Measuring product type with dynamics of online product review variance

Yili Hong, Pei Yu Chen, Lorin M. Hitt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

The concept of "product type" (experience versus search product) is increasingly important in business research and practice. However, it is not defined or measured precisely in the Internet age due to significantly lower search cost and changes in consumer information search behavior resulting from reliance on information and communications technology. We take advantage of the greatly available micro level online word-of-mouth data and infer product type based on statistical properties of online word of mouth (specifically, online product reviews). We draw on the law of large numbers (L.L.N), and the literature on informational content and online product reviews to analytically propose a mechanism to classify products. Our theoretical analyses indicate that, for a pure search product, when number of reviews (i.e. review sample size) increases as more consumers rate the product, variance of the mean rating will decrease. And for a product with more experience attributes, when number of reviews increases, the variance of the mean rating will not decrease and may instead increase depending on how dominant these experience attributes are. We collect archival data from Amazon to categorize the products and services. Implications of this analytical tool and empirical findings for research, theory and managerial practice are discussed.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems, ICIS 2012
Pages2034-2051
Number of pages18
StatePublished - Dec 1 2012
Externally publishedYes
EventInternational Conference on Information Systems, ICIS 2012 - Orlando, FL, United States
Duration: Dec 16 2012Dec 19 2012

Publication series

NameInternational Conference on Information Systems, ICIS 2012
Volume3

Other

OtherInternational Conference on Information Systems, ICIS 2012
CountryUnited States
CityOrlando, FL
Period12/16/1212/19/12

Keywords

  • Information content
  • Law of large numbers
  • Online product reviews
  • Product quality
  • Product type

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

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