Linkage between knowledge management and manufacturing performance: a structural equation modeling approach

• Main Authors: Li, Pin Tan, Kuan, Yew Wong
• Format: Article
• Published: Emerald Group Holdings Ltd. 2015
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/58482/; http://dx.doi.org/10.1108/JKM-11-2014-0487
• Institution: Universiti Teknologi Malaysia

Purpose - The purpose of this study is to examine the effect of knowledge management (KM) on manufacturing performance and the relationships among three KM measures, namely, knowledge resources, KM processes and KM factors. It also determined a collective set of KM metrics based on these three measures. Design/methodology/approach - Data were collected using questionnaires posted to 700 manufacturing companies in Malaysia from which 206 usable responses were obtained. The analysis and hypotheses testing were implemented using structural equation modeling. Findings - The results showed that the constructs of knowledge resources, KM processes and KM factors have significant and direct effects on manufacturing performance. In terms of covariance, the results also indicated that these three constructs were correlated with each other. Research limitations/implications - The sample over-represented large firms and the study was a cross-sectional approach that collected data at a single point in time. Practical implications - The results obtained would help managers to better understand the linkage between KM and manufacturing performance. They could use the results to manipulate their KM practices to improve their manufacturing performance. The proposed set of KM metrics could also act as a common language and provide directions for future research. Originality/value - This paper is one of the first empirical studies that has examined the relationship between KM and manufacturing performance. Furthermore, it has investigated the relationships among knowledge resources, KM processes and KM factors.