Dimensions of Consumer Expertise
Abstract
The purpose of this article is to review basic empirical results from the psychological literature in a way that provides a useful foundation for research on consumer knowledge. A conceptual organization for this diverse literature is provided by two fundamental distinctions. First, consumer expertise is distinguished from product-related experience. Second, five distinct aspects, or dimensions, of expertise are identified: cognitive effort, cognitive structure, analysis, elaboration, and memory. Improvements in the first two dimensions are shown to have general beneficial effects on the latter three. Analysis, elaboration, and memory are shown to have more specific interrelationships. The empirical findings related to each dimension are reviewed and, on the basis of those findings, specific research hypotheses about the effects of expertise on consumer behavior are suggested.
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Premium users are better equipped to develop conceptual structures such as beliefs and evaluations regarding the contents and value-added of the premium subscription than basic users.
“Because of their prior engagement with the premium features, the premium users are better equipped to develop conceptual structures (Alba & Hutchinson, 1987) such as beliefs and evaluations regarding the contents and value-added of the premium subscription than the basic users who generally need to rely on the information available to them from secondary sources.”
From What drives subscribing to premium in freemium services? A consumer value‐based view of differences between upgrading to and staying with premium (2020) · cites this paper as Alba & Hutchinson, 1987
The use of online music streaming in Finland is most common in age cohorts below 40 years, and the proportion of premium users is largest in age cohorts below 30 years.
“The use of online music streaming in Finland is most common in the age cohorts below 40 years, and the proportion of premium users is largest in the age cohorts below 30 years.”
From What drives subscribing to premium in freemium services? A consumer value‐based view of differences between upgrading to and staying with premium (2020) · cites this paper as [2]
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“Retrieval depends on the strength and structure of these associations: recall is more likely when the context at retrieval resembles the context at encoding (Alba and Hutchinson 1987; Bettman 1979; Lynch and Srull 1982).”
The Past, Present, and Future of Customer Knowledge Management: A Review and Research Agenda
Ourzik, V. Y. (2026) · Knowledge and Process Management · doi:10.1002/kpm.70076 · Cited by 1 · see citing works
- Authors
- Alba, J. W., & Hutchinson, J. W.
- Venue
- Journal of Consumer Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1987-03
- Volume
- 13
- Issue
- 4
- Pages
- 411
- ISSN
- 0093-5301 (ISSN-L)
- 1537-5277
- OpenAlex
- W2108860923
- Cited by
- 4,375
- References
- 363
- Citations by year
- 2026: 160 · 2025: 130 · 2024: 136 · 2023: 160 · 2022: 153 · 2021: 177 · 2020: 176 · 2019: 195 · 2018: 184 · 2017: 210 · 2016: 199 · 2015: 195 · 2014: 211 · 2013: 181 · 2012: 200
- FWCI
- 57.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Consumer Research (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior in Brand Consumption and Identification
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- consumer expertise, consumer knowledge, cognitive effort, cognitive structure, analysis, elaboration, memory, consumer behavior, research hypotheses
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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