Mapping and comparing the technology evolution paths of scientific papers and patents: an integrated approach for forecasting technology trends

Peng Liu, Wei Zhou, Lijie Feng, Jinfeng Wang (), Kuo-Yi Lin, Xuan Wu and Dingtang Zhang
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Peng Liu: Zhengzhou University
Wei Zhou: Zhengzhou University
Lijie Feng: Zhengzhou University
Jinfeng Wang: Shanghai Maritime University
Kuo-Yi Lin: Guilin University of Electronic Technology
Xuan Wu: Zhengzhou University
Dingtang Zhang: Zhengzhou Coal Mining Machinery Group Co., Ltd

Scientometrics, 2024, vol. 129, issue 4, No 1, 1975-2005

Abstract: Abstract Exploring the key technology evolution paths in specific technological domains is essential to stimulate the technological innovation of enterprises. There have been many methods to identify the technology evolution path, but many of them still had some limitations. Firstly, many studies consider only a single type of data source without analyzing and comparing multiple data sources, which may lead to incomplete evolution paths. Secondly, the text mining methods ignore the semantic relationships between technical terms, making path tracing inaccurate. In this study, we develop an integrated approach for mapping the technology evolution paths of scientific papers and patents. To better forecast the technology development trends, the gap analysis between scientific papers and patents and the identification of potential topics are also applied. The all-solid-state lithium-ion battery technology is selected for the empirical study and the related technology evolution trends and the technology opportunities are focused on. The empirical case research results show the proposed method’s validity and feasibility. This method can be helpful for understanding and analyzing the specific technology, which provides clues for forecasting technology development trends in enterprises. Furthermore, it contributes to the coordination of research and development efforts, which provides a reference for enterprises to identify technology innovation opportunities.

Keywords: Technology evolution path; Technology opportunities analysis; Technology trend; SAO (subject-action-object) semantic analysis; Topic modeling (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-024-04961-0

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