Acceptance of recommendations to buy in online retailing.
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Personalized online recommendations for products of interest improve women's online shopping experience.
“personalized online recommendations for products of interest improve women’s online shopping experience (Baier and Stüber, 2010).”
From Motivational and Affective Factors Underlying Consumer Dropout and Transactional Success in eCommerce: An Overview (2020) · cites this paper as Baier and Stüber, 2010
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Outfit Browser – An Image-data-driven User Interface for Self-service Systems in Fashion Stores
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Personalized Product Recommendations: Evidence from the Field
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- Authors
- Baier, D., & Stüber, E.
- Affiliations
- Brandenburg University of Technology Cottbus-Senftenberg (DE)
- Corresponding author
- Baier, Daniel
- ORCID
- Baier, Daniel
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 17
- Issue
- 3
- Pages
- 173-180
- ISSN
- 0969-6989 (ISSN-L)
- OpenAlex
- W2084468777
- Cited by
- 106
- References
- 67
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 10 · 2023: 2 · 2022: 12 · 2021: 7 · 2020: 11 · 2019: 7 · 2018: 7 · 2017: 3 · 2016: 6 · 2015: 10 · 2014: 7 · 2013: 2 · 2012: 9
- FWCI
- 11.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Retailing and Consumer Services (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- online retail, personalized recommendation, technology acceptance, consumer acceptance, recommendation quality, online shopping experience, customer satisfaction, personalization
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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