An Empirical Study on the Adoption Intention of IoT-based Medical Information Services: Focusing on the Moderating Effect of User Usability
DOI:
https://doi.org/10.61841/38n5fv36Keywords:
Smart healthcare system, Selective Attributes, user innovativeness, motivation for use, service suitability, adoption intension, user usefulness.Abstract
Background/Objectives: Based on the anticipation that IoT-based smart healthcare systems will lead to improvement of the quality and efficiency of healthcare services, an empirical analysis was conducted, with the aim of proposing the necessary strategic measures to enhance the adoption intention among potential users.
Methods/Statistical analysis: A survey was carried out from February to March 2019 using the convenient sampling method, targeting the members of a user group interested in the advancement of smart healthcare. A total of 327 questionnaire forms were returned, of which 321 forms, excluding the 6 forms that were deemed unsuitable, were used in analyses of descriptive statistics, Pearson correlation coefficient analysis and multiple regression analysis, using SPSS 22.0.
Findings: First, a multiple regression analysis was carried out in order to examine the effects of the Selective Attributes of an IoT-based smart healthcare system on the intention to accept the system. The results showed a positive (+) correlation between the motivation for use and service suitability among the Selective Attributes and the adoption intention, while the correlation between the adoption intention and user innovativeness was not statistically significant. Second, the user usefulness was found to have a moderating effect between the adoption intention and the Selective Attributes such as user innovation, motivation for use, and service suitability. The analysis results showed that the interaction effect of usefulness was statistically significant, meaning that as the user usefulness increased, the adoption intention also increased.
Improvements/Applications: This study analyzed the causality of Selective Attributes in the introduction of IoT- based smart healthcare system and analyzed the interaction effect of user usability.
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1. Lee YK, Park JY, Rho MJ, Wang BR, Choi In-Young, Doctors' Perception and Intention of the U-healthcare Service, The Journal of the Korea Contents Association, 2012, 12(2), pp. 349-357.
2. Kim S, Lee CW, Usage Intention of u-Healthcare Service Using Unified Theory of Technology Adoption and Usage, The Journal of the Korea Contents Association, 2013, 13(12), pp. 379-388.
3. Zheng Z, User Acceptance of Mobile Healthcare Applications: An Integrated Model of UTAUT and HBM Theory, Korean Policy Sciences Review, 2015, 19(3), pp. 203-236.
4. Pae YW, Bong JS, Min W, Shin Y, A Study on the Acceptance Factors of Healthcare Information Services Converged with Cognitive Computing, Journal of KIISE, 2015, 42(6), pp. 734-747.
5. Yang Y, Kim M, A Study on Behavioral Intention on u-Health using Health Promotion Model, Journal of the Korea Institute of Information and Communication Engineering, 2015, 19(3), pp. 747-755.
6. Goldsmith, R. E., Hofacker C. F., Measuring Consumer Innovativeness, Academy of Marketing Science, 1991, 19(2), pp. 209-221.
7. Nysveen, H., Pedersen, P., Thorbjornsen, H., Intentions to Use Mobile Services: Antecedents and Cross- service Comparisons, Journal of Academy of Marketing, 2005,
8. Pope N, Consumption Values, Sponsorship Awareness,Brand and Product Use, Journal of Product & Brand Management, 1998, 7(2), pp. 124-136.
9. Karahanna E, Straub DW, Chervany NL, Information Technology Adoption across Time: A Cross-Sectional Comparison of Pre-adoption and Post-adoption Beliefs, MIS Quarterly, 1999, 23(2), pp. 183-213.
10. Moore GC, Benbasat I, Development of an instrument to measure the perceptions of adopting and information technology innovation, Information System Research, 1999, 2(3), pp. 192-222.
11. Kim KD, Lee SH, A Study of the Factors Affecting the Adoption of WiBro Service, Journal of Communication Science, 2008, 8(3), pp. 45-74.
12. Rogers EM, Diffusion of Innovation,(4th ed.),NY: The Free Press, 2010.
13. Sung DK, Study on Perceived Usefulness and Perceived Risks of Mid-Program Ads Affecting to Intention to Allow Mid-Program Ads : Centering on Technology Acceptance Model and Innovation Resistance Model, Korean Journal of Journalism & Communication Studies, 2009, 53(6), pp. 379-404.
14. Davis. F, Perceived Usefulness. Perceived Ease of Use. and User Acceptance of Information Technology,
MIS Quarterly, 1989, 13(3), pp.318-339.
15. Lee SH, Kim DT, The Effects of Ubiquitous Attributes of Mobile Contents on Consumer Acceptance, Journal of the Korea Management Association, 2006, 19(2), pp. 651-678.
16. Aaker. J.L., Dimensions of Brand Personality, Journal of Marketing Research,1997, 34(4), pp. 347-403.
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