“Sorry, too much information”—Designing online review systems that support information search and processing

Janina Seutter (), Kristin Kutzner (), Maren Stadtländer (), Dennis Kundisch () and Ralf Knackstedt ()
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Janina Seutter: Paderborn University
Kristin Kutzner: University of Applied Sciences Zwickau
Maren Stadtländer: University of Hildesheim
Dennis Kundisch: Paderborn University
Ralf Knackstedt: University of Hildesheim

Electronic Markets, 2023, vol. 33, issue 1, No 46, 19 pages

Abstract: Abstract When faced with a large number of reviews, customers can easily be overwhelmed by information overload. To address this problem, review systems have introduced design features aimed at improving the scanning, reading, and processing of online reviews. Though previous research has examined the effect of selected design features on information overload, a comprehensive and up-to-date overview of these features remains outstanding. We therefore develop and evaluate a taxonomy for information search and processing in online review systems. Based on a sample of 65 review systems, drawn from a variety of online platform environments, our taxonomy presents 50 distinct characteristics alongside the knowledge status quo of the features currently implemented. Our study enables both scholars and practitioners to better understand, compare and further analyze the (potential) effects that specific design features, and their combinations, have on information overload, and to use these features accordingly to improve online review systems for consumers.

Keywords: Online review system; Design feature; Information overload; Taxonomy (search for similar items in EconPapers)
JEL-codes: D83 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12525-023-00664-1

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