Spatial Models in Marketing

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 crosssectional and longitudinal correlations among responses to be explicitly modeled...

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Bibliographic Details
Published in:	Marketing letters Vol. 16; no. 3/4; pp. 267 - 278
Main Authors:	Bradlow, Eric T., Bronnenberg, Bart, Russell, Gary J., Arora, Neeraj, Bell, David R., Duvvuri, Sri Devi, Hofstede, Frankel Ter, Sismeiro, Catarina, Thomadsen, Raphael, Yang, Sha
Format:	Journal Article
Language:	English
Published:	New York Springer 01-12-2005 Springer Nature B.V
Subjects:	Brands Business studies Category management Consumer behavior Consumers Contiguity Econometrics Economic models Geodetic position Market planning Marketing Marketing research Modeling Parametric models Radio frequency identification Science Spatial models Spatial statistics Statistical models Time series Variables
Online Access:	Get full text
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Summary:	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 crosssectional 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.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0923-0645 1573-059X
DOI:	10.1007/s11002-005-5891-3