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Comparative analysis of innovative diffusion in the high-tech markets of Japan and South Korea: a use–diffusion model approach

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Abstract

In recent years, many scholars and practitioners have raised doubt as to whether or not conventional research on the diffusion of innovation can explain and predict the needs and behavioral patterns of consumers in the raiding and converging market environment. Thus, it has been suggested that the use–diffusion model would be a good alternative framework to study innovation diffusion. This study explores whether the new model is effective in explaining and predicting the needs and innovative behavioral patterns of consumers in the Internet Protocol Television (IPTV) market in Japan and South Korea. Nation-wide surveys were conducted in Japan and South Korea for data collection, resulting in a large random sample (n = 500 in Japan and n = 500 in South Korea). Important findings of the study are: (1) product experience and sophistication of technology were found to be the most important factors in explaining the innovative diffusion process among IPTV users; (2) functional similarity, complementarity, and substitution effect were also main determinants for enhancing users’ satisfaction with IPTV services; (3) complexity and relative advantage were crucial measures of IPTV’s current technological level, functional performance, and quality with regard to services; and (4) a comparative analysis of diffusion patterns of IPTV between Japan and South Korea indicated that IPTV users in Japan appeared to be still in the phase of early adopters, while South Korean users have gone beyond to the phase of early majority in the adoption cycle.

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Notes

  1. To find respondents, there are several sampling methods: (1) non-probability sampling methods (e.g., purposive sample, volunteer subjects, haphazard sample) and (2) probability sampling methods (e.g., simple random sample, stratified sample, cluster sample). However, each sampling methods has advantages and disadvantages. Therefore, we had to carefully draw two different samples with regard to both accuracy and research expense. In Japan, we found respondents through an internet survey because it is becoming increasingly popular with many researchers in diverse fields such as marketing. On the other hand, in South Korea, we drew a simple random sample (i.e., face-to-face survey) for accuracy, although it is too expensive.

References

  • Ajzen I (1991) The theory of planned behavior. Org Behav Hum Decis Process 50(2):179–211

    Article  Google Scholar 

  • Atkin D (1995) Audio information services and the electronic media environment. Inf Soc Int J 11(1):75–83

    Article  Google Scholar 

  • Baaren E, Wijngaert L, Huizer E (2008) I want my HDTV? Underlying factors of perceived usefulness for high definition television. LNCS 5066:283–292

    Google Scholar 

  • Barbara KK, Thomas JJ (2003) From here to obscurity?: media substitution theory and traditional mediainan on-line world. J Ameri Soc for Infor Sci and Tech 54(3):260–273

    Google Scholar 

  • Berry LL, Carbone LP, Haeckel SH (2002) Managing the total customer experience. MIT Sloan Manag Rev 43(3):85–89

    Google Scholar 

  • Cai X (2001) A test of the functional equivalence principle in the new media environment. Unpublished doctoral dissertation. Indiana University, Indiana

  • Chin W (1998) The partial least squares approach to structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Lawrence Erlbaum Associates, Mahwah, NJ, pp 295–336

    Google Scholar 

  • Cognitiative R (1999) E-commerce and the evolution of retail shopping behaviour. Pulse Cust 1(2):67–89

    Google Scholar 

  • Cronin JJ Jr, Taylor SA (1992) Measuring service quality: a reexamination and extension. J Mark 56(3):55–68

    Article  Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  • Fidler R (1997) Mediamorphosis; understanding new media. Pine Forge press, California

    Google Scholar 

  • Fishbein M, Ajzen I (1975) Belief, attitude, intention and behaviour: an introduction to theory and research. Addison-Wesley, Massachusetts

    Google Scholar 

  • Ha WK, Hong YK (2008) IPTV innovation. The Electronic Times Co., Ltd

  • Hahn M, Park S, Krishnamurti L, Zoltners AA (1994) Analysis of new product diffusion using a four-segment trial-repeat model. Mark Sci 13(3):224–247

    Article  Google Scholar 

  • Hair JF Jr, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice-Hall, Upper Saddle River, NJ

    Google Scholar 

  • Hellier PK, Carr GM, Richard JA (2003) Customer repurchase intention: a general structural equation model. Euro J Mark 37:1762–1800

    Article  Google Scholar 

  • Hoffmann S, Soyez K (2010) A cognitive model to predict domain-specific consumer innovativeness. J Bus Res 63(7):778–785

    Article  Google Scholar 

  • Huberman BA, Pirolli PLT, Piktow JE, Lukose RM (1998) Strong regularities in world wide web surfing. Science 280(3):95–97

    Article  Google Scholar 

  • Jeffres L, Atkin D (1996) Predicting use of technologies for consumer and communication needs. J Broadcast Electron Media 40:318–330

    Article  Google Scholar 

  • Kim YJ (2005) A study on the participation in, use of, and satisfaction over cyber communities. Korea Press J 49(3):291–318

    Google Scholar 

  • Kim MT, Yi JH (2007) Innovativeness of n-generation consumers influencing use–diffusion and re-adoption of convergence products, and the influence of reference group’s conformity. Indus Econ Res 20(3):1253–1278

    Google Scholar 

  • Kivi A, Smura T, Toyli J (2008) Technology product evolution and the diffusion of new product features. Technol Forecast Soc Change 79:107–126

    Article  Google Scholar 

  • Lee SM, Olson D (2010) Convergenomics: strategic innovation in the convergence era. Gower Press, London

    Google Scholar 

  • Lee EJ, Lee JK, David WS (2002) The influence of communication source and mode on consumer adoption of technological innovation. J Consumer Aff 37(2):256–278

    Article  Google Scholar 

  • Li SCS (2004) Exploring the factors influencing the adoption of interactive cable television services in Taiwan. J Broadcast Electron Media 48(3):466–483

    Article  Google Scholar 

  • Mahler A, Rogers EM (1999) The diffusion of interactive communication innovations and the critical mass: the adoption of telecommunications services by German banks. Telecommun Policy 23:719–740

    Article  Google Scholar 

  • Martin IM, Stewart DW (2001) The differential impact of goal congruency on attitudes, intentions, and the transfer of brand equity. J Mark Res 38:471–484

    Google Scholar 

  • Mick D, Fournier S (1998) New product diffusion models in marketing: a review and direction for research. J Mark 54:1–26

    Google Scholar 

  • Moore GA (1991) Crossing the chasm: marketing and selling technology products to mainstream customers. Harper Business, New York

    Google Scholar 

  • Moore GC, Benbasat I (1991) Development of an instrument to measure the perceptions of adopting an information technology behavior. Inf Syst Res 2(3):192–222

    Article  Google Scholar 

  • Motohashi K, Lee DR, Sawng YW, Kim SH (2012) Innovative converged service and its adoption, use and diffusion: a holistic approach to diffusion of innovations, combining adoption–diffusion and use–diffusion paradigms. J Bus Econ Manag 13(2):308–333

    Article  Google Scholar 

  • Nishi T (2008) IPTV kakumei-hoso netto mobile no business model. Nikkei Business Publications, Inc. Tokyo, Japan

  • Noyes JM, Garland KJ (2006) Comment on evaluating cognitive demand. Percept Mot Skills 102(1):118–120

    Article  Google Scholar 

  • Price LL, Ridgeway NM (1983) Development of a scale to measure use innovativeness. Adv Consumer Res 10:679–684

    Google Scholar 

  • Ram S, Jung HS (1990) The conceptualization and measurement of product usage. J Acad Mark Sci 18(1):67–76

    Article  Google Scholar 

  • Rogers EM (1995) Diffusion of innovations, 4th edn. Free Press, New York

    Google Scholar 

  • Rogers EM (2003) Diffusion of innovations, 5th edn. Free Press, New York

    Google Scholar 

  • Sandström S, Edvardsson B, Kristensson P, Magnusson P (2008) Value in use through service experience. Manag Serv Qual 18(2):112–126

    Article  Google Scholar 

  • Shih CF, Venkatesh A (2004) Beyond adoption: development and application of a use–diffusion model. J Mark 68:59–72

    Article  Google Scholar 

  • Venkatesh V (2000) Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf Syst Res 11(4):342–365

    Article  Google Scholar 

  • Wold H (1985) Partial least squares. In: Kotz S, Johnson NL (eds) Encyclopedia of statistical science, vol 6. Wiley, New York, pp 581–591

    Google Scholar 

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Correspondence to Gang-Hoon Kim.

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Sawng, YW., Motohashi, K. & Kim, GH. Comparative analysis of innovative diffusion in the high-tech markets of Japan and South Korea: a use–diffusion model approach. Serv Bus 7, 143–166 (2013). https://doi.org/10.1007/s11628-012-0166-6

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