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Spatial Models in Marketing

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Author Info

  • 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

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Bibliographic Info

Article provided by Springer in its journal Marketing Letters.

Volume (Year): 16 (2005)
Issue (Month): 3 (December)
Pages: 267-278

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Handle: RePEc:kap:mktlet:v:16:y:2005:i:3:p:267-278

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Web page: http://www.springerlink.com/link.asp?id=100312

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References

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  1. Anderson, Simon P & de Palma, Andre, 1988. "Spatial Price Discrimination with Heterogeneous Products," Review of Economic Studies, Wiley Blackwell, vol. 55(4), pages 573-92, October.
  2. 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.
  3. 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.
  4. Bronnenberg, B.J.J.A.M. & Mahajan, V., 2001. "Unobserved retailer behavior in multimarket data: Joint spatial dependence in market shares and promotion variables," Open Access publications from Tilburg University urn:nbn:nl:ui:12-332642, Tilburg University.
  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. 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.
  7. Bronnenberg, B.J.J.A.M. & Sismeiro, C., 2002. "Using multimarket data to predict brand performance in markets for which no or poor data exist," Open Access publications from Tilburg University urn:nbn:nl:ui:12-332637, Tilburg University.
  8. 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.
  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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Citations

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Cited by:
  1. 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.
  2. 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.
  3. Bradlow, E. & Bronnenberg, B.J.J.A.M. & Russell, G.J. & Arora, N. & Bell, D. & Deepak, S.D. & Hofstede, F. ter & Sismeiro, C. & Thomadsen, R. & Yang, S., 2005. "Spatial models in marketing," Open Access publications from Tilburg University urn:nbn:nl:ui:12-332173, Tilburg University.
  4. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics, Springer, vol. 10(4), pages 419-452, December.
  5. 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.
  6. 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.
  7. Arauzo Carod, Josep Maria & Liviano Solís, Daniel & Manjón Antolín, Miguel C., 2008. "Empirical studies in industrial location: an assessment of their methods and results," Working Papers 2072/9257, Universitat Rovira i Virgili, Department of Economics.
  8. 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 Uni.
  9. 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.

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