Users’ Reception of Product Recommendations : Analyses Based on Eye Tracking Data

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationHCI in Business, Government and Organizations
Subtitle of host publication8th International Conference, HCIBGO 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings
EditorsFiona Fui-Hoon Nah, Keng Siau
Place of PublicationCham
PublisherSpringer
Pages90-104
ISBN (electronic)9783030777500
ISBN (print)9783030777494
Publication statusPublished - 2021

Publication series

NameLecture Notes in Computer Science
Volume12783
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Conference

Title8th International Conference on HCI in Business, Government and Organizations (HCIBGO 2021), held as part of the 23rd Human-computer Interaction International Conference (HCII 2021)
LocationVirtual
PlaceUnited States
CityWashington
Period24 - 29 July 2021

Abstract

Based on eye tracking technology, we study consumers’ overall attention to recommendations appearing at different time settings (i.e., early, mid, and late) and their attention to different information contained in each recommendation, such as recommendation signs, product descriptions, and reviews. By investigating consumers’ eye movement patterns and attention distributions on recommendations, we open the “black box” of why consumers’ reception to recommendations appearing at different time settings varies. The product preference construction literature and mindset theory help to explain why the early recommendations receive the most attention. The need for justification helps to explain why the late recommendations should receive more attention than the mid recommendations. Besides, the fact that not all information appearing in recommendations will receive every customer’s attention inspires a more efficient recommendation page design. By exploring the patterns of consumers’ attention to recommendations, we contribute to the accumulation of recommendation literature and provide guidance for the practice.

Research Area(s)

  • Attention distributions, Eye tracking, Recommendation agents

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

Users’ Reception of Product Recommendations: Analyses Based on Eye Tracking Data. / Jia, Feiyan; Shi, Yani; Sia, Choon Ling et al.
HCI in Business, Government and Organizations: 8th International Conference, HCIBGO 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings. ed. / Fiona Fui-Hoon Nah; Keng Siau. Cham: Springer, 2021. p. 90-104 (Lecture Notes in Computer Science; Vol. 12783).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review