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The Relationship Between Use of the Internet and Traditional Information Sources

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  • Satoshi Kitamura

Abstract

This study examines how the spread of the Internet has affected Japanese people’s information acquisition from traditional media or via traditional information channels. In particular, this study focuses on displacement and complementary effects and on devices for Internet access. Using representative data from Japan ( N = 1,179), the results show that Internet use via mobile phone has complementary effects on information acquisition from traditional media, while Internet use via personal computers does not. In addition, the results show that Internet use via personal computers has a displacement effect on information acquisition from radio. These findings are discussed with regard to communication means, social contexts, and media interfaces.

Suggested Citation

  • Satoshi Kitamura, 2013. "The Relationship Between Use of the Internet and Traditional Information Sources," SAGE Open, , vol. 3(2), pages 21582440134, May.
  • Handle: RePEc:sae:sagope:v:3:y:2013:i:2:p:2158244013489690
    DOI: 10.1177/2158244013489690
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    References listed on IDEAS

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    1. Park, JungKun & Chung, HoEun & Yoo, Weon Sang, 2009. "Is the Internet a primary source for consumer information search?: Group comparison for channel choices," Journal of Retailing and Consumer Services, Elsevier, vol. 16(2), pages 92-99.
    2. Stan J. Liebowitz & Alejandro Zentner, 2012. "Clash of the Titans: Does Internet use Reduce Television Viewing?," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 234-245, February.
    3. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    4. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    5. Ishii, Kenichi, 2004. "Internet use via mobile phone in Japan," Telecommunications Policy, Elsevier, vol. 28(1), pages 43-58, February.
    6. van Rijnsoever, Frank J. & Castaldi, Carolina & Dijst, Martin J., 2012. "In what sequence are information sources consulted by involved consumers? The case of automobile pre-purchase search," Journal of Retailing and Consumer Services, Elsevier, vol. 19(3), pages 343-352.
    7. Tsao, James C. & Sibley, Stanley D., 2004. "Displacement and Reinforcement Effects of the Internet and Other Media as Sources of Advertising Information," Journal of Advertising Research, Cambridge University Press, vol. 44(1), pages 126-142, March.
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    Cited by:

    1. Xiaoyi Shao & Xiaoli Ni, 2021. "How Does Family Intimacy Predict Self-Esteem in Adolescents? Moderation of Social Media Use Based on Gender Difference," SAGE Open, , vol. 11(1), pages 21582440211, March.

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