Publication Type
Journal Article
Version
publishedVersion
Publication Date
5-2018
Abstract
This article examined factors associated with the adoption of smart wearable devices. More specifically, this research explored the contributing and inhibiting factors that influence the adoption of wearable devices through in-depth interviews. The laddering approach was used in the interviews to identify not only the factors but also their relationships to underlying values. The wearable devices examined were a Smart Glass (Google Glass) and a Smart Watch (Sony Smart Watch 3). Two user groups, college students and working professionals, participated in the study. After the participants had the opportunity to try out each of the two devices, the factors that were most important in deciding whether to adopt or not to adopt the device were laddered. For the smart glasses, the most frequently mentioned factor was look-and-feel. For the smart watch, the availability of fitness apps was a key factor influencing adoption. In addition, factors which were linked to image, a personal value, were particularly important across both the student and working groups. This research provides support for the usefulness of the laddering approach to data collection and analysis, and provides some insight into key design criteria to better fit users’ needs and interests.
Keywords
College students, Data collection, Design criteria, In-depth interviews, Inhibiting factors, Smart wearables, Wearable devices, Working professionals
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering; Information Systems and Management
Publication
International Journal of Human-Computer Interaction
Volume
34
Issue
5
First Page
399
Last Page
409
ISSN
1044-7318
Identifier
10.1080/10447318.2017.1357902
Publisher
Taylor and Francis Group
Citation
ADAPA, Apurva; NAH, Fiona Fui-hoon; HALL, Richard H.; and SIAU, Keng.
Factors influencing the adoption of smart wearable devices. (2018). International Journal of Human-Computer Interaction. 34, (5), 399-409.
Available at: https://ink.library.smu.edu.sg/sis_research/9581
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/10447318.2017.1357902
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons