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Does the distribution of ratings affect online grocery sales? Evidence from Amazon

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Listed:
  • Chinonso E. Etumnu
  • Kenneth Foster
  • Nicole O. Widmar
  • Jayson L. Lusk
  • David L. Ortega

Abstract

Understanding the distribution of online consumer ratings for food products can provide insights that aid supply chain decisions. Using a researcher‐collected web‐scraped panel data set from Amazon, this article quantifies the effect of number of ratings, average rating, variance of ratings, and skewness of the rating distribution. Results show that the number of ratings and each of these moments of the distribution of online consumer ratings affect ground coffee sales ranking. The size of the effect of the distribution of ratings was found to vary with respect to the sales level of the coffee products. The results suggest that the distribution of online ratings plays an important informational role in e‐commerce platforms. As online grocery shopping continues to increase in popularity, a greater understanding of how online ratings and reviews may impact sales or products are needed by those in the agricultural and food supply chain. In particular, these results provide retail managers with an array of online consumer rating attributes to use in their demand forecasts. [EconLit citations: D12, D83, L81, M31, Q11].

Suggested Citation

  • Chinonso E. Etumnu & Kenneth Foster & Nicole O. Widmar & Jayson L. Lusk & David L. Ortega, 2020. "Does the distribution of ratings affect online grocery sales? Evidence from Amazon," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 501-521, October.
  • Handle: RePEc:wly:agribz:v:36:y:2020:i:4:p:501-521
    DOI: 10.1002/agr.21653
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    References listed on IDEAS

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    1. Laurian Unnevehr & James Eales & Helen Jensen & Jayson Lusk & Jill McCluskey & Jean Kinsey, 2010. "Food and Consumer Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(2), pages 506-521.
    2. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    3. Judith Chevalier & Austan Goolsbee, 2003. "Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com," Quantitative Marketing and Economics (QME), Springer, vol. 1(2), pages 203-222, June.
    4. Michael Luca, 2011. "Reviews, Reputation, and Revenue: The Case of Yelp.com," Harvard Business School Working Papers 12-016, Harvard Business School, revised Mar 2016.
    5. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    6. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    7. Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, September.
    8. H. Holly Wang & Na Hao & Qingjie Zhou & Michael E. Wetzstein & Yong Wang, 2019. "Is fresh food shopping sticky to retail channels and online platforms? Evidence and implications in the digital era," Agribusiness, John Wiley & Sons, Ltd., vol. 35(1), pages 6-19, January.
    9. Ioana Marinescu & Nadav Klein & Andrew Chamberlain & Morgan Smart, 2018. "Incentives Can Reduce Bias in Online Reviews," Working Papers id:12575, eSocialSciences.
    10. Dirk Engelmann & Martin Strobel, 2004. "Inequality Aversion, Efficiency, and Maximin Preferences in Simple Distribution Experiments," American Economic Review, American Economic Association, vol. 94(4), pages 857-869, September.
    11. Langan, Ryan & Besharat, Ali & Varki, Sajeev, 2017. "The effect of review valence and variance on product evaluations: An examination of intrinsic and extrinsic cues," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 414-429.
    12. Steffen Zimmermann & Philipp Herrmann & Dennis Kundisch & Barrie R. Nault, 2018. "Decomposing the Variance of Consumer Ratings and the Impact on Price and Demand," Information Systems Research, INFORMS, vol. 29(4), pages 984-1002, December.
    13. Khare, Adwait & Labrecque, Lauren I. & Asare, Anthony K., 2011. "The Assimilative and Contrastive Effects of Word-of-Mouth Volume: An Experimental Examination of Online Consumer Ratings," Journal of Retailing, Elsevier, vol. 87(1), pages 111-126.
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    Cited by:

    1. Chinonso E. Etumnu, 2022. "A competitive marketplace or an unfair competitor? An analysis of Amazon and its best sellers ranks," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 924-937, September.
    2. Varun Nayyar, 2022. "Reviewing the impact of digital migration on the consumer buying journey with robust measurement of PLS‐SEM and R Studio," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 542-556, May.
    3. Liu, Fu & Wei, Haiying & Wang, Xingyuan & Zhu, Zhenzhong & Chen, Haipeng Allan, 2023. "The influence of online review dispersion on consumers’ purchase intention: The moderating role of dialectical thinking," Journal of Business Research, Elsevier, vol. 165(C).
    4. Dipankar Das, 2022. "Measurement of Trustworthiness of the Online Reviews," Papers 2210.00815, arXiv.org, revised Nov 2023.
    5. Sandra Rousseau & Machteld Joly & Eline Poelmans, 2024. "Search characteristics, online consumer ratings, and beer prices," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 804-824, October.

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