. "Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel," Journal of Transport Geography, Elsevier, vol. 62(C), pages 122-135.
    8. Qing Zhai & Xinyu Cao & Patricia L. Mokhtarian & Feng Zhen, 2017. "The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods," Transportation, Springer, vol. 44(5), pages 885-904, September.
    9. Neiberger Cordula & Mensing Matthias & Kubon Jonas, 2020. "Geographische Handelsforschung im Zeitalter der Digitalisierung: Eine Bestandsaufnahme," ZFW – Advances in Economic Geography, De Gruyter, vol. 64(4), pages 197-210, November.
    10. Yang, Wenyue & Chen, Huiling & Wang, Wulin, 2020. "The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 88(C).
    11. Alexander Rossolov & Halyna Rossolova & José Holguín-Veras, 2021. "Online and in-store purchase behavior: shopping channel choice in a developing economy," Transportation, Springer, vol. 48(6), pages 3143-3179, December.
    12. Jing Li & Kevin Lo & Meng Guo, 2018. "Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China," IJERPH, MDPI, vol. 15(7), pages 1-11, June.
    13. Houshmand Masoumi & Atif Bilal Aslam & Irfan Ahmad Rana & Muhammad Ahmad & Nida Naeem, 2022. "Relationship of Residential Location Choice with Commute Travels and Socioeconomics in the Small Towns of South Asia: The Case of Hafizabad, Pakistan," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
    14. Tri Basuki Joewono & Ari K. M. Tarigan & Muhamad Rizki, 2019. "Segmentation, Classification, and Determinants of In-Store Shopping Activity and Travel Behaviour in the Digitalisation Era: The Context of a Developing Country," Sustainability, MDPI, vol. 11(6), pages 1-23, March.
    15. Honghu Sun & Feng Zhen & Yupei Jiang, 2020. "Study on the Characteristics of Urban Residents’ Commuting Behavior and Influencing Factors from the Perspective of Resilience Theory: Theoretical Construction and Empirical Analysis from Nanjing, Chi," IJERPH, MDPI, vol. 17(5), pages 1-17, February.
    16. Jiayu Wu & Qingsong He & Yunwen Chen & Jian Lin & Shantong Wang, 2020. "Dismantling the fence for social justice? Evidence based on the inequity of urban green space accessibility in the central urban area of Beijing," Environment and Planning B, , vol. 47(4), pages 626-644, May.
    17. Buldeo Rai, Heleen, 2021. "The net environmental impact of online shopping, beyond the substitution bias," Journal of Transport Geography, Elsevier, vol. 93(C).
    18. Akgün, Emine Zehra & Monios, Jason & Rye, Tom & Fonzone, Achille, 2019. "Influences on urban freight transport policy choice by local authorities," Transport Policy, Elsevier, vol. 75(C), pages 88-98.
    19. Yu, Biying & Zhang, Junyi & Li, Xia, 2017. "Dynamic life course analysis on residential location choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 281-292.
    20. Sovacool, Benjamin K. & Kester, Johannes & Noel, Lance & de Rubens, Gerardo Zarazua, 2019. "Income, political affiliation, urbanism and geography in stated preferences for electric vehicles (EVs) and vehicle-to-grid (V2G) technologies in Northern Europe," Journal of Transport Geography, Elsevier, vol. 78(C), pages 214-229.

    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:eee:jotrge:v:70:y:2018:i:c:p:123-130. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    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.