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| Identifying Technological Evolution Paths and Predicting Innovation Opportunities from the Perspective of Technological Form Iteration |
| Zhang Ke1,2,3, Wang Congxiang4, Wang Jinfeng5, Zhou Wei6, Feng Yicheng7 |
1.School of Information Management, Zhengzhou University, Zhengzhou 450001
2.Research Center for “Double World-Class Project” of Henan Province, Zhengzhou 450001
3.Data Governance Research Center of Henan Province, Zhengzhou 450001
4.School of Management, Zhengzhou University, Zhengzhou 450001
5.China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai 201306
6.School of Information Management, Wuhan University, Wuhan 430072
7.College of Engineering, Peking University, Beijing 100871 |
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Abstract Understanding the trajectory of technological evolution is crucial for fostering innovation. However, existing studies often overlook the granularity of evolutionary themes and the multi-level structure of evolutionary relationships, which limits comprehensive analysis of the evolutionary patterns and constrains the efficiency and advancement of technological innovation. From the perspective of technological form iteration, this study proposes a systematic method for identifying technological evolution paths and predicting innovation opportunities. First, a patent citation network is constructed and hierarchically layered using an appropriate algorithm. A high knowledge persistence (KP) contribution-based patent traversal algorithm is then employed to extract the main evolutionary paths. Next, technical forms are identified from patents, and an initial technological form evolution network is established based on the keyword-citation-keyword (KCK) principle. To enhance network reliability, a triple-criteria screening framework—comprising semantic similarity, attribute consistency, and temporal continuity—is introduced to filter relationships within the network. Finally, the search path count (SPC) algorithm is applied to determine the principal technological evolution paths in the refined network. Building on the dimensional law coupling principle from multi-dimensional technology innovation map, the most recent technological forms along each main path are iteratively developed to identify and generate potential innovation opportunities. A case study on polypropylene modification technology is conducted to validate the feasibility and effectiveness of the proposed approach. The findings provide a valuable reference for uncovering fine-grained technological evolution paths and for accurately and efficiently identifying innovation opportunities.
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Received: 19 September 2025
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