Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology

Zhichao Ba, Kai Meng, Yaxue Ma and Yikun Xia

Technological Forecasting and Social Change, 2024, vol. 200, issue C

Abstract: Technological opportunities are bred in intricate and interactive connections between science and technology (S&T). To identify these potential opportunities, lexical- or topic-based similarity approaches have been extensively applied to quantify S&T linkages; however, these lack consideration of different interaction patterns and lead-lag relationships between S&T. To this end, this study proposes a novel approach to detect technological opportunities within specific S&T topics by incorporating their structure-coupling patterns and temporal lead-lag distance. By transforming S&T knowledge systems into knowledge networks, a network coupling approach is employed to elaborate dynamic interaction patterns of S&T, and a time-lagged cross-correlation analysis is conducted to calculate their lead-lag distance under different time shifts. An evidence analysis from the energy conservation field demonstrates the feasibility and reliability of the proposed methodology in identifying technological opportunities implicit in S&T shared (exists in both S&T) and private topics (exists only in science or technology) from a topical dimension.

Keywords: Technological opportunities; Science-technology linkage; Network coupling; Lead-lag relationship; Energy conservation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162523008326
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523008326

DOI: 10.1016/j.techfore.2023.123147

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().