The impact of electronic word-of-mouth communication: A literature analysis and integrative model
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91% of respondents said they would like to consult online reviews, blogs, and other user-generated information before buying a new product or service.
“For example, 91% of respondents said they would like to consult online reviews, blogs, and other user-generated information before buying a new product or service [40].”
From Investigating the Impact of Critical Factors on Continuance Intention towards Cross-Border Shopping Websites (2019) · cites this paper as [40]
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- Authors
- Cheung, C. M. K., & Thadani, D. R.
- Affiliations
- Hong Kong Baptist University (HK)
- City University of Hong Kong (HK)
- Corresponding author
- Cheung, Christy M.K.
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2012-12
- Volume
- 54
- Issue
- 1
- Pages
- 461-470
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2040924390
- Cited by
- 2,005
- References
- 80
- Citations by year
- 2026: 334 · 2025: 274 · 2024: 176 · 2023: 189 · 2022: 161 · 2021: 169 · 2020: 133 · 2019: 132 · 2018: 105 · 2017: 106 · 2016: 101 · 2015: 53 · 2014: 50 · 2013: 21 · 2012: 1
- FWCI
- 123.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Decision Support Systems (publishedVersion)
- HKBU Institutional Repository (Hong Kong Baptist University) (submittedVersion)
- Funders
- Hong Kong Baptist University
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
- Keywords
- electronic word of mouth, consumer behavior, integrative framework, online reviews, consumer influence
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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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