Enforcing Trust as a Means to Improve Adoption of Connected Wearable Technologies

This paper carries out a study on enforcing trust as a means to improve user adoption of wearable technologies. These technologies can play an integral part in facilitating intelligent environments by collecting real-time data for input into networked controllers. The paper reviews wearable devices, their use and current concerns and challenges as well as the factors that influence adoption. The paper goes on to discuss trust as a concept, its models and how it relates to adoption. It also reports on the results of a survey questionnaire used to determine the factors that influence trust in users. These factors and a comparison of existing trust models were used to propose a new Trust Model for Wearable devices.

[1]  France Bélanger,et al.  Trust and Risk in eGovernment Adoption , 2008, AMCIS.

[2]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[3]  Francis Pereira,et al.  Digital home health and mHealth: Prospects and challenges for adoption in the U.S , 2011, 2011 50th FITCE Congress - "ICT: Bridging an Ever Shifting Digital Divide".

[4]  Bruno Crispo,et al.  Privacy and Identity Management for Life , 2011, IFIP Advances in Information and Communication Technology.

[5]  Shari Lawrence Pfleeger Technology, Transparency, and Trust , 2014, IEEE Secur. Priv..

[6]  Jan Tullberg,et al.  Trust—The importance of trustfulness versus trustworthiness , 2008 .

[7]  Xin Li,et al.  Why do we trust new technology? A study of initial trust formation with organizational information systems , 2008, J. Strateg. Inf. Syst..

[8]  Vladimiro Sassone,et al.  Trust models in ubiquitous computing , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

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

[10]  Thomas Springer,et al.  A conceptual framework for designing mHealth solutions for developing countries , 2013, MobileHealth '13.

[11]  Kai Rannenberg,et al.  Privacy and Identity Management for Life , 2011, Privacy and Identity Management for Life.

[12]  Paul A. Pavlou,et al.  Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model , 2003, Int. J. Electron. Commer..

[13]  Jordi Sabater-Mir,et al.  Review on Computational Trust and Reputation Models , 2005, Artificial Intelligence Review.

[14]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[15]  N. L. Chervany,et al.  Initial Trust Formation in New Organizational Relationships , 1998 .

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

[17]  Fred D. Davis,et al.  A critical assessment of potential measurement biases in the technology acceptance model: three experiments , 1996, Int. J. Hum. Comput. Stud..

[18]  Lisandro Zambenedetti Granville,et al.  Internet of Things in healthcare: Interoperatibility and security issues , 2012, 2012 IEEE International Conference on Communications (ICC).