A sense-making based model for effective decision making in implementing knowledge management within SMEs in Wuhan, China

• Main Author: Liu, Yao
• Format: Thesis
• Published: 2011
• Subjects: HD Industries. Land use. Labor; HD28 Management. Industrial Management
• Online Access: http://umpir.ump.edu.my/id/eprint/37062/

In today’s fast changing globalization, Small and Medium Enterprises (SMEs) around the globe need a very innovative and creative strategy and approach in order to achieve sustainable competitive advantages. Towards this end, knowledge management (KM) is widely believed or potentially utilized as a realizing tool by maximizing the benefits from their knowledge as well as other resources. Nonetheless, SMEs’ KM implementation (KMI) has been so far demonstrating poor outcomes resulted from various unsupportive aspects such as management, culture, technology, infrastructure, measure, KM process control and so on. Thus, given the limited availability of resources and conditions, it appears more significant for SMEs to effectively make KMI decisions through a rational process, which is exactly covered by sense making (SM) methodology. Thus, aimed at facilitating SMEs in building KM, this study established a SM-based KM evaluation model, by partitioning KMI into four inter-connected modules of sense making activities, including Environmental Analysis (EA), KM Activity Planning (KMAP), and KMI Decision Making (KMIDM) as independent variables and KM Measurement Index (KMMI) as dependent variable. The data was collected from 400 SMEs in Wuhan City, China, by mainly employing two-level survey questionnaires, along with some interviews, discussions and observations. The empirical analysis was systematically conducted from verifying the validity of the data, the constructs as well as the proposed measuring system, through normality tests, factor analysis, reliability analysis and correlation analysis accordingly. Series of regressions were conducted from both linear and non-linear perspectives, with moderator and mediator effects detected through hierarchical multiple regression approach. The utilized statistic software includes SPSS 16.0, Eviews 6.0 and Matlab 10.0. The derived results reveal the crucial factors that deserve more attention in SMEs’ KMI; the relationships amongst the tested factors with the best model suggested and the latent mechanisms that how SM based KM activities influence KM performance (KMP) and KM effectiveness (KME). More importantly, managerial implications are correspondingly provided especially for the Chinese SMEs from both micro and macro perspectives. The significance of the study is mainly in: i) the enrichment of the theory applications of both SM and KM; ii) the combination of both quantitative and qualitative methods thus providing more reliable results; iii) the distinguishing of KMP and KME with their correlations further investigated; iv) the investigations of both linear and non-linear relationships; v) the coverage of KMI in Chinese SMEs where KM is new and KMI is inadequately touched.