IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v20y2013i3p334-348.html
   My bibliography  Save this article

Spatial dependencies and spatial drift in public transport seasonal ticket revenue data

Author

Listed:
  • Müller, Sven
  • Wilhelm, Pascal
  • Haase, Knut

Abstract

When firms' customers are located in spatially dispersed areas, it can be difficult to manage service quality on a geographically small scale because the relative importance of service quality might vary spatially. Moreover, standard approaches discussed so far in the marketing science literature usually neglect spatial effects, such as spatial dependencies (spatial autocorrelation for example) and spatial drift (spatial non-stationarity). We propose a comprehensive approach based on spatial econometric methods that covers both issues. Based on the real company data on seasonal ticket revenue of a local public transport service company, we show that addressing such spatial effects of service data can improve management's ability to implement programs aimed at enhancing seasonal ticket revenue. In particular, the article shows how a spatial revenue response function might be specified.

Suggested Citation

  • Müller, Sven & Wilhelm, Pascal & Haase, Knut, 2013. "Spatial dependencies and spatial drift in public transport seasonal ticket revenue data," Journal of Retailing and Consumer Services, Elsevier, vol. 20(3), pages 334-348.
    • Handle: RePEc:eee:joreco:v:20:y:2013:i:3:p:334-348
    DOI: 10.1016/j.jretconser.2013.01.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698913000064
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2013.01.005?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. Karthik Sridhar & Ram Bezawada & Minakshi Trivedi, 2012. "Investigating the Drivers of Consumer Cross-Category Learning for New Products Using Multiple Data Sets," Marketing Science, INFORMS, vol. 31(4), pages 668-688, July.
    2. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, July.
    3. Bart J. Bronnenberg, 2005. "Spatial models in marketing research and practice," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(4‐5), pages 335-343, July.
    4. Luc Anselin, 2003. "Spatial Externalities, Spatial Multipliers, And Spatial Econometrics," International Regional Science Review, , vol. 26(2), pages 153-166, April.
    5. Richard Harris & John Moffat & Victoria Kravtsova, 2011. "In Search of ‘ W ’," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(3), pages 249-270, February.
    6. Eric Bradlow & Bart Bronnenberg & Gary Russell & Neeraj Arora & David Bell & Sri Duvvuri & Frankel Hofstede & Catarina Sismeiro & Raphael Thomadsen & Sha Yang, 2005. "Spatial Models in Marketing," Marketing Letters, Springer, vol. 16(3), pages 267-278, December.
    7. repec:bla:kyklos:v:52:y:1999:i:2:p:219-38 is not listed on IDEAS
    8. Yee Leung & Chang-Lin Mei & Wen-Xiu Zhang, 2000. "Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model," Environment and Planning A, , vol. 32(1), pages 9-32, January.
    9. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    10. Yefang Huang & Yee Leung, 2002. "Analysing regional industrialisation in Jiangsu province using geographically weighted regression," Journal of Geographical Systems, Springer, vol. 4(2), pages 233-249, June.
    11. repec:bla:scotjp:v:49:y:2002:i:3:p:336-55 is not listed on IDEAS
    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. Katarzyna Kopczewska, 2022. "Spatial machine learning: new opportunities for regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 713-755, June.
    2. Haase, Knut & Müller, Sven, 2014. "Upper and lower bounds for the sales force deployment problem with explicit contiguity constraints," European Journal of Operational Research, Elsevier, vol. 237(2), pages 677-689.

    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. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    2. P. Baecke & D. Van Den Poel, 2012. "Including Spatial Interdependence in Customer Acquisition Models: a Cross-Category Comparison," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/788, Ghent University, Faculty of Economics and Business Administration.
    3. V Kumar & Amalesh Sharma & Shaphali Gupta, 2017. "Accessing the influence of strategic marketing research on generating impact: moderating roles of models, journals, and estimation approaches," Journal of the Academy of Marketing Science, Springer, vol. 45(2), pages 164-185, March.
    4. Anastasia S. Saridou & Athanasios P. Vavatsikos & Evangelos Grigoroudis, 2024. "Multi-store consumer satisfaction benchmarking using spatial multiple criteria decision analysis," Operational Research, Springer, vol. 24(2), pages 1-26, June.
    5. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
    6. Shaoming Cheng & Huaqun Li, 2011. "Spatially Varying Relationships of New Firm Formation in the United States," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 773-789.
    7. Sven Müller, 2012. "Identifying spatial nonstationarity in German regional firm start-up data," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 32(2), pages 113-132, September.
    8. Akira Matsui & Daisuke Moriwaki, 2022. "Online-to-offline advertisements as field experiments," The Japanese Economic Review, Springer, vol. 73(1), pages 211-242, January.
    9. Lambert, Dayton M. & McNamara, Kevin T. & Garrett, Megan I., 2006. "An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(1), pages 1-17, April.
    10. P. Baecke & D. Van Den Poel, 2012. "Improving Customer Acquisition Models by Incorporating Spatial Autocorrelation at Different Levels of Granularity," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/819, Ghent University, Faculty of Economics and Business Administration.
    11. Benjamin Verhelst & Dirk Van den Poel, 2014. "Deep habits in consumption: a spatial panel analysis using scanner data," Empirical Economics, Springer, vol. 47(3), pages 959-976, November.
    12. Ferhan Gezici & Burçin Yazgı Walsh & Sinem Metin Kacar, 2017. "Regional and structural analysis of the manufacturing industry in Turkey," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 209-230, July.
    13. Ning Wang & Chang-Lin Mei & Xiao-Dong Yan, 2008. "Local Linear Estimation of Spatially Varying Coefficient Models: An Improvement on the Geographically Weighted Regression Technique," Environment and Planning A, , vol. 40(4), pages 986-1005, April.
    14. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    15. Stephen Matthews & Tse-Chuan Yang, 2012. "Mapping the results of local statistics," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 26(6), pages 151-166.
    16. Ayse Ozden Birkan & Serpil Kahraman Akdogu, 2016. "The geography of financial intermediation in Turkey: 1988–2013," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 31-61, July.
    17. Antonio Páez & Steven Farber & David Wheeler, 2011. "A Simulation-Based Study of Geographically Weighted Regression as a Method for Investigating Spatially Varying Relationships," Environment and Planning A, , vol. 43(12), pages 2992-3010, December.
    18. Kim, Sunghoon & DeSarbo, Wayne S. & Chang, Won, 2021. "Note: A new approach to the modeling of spatially dependent and heterogeneous geographical regions," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 792-803.
    19. Liu, Zhuping & Duan, Jason A & Mahajan, Vijay, 2020. "Dynamics and peer effects of brand revenue in college sports," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 756-771.
    20. Duncan A. Robertson, 2019. "Spatial Transmission Models: A Taxonomy and Framework," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 225-243, January.

    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:joreco:v:20:y:2013:i:3:p:334-348. 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-retailing-and-consumer-services .

    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.