Measuring the Value of Different Types of Product Information in the Electronic Retail of Books

Research output: Contribution to journalArticleScientificpeer-review


The value of different kinds of book information in electronic retail is measured using best–worst scaling, an approach making the respondent consider several information items simultaneously and choose the most and least preferred among them. Our respondents are both customers using municipal libraries and students. Theory on digital nativity, Hierarchical Bayes estimation and Latent Class analysis are used to study the heterogeneity of the preferences. Customer reviews give the most valuable information on an average. Especially digital immigrants rely more on samples, expert reviews, author presentations, blogs, and friends’ ratings. Preference clusters were identified where the extremes groups were those who highly valued peer information but not expert information and those who valued them vice versa. Customer reviews are appreciated by almost everyone, regardless of their state of digital nativity. The electronic retailer should make all efforts to provide the personalized information when the customer is browsing books online and offer a rich set of customer reviews.
Original languageEnglish
Pages (from-to)1777-1792
Number of pages16
JournalInternational Journal of Information Technology and Decision Making
Issue number5
Early online date16 Nov 2022
Publication statusPublished - Sept 2023
MoE publication typeA1 Journal article-refereed


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