Technology Forecasting by Analogy-based on Social Network Analysis: The Case of Autonomous Vehicles

Authors

Shuying Li, Chinese Academy of Sciences
Edwin Garces, Portland State University
Tugrul Daim, Portland State UniversityFollow

Sponsor

This paper is partially funded by the Basic Research Program of the National Research University Higher School of Economics (HSE) and by the Russian Academic Excellence Project '5-100'. This study is partially funded by the Chinese Academy of Science.

Published In

Technological Forecasting and Social Change

Document Type

Citation

Publication Date

11-1-2019

Abstract

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).

Description

© 2019 Elsevier Inc. All rights reserved.

Locate the Document

https://doi.org/10.1016/j.techfore.2019.119731

DOI

10.1016/j.techfore.2019.119731

Persistent Identifier

https://archives.pdx.edu/ds/psu/31072

Citation Details

Li, S., Garces, E., & Daim, T. (2019). Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles. Technological Forecasting and Social Change, 148, 119731.