Factors Influencing the Adoption of Smart Wearable Devices

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.

[1]  Keng Siau,et al.  An Experimental Study on Ubiquitous commerce Adoption: Impact of Personalization and Privacy Concerns , 2008, J. Assoc. Inf. Syst..

[2]  Philipp A. Rauschnabel,et al.  Augmented reality smart glasses: an investigation of technology acceptance drivers , 2016 .

[3]  RadhaKanta Mahapatra,et al.  Adoption and Use of Open Source Infrastructure Software by Large Corporations: The Case of MySQL , 2015, J. Database Manag..

[4]  Keng Siau,et al.  Adoption of mobile information services: An empirical study , 2014, Mob. Inf. Syst..

[5]  Seongcheol Kim,et al.  Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches , 2016, Comput. Hum. Behav..

[6]  Daejoong Kim,et al.  The Integrated Model of Smartphone Adoption: Hedonic and Utilitarian Value Perceptions of Smartphones Among Korean College Students , 2012, Cyberpsychology Behav. Soc. Netw..

[7]  Chris Baber,et al.  Wearable Computers: A Human Factors Review , 2001, Int. J. Hum. Comput. Interact..

[8]  Claus-Peter H. Ernst,et al.  The Potential Influence of Privacy Risk on Activity Tracker Usage: A Study , 2016 .

[9]  Tugrul Daim,et al.  Exploring the design factors of smart glasses , 2015, 2015 Portland International Conference on Management of Engineering and Technology (PICMET).

[10]  Fiona Fui-Hoon Nah,et al.  Smart Living for Elderly: Design and Human-Computer Interaction Considerations , 2016, HCI.

[11]  Thurasamy Ramayah,et al.  Wearable technologies: The role of usefulness and visibility in smartwatch adoption , 2016, Comput. Hum. Behav..

[12]  Hiromichi Hashizume,et al.  Perception of Wearable Computers for Everyday Life by the General Public: Impact of Culture and Gender on Technology , 2005, EUC.

[13]  Jengchung V. Chen,et al.  Acceptance and adoption of the innovative use of smartphone , 2007, Ind. Manag. Data Syst..

[14]  Howard E. Aldrich,et al.  The pervasive effects of family on entrepreneurship: toward a family embeddedness perspective , 2003 .

[15]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[16]  Bradley J. Rhodes,et al.  The wearable remembrance agent: A system for augmented memory , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[17]  Keng Siau,et al.  Developing an instrument to measure the adoption of mobile services , 2011 .

[18]  Keng Siau,et al.  Strategic implications of mobile technology: A case study using Value-Focused Thinking , 2005, J. Strateg. Inf. Syst..

[19]  Dong-Hee Shin,et al.  An acceptance model for smart watches: Implications for the adoption of future wearable technology , 2015, Internet Res..

[20]  Felix B. Tan,et al.  The Repertory Grid Technique: A Method for the Study of Cognition in Information Systems , 2002, MIS Q..

[21]  Alexander Brem,et al.  Who will buy smart glasses? Empirical results of two pre-market-entry studies on the role of personality in individual awareness and intended adoption of Google Glass wearables , 2015, Comput. Hum. Behav..

[22]  Mark Billinghurst,et al.  NEW WAYS TO MANAGE INFORMATION , 1999 .

[23]  M. Rokeach.  The Nature Of Human Values , 1974 .

[24]  Shih-Chih Chen,et al.  RECENT RELATED RESEARCH IN TECHNOLOGY ACCEPTANCE MODEL: A LITERATURE REVIEW , 2012, Australian Journal of Business and Management Research.

[25]  Claus-Peter H. Ernst,et al.  Does Perceived Health Risk Influence Smartglasses Usage , 2016 .

[26]  Adam Sagan,et al.  The quality of ladders generated by abbreviated hard laddering , 2010 .

[27]  Daniel W. E. Hein,et al.  Augmented Reality Smart Glasses and Knowledge Management: A Conceptual Framework for Enterprise Social Networks , 2016 .

[28]  Claus-Peter H. Ernst,et al.  The Influence of Subjective Norm on the Usage of Smartglasses , 2016 .

[29]  Shuping Yi,et al.  Adapting the Navigation Interface of Smart Watches to User Movements , 2017, Int. J. Hum. Comput. Interact..

[30]  Mark Billinghurst,et al.  Wearable Devices: New Ways to Manage Information , 1999, Computer.

[31]  Keng Siau,et al.  Understanding the values of mobile technology in education: a value-focused thinking approach , 2010, DATB.

[32]  Dorota Bourne,et al.  The Repertory Grid Technique , 2018 .

[33]  A. Stewart,et al.  Business applications of repertory grid , 1981 .

[34]  Paul Cain.  Unlock the Full Potential of Wearables with Organic TFTs , 2015 .

[35]  Daniel W. E. Hein,et al.  Fashion or Technology? A Fashnology Perspective on the Perception and Adoption of Augmented Reality Smart Glasses , 2016, i-com.

[36]  J. Gutman.  A Means-End Chain Model Based on Consumer Categorization Processes , 1982 .

[37]  Seongcheol Kim,et al.  Consumer valuation of the wearables: The case of smartwatches , 2016, Comput. Hum. Behav..

[38]  T. J. Reynolds,et al.  Laddering theory, method, analysis, and interpretation. , 2001 .

[39]  Joseph L. Dvorak,et al.  Moving Wearables into the Mainstream: Taming the Borg , 2007 .

[40]  Keng Siau,et al.  Value of Mobile Commerce to Customers , 2004, AMCIS.

[41]  H. Laborit,et al.  [Experimental study]. , 1958, Bulletin mensuel - Societe de medecine militaire francaise.

[42]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[43]  Steve Mann,et al.  An historical account of the 'WearComp' and 'WearCam' inventions developed for applications in 'personal imaging' , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[44]  Abeer Alsadoon,et al.  Ethical Implications of User Perceptions of Wearable Devices , 2018, Sci. Eng. Ethics.

[45]  Andrina Granic,et al.  Technology acceptance model: a literature review from 1986 to 2013 , 2014, Universal Access in the Information Society.

[46]  Keng Siau,et al.  The value of mobile applications: a utility company study , 2005, CACM.

[47]  Steven K. Feiner.  The importance of being mobile: some social consequences of wearable augmented reality systems , 1999, Proceedings 2nd IEEE and ACM International Workshop on Augmented Reality (IWAR'99).

[48]  G. Kelly.  The Psychology of Personal Constructs , 2020 .