IMPACT OF KNOWLEDGE MANAGEMENT ON SUPPLY CHAIN PERFORMANCE IN MANUFACTURING INDUSTRIES

Abstract

Knowledge is nowadays being regarded as the most important strategic resource in organizations, and the management of this knowledge is considered critical to organizational success. If organizations have to take strategic advantage of the knowledge they possess, they have to understand how the knowledge is created, shared, and used within and across the organizations. More and more organizations are attempting to set up knowledge management (KM) systems and practices to more effectively use the knowledge they have and numerous publications have discussed the importance of knowledge in organizations. Even so, there is much to learn and understand about how knowledge is created, shared, and used along the supply chain. In addition, manufacturing industries tend to focus specifically on their core business functions and way out more and more to outsourcing several of their non-core functions. In turn, this practice has lead to larger and more complex supply chains. The successful management of these chains is one of the primary objectives for manufacturing organizations to sustain competitiveness (Haq and Kannan, 2006). Therefore, value addition through supply chain management (SCM) has become a potentially valuable way of securing competitive advantage and improving organizational performance, as it is believed nowadays that competition is no longer between organizations, but among their supply chains. The integration of supply chains not only focuses on tangible resources and assets, but also on intangibles such as knowledge. Therefore, it can be emphasized that knowledge is becoming the primary resource capable of offering competitive advantage and continued growth for supply chain partners. Hence, the effective management of knowledge assets has become a top priority in a supply chain. However, the extant literatures have not specifically focused on empirically elaborating the impact of KM processes and SCM practices on supply chain performance. Looking to this gap in the literature, this study is focused on investigating the relationship among the measures of KM processes, SCM practices and supply chain performance in the context of manufacturing industries in India. Data are collected with the use of both random and non-random samples of 357 respondents belonging to top and middle level management executives in the area of supply chain management and knowledge management. The database consists of valid responses of 357 respondents from 88 manufacturing firms spread over 11 states in India. For data collection, a structured questionnaire comprising of 66 items using a 5-point Likert scale is developed. The kinds of validity of the measures in particular content-related (face and content validity), and construct-related (convergent and discriminant validity) have been thoroughly analyzed. The reliability of the entire measure is found to be satisfactory. The statistical analyses such as correlation analysis, exploratory factor analysis, and simple and hierarchical regression analysis were performed with the help of SPSS 15.0 to achieve study objectives, also confirmatory factor analysis was carried out with the help of LISREL 8.7 package to investigate the role of KM processes and supply chain practices in their relationship with the supply chain performance measures. The results of these analyses show that among the variables of firm's characteristics, firm's position in the supply chain is positively correlated with supply chain flexibility performance. In addition to this, firm's position in supply chain has substantial positive association with all factors ofKM process and SCM practices. Firm's size in terms of employee strength has significant positive correlation with overall KM processes and SCM practices. Importantly, all the studying variables show a significant positive relationship with constructs of supply chain performance. The findings of hierarchical regression analysis (HIM.) supported hypotheses related with objective 7. In general, the mediation implies acausal hypothetical relationship in which an independent variable causes a mediator that causes a dependent variable. The HRA results observed that SCM practice factors supply chain integration (SCI), Just-In-Time capabilities (JIT), and customer service management (CSM) significantly predicted supply chain flexibility performance. The mediators knowledge acquisition (KA) and knowledge protection (KP) cause for the diminishing effect of supply chain practices on supply chain flexibility performance. The main effects of SCM practice factors supply chain information sharing (IS), JIT, and CSM significantly predicted supply chain resource performance while knowledge application (KAP) and KP are found to mediate between SCM practices and supply chain resource performance. The effects of SCM practice factors SCI, JIT, and CSM significantly predicted supply chain output performance while KM processes, KA and KAP, act as mediators in the relationship between supply chain practices and output performance. Thus, these findings provide strong support for concerned hypotheses. Confirmatory factor analysis is conducted to assess the model fit with collected data and prove the developed models as statistically accepted models. This analysis is carried out for the model of (1) predictors of KM processes, supply chain practices and supply chain performance (2) mediating and moderating role of KM process factors in between SCM practices and supply chain performance, and (3) mediating role of SCM practices factors in between KM processes and supply chain performance. In line with Hair et al. (1998) and Joreskog and Sorbom (1993) the goodness-of-fit statistics of the analyses indicated that each model except moderating roles of KM processes and SCM practices (that are partially supported) are well confirmed with the data.