IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v76y2019icp245-253.html
   My bibliography  Save this article

Spatial data analytics of mobility with consumer data

Author

Listed:
  • Birkin, Mark

Abstract

Consumer data arising from the interaction between customers and service providers are becoming ubiquitous. These data are appealing for research because they are frequently collected and quickly released; they cover a wide variety of attitudes, lifestyles and behavioural characteristics; and they are often dynamically replenished and longitudinal. It is demonstrated that consumer data can make important contributions to understanding problems in transport geography and in solving applied problems ranging from migration, infrastructure investment and retail service provision to commuting and individual mobility. However more effective exploitation of these data depends on the construction of bridges to allow greater freedom in the transfer of data from the commercial to the academic sector; it requires development of frameworks for privacy and ethics in the secondary use of personal data; and it is contingent on the emergence of effective strategies for the amelioration of selection bias which impairs the quality of many consumer data sources.

Suggested Citation

  • Birkin, Mark, 2019. "Spatial data analytics of mobility with consumer data," Journal of Transport Geography, Elsevier, vol. 76(C), pages 245-253.
    • Handle: RePEc:eee:jotrge:v:76:y:2019:i:c:p:245-253
    DOI: 10.1016/j.jtrangeo.2018.04.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692317300212
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2018.04.012?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. Rubin, Ori & Mulder, Clara H. & Bertolini, Luca, 2014. "The determinants of mode choice for family visits – evidence from Dutch panel data," Journal of Transport Geography, Elsevier, vol. 38(C), pages 137-147.
    2. J Stillwell & M Bell & P Ueffing & K Daras & E Charles-Edwards & M Kupiszewski & D Kupiszewska, 2016. "Internal migration around the world: comparing distance travelled and its frictional effect," Environment and Planning A, , vol. 48(8), pages 1657-1675, August.
    3. Mordechai Haklay, 2010. "How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets," Environment and Planning B, , vol. 37(4), pages 682-703, August.
    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. Shaw, F. Atiyya & Wang, Xinyi & Mokhtarian, Patricia L. & Watkins, Kari E., 2021. "Supplementing transportation data sources with targeted marketing data: Applications, integration, and internal validation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 150-169.
    2. Rains, Tim & Longley, Paul, 2021. "The provenance of loyalty card data for urban and retail analytics," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    3. Ffion Carney, 2021. "Linking Loyalty Card Data to Public Transport Data to Explore Mobility and Social Exclusion in the Older Population," Sustainability, MDPI, vol. 13(11), pages 1-19, May.

    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. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    2. Yagci Sokat, Kezban & Dolinskaya, Irina S. & Smilowitz, Karen & Bank, Ryan, 2018. "Incomplete information imputation in limited data environments with application to disaster response," European Journal of Operational Research, Elsevier, vol. 269(2), pages 466-485.
    3. Amin Mobasheri & Yeran Sun & Lukas Loos & Ahmed Loai Ali, 2017. "Are Crowdsourced Datasets Suitable for Specialized Routing Services? Case Study of OpenStreetMap for Routing of People with Limited Mobility," Sustainability, MDPI, vol. 9(6), pages 1-17, June.
    4. Geoff Boeing, 2020. "Planarity and street network representation in urban form analysis," Environment and Planning B, , vol. 47(5), pages 855-869, June.
    5. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Brands, Ties & van Oort, Niels & Teller, David, 2021. "Multi-city exploration of built environment and transit mode use: Comparison of Melbourne, Amsterdam and Boston," Journal of Transport Geography, Elsevier, vol. 95(C).
    6. Zhenghong Tang & Tiantian Liu, 2016. "Evaluating Internet-based public participation GIS (PPGIS) and volunteered geographic information (VGI) in environmental planning and management," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(6), pages 1073-1090, June.
    7. Rubin, Ori & Bertolini, Luca, 2016. "Social and environmental sustainability of travelling within family networks," Transport Policy, Elsevier, vol. 52(C), pages 72-80.
    8. Bidur Devkota & Hiroyuki Miyazaki & Apichon Witayangkurn & Sohee Minsun Kim, 2019. "Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest," Sustainability, MDPI, vol. 11(17), pages 1-29, August.
    9. Mengdi Zhang & Xiao Wang & Zengxiang Zhang & Xiaoli Zhao, 2018. "Assessing the Potential of Rural Settlement Land Consolidation in China: A Method Based on Comprehensive Evaluation of Restricted Factors," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    10. Massimiliano Pittore & Marc Wieland & Kevin Fleming, 2017. "Perspectives on global dynamic exposure modelling for geo-risk assessment," 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. 86(1), pages 7-30, March.
    11. Katerina Tzavella & Alexander Fekete & Frank Fiedrich, 2018. "Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany," 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. 91(1), pages 29-57, April.
    12. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Teller, David, 2020. "Study design impacts on built environment and transit use research," Journal of Transport Geography, Elsevier, vol. 82(C).
    13. Duncan Light & Craig Young, 2015. "Toponymy as Commodity: Exploring the Economic Dimensions of Urban Place Names," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 39(3), pages 435-450, May.
    14. Dėdelė, Audrius & Miškinytė, Auksė & Andrušaitytė, Sandra & Nemaniūtė-Gužienė, Jolanta, 2020. "Dependence between travel distance, individual socioeconomic and health-related characteristics, and the choice of the travel mode: a cross-sectional study for Kaunas, Lithuania," Journal of Transport Geography, Elsevier, vol. 86(C).
    15. Zhao, Pengxiang & Jia, Tao & Qin, Kun & Shan, Jie & Jiao, Chenjing, 2015. "Statistical analysis on the evolution of OpenStreetMap road networks in Beijing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 59-72.
    16. Hae Ok Choi, 2020. "An Evolutionary Approach to Technology Innovation of Cadastre for Smart Land Management Policy," Land, MDPI, vol. 9(2), pages 1-19, February.
    17. 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).
    18. Nikolaos Papapesios & Claire Ellul & Amanda Shakir & Glen Hart, 2019. "Exploring the use of crowdsourced geographic information in defence: challenges and opportunities," Journal of Geographical Systems, Springer, vol. 21(1), pages 133-160, March.
    19. Rubin, Ori, 2015. "Contact between parents and adult children: The role of time constraints, commuting and automobility," Journal of Transport Geography, Elsevier, vol. 49(C), pages 76-84.
    20. Mikko Rönneberg & Mari Laakso & Tapani Sarjakoski, 2019. "Map Gretel: social map service supporting a national mapping agency in data collection," Journal of Geographical Systems, Springer, vol. 21(1), pages 43-59, March.

    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:76:y:2019:i:c:p:245-253. 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.