Journal of Systems Engineering and Electronics ›› 2026, Vol. 37 ›› Issue (1): 257-271.doi: 10.23919/JSEE.2026.000022

• SYSTEMS ENGINEERING • Previous Articles     Next Articles

Performance improvement method of new R&D institutions considering Bayesian network

Jianjun ZHU1(), Lin JIANG1,2,*()   

  1. 1College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    2School of Information Engineering, Yancheng Teachers University, Yancheng 224000, China
  • Received:2021-07-21 Accepted:2026-01-06 Online:2026-02-18 Published:2026-03-09
  • Contact: Lin JIANG E-mail:zhujianjun@nuaa.edu.cn;42952775@qq.com
  • About author:
    ZHU Jianjun was born in 1976. He received his Ph.D. degree from Northeastern University in 2005. He is a professor in Nanjing University of Aeronautics and Astronautics. His research interests are complex system decision-making and supply chain research. E-mail: zhujianjun@nuaa.edu.cn

    JIANG Lin was born in 1982. She received her M.S. degree from Hohai University in 2009 and Ph.D. degree from Nanjing University of Aeronautics and Astronautics in 2022. She is an associate researcher in Yancheng Teachers University. Her research interests are talent management and performance management. E-mail: 42952775@qq.com
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (72071106), Jiangsu Provincial Social Science Fund (23EYA001), Jiangsu Provincial Education Science Planning Fund (B-a/2024/08), and Jiangsu Higher Education Association Fund (24FYHLX090).

Abstract:

A performance improvement model of research and development (R&D) institutions based on evolutionary game and Bayesian network is proposed. First, the nature and performance factors of new R&D institutions are systematically analyzed, the appropriate factor model is found, and the sharing of performance benefits between institutions and employees, the change in distribution proportion, and the risk of institutional improvement and employee cooperation are considered. Second, based on the mechanism improvement and employee cooperation, the payment matrix is given and evolutionary game analysis is carried out to obtain a stable and balanced institutional improvement probability and employee cooperation probability. These two probability values are substituted into the Bayesian network model of performance improvement of new R&D institutions, and the posterior probability of performance improvement is predicted by Bayesian network reasoning and diagnosis to find effective improvement measures. Finally, practical case analysis is given to verify the effectiveness and practicability of the proposed method.

Key words: new research and development (R&D) institution, performance improvement, evolutionary game, Bayesian network, conditional probability