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An Empirical Analysis on Comparing Market Share with Concerns on Companies Measured Through Search Engine Suggests

Author

Listed:
  • Takehito Utsuro

    (University of Tsukuba)

  • Chen Zhao

    (University of Tsukuba)

  • Linghan Xu

    (University of Tsukuba)

  • Jiaqi Li

    (University of Tsukuba)

  • Yasuhide Kawada

    (Logworks Co., Ltd.)

Abstract

In this study, we present a method of predicting market share values using search engine data. Given a product-specific domain, we compare the rates of Web searches for different companies supplying similar products and consider them as concerns of those who search for Web pages. In the proposed method, concerns of those who search for Web pages are measured through search engine suggests. We then analyze whether rates of concerns of those who search for Web pages are correlated with the actual market shares. Next, we examine the page view statistics at the kakaku.com site as intermediate statistics and determine their correlation with the rates of concerns of those who search for Web pages and the market shares. The results of the analysis indicate significant correlation. Furthermore, we conduct an empirical study on determining the optimal correlation between the rates of concerns of those who search for Web pages and the market shares, as well as that between the rates of concerns of those who search for Web pages and the page view statistics at the kakaku.com site.

Suggested Citation

  • Takehito Utsuro & Chen Zhao & Linghan Xu & Jiaqi Li & Yasuhide Kawada, 2017. "An Empirical Analysis on Comparing Market Share with Concerns on Companies Measured Through Search Engine Suggests," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(1), pages 3-19, March.
    • Handle: RePEc:spr:gjofsm:v:18:y:2017:i:1:d:10.1007_s40171-016-0147-z
    DOI: 10.1007/s40171-016-0147-z
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    References listed on IDEAS

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    1. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    2. 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.
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