Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles

• Published in: Technological forecasting & social change Vol. 148; p. 119731
• Main Authors: Li, Shuying, Garces, Edwin, Daim, Tugrul
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.11.2019; Elsevier Science Ltd
• Subjects: Analogies; Analogy-based; Autonomous vehicles; Complex networks; Density; Forecasting; Network analysis; Network centrality metrics; New technology; SNA; Social network analysis; Social networks; Technological forecasting; Technology; Technology forecasting; Uncertainty; Social network analysis; SNA; Complex networks; Technology forecasting; Analogy-based; Autonomous vehicles; Network centrality metrics
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/j.techfore.2019.119731

During the last years, new technologies have been developing at a rapid pace; however, new technologies carry risks and uncertainties. Technology forecasting by analogy has been used in the case of emerging technologies; nevertheless, the use of analogies is subject to several problems such as lack of inherent necessity, historical uniqueness, historically conditioned awareness, and casual analogies. Additionally, the natural process of selecting the analogy technology is based on subjective criteria for technological similarities or inductive inference. Since many analogies are taken qualitatively and rely on subjective assessments, this paper presents a quantitative comparison process based on the Social Network Analysis (SNA) and patent analysis for selecting analogous technologies. In this context, the paper presents an analysis of complex patent network structures using centrality and density metrics in order to reduce the lack of information or the presence of uncertainties. The case of Autonomous Vehicles (AVs) is explored in this paper, comparing three candidate technologies which have been chosen based on the similarities with the target technologies. The best candidate technology is selected based on the analysis of two main centrality metrics (average degree and density). •An integrated methodology for analogy based technology forecasting is introduced•Integrated use of multiple data sources ranging from publications to grants•using SNA to identify collaborations and using collaboration density for analogy•Technology life cycle stages for automotive technologies•Collaboration networks for automotive technologies