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Technological innovation is a dynamic process that spans the lifecycle of an idea, from scientific research to production. Within this process, there are few key innovations that significantly impact a technology’s development, and the ability to identify and trace the development of these key innovations comes with a great payoff for researchers and technology managers. In this paper, we present a framework for identifying the technology’s main evolutionary pathway of a technology. What is unique about this framework is that we introduce new indicators that reflect the connectivity and the modularity in the interior citation network to distinguish between the stages of a technology’s development. We also show how information about a family of patents can be used to build a comprehensive patent citation network. Last, we apply integrated approaches of main path analysis (MPA) -- namely global main path analysis and global key-route main analysis -- for extracting technological trajectories at different technological stages. We illustrate this approach with Dye-Sensitized Solar Cells (DSSCs), a low-cost solar cell belonging to the group of thin film solar cells, contributing to the remarkable growth in the renewable energy industry. The results show how this approach can trace the main development trajectory of a research field and distinguish key technologies to help decision-makers manage the technological stages of their innovation processes more effectively.
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An Approach to Construct Technological Convergence Networks Across Different IPC Hierarchies and Identify Key Technology Fields
Technological convergence network (TCN) is an effective method to identify the advancement of technology convergence. However, the previous TCN investigations are limited to a single level of IPC (abbreviation of International Patent Classification) rather than different IPC hierarchies, which can only provide decision support for policy-makers with one dimension instead of various ones. In this study, we propose a new approach to construct TCNs across different IPC hierarchies based on technology co-classification analysis, and further identify key technology fields by employing the indicator of betweenness centrality (BC) in the TCNs from any IPC hierarchy. This study makes two important contributions. First, theoretically, our study is to contribute to understanding the advancement of technological convergence from various IPC hierarchies, rather than a single IPC level. Second, methodologically, the new approach we propose can benefit decision-makers serving at various levels of technology management agencies. We conclude possible implications and future directions.
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- Award ID(s):
- 1759960
- PAR ID:
- 10312719
- Date Published:
- Journal Name:
- IEEE Transactions on Engineering Management
- ISSN:
- 0018-9391
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TEM.2021.3120709
