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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

    as
    1. Marshall P. & Bradlow E.T., 2002. "A Unified Approach to Conjoint Analysis Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 674-682, September.
    2. Bart J. Bronnenberg & Vijay Mahajan, 2001. "Unobserved Retailer Behavior in Multimarket Data: Joint Spatial Dependence in Market Shares and Promotion Variables," Marketing Science, INFORMS, vol. 20(3), pages 284-299, October.
    3. Michel Wedel & Rik Pieters, 2000. "Eye Fixations on Advertisements and Memory for Brands: A Model and Findings," Marketing Science, INFORMS, vol. 19(4), pages 297-312, October.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Frenkel Ter Hofstede & Michel Wedel & Jan-Benedict E.M. Steenkamp, 2002. "Identifying Spatial Segments in International Markets," Marketing Science, INFORMS, vol. 21(2), pages 160-177, July.
    6. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    7. Pradeep Chintagunta & Jean-Pierre Dubé & Khim Yong Goh, 2005. "Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models," Management Science, INFORMS, vol. 51(5), pages 832-849, May.
    8. Simon P. Anderson & André De Palma, 1988. "Spatial Price Discrimination with Heterogeneous Products," Review of Economic Studies, Oxford University Press, vol. 55(4), pages 573-592.
    9. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
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    7. 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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    13. 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 - Leibniz Information Centre for Economics.
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    19. 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.
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    23. Duncan A. Robertson, 2019. "Spatial Transmission Models: A Taxonomy and Framework," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 225-243, January.
    24. 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.

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