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Innovation Diffusion: Mobile Telephony Adoption In China

Author

Listed:
  • XIELIN LIU

    (Graduate University of Chinese Academy of Sciences, School of Management, 80 Zhongguancun East Road, Beijing 1000190, China)

  • FENG-SHANG WU

    (Chengchi University, Graduate Institute of Technology and Innovation Management, 64 ZhiNan Rd. Sec. 2, Taipei 11605, Taiwan)

  • WEN-LIN CHU

    (Chengchi University, Graduate Institute of Technology and Innovation Management, 64 ZhiNan Rd. Sec. 2, Taipei 11605, Taiwan)

Abstract

The rapid diffusion of mobile telephony is an important subject in diffusion studies of innovation. This study attempts to learn how mobile telephony diffuses in China, which has the most mobile telephone subscribers worldwide, in terms of the appropriate growth model and forces driving the diffusion. To identify the appropriate growth model, this study compares the fitness and forecasting ability of three conventional models — the Logistic, Bass, and Gompertz models. The determinants of the diffusion rate are then analyzed based on the most appropriate model. Empirical results, based on data for mobile telephone subscribers in China for 1986–2007, indicate that the Gompertz model performs best. Moreover, the four determinants for the diffusion rate are: number of fixed-line telephone subscribers, the low cost of mobile handsets, pre-paid service and the personal handy-phone system (PHS) service.

Suggested Citation

  • Xielin Liu & Feng-Shang Wu & Wen-Lin Chu, 2009. "Innovation Diffusion: Mobile Telephony Adoption In China," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 245-271.
    • Handle: RePEc:wsi:ijimxx:v:13:y:2009:i:02:n:s1363919609002285
    DOI: 10.1142/S1363919609002285
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    References listed on IDEAS

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    1. Shy,Oz, 2001. "The Economics of Network Industries," Cambridge Books, Cambridge University Press, number 9780521805001, January.
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    Cited by:

    1. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).

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