A Study on Factors Influencing Elderly Intention to Use Smart Home in Thailand : A Pilot Study

Thailand has become an aging society because of the growing number of the elderly. This change has reduced the welfare of older persons which has resulted in a decreased quality of life. To improve the elderly’s quality of life, a smart home with advanced technology could solve this problem. The objective of this study was to examine the factors that influence Thai elderly intention to use a smart home. The technology acceptance model and the aging characteristic variables were applied to develop the conceptual model. Six factors, namely Perceived Usefulness, Attitude, Perceived Physical condition, Computer Self-efficacy, Perceived Reliability and Subjective norm were tested. The data was gathered from 41 Thai elderly citizens by using an online questionnaire and regression analysis was conducted to analyze the data. The results showed that computer self-efficacy was the most dominant factor that influenced the elderly intention to use smart home, and the preliminary research model was modified from the results of statistical testing. The implications of this study and future research were discussed. Keywords—Smart home; technology adoption; Older user; adoption factors; Aging characteristic factors;

[1]  Fred D. Davis.  A technology acceptance model for empirically testing new end-user information systems : theory and results , 1985 .

[2]  Fred D. Davis,et al.  Development and Test of a Theory of Technological Learning and Usage , 1992 .

[3]  Seongcheol Kim,et al.  Understanding the factors affecting online elderly user's participation in video UCC services , 2009, Comput. Hum. Behav..

[4]  G. Dewsbury.  The Social and Psychological Aspects of Smart Home Technolgy within the Care Sector , 2001 .

[5]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

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

[7]  Antti Salovaara,et al.  Information technologies and transitions in the lives of 55-65-year-olds: The case of colliding life interests , 2010, Int. J. Hum. Comput. Stud..

[8]  Nigel H. Lovell,et al.  Using information technology to improve the management of chronic disease , 2003, The Medical journal of Australia.

[9]  Nigel H. Lovell,et al.  Patients' perceptions of a home telecare system , 2008, Int. J. Medical Informatics.

[10]  Paul Jen-Hwa Hu,et al.  Information Technology Acceptance by Individual Professionals: A Model Comparison Approach , 2001, Decis. Sci..

[11]  P Whitten,et al.  Nurse and patient reactions to a developmental home telecare system , 1998, Journal of telemedicine and telecare.

[12]  Mika Immonen,et al.  Telecare services for aging people: Assessment of critical factors influencing the adoption intention , 2013, Comput. Hum. Behav..

[13]  Elizabeth M. Weiss,et al.  Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales , 2004, Comput. Hum. Behav..

[14]  David B. Eastwood,et al.  A Two-Step Estimation of Consumer Adoption of Technology-Based Service Innovations , 2003 .

[15]  M. Skubic,et al.  Findings from a participatory evaluation of a smart home application for older adults. , 2008, Technology and health care : official journal of the European Society for Engineering and Medicine.

[16]  Tai-hoon Kim,et al.  Applications, Systems and Methods in Smart Home Technology: A Review , 2010 .

[17]  Diane J. Cook,et al.  How smart are our environments? An updated look at the state of the art , 2007, Pervasive Mob. Comput..

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

[19]  M. Chan,et al.  Smart homes - current features and future perspectives. , 2009, Maturitas.

[20]  A. Bandura.  Self-Efficacy: The Exercise of Control , 1997, Journal of Cognitive Psychotherapy.

[21]  L. Johnson,et al.  Why consumers use and do not use technology‐enabled services , 2006 .

[22]  Hongnian Yu,et al.  Perception of Smart Home Technologies toAssist Elderly People , 2010 .

[23]  Tsipi Heart,et al.  Older adults: Are they ready to adopt health-related ICT? , 2013, Int. J. Medical Informatics.

[24]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[25]  Xin Li,et al.  Predicting user trust in information systems: a comparison of competing trust models , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[26]  Brian D. Carpenter,et al.  Computer use among older adults in a naturally occurring retirement community , 2007, Comput. Hum. Behav..

[27]  Shin-Yuan Hung,et al.  Understanding physicians' acceptance of the Medline system for practicing evidence-based medicine: A decomposed TPB model , 2012, Int. J. Medical Informatics.

[28]  Glen H. Elder,et al.  Revisiting age identity: A research note. , 2002 .

[29]  Per Lynggaard,et al.  Smart Cities and the Ageing Population , 2014 .

[30]  Thurasamy Ramayah,et al.  User Acceptance of the E-Government Services in Malaysia: Structural Equation Modelling Approach , 2010, Interdisciplinary Journal of Information, Knowledge, and Management.

[31]  Carl May,et al.  Telecare: Perspectives on the changing role of patients and citizens , 2005, Journal of telemedicine and telecare.

[32]  Leo R. Vijayasarathy,et al.  Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model , 2004, Inf. Manag..

[33]  A. Bandura.  Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

[34]  P. Pasquina,et al.  Sensor technology for smart homes. , 2011, Maturitas.

[35]  Abdulmotaleb El-Saddik,et al.  Control your smart home with an autonomously mobile smartphone , 2013, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

[36]  Scott R. Beach,et al.  Preferences and concerns for quality of life technology among older adults and persons with disabilities: National survey results , 2010 .

[37]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[38]  Alexander Peine,et al.  The rise of the “innosumer”—Rethinking older technology users , 2014 .

[39]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[40]  Ala-Mutka Kirsti Maria,et al.  Active Ageing and the Potential of ICT for Learning , 2008 .

[41]  Zhaohua Deng,et al.  Comparison of the middle-aged and older users' adoption of mobile health services in China , 2014, Int. J. Medical Informatics.

[42]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[43]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[44]  M. Mckee,et al.  How can health systems respond to population ageing , 2009 .

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