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Article
Knowledge, Perceived Benefits, Adoption, and Use of Smart Home Products
International Journal of Human-Computer Interaction
  • Daniel Burton Shank, Missouri University of Science and Technology
  • David Wright, Missouri University of Science and Technology
  • Rohan Lulham
  • Clementine Thurgood
Abstract

What are the relationships between knowledge of, perceived benefits, adoption of, and use of smart home products? To explore this question, in our first two studies we focus on the general population’s perceptions of benefits across many types of smart home products by creating a corpus of smart home product descriptions. Study 1 (n = 399) shows that previous product knowledge influences a range of perceived benefits. Study 2 (n = 242) demonstrates which benefits increase non-owners’ likelihood of adopting these products. In study 3, we longitudinally survey eight residents in living laboratory houses equipped with 10 integrated smart home products. We find over a year access to the products increases perceptions of their benefits, but does not increase their actual use. Collectively, these studies contribute to an increased understanding of the relationship among benefits, use, and adoption of this emerging technology.

Department(s)
Psychological Science
Second Department
English and Technical Communication
Comments
This research was generously supported by funding from (1) the Centre for Contemporary Design Practices, University of Technology Sydney, (2) the Melbourne School of Psychological Sciences, University of Melbourne, and (3) the College of Arts, Sciences, and Business, Missouri University of Science & Technology.
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 Taylor & Francis, All rights reserved.
Publication Date
12-16-2020
Publication Date
16 Dec 2020
Citation Information
Daniel Burton Shank, David Wright, Rohan Lulham and Clementine Thurgood. "Knowledge, Perceived Benefits, Adoption, and Use of Smart Home Products" International Journal of Human-Computer Interaction (2020) ISSN: 1044-7318; 1532-7590
Available at: http://works.bepress.com/daniel-shank/34/