디지털융복합연구 (Journal of Digital Convergence)

  • 제16권5호
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  • Pages.153-162
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  • 2018
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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모바일 헬스케어의 혁신확산 요인이 이용의도에 미치는 영향 연구: 혁신성향의 조절효과를 중심으로

A Study on the Impact of Mobile Healthcare's Diffusion of Innovation Factors on Intention to Use: Focusing on Moderating Effects of Innovation Propensity

  • 투고 : 2018.03.08
  • 심사 : 2018.05.20
  • 발행 : 2018.05.28
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초록

헬스케어의 패러다임이 질병치료 중심에서 예방 및 관리 중심으로 변화함에 따라 자신의 건강을 관리하는 트렌드와 더불어 모바일 헬스케어의 성장세가 지속되고 있다. 모바일 헬스케어의 기술은 지속적으로 성장하고 있지만, 소비자의 수용은 다소 부진하다. 이에 모바일 헬스케어와 관련된 다양한 연구가 진행되어 왔지만, 수용자의 특성을 고려한 연구는 부족한 현실이다. 따라서 본 연구에서는 모바일 헬스케어의 혁신 확산 요인이 이용의도에 미치는 영향 관계를 파악하고, 이 영향관계에서 혁신 성향의 조절 효과를 검정하였다. 연구 결과 모바일 헬스케어의 상대적 유익성, 적합성, 관찰 가능성, 유용성이 이용의도에 영향을 미치는 것으로 나타났다. 또한 복잡성, 시험 가능성, 유용성이 이용의도에 미치는 영향 관계에서 혁신 성향의 조절 효과가 있는 것으로 나타났다. 본 연구는 혁신 성향이라는 개념을 이용하여 혁신 확산 요인과 이용의도와의 영향 관계에서 주요한 조절 변수임을 확인하였음에 시사점을 갖는다. 또한 모바일 헬스케어의 공급자 입장에서 소비자의 혁신 성향을 고려되어야 하는 요인임을 시사한다.

The technology of mobile healthcare is steadily growing, but acceptance of consumers is sluggish. Various studies related to mobile healthcare have been conducted, but studies on the characteristics of prisoners are lacking. Therefore, in this study, we examined the effect of diffusion factors of mobile health care on the intention to use, and examined the moderating effect of innovation propensity. The results show that the relative advantage, compatibility, observability, and usefulness of mobile health care affect the intention to use. In addition, the innovation propensity has a moderating effect on the influence of complexity, trialability, and usafulness on intention to use. This study suggests that the use of the concept of innovation propensity has been confirmed as a major control variable in the relationship between innovation diffusion factors and utilization intention. In addition, it suggests that consumers' innovation tendency is a factor to be taken into consideration for suppliers of mobile healthcare.

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참고문헌

  1. Endeavour Partners, L.L.C. (2014). Inside Wearables-How the Science of Behavior Change Offers the Secret to Long-Term Engagement. USA : Endeavour Partners, L.L.C.
  2. P. Olson. (2014). Wearable tech is plugging into health insurance. USA : Forbes
  3. P. Y. Chau & P. J. H. Hu. (2002). Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories. Information & management, 39(4), 297-311. https://doi.org/10.1016/S0378-7206(01)00098-2
  4. S. P. Lin. (2011). Determinants of adoption of mobile healthcare service. International Journal of Mobile Communications, 9(3), 298-315. https://doi.org/10.1504/IJMC.2011.040608
  5. B. Kijsanayotin, S. Pannarunothai, S & S. M. Speedie. (2009). Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model. International journal of medical informatics, 78(6), 404-416. https://doi.org/10.1016/j.ijmedinf.2008.12.005
  6. H. S. Yoo, M. Y. Kim & O. B. Kwon. (2008). A study of factors influencing ubiquitous computing service acceptance. The Journal of Society for e-Business Studies, 13(2), 117-147.
  7. L. S. Lee, J. S. Jeong & K. Y. Noh.(2017). Psychological Factors Influencing Continuous Use of Mobile Healthcare Applications. Journal of Digital Convergence, 15(7), 445-456. https://doi.org/10.14400/JDC.2017.15.7.445
  8. Z. Zheng. (2015). User Acceptance of Mobile Healthcare Applications : An Integrated Model of UTAUT and HBM Theory. Korean policy sciences review, 19(3), 203-236.
  9. O. H. Lee & S. W. Ham. (2017). A Study on Influence Factors of Mobile Healthcare Service Using Structural Equation Modeling. Journal of the Korea Academia-Industrial cooperation Society, 18(3), 418-427. https://doi.org/10.5762/KAIS.2017.18.3.418
  10. Y. J. Kim. (2012). Exploratory Study on Acceptance Intention of Mobile Devices and Applications for Healthcare Services. The Journal of the Korea Contents Association, 12(9), 369-379. https://doi.org/10.5392/JKCA.2012.12.09.369
  11. J. N. Sheth (1981). Psychology of Innovation Resistance: The Less Developed Concept (LDC) in Diffusion Research, Research in Marketing, 273-282.
  12. Y. S. Ma., D. Y. Yeon & S. H. Park. (2015). Moderating Effect of Consumer Innovativeness on Relationship between Sportwearable Device's Innovation Attribute and Innovation Resistance of College Students. Korean Journal of Sport Science, 26(4), 861-873. https://doi.org/10.24985/kjss.2015.26.4.861
  13. G. A. Moore (2002). Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers. New York, United States: Harper Collins.
  14. Kay, M., Santos, J. & Takane, M. (2011). mHealth: New horizons for health through mobile technologies. World Health Organization, 64(7), 66-71.
  15. G. Y. Lee & D. M. Lee. (2018). A study on the Future Bathroom Coupled with Smart Healthcare System. Journal of the Korea Convergence Society, 9(3), 203-209. https://doi.org/10.15207/JKCS.2018.9.3.203
  16. B. W. Min (2016). An Improvement of Personalized Computer Aided Diagnosis Probability for Smart Healthcare Service System. Journal of Convergence for Information Technology, 6(4), 79-84. https://doi.org/10.22156/CS4SMB.2016.6.4.079
  17. S. J. Yoo & S. Y. Moon. (2016). Diagnosis and prospect of bio-health industry for sustainable growth of Korean economy. Seoul, Korea : KISTEP.
  18. Rogers, E. M. (1962), Diffusion of Innovation, New York, USA : The Free Press.
  19. Y. S. Seo & S. S. Lee. (2014). A Study on Consumer Satisfaction and Willingness to Recommend by the Innovation Diffusion Theory: Comparison on Different Technology Adoption Stages of Smartphone. Journal of Consumption Culture, 17, 89-111. https://doi.org/10.17053/jcc.2014.17.1.005
  20. S. Emani,, C. K. Yamin, E. Peters, A. S. Karson, S. R. Lipsitz, J. S. Wald, D. H. Williams & D. W. Bates. (2012). Patient perceptions of a personal health record: a test of the diffusion of innovation model. Journal of medical Internet research, 14(6), e150 https://doi.org/10.2196/jmir.2278
  21. G. Y. Kwon & D. G. Lee. (2013). A Study on the Impact of Personal Characteristics on the Use Intent of Smart-phone. Korean Business Review, 6(1), 85-107.
  22. J. Carter (1998). Why settle for 'early adopters'?: The need to focus on 'Innovators'. Admap, 33, 41-43.
  23. R. E. Goldsmith & C. F. Hofacker,(1991). Measuring consumer innovativeness. Journal of the Academy of Marketing Science, 19(3), 209-221. https://doi.org/10.1007/BF02726497
  24. J. B. Hartman, K. C. Gehrt & K. Watchravesringkan. (2004). Re-examination of the concept of innovativeness in the context of the adolescent segment: Development of a measurement scale. Journal of Targeting, Measurement and Analysis for Marketing, 12(4), 353-365. https://doi.org/10.1057/palgrave.jt.5740122
  25. Y. S. Ma, K.M. Cho., & J. H. Chin. (2014). The Structural Relationship of Smart Sports Wears among Percieved Attributes, Product Attribute and Innovation Resistance. Korean Journal of Sport Science, 25(3), 513-526. https://doi.org/10.24985/kjss.2014.25.3.513
  26. S. U. Yun. (2016). A study of integrative adoption model regarding social TV. Journal of Communication Science, 16(2), 145-183. https://doi.org/10.14696/jcs.2016.06.16.2.145
  27. K. Lee & S. Khan. (2007). Technology Adoption at the Consumer Level: Focus on Internet Based Communication Technology. AMCIS 2007 Proceedings, 431.
  28. S. T. Nam, D. G. Kim & C. Y. Jin. (2013). A study on the continuous intention to use for Smartphone based on the innovation diffusion theory. Journal of the Korea Institute Of Information and Communication Engineering, 17(5), 1219-1226. https://doi.org/10.6109/jkiice.2013.17.5.1219