Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance
The system of scientific innovation can be characterized as a complex, multi-layered network of actors, their products and knowledge elements. Despite the progress that has been made, a more comprehensive understanding of the interactions and dynamics of this multi-layered network remains a signific...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
|
| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2024.1492731/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841561157511413760 |
|---|---|
| author | Yangyang Jia Hongshu Chen Jingkang Liu Xuefeng Wang Rui Guo Ximeng Wang |
| author_facet | Yangyang Jia Hongshu Chen Jingkang Liu Xuefeng Wang Rui Guo Ximeng Wang |
| author_sort | Yangyang Jia |
| collection | DOAJ |
| description | The system of scientific innovation can be characterized as a complex, multi-layered network of actors, their products and knowledge elements. Despite the progress that has been made, a more comprehensive understanding of the interactions and dynamics of this multi-layered network remains a significant challenge. This paper constructs a multilayer longitudinal network to abstract institutions, products and ideas of the scientific system, then identifies patterns and elucidates the mechanism through which actor collaboration and their knowledge transmission influence the innovation performance and network dynamics. Aside from fostering a collaborative network of institutions via co-authorship, fine-grained knowledge elements are extracted using KeyBERT from academic papers to build knowledge network layer. Empirical studies demonstrate that actor collaboration and their unique and diverse ideas have a positive impact on the performance of the research products. This paper also presents empirical evidence that the embeddedness of the actors, their ideas and features of their research products influence the network dynamics. This study gains a deeper understanding of the driving factors that impact the interactions and dynamics of the multi-layered scientific networks. |
| format | Article |
| id | doaj-art-01267ac308bd4ac49522f4ef533201f2 |
| institution | Kabale University |
| issn | 2296-424X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj-art-01267ac308bd4ac49522f4ef533201f22025-01-03T05:10:20ZengFrontiers Media S.A.Frontiers in Physics2296-424X2025-01-011210.3389/fphy.2024.14927311492731Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performanceYangyang Jia0Hongshu Chen1Jingkang Liu2Xuefeng Wang3Rui Guo4Ximeng Wang5School of Management, Beijing Institute of Technology, Beijing, ChinaSchool of Management, Beijing Institute of Technology, Beijing, ChinaSchool of Economics, Beijing Institute of Technology, Beijing, ChinaSchool of Management, Beijing Institute of Technology, Beijing, ChinaSchool of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, ChinaCyber Finance Department, Postal Savings Bank of China, Beijing, ChinaThe system of scientific innovation can be characterized as a complex, multi-layered network of actors, their products and knowledge elements. Despite the progress that has been made, a more comprehensive understanding of the interactions and dynamics of this multi-layered network remains a significant challenge. This paper constructs a multilayer longitudinal network to abstract institutions, products and ideas of the scientific system, then identifies patterns and elucidates the mechanism through which actor collaboration and their knowledge transmission influence the innovation performance and network dynamics. Aside from fostering a collaborative network of institutions via co-authorship, fine-grained knowledge elements are extracted using KeyBERT from academic papers to build knowledge network layer. Empirical studies demonstrate that actor collaboration and their unique and diverse ideas have a positive impact on the performance of the research products. This paper also presents empirical evidence that the embeddedness of the actors, their ideas and features of their research products influence the network dynamics. This study gains a deeper understanding of the driving factors that impact the interactions and dynamics of the multi-layered scientific networks.https://www.frontiersin.org/articles/10.3389/fphy.2024.1492731/fullscientific innovationcomplex networknetwork dynamicsstochastic actor-oriented modelcollaboration networkknowledge network |
| spellingShingle | Yangyang Jia Hongshu Chen Jingkang Liu Xuefeng Wang Rui Guo Ximeng Wang Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance Frontiers in Physics scientific innovation complex network network dynamics stochastic actor-oriented model collaboration network knowledge network |
| title | Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance |
| title_full | Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance |
| title_fullStr | Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance |
| title_full_unstemmed | Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance |
| title_short | Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance |
| title_sort | exploring network dynamics in scientific innovation collaboration knowledge combination and innovative performance |
| topic | scientific innovation complex network network dynamics stochastic actor-oriented model collaboration network knowledge network |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2024.1492731/full |
| work_keys_str_mv | AT yangyangjia exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance AT hongshuchen exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance AT jingkangliu exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance AT xuefengwang exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance AT ruiguo exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance AT ximengwang exploringnetworkdynamicsinscientificinnovationcollaborationknowledgecombinationandinnovativeperformance |