AUTHOR=Le Chengyi , Li Wenxin 

TITLE=Analysis on the Influence Path of User Knowledge Withholding in Virtual Academic Community – Based on Structural Equation Method-Artificial Neural Network Model

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.764857

DOI=10.3389/fpsyg.2022.764857

ISSN=1664-1078

ABSTRACT=The large number of diving users and the prominent phenomenon of knowledge withholding have become the key problems hindering the development of online and offline organizations, and also the frontier theme in the field of knowledge management. In order to explore the influence path of online virtual academic community users' knowledge withholding, based on the relevant theories of sociology and psychology, this paper proposed to build a theoretical model of knowledge withholding from the two dimensions of enabling and inhibiting. By collecting the user data of four virtual academic communities of China, this paper used a method of combining structural equation model with cross layer neural network for empirical analysis. The results showed that the inhibition of community privacy protection on user knowledge withholding was significantly improved. In the enabling dimension, knowledge power was the main reason to promote users to form knowledge psychological ownership, and then affected users' knowledge withholding. The goodness of fit in the model could be improved by using the cross layer connected neural network model to update the path coefficient of the structural equation model. This research has certain guiding significance for improving the knowledge withholding of users in virtual academic community and creating a good academic exchange atmosphere.