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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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    Cited by:

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    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. 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, August.
    4. 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.
    5. 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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    11. 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.
    12. Margaret Aksoy-Pierson & Gad Allon & Awi Federgruen, 2013. "Price Competition Under Mixed Multinomial Logit Demand Functions," Management Science, INFORMS, vol. 59(8), pages 1817-1835, August.
    13. 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.
    14. Trivedi, Minakshi, 2011. "Regional and Categorical Patterns in Consumer Behavior: Revealing Trends," Journal of Retailing, Elsevier, vol. 87(1), pages 18-30.
    15. 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.
    16. C. Marinelli & S. Savin, 2008. "Optimal Distributed Dynamic Advertising," Journal of Optimization Theory and Applications, Springer, vol. 137(3), pages 569-591, June.
    17. 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.
    18. 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.
    19. 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.
    20. Akira Matsui & Daisuke Moriwaki, 2022. "Online-to-offline advertisements as field experiments," The Japanese Economic Review, Springer, vol. 73(1), pages 211-242, January.
    21. 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.
    22. Moon, Sangkil & Azizi, Kathryn, 2013. "Finding Donors by Relationship Fundraising," Journal of Interactive Marketing, Elsevier, vol. 27(2), pages 112-129.
    23. Moon, Sangkil & Jalali, Nima & Song, Reo, 2022. "Green-lighting scripts in the movie pre-production stage: An application of consumption experience carryover theory," Journal of Business Research, Elsevier, vol. 140(C), pages 332-345.
    24. Duncan A. Robertson, 2019. "Spatial Transmission Models: A Taxonomy and Framework," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 225-243, January.
    25. 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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