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Using Google Trends in Management Fashion Research: A Short Note

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  • Dag Øivind Madsen

    (USN - University College of Southeast Norway)

Abstract

Google Trends (GT) is an analytic tool for measuring and monitoring Internet search data. In recent years GT been utilized for research in fields as diverse as health care, political science and economics. This short paper looks at the possibilities of using GT in management fashion research. GT could have a natural application in the study of management fashion. After all, a key question of interest to management fashion researchers is how the popularity of management concepts and ideas evolves over time. The paper discusses the pros and cons of using GT in management fashion research. Using Internet search data can possibly reveal intentions and expectations in the management fashion market, provide indicators of future fashion demand, and as well as indicate "outbreaks" of contagious management concepts and ideas.

Suggested Citation

  • Dag Øivind Madsen, 2016. "Using Google Trends in Management Fashion Research: A Short Note," Working Papers hal-01343880, HAL.
    • Handle: RePEc:hal:wpaper:hal-01343880
    Note: View the original document on HAL open archive server: https://hal.science/hal-01343880
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    File URL: https://hal.science/hal-01343880/document
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    References listed on IDEAS

    as
    1. Dag Øivind Madsen, 2014. "How do managers encounter fashionable management concepts? A study of balanced scorecard adopters in Scandinavia," International Journal of Management Concepts and Philosophy, Inderscience Enterprises Ltd, vol. 8(4), pages 249-267.
    2. Rossem, Annick Van & Veen, Kees Van, 2011. "Managers' awareness of fashionable management concepts: An empirical study," European Management Journal, Elsevier, vol. 29(3), pages 206-216, June.
    3. Jos Benders & Jurriaan Nijholt & Stefan Heusinkveld, 2007. "Using Print Media Indicators in Management Fashion Research," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(6), pages 815-829, December.
    4. 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.
    5. Jung, Dong-II & Lee, Won-Hee, 2016. "Crossing the management fashion border: The adoption of business process reengineering services by management consultants offering total quality management services in the United States, 1992–2004," Journal of Management & Organization, Cambridge University Press, vol. 22(5), pages 702-719, September.
    6. Hoque, Zahirul, 2014. "20 years of studies on the balanced scorecard: Trends, accomplishments, gaps and opportunities for future research," The British Accounting Review, Elsevier, vol. 46(1), pages 33-59.
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    Cited by:

    1. Daniel E. O'Leary, 2024. "Toward an extended framework of exhaust data for predictive analytics: An empirical approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
    2. Dag Øivind Madsen & Kåre Slåtten, 2022. "The Possibilities and Limitations of Using Google Books Ngram Viewer in Research on Management Fashions," Societies, MDPI, vol. 12(6), pages 1-12, November.
    3. Emmanuel Sirimal Silva & Hossein Hassani & Dag Øivind Madsen & Liz Gee, 2019. "Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends," Social Sciences, MDPI, vol. 8(4), pages 1-23, April.

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