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Technology Foresight: A Bibliometric Analysis to Identify Leading and Emerging Methods

Author

Listed:
  • Elizabeth Gibson

    (University of Colorado at Boulder (USA))

  • Tugrul Daim

    (Portland State University (USA))

  • Edwin Garces

    (Portland State University (USA))

  • Marina Dabic

    (Nottingham Trent University (UK) and University of Zagreb (Croatia))

Abstract

Foresight studies provide essential information used by the government, industry and academia for technology planning and knowledge expansion. They are complicated, resource-intensive, and quite expensive. The approach, methods, and techniques must be carefully identified and selected. Despite the global importance of foresight activities, there are no frameworks to help one develop and plan a proper foresight study. This paper begins to close this gap by analyzing and comparing different schools of thought and updating the literature with the most current tools and methods. Data mining techniques are used to identify articles through an extensive literature review. Social Network Analysis (SNA) techniques are used to identify and analyze leading journals, articles, and researchers. A framework is developed here to provide a guide to help in the selection of methods and tools for different approaches.

Suggested Citation

  • Elizabeth Gibson & Tugrul Daim & Edwin Garces & Marina Dabic, 2018. "Technology Foresight: A Bibliometric Analysis to Identify Leading and Emerging Methods," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(1), pages 6-24.
    • Handle: RePEc:hig:fsight:v:12:y:2018:i:1:p:6-24
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    References listed on IDEAS

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    Cited by:

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    2. Beata Poteralska, 2021. "Support for the Development of Technological Innovations at an R&D Organisation," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    3. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    4. Li, Shuying & Zhang, Xian & Xu, Haiyun & Fang, Shu & Garces, Edwin & Daim, Tugrul, 2020. "Measuring strategic technological strength :Patent Portfolio Model," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    5. Seyed Mahmoud Zanjirchi & Mina Rezaeian Abrishami & Negar Jalilian, 2019. "Four decades of fuzzy sets theory in operations management: application of life-cycle, bibliometrics and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1289-1309, June.
    6. Artjom Rafaelevich Nagimov & Elvir Munirovich Akhmetshin & Valeriy Pavlovich Slanov & Raisa Nikolaevna Shpakova & Mikhail Prokopievich Solomonov & Dmitry Pavlovich Il'yaschenko, 2018. "Foresight Technologies in the Formation of a Sustainable Regional Development Strategy," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 741-752.

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    More about this item

    Keywords

    technology foresight; strategic foresight; adaptive foresight; Social Network Analysis (SNA); bibliometric tools; data mining; text mining;
    All these keywords.

    JEL classification:

    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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