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.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Allenby, Greg M. and Peter E. Rossi. (1998). “Marketing Models of Consumer Heterogeneity,” Journal of Econometrics 89, 57–78.
Anderson S. P. and A. de Palma. (1988). “Spatial Price Discrimination with Heterogeneous Products,” The Review of Economic Studies 55, 573–592.
Anselin, Luc. (1988). Spatial Econometrics: Methods and Models, Dorddrecht: Kluwer Academic Publishers.
Anselin, Luc. (2001). “Spatial Econometrics,” in B. Baltagi (ed.), A Companion to Theoretical Econometrics, Oxford: Basil Blackwell, 310–330.
Anselin, Luc. (2002). “Under the Hood: Issues in the Specification and Interpretation of Spatial Regression Models,” Agricultural Economics 17(3), 247–267.
Aribarg, A., N. Arora, and H. Onur Bodur. (2002). “Understanding the Role of Preference Revision and Concession in Group Decisions,” Journal of Marketing Research, 39(August), 336–349.
Arora, Neeraj. (2004). “Joint Decision Making and Spatial Models,” Position Paper, Session on Spatial Models in Marketing, Invitational Choice Symposium.
Arora, Neeraj and Greg M. Allenby. (1999). “Measuring the Influence ofIndividual Preference Structures in Group Decision Making,” Journal of Marketing Research 36(November), 476–487.
Bell,David R. and Sangyoung Song. (2004). “Social Contagion and Trial on the Internet:Evidence from Online Grocery Retailing,” Working Paper, Wharton School of Management, University of Pennsylvania.
Besag, Julian. (1974). “Spatial Interaction and the Statistical Analysis of Lattice Systems,” Journal of the Royal Statistical Society B 36, 192–236.
Besag, Julian. (1975). “Statistical Analysis of Non-Latice Data,” The Statistician 24, 179–195.
Bronnenberg, Bart J. (2004). “Spatial Models in Marketing Research and Practice,” Applied Stochastic Models in Business and Industry (forthcoming).
Bronnenberg, Bart J. and Vijay Mahajan. (2001). “Unobserved Retailer Behavior in Multimarket Data: Joint Spatial Dependence in Market Shares and Promotion Variables,” Marketing Science 20(Summer), 284–299
Bronnenberg, Bart J. and Catarina Sismeiro. (2002). “Using Multimarket Data to Predict Brand Performance in Markets for Which No or Poor Data Exist,” Journal of Marketing Research 39(February), 1–17.
Bronnenberg, Bart J., Sanjay Dhar and Jean-Pierre Dube. (2005), “Market Structure and the Geographic Distribution of Brand Shares in Consumer Packaged Goods Industries,” Working Paper, Anderson School of Management, UCLA.
Brunsdon, Chris, Stewart Fotheringham, and Martin Charlton. (1998). “Geographically Weighted Regression: Modeling Spatial Non-Stationarity,” The Statistician 47(3), 431–443.
Chintagunta, Pradeep, Dube, Jean-Pierre, and Goh, Kim Yong. (2004). “Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models,” Management Science (forthcoming).
Cressie, Noel A. C. (1993). Statistics for Spatial Data, New York: John Wiley and Sons.
Duvvuri, Sri Devi, Tom Gruca, and Gary J. Russell. (2004). “Modeling Household Response Heterogeneity Using Spatial Measures of Similarity,” Presentation at the MRSIG Special Session, AMA Educators' Conference.
DeSarbo, Wayne S. and J. Wu. (2001). “The Joint Spatial Representation of Multiple Variable Batteries Collected in Marketing Research,” Journal of Marketing Research 38(May), 244–253.
Fotheringham, A. S., C. A. Brunsdon, and M. Charlton. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, New York: John Wiley and Sons.
Haining, Robert. (1997). Spatial Data Analysis in the Social and Environmental Sciences, New York: Cambridge University Press.
Jank, Wolfgang, and P. K. Kannan. (2003). “Understanding Geographical Markets of Online Firms Using Spatial Models of Consumer Choice,” Working Paper, Maryland Business School, University of Maryland.
Larson, J. S., E. T. Bradlow, and P. Fader. (2005). “An Exploratory Look at In-Store Supermarket Shopping Paths,” International Journal of Research in Marketing (forthcoming).
LeSage, James P. (1999). Spatial Econometrics, Morgantown: Regional Research Institute, University of West Virginia.
LeSage, James P. (2000). “Bayesian Estimation of Limited Dependent-Variable Spatial Autoregressive Models,” Geographical Analysis 32(1), 19–35.
LeSage, James P. (2003). “A Family of Geographically Weighted Regression Models,” Working Paper, Department of Economics, University of Toledo.
LeSage, James P. and R. K. Pace. (2000). “Using Matrix Exponentials to Explore Spatial Structure in Regression Relationships,” Working Paper, Department of Economics, University of Toledo.
Manchanda, P., A. Ansari, and S. Gupta. (1999). “The Shopping Basket: A Model for Multicategory Purchase Incidence Decisions,” Marketing Science 18(2), 95–114.
Marshall, P. and E. T. Bradlow. (2002). “A Unified Approach to Conjoint Analysis Models,” Journal of the American Statistical Association 97(459), 674–682.
Mittal, Vikas, Wagner A. Kamakura, and Rahul Govind. (2004). “Geographic Patterns in Customer Service and Satisfaction: An Empirical Investigation,” Journal of Marketing 68, 48–62.
Moon, Sangkil and Gary J. Russell. (2004). “A Spatial Choice Model for Product Recommendations,” Working Paper, Tippie School of Business, University of Iowa.
Murphy, Edward D. (2004). “Tracking Grocery Hot Spots,” Portland Press Herald, Tuesday, January 27, 2004 edition (http://www.MaineToday.com/).
Pace, R. K. and Barry. (1997). “Quick Computation of Regressions with a Spatially Autoregressive Dependent Variable,” Geographical Analysis 29(1).
Pace, R. K. and Barry. (1999), “Monte Carlo Estimates of the Log Determinant of Large Spatial Matrices,” Linear Algebra and its Applications 289(1–3), 41–54.
Pace, R. K. and Dongya Zou. (2000). “Closed-Form Maximum Likelihood Estimates of Nearest Neighbor Spatial Dependence,” Geographical Analysis 32(2), 154–172.
Ripley, B. D. (1988). Statistical Inference for Spatial Processes, New York: Cambridge University Press.
Rigaux, Philippe, Michel Scholl, and Agnes Voisard. (2002), Spatial Databases with Application to GIS, New York: Academic Press.
Russell, Gary J. and Ann Petersen. (2000). “Analysis of Cross-Category Dependence in Market Basket Selection,” Journal of Retailing 76, 367–392.
Sismeiro, Catarina. (2004). “Microlevel Spatial Data: Challenges and the Effects of Macrolevel Structure,” Position Paper, Session on Spatial Models in Marketing, Invitational Choice Symposium.
Sorensen Associates. (2004). Introducing Path Tracker, Product Brochure, http://www.sorensen-associates.com/.
Tanner, Martin A. (1996). Tools for Statistical Inference: Methods for the Exploration of Poseterior Distributions and Likelihood Functions, New York: Springer-Verlag.
Ter Hofstede, Frenkel, Michel Wedel, and Jan-Benedict E. M. Steenkamp. (2002). “Identifying Spatial Segments in International Markets,” Marketing Science 21, 160–177.
Ter Hofstede, Frenkel. (2004). “On the Spatial Organization of Consumer Needs,” Position Paper, Session on Spatial Models in Marketing, Invitational Choice Symposium.
Thomadsen, Raphael. (2004). “Optimal Location Choice: Which Products Should Firms Offer?,” Presentation, Session on Spatial Models in Marketing, Invitational Choice Symposium.
Train, Kenneth E. (2003). Discrete Choice Methods with Simulation, New York: Cambridge University Press.
Waller, Lance A., Bradley P. Carlin and Hong Xia. (1997). “Structuring Correlation Within Hierarchical Spatio-temporal Models for Disease Rates,” in Timothy G. Gergoire et al. (eds.), Modelling Longitudinal and Spatially Correlated Data, New York: Springer-Verlag, 309–319.
Wedel, Michel and Rik Pieters. (2000). “Eye Fixations on Advertisements and Memory for Brands: A Model and Findings,” Marketing Science 19, 297–312.
Yang, Sha and Greg M. Allenby. (2003). “Modeling Interdependent Consumer Preferences,” Journal of Marketing Research 40, 282–294.
Yang, Sha. (2004). “Understanding the Interdependence in Consumer Preferences via Spatial Modeling,” Position Paper, Session on Spatial Models in Marketing, Invitational Choice Symposium.
This paper is based upon the discussions of the Spatial Models in Marketing seminar at the Sixth Invitational Choice Symposium, June 2004. Eric T. Bradlow, Bart Bronnenberg and Gary J. Russell served as co-chairs of the session.
About this article
Cite this article
Bradlow, E.T., Bronnenberg, B., Russell, G.J. et al. Spatial Models in Marketing. Market Lett 16, 267–278 (2005). https://doi.org/10.1007/s11002-005-5891-3
- Spatial Autocorrelation
- Important Research
- Spatial Model
- Science Application