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Spatial Models in Marketing

Author

Listed:
  • Eric Bradlow
  • Bart Bronnenberg
  • Gary Russell

    ()

  • Neeraj Arora
  • David Bell
  • Sri Duvvuri
  • Frankel Hofstede
  • Catarina Sismeiro
  • Raphael Thomadsen
  • Sha Yang

Abstract

Marketing science models typically assume that responses of one entity (firm or consumer) are unrelated to responses of other entities. In contrast, models constructed using tools from spatial statistics allow for cross-sectional and longitudinal correlations among responses to be explicitly modeled by locating entities on some type of map. By generalizing the notion of a map to include demographic and psychometric representations, spatial models can capture a variety of effects (spatial lags, spatial autocorrelation, and spatial drift) that impact firm or consumer decision behavior. Marketing science applications of spatial models and important research opportunities are discussed. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • 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.
    • Handle: RePEc:kap:mktlet:v:16:y:2005:i:3:p:267-278
    DOI: 10.1007/s11002-005-5891-3
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Erik Brynjolfsson & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2009. "Battle of the Retail Channels: How Product Selection and Geography Drive Cross-Channel Competition," Management Science, INFORMS, vol. 55(11), pages 1755-1765, November.
    2. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - German National Library of Economics.
    3. 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.
    4. 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.
    5. 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.
    6. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    7. Sam K. Hui & Peter S. Fader & Eric T. Bradlow, 2009. "Path Data in Marketing: An Integrative Framework and Prospectus for Model Building," Marketing Science, INFORMS, vol. 28(2), pages 320-335, 03-04.
    8. Josep-Maria Arauzo-Carod & Daniel Liviano-Solis & Miguel Manjón-Antolín, 2010. "Empirical Studies In Industrial Location: An Assessment Of Their Methods And Results," Journal of Regional Science, Wiley Blackwell, vol. 50(3), pages 685-711.
    9. Vincent Nijs & Kanishka Misra & Eric T. Anderson & Karsten Hansen & Lakshman Krishnamurthi, 2010. "Channel Pass-Through of Trade Promotions," Marketing Science, INFORMS, vol. 29(2), pages 250-267, 03-04.
    10. Hernández-Mireles, C., 2010. "Finding the Influentials that Drive the Diffusion of New Technologies," ERIM Report Series Research in Management ERS-2010-023-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Paik, Jane & Ying, Zhiliang, 2012. "A composite likelihood approach for spatially correlated survival data," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 209-216, January.
    12. B. Verhelst & D. Van Den Poel, 2012. "Deep Habits in Consumption: A Spatial Panel Analysis Using Scanner Data," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/823, Ghent University, Faculty of Economics and Business Administration.
    13. 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.

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