The effect of teacher-student collaboration on academic innovation in universities: an exploration from the perspective of collaborative process

Dr Wenhui Pan is Lecturer in the Department of Economics and Management, Xi’an University of Posts and Telecommunications, Xi’an, Shaanxi Province, China. Her research areas cover knowledge discovery and management, network analysis and empirical research, specifically how network structure affects knowledge sharing. Wenhui Pan focuses on scientific network, especially the relationship between network structure and research innovation to discover how scholars select their research topics and team members to increase innovation. In last years, she has published four SSCI papers in Technology Analysis and Strategic Management, Evaluation and Program Planning. 1. Wenhui Pan, Pengwei Zhao, Xianfeng Ding (2019), The effects of network structure on research innovation: an analysis from a content perspective using the data of R&D funding, Technology Analysis and Strategic Management, 31(12):1430-1446. (SSCI), 000471393700001. 2. Wenhui Pan, Pengwei Zhao, Chunxiu Qin, Xianfeng Ding (2020), How do new members affect the relationship between principal investigator’s network position and academic output of granted fund? Evaluation and Program Planning, Volume 78:101744 (SSCI), 000501619500011. 3. Wenhui Pan, Pengwei Zhao, Xianfeng Ding (2022). How to design collaboration strategies in high-output and low-output networks: considering the role of internal social capital, Technology Analysis and Strategic Management (SSCI), Online.000686403200001. 4. Wenhui Pan (2022), Can high-interest similarity really promote the efficiency of technological collaboration? An analysis of time and space dimensions, Technology Analysis and Strategic Management (SSCI), Online.000814612800001.

Zhenxing Liu has focused on technology analysis for several years and has published several papers which are indexed in SCI database. In particular, he is adept at using empirical analysis to explore technological output and predict technological trends.