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The Trap of Quantification of Advertising Effectiveness: A Preliminary Study of the Ethical Challenges of Native Advertising

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Multidisciplinary Social Networks Research (MISNC 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 540))

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Abstract

As a new advertising form that uses the SNS, the native advertising has been attracting attention. It presents the ad as a natural reading, such as the article. One of the factors that allow such advertising is a big data and life log. However, analysis of big data and life log contains the ethical issues. In this paper, in order to consider the ethical issues, two cultures (that is, Quantification and Relationship Paradigm) that marketing science are focused. In particular, the problems of the trap of quantification, that is, myopia will cause some ethical problems.

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Author information

Authors and Affiliations

  1. Faculty of Informatics, Kansai University, 2-1 Ryozenji-cho, Takatsuki, Osaka, 560-1095, Japan

    Hiroshi Koga

Authors
  1. Hiroshi Koga
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Correspondence to Hiroshi Koga .

Editor information

Editors and Affiliations

  1. National University of Kaohsiung, Kaohsiung City, Taiwan

    Leon Wang

  2. Matsuyama University, Matsuyama, Japan

    Shiro Uesugi

  3. National University of Kaohsiung, Kaohsiung City, Taiwan

    I-Hsien Ting

  4. Osaka University, Osaka, Japan

    Koji Okuhara

  5. National University of Kaohsiung, Kaohsiung City, Taiwan

    Kai Wang

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Koga, H. (2015). The Trap of Quantification of Advertising Effectiveness: A Preliminary Study of the Ethical Challenges of Native Advertising. In: Wang, L., Uesugi, S., Ting, IH., Okuhara, K., Wang, K. (eds) Multidisciplinary Social Networks Research. MISNC 2015. Communications in Computer and Information Science, vol 540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48319-0_43

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  • DOI: https://doi.org/10.1007/978-3-662-48319-0_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48318-3

  • Online ISBN: 978-3-662-48319-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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