IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v3y2013i2p2158244013489690.html
   My bibliography  Save this article

The Relationship Between Use of the Internet and Traditional Information Sources

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2158244013489690
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2158244013489690?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. (Kay) Byun, Kyung-ah & Ma, Minghui & Kim, Kevin & Kang, Taeghyun, 2021. "Buying a New Product with Inconsistent Product Reviews from Multiple Sources: The Role of Information Diagnosticity and Advertising," Journal of Interactive Marketing, Elsevier, vol. 55(C), pages 81-103.
    2. Lin, Wan-Ying & Zhang, Xinzhi & Jung, Joo-Young & Kim, Yong-Chan, 2013. "From the wired to wireless generation? Investigating teens’ Internet use through the mobile phone," Telecommunications Policy, Elsevier, vol. 37(8), pages 651-661.
    3. Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.
    4. Brett Danaher & Michael D. Smith & Rahul Telang, 2014. "Piracy and Copyright Enforcement Mechanisms," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 25-61.
    5. Xiaoli Wang & Shuangsheng Wu & C Raina MacIntyre & Hongbin Zhang & Weixian Shi & Xiaomin Peng & Wei Duan & Peng Yang & Yi Zhang & Quanyi Wang, 2015. "Using an Adjusted Serfling Regression Model to Improve the Early Warning at the Arrival of Peak Timing of Influenza in Beijing," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    6. Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    7. M. Narciso, 2022. "The Unreliability of Online Review Mechanisms," Journal of Consumer Policy, Springer, vol. 45(3), pages 349-368, September.
    8. Markowitz, Sara & Nesson, Erik & Robinson, Joshua J., 2019. "The effects of employment on influenza rates," Economics & Human Biology, Elsevier, vol. 34(C), pages 286-295.
    9. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
    10. Jesse T. Richman & Ryan J. Roberts, 2023. "Assessing Spurious Correlations in Big Search Data," Forecasting, MDPI, vol. 5(1), pages 1-12, February.
    11. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    12. Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(11), pages 60-70, November.
    13. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    14. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    15. Yangkun Huang & Xiaoping Xu & Sini Su, 2021. "Diverging from News Media: An Exploratory Study on the Changing Dynamics between Media and Public Attention on Cancer in China from 2011–2020," IJERPH, MDPI, vol. 18(16), pages 1-13, August.
    16. Vosen, Simeon & Schmidt, Torsten, 2012. "A monthly consumption indicator for Germany based on Internet search query data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19(7), pages 683-687.
    17. Victor M. Bennett & Robert Seamans & Feng Zhu, 2015. "Cannibalization and option value effects of secondary markets: Evidence from the US concert industry," Strategic Management Journal, Wiley Blackwell, vol. 36(11), pages 1599-1614, November.
    18. Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
    19. Sean Coogan & Zhixian Sui & David Raubenheimer, 2018. "Gluttony and guilt: monthly trends in internet search query data are comparable with national-level energy intake and dieting behavior," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-9, December.
    20. Tobias Preis & Federico Botta & Helen Susannah Moat, 2020. "Sensing global tourism numbers with millions of publicly shared online photographs," Environment and Planning A, , vol. 52(3), pages 471-477, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:3:y:2013:i:2:p:2158244013489690. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.