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An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence

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  • Li, Munan
  • Porter, Alan L.
  • Suominen, Arho
  • Burmaoglu, Serhat
  • Carley, Stephen

Abstract

How to evaluate or measure the emergence degree or level for a specific technology is rarely discussed in the prior studies, and it should be a valuable issue for the relevant areas on technology forecasting, foresight, and technological strategies for macro and micro economies, particularly for those emerging economies who are chasing the technology advances in the developed countries. A conceptual framework inspired by swarm intelligence theory is introduced to measure the emergence degree or level for a specific technology. Swarm intelligence belongs to complex systems theory, and has evolved into a helpful tool for heuristic algorithms and optimization computation, and brought forward an insightful perspective on the evolution and emergence of natural or social systems in the past decades. To verify the proposed framework for measuring emergence degree of a specific technology based on the basic philosophy of swarm intelligence, a case study analyzes an annual set of emerging technologies of the World Economic Forum. The theoretical and empirical analyses could present a fresh vision to investigate the essence of technology emergence, and provide some supplemental thoughts for the policy-making on those emerging or new technologies.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:tefoso:v:166:y:2021:i:c:s0040162521000536
    DOI: 10.1016/j.techfore.2021.120621
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    1. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).

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