Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

A study on the continuous intention to use for Smartphone based on the innovation diffusion theory: Considered on the loyalty between users of iOS and Android platform

혁신확산이론에 따른 스마트폰 지속사용의도에 관한 연구: 아이폰 사용자와 안드로이드 사용자의 충성도 비교를 고려하여

  • 남수태 (원광대학교 대학원 정보관리학과) ;
  • 김도관 (원광대학교 정보전자상거래학부) ;
  • 진찬용 (원광대학교 정보전자상거래학부)
  • Received : 2013.03.08
  • Accepted : 2013.04.01
  • Published : 2013.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study was aimed to analyze factors affecting on continuous intention to use of Smartphone based on the innovation diffusion theory. Also, by using the demographic characteristics were compared whether the difference in the loyalty on between user group of iOS and Android platform. Predictor factors were selected innovation, convenience, economic cost, social influence, communication channel, compatibility and complexity suggested on the innovation diffusion theory. Participants of this study were 278 Smartphone users in Busan city and Gyeongnam province in accordance with convenience sampling. IBM SPSS Statistics 19 were employed for descriptive statistics, Smart PLS(partial least squares) was employed for confirmatory factor analysis and path analysis of casual relationship among variables and effect. Analytical results show that all paths except path from complexity to the continuous intention to use and loyalty are significant. The comparison loyalty on between user group of iOS and android platform are significant. This study suggests practical and theoretical implications based on the results.

본 연구에서는 혁신확산이론을 기반으로 스마트폰 지속적 사용의도에 미치는 영향을 분석하고자 하였다. 또한 인구통계학적 특성을 이용하여 아이폰 사용자와 안드로이드 플랫폼 사용자 그룹의 충성도 차이가 있는지를 비교하였다. 예측변수로는 혁신확산이론에서 제시된 혁신성과 편리성, 경제적 비용, 사회적 영향, 커뮤니케이션 채널, 적합성 그리고 복잡성을 선택하였다. 연구대상은 부산 경남지역에 거주하는 스마트폰 사용자 278명이며 설문지를 통해 자료를 수집하였다. 인구통계학적인 분석은 IBM SPSS Statistics 19로 하였고 Smart PLS를 사용하여 확인적 요인분석과 변수들 간의 인과관계에 대한 경로분석을 실시하였다. 분석결과 복잡성을 제외한 스마트폰 지속사용의도와 충성도에 이르는 모든 경로가 유의미한 영향을 미치는 것으로 나타났다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.

Keywords

References

  1. E. M. Rogers, Diffusion of innovations (7th ed.), New York: Free Press, 2005.
  2. E. M. Rogers and F. F. Shoemaker, Communication of innovation: A cross cultural approach, Second Edition, The Free Press, 1971.
  3. V. Venkatesh and S. A. Brown, "A longitudinal investigation of personal computers in homes: Adopion determinants and emerging challenge," MIS Quarterly, Vol. 25, No. 1, pp. 71-102, 2001. https://doi.org/10.2307/3250959
  4. R. Agarwal and J. Prasad, "A conceptual and operational definition of personal innovativeness in the domain of information technology," Information System Research, Vol. 9, No. 2, pp. 204-15, 1998. https://doi.org/10.1287/isre.9.2.204
  5. F. D. Davis, "Perceived usefulness ease of use, and use acceptance of information technology," MIS Quarterly, Vol. 13, No. 3, pp. 319-340, 1989. https://doi.org/10.2307/249008
  6. I. Ajzen and T. J. Madden, "Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control," Journal of Experimental Social Psychology, Vol. 22, pp. 453-474, 1986. https://doi.org/10.1016/0022-1031(86)90045-4
  7. 손규식, "스마트폰 애플리케이션 사용의도 결정 요인에 대한 실증 연구," 한국산학기술학회논문지, 제13권, 제2호, pp. 628-635, 2012. https://doi.org/10.5762/KAIS.2012.13.2.628
  8. V. A. Zeitham, L. B. Leonard and A. Parasuraman, "The behavioral consequences of service quality," Journal of Marketing, Vol. 6, No. 1, pp. 31-46, 1996.
  9. B. J. Babin, Y. K. Lee, C. K. Lee and S. k. Lee, "Festival scapes and patrons' emotions, satisfaction and loyalty," Journal of Business Research, Vol. 61, No. 1, pp. 56-64, 2008. https://doi.org/10.1016/j.jbusres.2006.05.009
  10. E. M. Rogers and F. F. Shoemaker, Communication of innovation: A cross cultural approach, Second Edition, The Free Press, 1971.
  11. D. A. Admas, R. R. Nelson and P. A. Todd, "Perceived usefulness, ease of use, and usage of information technology: A replication," MIS Quarterly, Vol. 16, No. 2, pp. 227-247, 1992. https://doi.org/10.2307/249577
  12. S. Taylor and P. A. Todd, "Understanding information technology usage: A test of competing models," Information Systems Research, Vol. 6, No. 2, pp. 144-176, 1995. https://doi.org/10.1287/isre.6.2.144
  13. V. Venkatesh, "Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model," Information System Research, Vol. 11, No. 4, pp. 342-365, 2000. https://doi.org/10.1287/isre.11.4.342.11872
  14. F. D. Davis, R. P. Bagozzi and P. R. Warshaw, "User acceptance of computer technology: A comparison of two theoretical model," Management Science, Vol. 35, No. 8, pp. 982-1003, 1989. https://doi.org/10.1287/mnsc.35.8.982
  15. R. P. Bagozzi and C. Fornell, "Theoretical concepts, measurement, and meaning in: A second generation of multivariate analysis," C. Fornell (ed.), Praeger, 1982.
  16. W. W. Chin, The partial least squares approach to structural equation modeling, In G. A. Marcoulides (Ed.), Lawrence Erlbaum, New Jersey, 1998.
  17. W. W. Chin, B. L. Marcolin and P. R. Newsted, "A partial least squares latent variable modeling approach for measuring interaction effects: Results from a monte carlo simulation study and an electronic mail emotion/adoption study," Information Systems Research, Vol. 14, No. 2, pp. 189-217, 2003. https://doi.org/10.1287/isre.14.2.189.16018
  18. C. Fornell and F. L. Bookstein, "Two structural equation models: LISREL and PLS applied to consumer exit-voice theory," Journal of Marketing Research, Vol. 19, No. 4, p. 440-452, 1982. https://doi.org/10.2307/3151718
  19. D. Gefen, "E-commerce: The role of familiarity and trust," Omega, Vol. 28, No. 6, pp. 725-737, 2000. https://doi.org/10.1016/S0305-0483(00)00021-9
  20. J. C. Nunnally, Psychometric theory, McGraw-Hill, New York, 1967.
  21. J. O. Cohen, Statistical power analysis for the behavioral sciences (2nd ed.), Hillsdale, Lawrence Erlbaum, New Jersey, 1988.
  22. M. Tenenhaus, V. E. Vinzia, Y. M. Chatelinc and C. Laurob, "PLS path modeling," Computational Statistics and Data Analysis, Vol. 48, No. 1, pp. 159-205, 2005. https://doi.org/10.1016/j.csda.2004.03.005
  23. B. Efron and R. Tibshirani, "Improvements on cross validation: The 0.632+ bootstrap method," Journal of the American Statistical Association, Vol. 92, No. 438, pp. 548-560, 1997.

Cited by

  1. A Meta-analysis and Review of External Factors based on the Technology Acceptance Model : Focusing on the Journals Related to Smartphone in Korea vol.18, pp.4, 2014, https://doi.org/10.6109/jkiice.2014.18.4.848
  2. 정보시스템 성공모형을 기반으로 한 모바일월렛 지속사용의도에 미치는 영향 요인 분석 vol.13, pp.4, 2013, https://doi.org/10.9716/kits.2014.13.4.325
  3. 인터넷 환경에서 대학생의 라이프스타일 특성에 따른 스마트폰 중독성향 비교 vol.20, pp.1, 2013, https://doi.org/10.6109/jkiice.2016.20.1.185
  4. 정보보안이 안드로이드와 iOS 기반 스마트폰 소비자 선호에 미치는 영향 vol.18, pp.1, 2017, https://doi.org/10.7472/jksii.2017.18.1.105
  5. 넷플릭스(Netflix) 이용자의 지속적 이용의도의 결정 요인에 관한 연구: 한국과 대만의 이용자에 대한 국가 간 비교분석 vol.61, pp.5, 2013, https://doi.org/10.20879/kjjcs.2017.61.5.011
  6. 모바일 헬스케어의 혁신확산 요인이 이용의도에 미치는 영향 연구: 혁신성향의 조절효과를 중심으로 vol.16, pp.5, 2013, https://doi.org/10.14400/jdc.2018.16.5.153