A systematic idea generation approach for developing a new technology: Application of a socio-technical transition system

Keeeun Lee, Sunhye Kim, Byungun Yoon

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Socio-technical systems have been highlighted as a new driver of novel idea generation, providing greater insights for new product development (NPD) in different fields. This research implements a broad set of indicators that measure both the technological and social features for a panel of 50 coevolution cases, and uses a structural vector autoregressive (SVAR) model in order to investigate the long-run relationships and coevolution patterns between technology and society. Technology evolution patterns were analysed using text data from patents, and social evolution patterns were investigated using text data from different news outlets. These influential relationships between technical and societal variables adopted from the SVAR model are examined over the course of this study. In addition, this research identifies various coefficients derived from this influential relationship, and draws out evolutionary patterns to verify how they have influenced each other over time. The results indicate that socio-technical systems are generally driven by the coevolution of three main technological variables (tangibility, safety and diffusion) and five social variables (intellectualization, informatization, polarization, connectivity and serviceability). This research contributes towards improving the explanatory power of coevolution patterns between society and technology, and more strongly establishes a set of insightful strategies for technological development.

Original languageEnglish
Article number121431
JournalTechnological Forecasting and Social Change
Volume176
DOIs
StatePublished - Mar 2022

Keywords

  • Coevolution
  • Socio-technical system
  • Structural vector autoregressive model
  • Technology idea generation

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