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Cited by 117Recommender Systems and TechniquesDigital Marketing and Social MediaConsumer Retail Behavior Studies

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Assessing the impact of recommender agents on on-line consumer unplanned purchase behavior

Hostler, R. Eric, Yoon, Victoria Y., Guo, Zhiling, Guimaraes, Tor, Forgionne, Guisseppi·2011·Information & Management
DOI 10.1016/j.im.2011.08.002
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Abstract

Recommendation agents (RAs) have been used by many Internet businesses such as Amazon and Netflix. However, few authors have studied how consumer behavior is affected by those that make suggestions to online consumers based on their recent shopping behavior. Fewer still have examined the role that RAs play in influencing impulse purchasing decisions online. Our study developed a theoretical model to illustrate the impact of RAs on online consumer behavior. The model was tested through an online shopping simulation which used a collaborative filtering based product RA. Particular attention was paid to the effects of an RA on consumer behavior; we found that it increased promotion and product search effectiveness, user satisfaction with the website, and unplanned purchases. Results showed that our model provided insights into the impact of an RA on online consumer behavior and thus provided suggestions for implementing effective systems.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.im.2011.08.002

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

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Verification

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Citations

Cites

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Cited by

Metadata

Authors
Hostler, R. E., Yoon, V. Y., Guo, Z., Guimaraes, T., & Forgionne, G.
Affiliations
  • York College of Pennsylvania (US)
  • Virginia Commonwealth University (US)
  • City University of Hong Kong (HK)
  • University of Maryland, Baltimore County (US)
ORCID
Venue
Information & Management
Publisher
Elsevier BV
Published
2011-12
Volume
48
Issue
8
Pages
336-343
ISSN
0378-7206 (ISSN-L)
DOI
10.1016/j.im.2011.08.002
OpenAlex
W2162939048
Cited by
117
References
39
Citations by year
2026: 4 · 2025: 6 · 2024: 10 · 2023: 9 · 2022: 11 · 2021: 8 · 2020: 10 · 2019: 11 · 2018: 7 · 2017: 8 · 2016: 7 · 2015: 9 · 2014: 5 · 2013: 9 · 2012: 3
FWCI
15.64
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Information & Management (publishedVersion)
  • Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Retail Behavior Studies
Keywords
recommendation agents, online shopping, unplanned purchases, impulse buying, collaborative filtering, online consumer behavior, promotion effectiveness

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.

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Data sources

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.