Publication | Closed Access
Knowledge management driven firm performance: the roles of business process capabilities and organizational learning
249
Citations
92
References
2014
Year
Firm PerformanceBusiness IntelligenceKnowledge CreationOrganizational BehaviorKnowledge Management StrategyLearning OrganizationManagement DevelopmentManagementKnowledge ResourcesManagerial CapabilityFair KnowledgeStrategyStrategic ManagementDynamic CapabilityOrganizational CommunicationKnowledge SharingBusiness Process CapabilitiesBusinessBusiness StrategyKnowledge Management
Purpose – This paper aims at defining a model to properly evaluate knowledge management (KM) value. Empirical studies have found little or no improvement in organizational performance despite large KM investments. Design/methodology/approach – The KM-driven performances are rooted in knowledge resources based on the knowledge-based view. Further, the KM-driven performances are mediated by business process capabilities. Organizational learning is critically complementary to KM for being a moderator to knowledge resources. A model was proposed for defining the performance with the relationships between these issues. A survey was conducted for collecting empirical data. Partial least squares was used for path analysis. Findings – Knowledge resources lay a foundation on the KM-driven performance through the mediator of business process capabilities. Specifically, knowledge assets and process capabilities are two different but relevant drivers in a value creation process. The findings particularly provide evidence to explain the knowledge-based view and the mediator of business process capabilities. Practical implications – While an organization owns important knowledge resources in the industry, it should dedicate its effort to the improvement of business process capabilities for well-achieving final performance. The KM-driven performance should be considered for both financial and non-financial indicators in a complementary manner. Originality/value – Extant theories may provide inadequate methods to evaluate KM-enabled performance. This study attempted to define an effective model for this issue. This model empirically demonstrated its capability to work on this issue.
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