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Facilitating the discovery of relevant studies on risk analysis for three-dimensional printing based on an integrated framework

Author

Listed:
  • Munan Li

    (South China University of Technology)

  • Alan L. Porter

    (Georgia Institute of Technology
    Search Technology)

Abstract

In an accurate and timely manner, capturing the risk signals for a specific emerging technology from academic publications is important to facilitate risk governance and to reduce the potential negative impact on socioeconomic systems. In the past decade, three-dimensional printing (3D printing) has become a promising emerging technology. To identify the relevant research on risk analysis for 3D printing, “term clumping” on “risk analysis” is explored using a quantitative method, and an integrated framework for risk identification is proposed with regard to 3D printing. This method involves a variation of TF*IDF and several new metrics for a Boolean query of the literature. The empirical results for the risk analysis studies of 3D printing show that, to date, very little attention has been paid to the relevant topics. However, although the risk signals of 3D printing are still weak and dispersed in many different categories, the potential threats to human health, cyber-security, and the environment are revealed in some facets. This enables initiation of strategies for anticipatory governance, involving science and technology policies and regulations.

Suggested Citation

  • Munan Li & Alan L. Porter, 2018. "Facilitating the discovery of relevant studies on risk analysis for three-dimensional printing based on an integrated framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 277-300, January.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:1:d:10.1007_s11192-017-2570-0
    DOI: 10.1007/s11192-017-2570-0
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    References listed on IDEAS

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    Cited by:

    1. Yujin Jeong & Hyejin Jang & Byungun Yoon, 2021. "Developing a risk-adaptive technology roadmap using a Bayesian network and topic modeling under deep uncertainty," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3697-3722, May.
    2. Munan Li, 2018. "Classifying and ranking topic terms based on a novel approach: role differentiation of author keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 77-100, July.
    3. Wang, Zhinan & Porter, Alan L. & Wang, Xuefeng & Carley, Stephen, 2019. "An approach to identify emergent topics of technological convergence: A case study for 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 723-732.
    4. Karlijn Muiderman & Aarti Gupta & Joost Vervoort & Frank Biermann, 2020. "Four approaches to anticipatory climate governance: Different conceptions of the future and implications for the present," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(6), November.
    5. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

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