Jiuling Xiao

Dr. Jiuling Xiao


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 June 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
JXJiuling Xiao
Jiuling Xiao
YBYuting Bao
Yuting Bao
JWJiankang Wang
Jiankang Wang
HYHaiyun Yu
Haiyun Yu
ZMZhenzhong Ma
Zhenzhong Ma
LJLei Jing
Lei Jing
Knowledge sharing plays an important role in promoting innovation and helping improve R&D team performance in the digital age. Based on the evolutionary game theory, this study develops an evolutionary game model of knowledge sharing in R&D teams in order to explore its system evolution path, the evolutionary stability strategy, and the influencing mechanism in knowledge sharing. Then using a simulation model, this study examines the dynamic evolution process of knowledge sharing within R&D teams. The results show that the effectiveness of knowledge sharing in the R&D teams can be promoted by R&D team members’ cognitive ability, knowledge absorption ability, knowledge transformation ability, knowledge innovation ability, and the degree of knowledge complementarity within teams. The simulation results further show that reducing the environmental risk can also effectively improve R&D teams’ innovation performance. The findings of this study thus provide evidence for knowledge sharing as an important route to sustainable development.

6 August 2020 in Sustainability
Verified
Journal Article
Open access
PDF file
HTHouxing Tang
Houxing Tang
ZMZhenzhong Ma
Zhenzhong Ma
JXJiuling Xiao
Jiuling Xiao
LXLei Xiao
Lei Xiao
Knowledge management has become increasingly important in the era of knowledge economy. This study explores what is an optimal knowledge network for more efficient knowledge diffusion among strategic partners in order to provide insights on sustainable enterprises and a more knowledge-efficient innovation ecosystem. Based on simulated analyses of the efficiency of knowledge network models, including regular network, random network, and small world network, this study shows that a random knowledge network is more efficient for knowledge diffusion when a mixture knowledge trade rule is used. This study thus helps identify which knowledge networks facilitate knowledge exchange among collaborative partners for sustainable knowledge management. Management practitioners and policymakers can use the findings to design more appropriate knowledge exchange networks to improve the efficiency of knowledge diffusion in an innovation ecosystem.