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Published in: Customer Needs and Solutions 2/2014

01-06-2014 | Research Article

An Across-Store Analysis of Intrinsic and Extrinsic Cross-Category Effects

Authors: Venkatesh Shankar, P. K. Kannan

Published in: Customer Needs and Solutions | Issue 2/2014

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Abstract

An important part of the rapidly growing shopper marketing practice is cross-category retail management. In managing two related product categories, retailers face some important questions: Which category should be stocked more? How close to each other should they be stocked in the store (aisle adjacency)? Which category should be promoted more often? And when should the two categories be sold as a bundle? To address these questions, we examine how purchases of related product and subproduct categories influence one another, and how the relative aisle locations of two related product categories influence their respective purchases. We consider both extrinsic (aisle location-based) and intrinsic (affinity-based) cross-category effects. Using aggregate store level data together with store descriptor and store shopper demographic data, we estimate a simultaneous system of models for two related product categories, soft drinks and salty snacks. We also estimate a system of salty snack subcategory purchase models. We find that both extrinsic and intrinsic cross-category effects are asymmetric, that is, different categories and subcategories have different effects on one another. We discuss the theoretical and managerial implications of these findings.

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Footnotes
1
Retailers also need to address the issue of how much shelf space to allocate to each brand. Since our paper does not consider shelf space issues, we do not pursue this issue in the paper.
 
2
For simplicity, in this discussion, we ignore the processes by which shoppers classify products into categories, see Cohen and Basu [7].
 
3
We mention a bundled product as a conceptual endpoint for in-store product proximity. However, this research focuses on the proximity of different categories’ locations within the store. Because its relevance to this paper is peripheral, we do not review bundling research.
 
4
Many retail chains, including the chain we study, typically have common pricing and promotional variables across stores in a geographical area. Therefore, even if we were to include average pricing and promotion variables in our cross-sectional model, such variables will unlikely differ across stores within the same chain.
 
5
Because each subcategory is in the same aisle as the parent category, we do not have the relative aisle adjacencies of the subcategories as independent variables. Instead, we use the aisle adjacency with respect to soft drinks as the independent variable.
 
6
We could potentially add another model with aisle adjacency as a function of exogenous variables such as category shelf space requirement, category sales, and other in-store locational constraints. However data on these additional exogenous variables are not easy to obtain. Moreover, stores do not vary aisle adjacency systematically over time for us to obtain more observations.
 
7
We also estimated all the models using ordinary least squares (OLS). However, all models showed significant and high cross-error correlation between the salty snack and beverage equations. Therefore, we interpret the 3SLS results. The substantive results from the OLS estimation are mostly consistent with those of the 3SLS estimation. The detailed results can be obtained from the authors.
 
8
To validate the results from the system of subcategory models on the groups of complements and substitutes, we also performed cluster analyses (both k-means and Ward’s hierarchical analyses) on the purchases of all salty snack subcategories. The cluster analyses produced two maximally differentiated clusters, one with potato, tortilla, corn chips, and popcorn, and the other with cheese puffs and pretzels. Thus, the results from the 3SLS models are consistent with those from the cluster analyses. Unlike cluster analysis, our approach provides the signs and magnitudes of the cross-effects.
 
9
We realize that we do not analyze promotional data in this paper. However, because the expected effect of promotions is similar to that of nontemporal extrinsic effects, we are able to offer managerial suggestions on temporal intrinsic effects.
 
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Metadata
Title
An Across-Store Analysis of Intrinsic and Extrinsic Cross-Category Effects
Authors
Venkatesh Shankar
P. K. Kannan
Publication date
01-06-2014
Publisher
Springer US
Published in
Customer Needs and Solutions / Issue 2/2014
Print ISSN: 2196-291X
Electronic ISSN: 2196-2928
DOI
https://doi.org/10.1007/s40547-014-0012-1

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