How do enhanced and unique features affect new product preference? The moderating role of product familiarity
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Single-item measures of familiarity are well-established and have been used in consumer behavior and psychology research due to their efficiency and validity.
“Single-item measures of familiarity are well-established and have been used in consumer behavior and psychology research due to their efficiency and validity [42,85,89,90].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [90]
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- Authors
- Zhou, K. Z., & Nakamoto, K.
- Affiliations
- University of Hong Kong (HK)
- Virginia Tech (US)
- Corresponding author
- Zhou, Kevin Zheng
- ORCID
- Zhou, Kevin Zheng
- Venue
- Journal of the Academy of Marketing Science
- Published
- 2007-02-23
- Volume
- 35
- Issue
- 1
- Pages
- 53-62
- ISSN
- 0092-0703 (ISSN-L)
- 1552-7824
- OpenAlex
- W2120596871
- Cited by
- 124
- References
- 25
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 14 · 2023: 7 · 2022: 5 · 2021: 11 · 2020: 6 · 2019: 7 · 2018: 4 · 2017: 4 · 2016: 10 · 2015: 7 · 2014: 4 · 2013: 6 · 2012: 5
- FWCI
- 10.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Academy of Marketing Science (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior in Brand Consumption and Identification
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- product familiarity, product differentiation, performance uncertainty, consumer preferences
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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