Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2021

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.

Keywords

Black boxes, Eye movement patterns, Eye tracking technologies, Product descriptions, Product recommendation, Provide guidances

Discipline

Computer Engineering | Databases and Information Systems

Research Areas

Data Science and Engineering; Information Systems and Management; Intelligent Systems and Optimization

Publication

Proceedings of the 8th International Conference on HCI in Business, Government and Organizations, Virtual, Online, 2021 July 24-29

First Page

90

Last Page

104

ISBN

9783030777494

Identifier

10.1007/978-3-030-77750-0_6

Publisher

Springer

City or Country

Berlin

Additional URL

https://doi.org/10.1007/978-3-030-77750-0_6

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