Exploring Electronic Word-of-Mouth (eWOM) in The Consumer Purchase Decision-Making Process: The Case of Online Holidays – Evidence from United Kingdom (UK) Consumers
Abstract
This study explores the role of electronic word-of-mouth (eWOM) in the consumer decision-making process when purchasing a holiday. Using an ethnographic approach, it explores the role of eWOM on consumers’ attitudes toward online reviews (eReviews) and their subsequent behavior. Across the consumer decision-making processes – information search, evaluation, and purchase – the study develops a conceptual framework with three eWOM dimensions: (1) motivation, (2) source, and (3) content. Findings explore the variations of eWOM’s influence across the decision-making stages with implications for theory and practice. The study further highlights implications for segmentation practices in the tourism industry.
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Travel purchases are divided into three stages: information search, alternative appraisal, and investment.
“Travel purchases are divided into three stages (Chen et al., 2015): information search, alternative appraisal, and investment.”
From Welcome to the destination! Social media influencers as cogent determinant of travel decision: A systematic literature review and conceptual framework (2023) · cites this paper as Chen et al., 2015
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A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549 · see citing works
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004) · Journal of Interactive Marketing · doi:10.1002/dir.10073 · Cited by 5,916 · see citing works
Integrating quantitative and qualitative research: How is it done
Bryman, A. (2006) · Qualitative Research · doi:10.1177/1468794106058877 · Cited by 3,354 · see citing works
User generated content: the use of blogs for tourism organisations and tourism consumers
Akehurst, G. (2009) · Service Business · doi:10.1007/s11628-008-0054-2 · Cited by 422 · see citing works
Gretzel, U., Yuan, Y.-L., & Fesenmaier, D. R. (2000) · Journal of Travel Research · doi:10.1177/004728750003900204 · Cited by 384 · see citing works
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Saini, H., Kumar, P., & Oberoi, S. (2023) · Cogent Social Sciences · doi:10.1080/23311886.2023.2240055 · Cited by 51 · see citing works
Crnjak-Karanović, B., Kursan Milaković, I., & Elez, J. (2023) · Young Consumers · doi:10.1108/yc-08-2022-1590 · Cited by 20 · see citing works
- Authors
- Chen, C.-H., Nguyen, B., Klaus, P. “., & Wu, M.-S.
- Affiliations
- Oxford Brookes University (GB)
- East China University of Science and Technology (CN)
- École Supérieure du Commerce Extérieur (FR)
- University of Winchester (GB)
- Corresponding author
- Chen, Cheng-Hao
- Venue
- Journal of Travel & Tourism Marketing
- Publisher
- Informa UK Limited
- Published
- 2015-07-03
- Volume
- 32
- Issue
- 8
- Pages
- 953-970
- ISSN
- 1054-8408 (ISSN-L)
- 1540-7306
- OpenAlex
- W1753765673
- Cited by
- 107
- References
- 5
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 13 · 2023: 15 · 2022: 19 · 2021: 15 · 2020: 12 · 2019: 10 · 2018: 7 · 2017: 3 · 2016: 4
- FWCI
- 15.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Travel & Tourism Marketing (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- 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 › Sociology and Political Science › Diverse Aspects of Tourism Research
- Keywords
- electronic word of mouth, online reviews, purchase decision, online travel, information search, consumer attitudes, tourist segmentation, United Kingdom consumers
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