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Cited by 406

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Divide and Prosper: Consumers’ Reactions to Partitioned Prices

Morwitz, Vicki G., Greenleaf, Eric A., Johnson, Eric J.·1998·Journal of Marketing Research

Abstract

Many firms divide a product's price into two mandatory parts, such as the base price of a mail-order shirt and the surcharge for shipping and handling, rather than charging a combined, all-inclusive price. The authors call this strategy partitioned pricing. Although firms presumably use partitioned pricing to increase demand and profits, there is little clear empirical support that these prices increase demand or any theoretical explanation for why this should occur. The authors test hypotheses of how consumers process partitioned prices and how partitioned pricing affects consumers’ processing and recall of total costs and their purchase intentions and certain types of demand. The results suggest that partitioned prices decrease consumers’ recalled total costs and increase their demand. The manner in which the surcharge is presented and consumers’ affect for the brand name also influence how they react to partitioned prices.

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Metadata

Authors
Morwitz, V. G., Greenleaf, E. A., & Johnson, E. J.
Venue
Journal of Marketing Research
Published
1998-11
Volume
35
Issue
4
Pages
453-463
ISSN
  • 0022-2437 (ISSN-L)
  • 1547-7193
OpenAlex
W3124346291
Cited by
406
References
7
FWCI
17.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Divide and Prosper: Consumers’ Reactions to Partitioned Prices. https://app.cochat.ai/papers/10.1177/002224379803500404
The paper
Morwitz, V. G., Greenleaf, E. A., & Johnson, E. J. (1998). Divide and Prosper: Consumers’ Reactions to Partitioned Prices. Journal of Marketing Research. https://doi.org/10.1177/002224379803500404

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.