Exploring the influence of online reviews and motivating factors on sales: A meta-analytic study and the moderating role of product category

Li K, Chen Y, Zhang L, (2020), Exploring the influence of online reviews and motivating factors on sales: A meta-analytic study and the moderating role of product category, Journal of Retailing and Consumer Services, Volume 55, July 2020, 102107

https://www.sciencedirect.com/science/article/abs/pii/S0969698919304011

Mots clés : Avis en ligne, Facteurs motivants, Ventes de produits, Catégorie de produit, Méta-analyse, Effet modérateur

Résumé : Les avis en ligne, qui influencent considérablement les ventes de produits, ont été un sujet de recherche central dans le domaine du marketing. Pendant ce temps, certains facteurs de motivation liés aux détaillants en ligne ont été liés aux ventes de produits. Alors que plusieurs articles ont examiné l’impact entre les critiques en ligne et les facteurs de motivation sur les ventes de produits, de nombreuses conclusions tirées sont contradictoires. À partir de 28 études axées sur les avis et les ventes en ligne, cette étude effectue une méta-analyse pour analyser les véritables impacts de six facteurs liés aux avis (c.-à-d. Le nombre d’avis, le nombre d’étoiles, l’écart-type des notes, l’utilité, la durée de l’avis et le sentiment) et deux facteurs de motivation (c.-à-d. rabais sur les prix et expédition spéciale) sur les ventes de produits. Pendant ce temps, ce document étudie également comment un facteur lié au produit (c.-à-d. L’âge du produit) et un facteur lié aux examinateurs (i. e., la réputation de l’examinateur) influencent la relation entre les avis en ligne et les ventes de produits. De plus, pour étudier l’effet modérateur de la catégorie de produits, nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seules la longueur de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie. Nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seule la durée de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie. Nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seules la durée de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie.


Archak, N., Ghose, A., Ipeirotis, P.G., 2011. Deriving the pricing power of product
features by mining consumer reviews. Manag. Sci. 57, 1485–1509.
Artursson, E., 2015. Online Ratings–Who Decides what Games You Buy. Master Thesis in
Economics. Lunds Universitet.
Babi�c Rosario, A., Sotgiu, F., De Valck, K., Bijmolt, T.H.A., 2016. The effect of electronic
word of mouth on sales: A meta-analytic review of platform, product, and metric
factors. J. Mark. Res 53 (3), 297–318.
Bao, T., Chang, T.S., 2014a. Finding disseminators via electronic word of mouth message
for effective marketing communications. Decis. Support Syst. 67, 21–29.
Bao, T., Chang, T.S., 2014b. Why Amazon uses both the New York Times Best Seller List
and customer reviews: an empirical study of multiplier effects on product sales from
multiple earned media. Decis. Support Syst. 67, 1–8.
Blundell, M., 2014. Understanding and synthesizing my numerical data. A. Boland, M.G.
Cherry, R. Dickson (Eds.), Doing a Syst. Rev. Sage, London, UK 99–123.
Bosman, D.J., Boshoff, C., Van Rooyen, G.-J., 2013. The review credibility of electronic
word-of-mouth communication on e-commerce platforms. Manag. Dyn. J. South.
Afr. Inst. Manag. Sci. 22, 29–44.
Caballero, L., 2015. The Impact of Online Ratings on Video Game Sales. Master Thesis in
Management. Nova School of Business and Economics.
Chatterjee, P., 2001. Online Reviews: Do Consumers Use Them?.
Chen, K., Luo, P., Wang, H., 2017. An influence framework on product word-of-mouth
(WoM) measurement. Inf. Manag. 54, 228–240.
Chen, P.-Y., Dhanasobhon, S., Smith, M.D., 2008. All reviews are not created equal: the
disaggregate impact of reviews and reviewers at amazon. com, Working paper,
Carnegie Mellon University. Available at: SSRN. https://ssrn.com/abstract¼918083.
https://doi.org/10.2139/ssrn.918083.
Chen, P.-Y., Wu, S., Yoon, J., 2004. The impact of online recommendations and consumer
feedback on sales. In: International Conference on Information Systems (ICIS),
pp. 711–724.
Chen, Y., Xie, J., 2008. Online consumer review: word-of-mouth as a new element of
marketing communication mix. Manag. Sci. 54, 477–491.
Cho, Y., Im, I., Hiltz, R., Fjermestad, J., 2002. An analysis of online customer complaints:
implications for web complaint management. In: Proceedings of the 35th Annual
Hawaii International Conference on System Sciences. IEEE, Hawaii, pp. 2308–2317.
Clemons, E.K., Gao, G.G., Hitt, L.M., 2006. When online reviews meet
hyperdifferentiation: a study of the craft beer industry. J. Manag. Inf. Syst. 23,
149–171.
Cui, G., Lui, H.-K., Guo, X., 2012. The effect of online consumer reviews on new product
sales. Int. J. Electron. Commer. 17, 39–58.
Cui, J., Pan, Y., Wang, L., 2012b. Impact of online review on sales: an empirical
investigation of experience products with different popularities. In: 2012
International Conference on Management of E-Commerce and E-Government. IEEE,
pp. 48–53.
DerSimonian, R., Kacker, R., 2007. Random-effects model for meta-analysis of clinical
trials: an update. Contemp. Clin. Trials 28, 105–114.
Dixit, S., Badgaiyan, A.J., Khare, A., 2019. An integrated model for predicting
consumer’s intention to write online reviews. J. Retailing Consum. Serv. 46,
112–120.
Duan, W., Gu, B., Whinston, A.B., 2008. Do online reviews matter?—an empirical
investigation of panel data. Decis. Support Syst. 45, 1007–1016.
Dwivedi, Y.K., Rana, N.P., Chen, H., Williams, M.D., 2011. A meta-analysis of the unified
theory of acceptance and use of technology (UTAUT). In: IFIP International Working
Conference on Governance and Sustainability in Information Systems-Managing the
Transfer and Diffusion of it. Springer, pp. 155–170.
Ehrmann, T., Schmale, H., 2008. The hitchhiker’s guide to the long tail: the influence of
online-reviews and product recommendations on book sales-Evidence from German
online retailing. In: International Conference on Information Systems, p. 157.
Eliashberg, J., Sawhney, M.S., 1994. Modeling goes to Hollywood: predicting individual
differences in movie enjoyment. Manag. Sci. 40, 1151–1173.
Fang, H., Zhang, J., Bao, Y., Zhu, Q., 2013. Towards effective online review systems in
the Chinese context: a cross-cultural empirical study. Electron. Commer. Res. Appl.
12, 208–220.
Field, A.P., 2001. Meta-analysis of correlation coefficients: a Monte Carlo comparison of
fixed-and random-effects methods. Psychol. Methods 6, 161.
Firth, J., Torous, J., Nicholas, J., Carney, R., Pratap, A., Rosenbaum, S., Sarris, J., 2017.
The efficacy of smartphone-based mental health interventions for depressive
symptoms: a meta-analysis of randomized controlled trials. World Psychiatr. 16,
287–298.
Fleiss, J.L., 1993. Review papers: the statistical basis of meta-analysis. Stat. Methods
Med. Res. 2, 121–145.
Floyd, K., Freling, R., Alhoqail, S., Cho, H.Y., Freling, T., 2014. How online product
reviews affect retail sales: a meta-analysis. J. Retailing 90, 217–232.
Forman, C., Ghose, A., Wiesenfeld, B., 2008. Examining the relationship between reviews
and sales: the role of reviewer identity disclosure in electronic markets. Inf. Syst. Res.
19, 291–313.
Franke, G.R., Huhmann, B.A., Mothersbaugh, D.L., 2004. Information content and
consumer readership of print ads: a comparison of search and experience products.
J. Acad. Market. Sci. 32, 20–31.
Girard, T., Dion, P., 2010. Validating the search, experience, and credence product
classification framework. J. Bus. Res. 63, 1079–1087.
Glass, G.V., 1976. Primary, secondary, and meta-analysis of research. Educ. Res. 5, 3–8.
Gu, B., Park, J., Konana, P., 2012. Research note—the impact of external word-of-mouth
sources on retailer sales of high-involvement products. Inf. Syst. Res. 23, 182–196.
Gu, B., Tang, Q., Whinston, A.B., 2013. The influence of online word-of-mouth on long
tail formation. Decis. Support Syst. 56, 474–481.
Gurevitch, J., Koricheva, J., Nakagawa, S., Stewart, G., 2018. Meta-analysis and the
science of research synthesis. Nature 555, 175–182.
Hellofs, L.L., Jacobson, R., 1999. Market share and customers’ perceptions of quality:
when can firms grow their way to higher versus lower quality? J. Market. 63, 16–25.
Herrmann, A., Huber, F., Coulter, R.H., 1997. Product and service bundling decisions and
their effects on purchase intention. Pricing Strategy & Pract. 5 (3), 99–104.
Hong, H., Xu, D., Wang, G.A., Fan, W., 2017. Understanding the determinants of online
review helpfulness: a meta-analytic investigation. Decis. Support Syst. 102, 1–11.
Hu, N., Bose, I., Koh, N.S., Liu, L., 2012. Manipulation of online reviews: an analysis of
ratings, readability, and sentiments. Decis. Support Syst. 52, 674–684.
Hu, N., Koh, N.S., Reddy, S.K., 2014. Ratings lead you to the product, reviews help you
clinch it? The mediating role of online review sentiments on product sales. Decis.
Support Syst. 57, 42–53.
Hu, N., Liu, L., Zhang, J.J., 2008. Do online reviews affect product sales? The role of
reviewer characteristics and temporal effects. Inf. Technol. Manag. 9, 201–214.
Jiang, B.-J., Wang, B., 2008. Impact of consumer reviews and ratings on sales, prices, and
profits: theory and evidence. In: International Conference on Information Systems,
p. 141.
Jim�enez, F.R., Mendoza, N.A., 2013. Too popular to ignore: the influence of online
reviews on purchase intentions of search and experience products. J. Interact.
Market. 27, 226–235.
Kim, J.B., 2014. Impact of online customer reviews and incentives on the product sales at
the online retail store: an empirical study at Amazon. com. In: Twentieth Americas
Conference on Information Systems, pp. 1–11.
King, W.R., He, J., 2006. A meta-analysis of the technology acceptance model. Inf.
Manag. 43, 740–755.
Lau, R.Y.K., Zhang, W., Bruza, P.D., Wong, K.-F., 2011. Learning domain-specific
sentiment lexicons for predicting product sales. In: 2011 IEEE 8th International
Conference on E-Business Engineering. IEEE, pp. 131–138.
Lee, J., Park, D.-H., Han, I., 2008. The effect of negative online consumer reviews on
product attitude: an information processing view. Electron. Commer. Res. Appl. 7,
341–352.
Lee, T.Y., Bradlow, E.T., 2011. Automated marketing research using online customer
reviews. J. Market. Res. 48, 881–894.
Li, H., Fang, Y., Wang, Y., Lim, K.H., Liang, L., 2015. Are all signals equal? Investigating
the differential effects of online signals on the sales performance of e-marketplace
sellers. Inf. Technol. People 28, 699–723.
Li, X., Hitt, L.M., 2010. Price effects in online product reviews: an analytical model and
empirical analysis. MIS Q. 809–831.
Li, X., Hitt, L.M., 2008. Self-selection and information role of online product reviews. Inf.
Syst. Res. 19, 456–474.
Li, X., Wu, C., Mai, F., 2019. The effect of online reviews on product sales: a joint
sentiment-topic analysis. Inf. Manag. 56, 172–184.
Lim, C., 1999. A meta-analytic review of international tourism demand. J. Trav. Res. 37,
273–284.
Lin, Z., 2014. An empirical investigation of user and system recommendations in ecommerce. Decis. Support Syst. 68, 111–124.
Lipsey, M.W., Wilson, D.B., 2001. Practical Meta-Analysis. Sage Publications, Inc.
Liu, Q., Huang, S., Zhang, L., 2016. The influence of information cascades on online
purchase behaviors of search and experience products. Electron. Commer. Res. 16,
553–580.
Liu, Q., Zhang, X., Zhang, L., Zhao, Y., 2018. The interaction effects of information
cascades, word of mouth and recommendation systems on online reading behavior:
an empirical investigation. Electron. Commer. Res. 1–27 https://doi.org/10.1007/
s10660-018-9312-0.
Maslowska, E., Malthouse, E.C., Bernritter, S.F., 2017. The effect of online customer
reviews’ characteristics on sales. In: Advances in Advertising Research, vol. VII.
Springer, pp. 87–100.
Meiseberg, B., 2016. The effectiveness of e-tailers’ communication practices in
stimulating sales of niche versus popular products. J. Retailing 92, 319–332.
K. Li et al.
Journal of Retailing and Consumer Services 55 (2020) 102107
11
Meng, Y., Wang, H., Zheng, L., 2018. Impact of online word-of-mouth on sales: the
moderating role of product review quality. New Rev. Hypermedia Multimedia 24,
1–27.
Moe, W., 2009. How Much Does a Good Product Rating Help a Bad Product? Modeling
the Role of Product Quality in the Relationship between Online Consumer Ratings
and Sales, Working Paper. University Of Maryland College Park.
Monroe, K.B., 2003. Pricing: Making Profitable Decisions, third ed. McGraw Hill Book
Company, New York.
Moon, S., Park, Y., Seog Kim, Y., 2014. The impact of text product reviews on sales. Eur.
J. Market. 48, 2176–2197.
Mudambi, S.M., Schuff, D., 2010. What makes a helpful online review? A study of
customer reviews on Amazon. com. MIS Q. 34, 185–200.
Nelson, P., 1974. Advertising as information. J. Polit. Econ. 82, 729–754.
Park, C., Lee, T.M., 2009. Information direction, website reputation and eWOM effect: a
moderating role of product type. J. Bus. Res. 62, 61–67.
Park, C.W., Stice, E.K., 2000. Analyst forecasting ability and the stock price reaction to
forecast revisions. Rev. Account. Stud. 5, 259–272.
Park, D.-H., Lee, J., Han, I., 2007. The effect of on-line consumer reviews on consumer
purchasing intention: the moderating role of involvement. Int. J. Electron. Commer.
11, 125–148.
Purnawirawan, N., Eisend, M., De Pelsmacker, P., Dens, N., 2015. A meta-analytic
investigation of the role of valence in online reviews. J. Interact. Market. 31, 17–27.
Ren, J., Nickerson, J.V., 2019. Arousal, valence, and volume: how the influence of online
review characteristics differs with respect to utilitarian and hedonic products. Eur. J.
Inf. Syst. 28, 272–290.
Rese, A., Schreiber, S., Baier, D., 2014. Technology acceptance modeling of augmented
reality at the point of sale: can surveys be replaced by an analysis of online reviews?
J. Retailing Consum. Serv. 21, 869–876.
Rosenthal, R., 1986. Meta-analytic procedures for social science research. Educ. Res. 15,
18–20.
Sahoo, N., Srinivasan, S., Dellarocas, C., 2013. The impact of online product reviews on
product returns and net sales. In: 2013 Workshop on Information Systems
Economics, Milan, Italy.
Schubert, P., Ginsburg, M., 2000. Virtual communities of transaction: the role of
personalization in electronic commerce. Electron. Mark. 10, 45–55.
Sparks, B.A., Browning, V., 2011. The impact of online reviews on hotel booking
intentions and perception of trust. Tourism Manag. 32, 1310–1323.
Tang, T., Fang, E., Wang, F., 2014. Is neutral really neutral? The effects of neutral usergenerated content on product sales. J. Market. 78, 41–58.
Weisstein, F.L., Song, L., Andersen, P., Zhu, Y., 2017. Examining impacts of negative
reviews and purchase goals on consumer purchase decision. J. Retailing Consum.
Serv. 39, 201–207.
Wu, J., Du, L., Dang, Y., 2018. Research on the impact of consumer review sentiments
from different websites on product sales. In: 2018 IEEE International Conference on
Software Quality, Reliability and Security Companion (QRS-C). IEEE, pp. 332–338.
Yan, J., Zhang, Li, Zhang, Lei, 2012. An empirical study of the impact of review content
on online reviews helpfulness in e-commerce. Inf. Sci. 30, 713–718.
Yang, Y., Park, S., Hu, X., 2018. Electronic word of mouth and hotel performance: a
meta-analysis. Tourism Manag. 67, 248–260. https://doi.org/10.1016/j.
tourman.2018.01.015.
Yao, R., Chen, J., 2013. Predicting movie sales revenue using online reviews. In: 2013
IEEE International Conference on Granular Computing (GrC). IEEE, pp. 396–401.
Ye, Q., Law, R., Gu, B., Chen, W., 2011. The influence of user-generated content on
traveler behavior: an empirical investigation on the effects of e-word-of-mouth to
hotel online bookings. Comput. Hum. Behav. 27, 634–639.
Ye, Y., Zhao, Y., Shang, J., Zhang, L., 2019. A hybrid IT framework for identifying highquality physicians using big data analytics. Int. J. Inf. Manag. 47, 65–75.
You, Y., Vadakkepatt, G.G., Joshi, A.M., 2015. A meta-analysis of electronic word-ofmouth elasticity. J. Market. 79, 19–39.
Zhang, L., Ma, B., Cartwright, D.K., 2013. The impact of online user reviews on cameras
sales. Eur. J. Market. 47, 1115–1128.
Zhang, L., Zhu, J., Liu, Q., 2012. A meta-analysis of mobile commerce adoption and the
moderating effect of culture. Comput. Hum. Behav. 28, 1902–1911.
Zhao, Y., Ni, Q., Zhou, R., 2018. What factors influence the mobile health service
adoption? A meta-analysis and the moderating role of age. Int. J. Inf. Manag. 43,
342–350.
Zhu, F., Zhang, X., 2010. Impact of online consumer reviews on sales: the moderating
role of product and consumer characteristics. J. Market. 74, 133–148.
Zhu, L., Yin, G., He, W., 2014. Is this opinion leader’s review useful? Peripheral cues for
online review helpfulness. J. Electron. Commer. Res. 15, 267.