A STUDY TO UNDERSTAND OUT LEADERSHIP IN THE USE OF TECHNIQUES FOR KNOWLEDGE MANAGEMENT IN THE KINGDOM OF CHINA

Abstract

Against the background of the enabling setting of several developing technologies, led by Big Data, this research examines the variance of knowledge management activities, information sharing, and knowledge production, across different industries within the Greater China area. To abbreviate the enabling environment, researchers have come up with the acronym “Big Data Context” (BDC). In the BDC, this study uses quantitative methodologies to delve into the development and exchange of organisational knowledge. A quantitative technique was used in this investigation. The researchers recorded field notes and conducted 24 semi-structured interviews with their informants. Second, using a thorough industry-scale survey, a quantitative method called structural equation modelling (SEM) was used to assess the dependability of the model’s primary structure. The constructs as variables have a subtle but comprehensive and mostly beneficial effect on knowledge sharing and production in the BDC/KM environment. Using the constructs as variables, the SEM method confirmed that peripheral contributors to knowledge sharing and core mediators for knowledge creation were the substantive determinants. Several new technologies are shaping the Big Data context in the China area, according to the current substantive theory. Having Big Data at its heart greatly influences the dissemination and generation of new information. According to the results, BDC’s potential should not be ignored as a component of the knowledge management system.