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Cited by 298

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Taxonomy of Buying Decision Approaches

Bunn, Michele D.·1993·Journal of Marketing

Abstract

The author reports the development of a classification scheme of buying patterns and situations. Unlike previous conceptual schemes, it consists of six prototypical “buying decision approaches” identified through an empirically based taxonomy development procedure. A mix of underlying buying activities distinguishes the categories: search for information, use of analysis techniques, focus on proactive issues, and reliance on control mechanisms. The use of a particular buying decision approach depends on four situational characteristics: purchase importance, task uncertainty, extensiveness of choice, and perceived buyer power. The findings reveal some patterns that are similar to previous classification schemes, but new variations allow for a conceptual extension of the literature. The resulting framework is useful to marketing managers, who can view their customer segments in terms of the categories in the taxonomy. Further, it provides a tool by which sales representatives can develop adaptive selling approaches based on a small set of buying situations and corresponding buying decision approaches.

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Metadata

Authors
Bunn, M. D.
Venue
Journal of Marketing
Published
1993-01
Volume
57
Issue
1
Pages
38-56
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
OpenAlex
W2090288937
Cited by
298
References
1
FWCI
33.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Taxonomy of Buying Decision Approaches. https://app.cochat.ai/papers/10.1177/002224299305700103
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Bunn, M. D. (1993). Taxonomy of Buying Decision Approaches. Journal of Marketing. https://doi.org/10.1177/002224299305700103

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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.