新兴技术
新兴市场
数据科学
比例(比率)
计算机科学
秩(图论)
人工智能
经济
地理
数学
地图学
宏观经济学
组合数学
作者
Avi Goldfarb,Bledi Taska,Florenta Teodoridis
出处
期刊:Research Policy
[Elsevier BV]
日期:2022-10-14
卷期号:52 (1): 104653-104653
被引量:183
标识
DOI:10.1016/j.respol.2022.104653
摘要
Many emerging technologies have aspects of General Purpose Technologies (GPTs). However, true GPTs are rare and hold potential for large-scale economic impact. Thus, it is important for policymakers and managers to assess which emerging technologies are likely GPTs. We describe an approach that uses data from online job ads to rank emerging technologies on their GPT likelihood. The approach suggests which technologies are likely to have a broader economic impact, and which are likely to remain useful but narrower enabling technologies. Our approach has at least 5 years predictive power distinct from prevailing patent-based methods of identifying GPTs. We apply our approach to 21 different emerging technologies, and find that a cluster of technologies comprised of machine learning and related data science technologies is relatively likely to be a GPT.
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