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Examining Choice Overload across Single-list andMulti-list User Interfaces
Marketing and Consumer Behaviour Group, Wageningen University & Research, Wageningen, Netherlands; MediaFutures, University of Bergen, Bergen, Norway.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.ORCID iD: 0000-0003-4344-9986
2022 (English)In: Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systemsco-located with 16th ACM Conference on Recommender Systems (RecSys 2022) / [ed] P. Brusilovsky, M. de Gemmis, A. Felfernig, P. Lops, M. Polignano, G. Semeraro & M. C. Willemsen, CEUR-WS , 2022, p. 3-17Conference paper, Published paper (Refereed)
Abstract [en]

Recommender systems are prone to triggering choice overload among users due to the typically largeset sizes. Various applications have been developed that aim to overcome this through interface design,notably by so-called multi-list recommender systems. However, to what extent such user interface designactually reduces choice overload compared to single-list interfaces has yet to be examined. In a user study(𝑁 = 150), we compared three common user interfaces (UIs) in the context of recipe recommendation: asingle-list UI, a grid UI and a multi-list UI. Whereas earlier studies found differences in choice difficultyand choice satisfaction across grid-based and multi-list recommender interfaces, we observed no suchdifferences, as the explanations were possibly not sufficiently helpful. Instead, we found that grid-basedUIs and multi-list UIs had a higher perceived ease of use than a single-list UI, which in turn reducedchoice difficulty. The benefits of such interfaces, thus, may lie in the organization of the UI, at least inthe recipe domain. 

Place, publisher, year, edition, pages
CEUR-WS , 2022. p. 3-17
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 3222
Keywords [en]
Choice Overload, User Interface, User Experience, Recommender Systems, Food
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hj:diva-58606Scopus ID: 2-s2.0-85139921617OAI: oai:DiVA.org:hj-58606DiVA, id: diva2:1702101
Conference
IntRS’22: Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, September 22, 2022, Seattle, US (hybrid event)
Available from: 2022-10-10 Created: 2022-10-10 Last updated: 2022-10-26Bibliographically approved

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Ferwerda, Bruce

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