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Using a Variety-Seeking Model to Identify Substitute and Complementary Relationships among Competing Products

Lattin, James M., Mcalister, Leigh·1985·Journal of Marketing Research

Abstract

Current techniques using brand-switching data to infer competitive relationships among products are based on the assumption that those brands most frequently switched between are the closest substitutes. For product classes in which variety seeking is an important determinant of consumer behavior, this assumption is probably violated. A technique is proposed which accounts for the fact that consumers may switch between brands not because the brands are substitutes, but because the brands complement one another to meet the consumers’ desire for variety. The approach utilizes constrained nonlinear optimization to determine model coefficients that describe substitution and complementarity among brands. The proposed technique is illustrated with individual consumption histories for a frequently purchased packaged good and is shown to extend the range of insights provided by current brand-switching techniques.

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Metadata

Authors
Lattin, J. M., & Mcalister, L.
Venue
Journal of Marketing Research
Published
1985-08
Volume
22
Issue
3
Pages
330-339
ISSN
  • 0022-2437 (ISSN-L)
  • 1547-7193
OpenAlex
W2020845025
Cited by
229
References
0
FWCI
17.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Using a Variety-Seeking Model to Identify Substitute and Complementary Relationships among Competing Products. https://app.cochat.ai/papers/10.1177/002224378502200308
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Lattin, J. M., & Mcalister, L. (1985). Using a Variety-Seeking Model to Identify Substitute and Complementary Relationships among Competing Products. Journal of Marketing Research. https://doi.org/10.1177/002224378502200308

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.