The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry
Abstract
We analyze how online reviews are used to evaluate the effectiveness of product differentiation strategies based on the theories of hyperdifferentiation and resonance marketing. Hyperdifferentiation says that firms can now produce almost anything that appeals to consumers and they can manage the complexity of the increasingly diverse product portfolios that result. Resonance marketing says that informed consumers will purchase products that they actually truly want. When consumers become more informed, firms that provide highly differentiated products should experience higher growth rates than firms with less differentiated offerings. We construct measures of product positioning based on online ratings and find supportive evidence using sales data from the craft beer industry. In particular, we find that the variance of ratings and the strength of the most positive quartile of reviews play a significant role in determining which new products grow fastest in the market-place. This supports our expectations for resonance marketing.
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Cites
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
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Park, D.-H., & Kim, S. (2008) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2007.12.001 · Cited by 837
Zhang, Z., Ye, Q., Law, R., & Li, Y. (2010) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2010.02.002 · Cited by 760
Hsu, C.-L., & Lin, J. C.-C. (2015) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2014.11.003 · Cited by 662
Hu, N., Koh, N. S., & Reddy, S. K. (2014) · Decision Support Systems · doi:10.1016/j.dss.2013.07.009 · Cited by 406
Zhao, L., Lu, Y., Wang, B., Chau, P. Y. K., & Zhang, L. (2012) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2012.02.006 · Cited by 389
Yin, D., Mitra, S., & Zhang, H. (2016) · Information Systems Research · doi:10.1287/isre.2015.0617 · Cited by 365
Kwark, Y., Chen, J., & Raghunathan, S. (2017) · MIS Quarterly · doi:10.25300/misq/2017/41.3.05 · Cited by 350
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Kim, J. M., Jun, M., & Kim, C. K. (2018) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2018.05.002 · Cited by 118
Liu, Y., & Tang, X. (2018) · Information Technology & People · doi:10.1108/itp-10-2016-0242 · Cited by 111
Haque, M. R., & Rubya, S. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555146 · Cited by 48
Zhang, X., Ferreira, P., de Matos, M. G., & Belo, R. (2021) · MIS Quarterly · doi:10.25300/misq/2021/14971 · Cited by 29
Metadata
- Authors
- Clemons, E. K., Gao, G. G., & Hitt, L. M.
- Venue
- Journal of Management Information Systems
- Publisher
- Informa UK Limited
- Published
- 2006-10
- Volume
- 23
- Issue
- 2
- Pages
- 149-171
- ISSN
- 0742-1222 (ISSN-L)
- 1557-928X
- OpenAlex
- W2169955073
- Cited by
- 827
- References
- 1
- FWCI
- 59.94
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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