Year: 2018
Type: dissertation
Abstract: This dissertation argues for new directions in the field of technology foresight. Technology foresight was formulated on the basis of qualitative and participatory research. Initially, most foresight activities were triggered by the prospect of a handful number of experts, but recent studies highlight theoretical paradigm shifts toward a more comprehensive and data-driven approach to creating shared insights on the future of emerging technologies. Much of the research up to now, however, has been descriptive in nature, and a definite method of realizing the notion has not yet been addressed in the existing literature to a large extent. To this end, we have attempted to formalize the concept of data-driven technology foresight by incorporating unconventional data sources – future-oriented web data, Wikipedia data, and scientific publication data – and different analytical tools – Latent Semantic Analysis, IdeaGraph, and Morphological Analysis. Four distinct foresight frameworks were proposed for the proactive management process of emerging technologies: impact identification, impact analysis, plan development, and technology ideation. \nThe study was guided by the following research questions: (1) what kinds of data sources are available on the web and which of those are considered useful in foresight studies? (2) Where could we incorporate these data sources and which techniques are most suitable for the given purposes? (3) Which foresight-related fields would particularly benefit from applying a data-driven approach and what are the positive effects? The proposals outlined should be considered exploratory and open-ended. It is designed to determine the nature of the problem, rather than to offer definitive and conclusive answers. Nevertheless, the proposed scheme may well provide not just a rationale but a theoretical grounding for this newly introduced notion. This dissertation is expected to yield a foothold for the readers to better comprehend and act on this new shift in the field of technology foresight.
Author: 권희열
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3033537061