Investigating the potential impact of non-personalized recommendations in the OPAC: Amazon vs.

Simon Wakeling, Paul Clough, Barbara Sen

Research output: Book chapter/Published conference paperConference paperpeer-review

5 Citations (Scopus)


Recent research into the functionality of Online Public Access Catalogues (OPACs) has led to a call for such systems to incorporate functionality to facilitate resource discovery, and replicate the information search experience users encounter elsewhere on the Web. Recommendations represent one such feature. Developments so far in this area indicate that non-personalized or item-level recommendations are most suited to the OPAC environment. Whilst a number of such systems have been developed and implemented, research has yet to investigate fully the impact of such recommendations on user performance, search behavior, and system perceptions. This paper presents the results of an exploratory laboratory-based study comparing user behavior in Amazon, which offers non-personalized recommendations, and, which does not. An analysis of task performance and participant interactions with the systems reveals that the presence of non-personalized recommendations improves resource discovery, search efficiency, and perceived usability. ?? 2014 ACM.
Original languageEnglish
Title of host publicationProceedings of the 5th Information Interaction in Context Symposium
Subtitle of host publicationIIiX 2014
EditorsDavid Elsweiler, Bernd Ludwig
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Print)9781450329767
Publication statusPublished - 2014
EventInformation Interaction in Context Symposium - University of Regensburg, Regensburg, Germany
Duration: 26 Aug 201430 Aug 2014 (Proceedings)


ConferenceInformation Interaction in Context Symposium
Internet address


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