The DOI matches its Crossref record; 79 of the 81 references it cites were found in a registry or an index.
The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors
Open accessAbstract
The increasing amount of electronic word of mouth (eWOM) has significantly affected the way consumers make purchase decisions. Empirical studies have established an effect of eWOM on sales but disagree on which online platforms, products, and eWOM metrics moderate this effect. The authors conduct a meta-analysis of 1,532 effect sizes across 96 studies covering 40 platforms and 26 product categories. On average, eWOM is positively correlated with sales (.091), but its effectiveness differs across platform, product, and metric factors. For example, the effectiveness of eWOM on social media platforms is stronger when eWOM receivers can assess their own similarity to eWOM senders, whereas these homophily details do not influence the effectiveness of eWOM for e-commerce platforms. In addition, whereas eWOM has a stronger effect on sales for tangible goods new to the market, the product life cycle does not moderate the eWOM effectiveness for services. With respect to the eWOM metrics, eWOM volume has a stronger impact on sales than eWOM valence. In addition, negative eWOM does not always jeopardize sales, but high variability does.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Indeed, online WOM has been—and, we contend, will continue to be—important in marketing (e.g., in the meta-analysis by Babić Rosario et al. 2016 the authors found, on average, a positive correlation between online WOM and sales).”
From The future of social media in marketing (2020) · cites this paper as Babić Rosario et al. 2016
Citations
Cites
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
(1993) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(93)91697-o · Cited by 18,452
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
A Simple Model of Herd Behavior
Banerjee, A. V. (1992) · The Quarterly Journal of Economics · doi:10.2307/2118364 · Cited by 6,556
The Effect of Word of Mouth on Sales: Online Book Reviews
Chevalier, J. A., & Mayzlin, D. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.345 · Cited by 6,003
The Handbook of Research Synthesis and Meta-Analysis
(2019) · doi:10.7758/9781610448864 · Cited by 4,553
The psychology of social impact
Latané, B. (1981) · American Psychologist · doi:10.1037/0003-066x.36.4.343 · Cited by 2,864
Social Ties and Word-of-Mouth Referral Behavior
Brown, J. J., & Reingen, P. H. (1987) · Journal of Consumer Research · doi:10.1086/209118 · Cited by 2,388
Consumer Choice between Hedonic and Utilitarian Goods
Dhar, R., & Wertenbroch, K. (2000) · Journal of Marketing Research · doi:10.1509/jmkr.37.1.60.18718 · Cited by 2,239
Feldman, J. M., & Lynch, J. G. (1988) · Journal of Applied Psychology · doi:10.1037/0021-9010.73.3.421 · Cited by 2,070
Flagged first, then by citations
2 of the 81 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
- Hiura Kazuki, 2010, Journal of eBusiness, 10, 38
- Lipsey Mark W., 2001, Applied Social Research Methods Series Practical Meta-Analysis
- Rosenthal Robert, 1988, Applied Social Research Methods Series Meta-Analytic Procedures for Social Research
- Zeithaml Valarie A., 1981, Marketing of Services, 186
Cited by
Sorted by citations
Items 301–400 of 1,112
Antecedents and consequences of corporate social responsibility: a meta-analysis
Santini, F. D. O., Ladeira, W. J., Dalmoro, M., & de Matos, C. A. (2021) · Journal of Social Marketing · doi:10.1108/jsocm-08-2020-0157 · Cited by 30
Tseng, S.-L., Lu, S., Weathers, D., & Grover, V. (2023) · Decision Support Systems · doi:10.1016/j.dss.2023.113981 · Cited by 30
El-Baz, B. E.-S., Elseidi, R. I., & El-Maniaway, A. M. (2018) · International Journal of Online Marketing · doi:10.4018/ijom.2018100101 · Cited by 30
Shaker, A. K., Mostafa, R. H. A., & Elseidi, R. I. (2021) · European Journal of Management and Business Economics · doi:10.1108/ejmbe-01-2021-0036 · Cited by 30
Stieglitz, S., Meske, C., Roß, B., & Mirbabaie, M. (2018) · Information Systems Frontiers · doi:10.1007/s10796-018-9867-2 · Cited by 32
Marconatto, D. A. B., Teixeira, E. G., Santini, F. D. O., & Ladeira, W. J. (2021) · Journal of Small Business and Enterprise Development · doi:10.1108/jsbed-11-2020-0411 · Cited by 29
Huang, G. I., Wong, I. A., Xiong, X., & Yi, K. (2022) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2022.103267 · Cited by 29
Purchase decision in terms of content marketing and e-WOM on social media
Santy, R. D., & Andriani, R. (2023) · Journal of Eastern European and Central Asian Research (JEECAR) · doi:10.15549/jeecar.v10i6.1502 · Cited by 29
Sharing product harm information: The effects of self-construal and self-relevance
Akpınar, E., Verlegh, P. W. J., & Smidts, A. (2018) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2018.01.001 · Cited by 28
Liu, R., An, E., & Zhou, W. (2021) · The Journal of Marketing Theory and Practice · doi:10.1080/10696679.2020.1867478 · Cited by 30
Artificial Intelligence Applications to Customer Feedback Research: A Review
Lee, P. S., Chakraborty, I., & Banerjee, S. (2023) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1548-643520230000020010 · Cited by 33
Baah-Peprah, P., & Shneor, R. (2021) · International Journal of Big Data Management · doi:10.1504/ijbdm.2021.10041844 · Cited by 28
Impacts of logistics information on sales: Evidence from Alibaba
Luo, J., Rong, Y., & Zheng, H. (2020) · Naval Research Logistics (NRL) · doi:10.1002/nav.21884 · Cited by 27
More than words: Understanding how valence and content affect review value
Qiao, T., Shan, W., Zhang, M., & Wei, Z. (2022) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2022.103274 · Cited by 27
Debates and assumptions about motion picture performance: a meta-analysis
Carrillat, F. A., Legoux, R., & Hadida, A. L. (2018) · UTS ePRESS (University of Technology Sydney) · doi:10.17863/cam.17354 · Cited by 27
Relative persuasiveness of repurchase intentions versus recommendations in online reviews
Ravula, P., Jha, S., & Biswas, A. (2022) · Journal of Retailing · doi:10.1016/j.jretai.2022.06.001 · Cited by 27
Arora, A. S., Arora, A., & Taras, V. (2019) · International Journal of Cross Cultural Management · doi:10.1177/1470595819856379 · Cited by 30
Understanding the influence of culture on customer engagement and recommendation intentions
Messner, W. (2020) · Journal of Strategic Marketing · doi:10.1080/0965254x.2020.1849363 · Cited by 28
Bozkurt, S., & Gligor, D. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102448 · Cited by 27
The complexities of consumer empowerment in the modern consumption environment
Han, J. J., & Broniarczyk, S. M. (2022) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2022.101333 · Cited by 30
Delre, S. A., & Luffarelli, J. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.113329 · Cited by 33
Kim, D. Y., & Kim, S. Y. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103409 · Cited by 27
When online reviews meet ACSI: how ACSI moderates the effects of online reviews on hotel revenue
Gao, B., Xiaojie, D., Chen, W., Jiang, X., & Wu, J. (2020) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2020.1767261 · Cited by 27
On linking socioeconomic status to consumer loyalty behaviour
White, C. J., & Tong, E. (2019) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.05.001 · Cited by 27
Offensive pricing strategies for online platforms
Li, F., DU, T. C.-T., & Wei, Y. R. (2019) · International Journal of Production Economics · doi:10.1016/j.ijpe.2019.06.009 · Cited by 28
Chen, L., Rai, A., Chen, W., & Guo, X. (2024) · Information Systems Research · doi:10.1287/isre.2021.0150 · Cited by 26
Electronic word of mouth analysis for new product positioning evaluation
Gregoriades, A., & Pampaka, M. (2020) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2020.100986 · Cited by 26
Cultural and Individual Differences in Online Reviews
Messner, W. (2020) · Journal of International Consumer Marketing · doi:10.1080/08961530.2020.1722980 · Cited by 28
In platform we trust: How interchangeability affects trust decisions in collaborative consumption
Chameroy, F., Salgado, S., de Barnier, V., & Chaney, D. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122997 · Cited by 31
Impact of customer orientation on word-of-mouth and cross-buying
Mukerjee, K., & Shaikh, A. (2018) · Marketing Intelligence & Planning · doi:10.1108/mip-01-2018-0030 · Cited by 26
How collectivistic values affect online word-of-mouth
Pezzuti, T., & Leonhardt, J. M. (2020) · International Journal of Market Research · doi:10.1177/1470785320929200 · Cited by 26
Social media or online shopping websites: Will/how platforms influence eWOM effectiveness
Ni, Y., & Cheng, Q. (2024) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2024.101358 · Cited by 28
It’s not fake, it’s biased: insights into morality of incentivized reviewers
Rynarzewska, A. I. (2019) · Journal of Consumer Marketing · doi:10.1108/jcm-02-2018-2570 · Cited by 27
I like my app but I wanna try yours: exploring user switching from a learning perspective
Gu, J., Wang, X., & Lu, T. (2019) · Internet Research · doi:10.1108/intr-07-2018-0310 · Cited by 28
m-WOM in a brand’s Facebook fan page
Blas, S. S., Alcañiz, J. E. B., & Buzova, D. (2017) · Online Information Review · doi:10.1108/oir-08-2016-0237 · Cited by 25
Hornik, J., Satchi, R. S., & Rachamim, M. (2018) · Internet Research · doi:10.1108/intr-11-2017-0415 · Cited by 25
IOT-Enhanced Digital Marketing Conceptual Framework
Badica, A. L., & Mitucă, M. O. (2021) · BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE · doi:10.18662/brain/12.4/262 · Cited by 25
Measuring and managing service productivity: a meta-analysis
Hofmeister, J., Kanbach, D. K., & Hogreve, J. (2023) · Review of Managerial Science · doi:10.1007/s11846-023-00620-5 · Cited by 31
Buy Now, Think Later: Impulsive Buying Behavior among Generation Z in Indonesia
Fahriansah, F., Safarida, N., & Midesia, S. (2023) · Share Jurnal Ekonomi dan Keuangan Islam · doi:10.22373/share.v12i2.17453 · Cited by 25
Weber, T. J., Muehling, D. D., & Kareklas, I. (2019) · Journal of Marketing Communications · doi:10.1080/13527266.2019.1671479 · Cited by 24
Aesthetic quality matters: The visual effect of review helpfulness evaluation
Pan, X., Xie, L., & Hou, L. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103615 · Cited by 24
Promotions of online reviews from a channel perspective
Yang, W., Zhang, J., & Yan, H. (2022) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2022.102697 · Cited by 24
Customer management in Internet-based platform firms: review and future research directions
Yang, Z. G. O., Diao, Z., & Kang, J. S. (2020) · Marketing Intelligence & Planning · doi:10.1108/mip-01-2020-0012 · Cited by 25
Exploring Youtube Marketing Communication Among 200 Leading National Advertisers
Park, J., & McMahan, C. (2020) · Journal of Promotion Management · doi:10.1080/10496491.2020.1851845 · Cited by 24
Changes in service quality of sharing accommodation: Evidence from airbnb
Zuo, W., Bai, W., Zhu, W., He, X., & Qiu, X. (2022) · Technology in Society · doi:10.1016/j.techsoc.2022.102092 · Cited by 24
How to strategically respond to online hotel reviews: A strategy-aware deep learning approach
Ku, C., Chang, Y., & Wang, Y. (2024) · Information & Management · doi:10.1016/j.im.2024.103970 · Cited by 25
Assessing credibility in eWOM: a meta-analysis using the heuristic-systematic model
Chauhan, S., & Gupta, P. (2024) · Journal of Enterprise Information Management · doi:10.1108/jeim-01-2024-0027 · Cited by 25
Brand equity in Caribbean financial services: the moderating role of service providers
Rambocas, M., & Arjoon, S. (2019) · International Journal of Bank Marketing · doi:10.1108/ijbm-05-2019-0167 · Cited by 24
Hoekstra, J. C., & Leeflang, P. S. H. (2022) · European Management Journal · doi:10.1016/j.emj.2022.04.007 · Cited by 24
Attracting the millennial customer: the case of food trucks
Kraus, S., Sen, S. S., Savitskie, K., Ranganathan, S. K., & Brooks, J. (2022) · British Food Journal · doi:10.1108/bfj-09-2021-0996 · Cited by 24
How electronic word of mouth (eWOM) shapes consumer social media shopping
Beck, B. B., Koskie, M. M., & Locander, W. B. (2023) · Journal of Consumer Marketing · doi:10.1108/jcm-01-2023-5817 · Cited by 24
da Silva, N. S. D. A. C., & Vieira, V. A. (2019) · Revista Eletrônica de Ciência Administrativa · doi:10.21529/recadm.2019008 · Cited by 24
Can Online Consumer Reviews Signal Restaurant Closure: A Deep Learning-Based Time-Series Analysis
Tao, J., & Zhou, L. (2020) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2020.3016329 · Cited by 23
Guanxi or Justice? An Empirical Study of WeChat Voting
Zhou, Y., Yu, Y., Chen, X., & Zhou, X. (2018) · Journal of Business Ethics · doi:10.1007/s10551-018-4053-5 · Cited by 23
Dynamic and global drivers of salesperson effectiveness
Claro, D. P., RAMOS, C. S. D. M., & Palmatier, R. W. (2023) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-023-00954-2 · Cited by 23
Lee, J., & Park, C. H. (2022) · Internet Research · doi:10.1108/intr-11-2020-0632 · Cited by 23
Social and Demographic Predictors of Consumers’ Word of Mouth Engagement in Czechia
Mladenović, D., Bruni, R., & Kalia, P. (2020) · Journal of International Consumer Marketing · doi:10.1080/08961530.2020.1800547 · Cited by 23
Trust in the financial services context: a meta-analysis
Santini, F. D. O., Eberle, L., Ladeira, W. J., Milan, G. S., Graciola, A. P., & Sampaio, C. H. (2023) · International Journal of Bank Marketing · doi:10.1108/ijbm-06-2022-0248 · Cited by 23
Can online health information sources really improve patient satisfaction?
Sun, Y., Yu, J., Chiu, Y.-L., & Hsu, Y. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.940800 · Cited by 23
Recommendation matters: how does your social capital engage you in eWOM?
Baykal, B., & Hesapçı, Ö. (2022) · Journal of Consumer Marketing · doi:10.1108/jcm-08-2021-4842 · Cited by 26
Information technology adoption by small and medium enterprises: a meta-analysis
Santini, F. D. O., de Matos, C. A., Ladeira, W. J., Jardim, W. C., & Perin, M. G. (2022) · Journal of Small Business & Entrepreneurship · doi:10.1080/08276331.2022.2145787 · Cited by 23
Effects of app pricing structures on product evaluations
Wolkenfelt, M. R. J., & Situmeang, F. (2020) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-11-2018-0141 · Cited by 22
Transmission of negative brand-relevant content on social media
Powell, A. E., Stavros, C., & Dobele, A. R. (2021) · Journal of Product & Brand Management · doi:10.1108/jpbm-12-2020-3258 · Cited by 22
Cheng, X., Zeng, A., Yang, B., Liu, Y., & Zhang, X. (2025) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2025.101497 · Cited by 22
A dynamic evolutionary game model of web celebrity brand eWOM marketing control strategy
Liao, M., Zhang, J., & Wang, R. (2020) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-11-2019-0682 · Cited by 22
THE DYNAMIC EFFECTS OF ONLINE PRODUCT REVIEWS ON PURCHASE DECISIONS
Chen, J., Kou, G., & Peng, Y. (2018) · Technological and Economic Development of Economy · doi:10.3846/tede.2018.4545 · Cited by 23
Exploring the spoiler effect in the digital age: Evidence from the movie industry
Li, Y., Luo, X. R., Kai, L., & Xiao-bo, X. (2022) · Decision Support Systems · doi:10.1016/j.dss.2022.113755 · Cited by 22
Xu, Z., & Minghui, Q. (2023) · Mathematics · doi:10.3390/math11143059 · Cited by 22
The influence of online review adoption on the profitability of capacitated supply chains
Huang, S., Potter, A. T., Eyers, D. R., & Li, Q. (2021) · Omega · doi:10.1016/j.omega.2021.102501 · Cited by 21
Impact of Political Television Advertisements on Viewers’ Response to Subsequent Advertisements
Fossen, B. L., Mallapragada, G., & De, A. (2020) · Marketing Science · doi:10.1287/mksc.2020.1260 · Cited by 21
The influence of launching mobile channels on online customer reviews
Kim, J. M., Lee, E., & Mariani, M. M. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.08.048 · Cited by 21
Can negative buzz increase awareness and purchase intent?
Han, J. A., Feit, E. M., & Srinivasan, S. (2019) · Marketing Letters · doi:10.1007/s11002-019-09501-y · Cited by 21
Chen, H., Duan, W., & Zhou, W. (2021) · Information & Management · doi:10.1016/j.im.2021.103532 · Cited by 21
Overcoming Institutional and Infrastructure Weaknesses in China via Online Third-Party Marketplaces
Bei, Z., & Gielens, K. (2020) · Journal of International Marketing · doi:10.1177/1069031x20915850 · Cited by 21
Network capabilities and firm performance: a meta-analytical study
Wegner, D., Santini, F. D. O., & Toigo, T. (2023) · Management Decision · doi:10.1108/md-11-2021-1430 · Cited by 21
Price sensitivity and online shopping behavior during the COVID-19 pandemic
Rahmani, V., & Kordrostami, E. (2023) · Journal of Consumer Marketing · doi:10.1108/jcm-07-2021-4777 · Cited by 21
Social media insights for non-luxury fashion SMEs in emerging markets: evidence from young consumers
Senanu, B., Anning‐Dorson, T., & Tackie, N. N. (2023) · Journal of Fashion Marketing and Management · doi:10.1108/jfmm-02-2022-0026 · Cited by 21
Yang, H., Xu, N., Lin, X., & Zhang, W. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100833 · Cited by 22
Has the COVID-19 pandemic changed the influence of word-of-mouth on purchasing decisions?
Byun, K. J., Park, J., Yoo, S., & Cho, M. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103411 · Cited by 23
The Impact of Online Q&As on Product Sales: The Case of Amazon Answer
Khern-am-nuai, W., Ghasemkhani, H., Qiao, D., & Kannan, K. (2023) · Information Systems Research · doi:10.1287/isre.2023.1233 · Cited by 20
Hamby, A. M., Kim, H., & Spezzano, F. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114289 · Cited by 20
Kovács, B. (2024) · Organizational Research Methods · doi:10.1177/10944281231223412 · Cited by 23
A discrete electronic word-of-mouth propagation model and its application in online social networks
Wang, J., Wang, X., & Li, Y. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.121172 · Cited by 20
Investigating conflicting online review information:evidence from Amazon.com
Kordrostami, E., & Rahmani, V. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102125 · Cited by 21
Kim, Y., Lee, M., Kim, B.-D., & Roh, T. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.103759 · Cited by 20
The Impact of Digital Innovations on Marketing and Consumers
Ratchford, B. T. (2019) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1548-643520190000016005 · Cited by 22
A relationship marketing perspective on delight, its antecedents and outcomes in a banking context
Svotwa, T. D., Makanyeza, C., Roberts-Lombard, M., & Jaiyeoba, O. O. (2023) · European Business Review · doi:10.1108/ebr-09-2022-0170 · Cited by 20
Not all consumer-generated images are attractive and persuasive: A heuristic cue perspective
Zheng, Y., Ma, B., Zhou, X., & Lu, B. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108285 · Cited by 20
Tan, W.-K. (2022) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-06-2021-0456 · Cited by 20
A comparison of hotel ratings between verified and non-verified online review platforms
Figini, P., Vici, L., & Viglia, G. (2020) · International Journal of Culture Tourism and Hospitality Research · doi:10.1108/ijcthr-10-2019-0193 · Cited by 20
Online program engagement and audience size during television ads
Fossen, B. L., & Bleier, A. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-021-00769-z · Cited by 19
Noguti, V. (2022) · European Journal of Marketing · doi:10.1108/ejm-09-2020-0695 · Cited by 19
Competing for Temporary Advantage in a Hypercompetitive Mobile App Market
James, T. L., Qiao, Z., Shen, W., Wang, G. A., & Fan, W. (2023) · MIS Quarterly · doi:10.25300/misq/2022/15079 · Cited by 19
“Click like if you like it”: the effect of directional posts on social network sites
López, M., Piñero, M. S., & Verlegh, P. W. J. (2017) · Online Information Review · doi:10.1108/oir-01-2016-0020 · Cited by 19
Consumers gain equivalent levels of happiness from sharing about an experience and an object
Bastos, W. (2019) · European Journal of Marketing · doi:10.1108/ejm-04-2018-0233 · Cited by 19
Overcoming the blockchain technology credibility gap
Mazzù, M. F., Pozharliev, R., Andria, A., & Baccelloni, A. (2023) · Psychology and Marketing · doi:10.1002/mar.21855 · Cited by 19
Investigating the effects of textual reviews from consumers and critics on movie sales
Deng, T. (2020) · Online Information Review · doi:10.1108/oir-10-2019-0323 · Cited by 22
Zhang, M., Wang, L., Li, Y., & Wang, G. A. (2022) · Tourism Management · doi:10.1016/j.tourman.2022.104622 · Cited by 19
Tseng, T. H., Chang, S.-H., Wang, Y.-M., Wang, Y.-M., & Lin, S.-J. (2020) · Sustainability · doi:10.3390/su13010193 · Cited by 19
Kitirattarkarn, G. P., Tao, W., & Tsai, W. S. (2020) · Internet Research · doi:10.1108/intr-03-2020-0133 · Cited by 19
Metadata
- Authors
- Babić Rosario, A., Sotgiu, F., De Valck, K., & Bijmolt, T. H. A.
- Affiliations
- HEC Paris
- Vrije Universiteit Amsterdam (NL)
- Faculty of Economics and Business, University of Groningen
- Paris
- Corresponding author
- Sotgiu, Francesca
- Bijmolt, Tammo H.A.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 2016-06
- Volume
- 53
- Issue
- 3
- Pages
- 297-318
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2239794783
- Cited by
- 1,073
- References
- 81
- Citations by year
- 2026: 99 · 2025: 85 · 2024: 108 · 2023: 141 · 2022: 143 · 2021: 124 · 2020: 117 · 2019: 110 · 2018: 83 · 2017: 39 · 2016: 23
- FWCI
- 161.09
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Journal of Marketing Research (publishedVersion)
- Digital Commons - DU (University of Denver) (submittedVersion, cc-by-nc-nd)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- VU Research Portal (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Agence Nationale de la Recherche (LABX-0047, ANR-11-IDEX-0003, ANR-11-LABX-0047, ANR-11-IDEX)
- Fondation HEC (ANR‐11‐IDEX‐0003/Labex Ecodec/ANR‐11‐LABX‐0047, Ecodec/ANR-11-LABX-0047, ANR-11-IDEX-0003/Labex, F1307)
- Labex Ecodec (ANR-11-IDEX-0003/Labex Ecodec/ANR-11-LABX-0047, ANR - 11-LABX-0047, ANR-11-IDEX-0003/Labex, Ecodec/ANR-11-LABX-0047, ANR-11-IDEX-0003)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- electronic word of mouth, sales, social networking sites, e-commerce platforms, homophily, product life cycle, tangible goods, service, purchase decision
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 ›
Are you an author, or do you see a problem with this page? Request a review