A Holistic View of the Knowledge Life Cycle: The Knowledge Management Cycle (KMC) Model
Keywords:Keywords: Knowledge management, KM life cycle, KM framework, initiatives, technology, knowledge, knowledge assets, tacit, codified, encapsulated
AbstractAbstract: As more companies implement knowledge management (KM), they require a practical and coherent strategy and practice anchored in a valid and comprehensive KM life cycle model or framework. Using a knowledge‑based view, this paper aims to improve how firms conceptualize, strategize, and manage organizational knowledge. The paper opens with an analysis of organizational knowledge and knowledge assets. Appropriate conceptualization and partitioning of knowledge is required since the cost, benefit, and imitability of knowledge assets largely depend on their form. Subsequently, the paper provides a historical and chronological overview of some of the most influential KM life cycle models, based on their scholarly adoption and frequency of use by practitioners. Each represents an advance in the thinking concerning the KM life cycle and introduces valuable new elements to be considered in understanding how organizational knowledge is processed throughout its useful lifespan. Life cycle models examined include Wiig (1993), Meyer and Zack (1999), Bukowitz and Williams (1999), and McElroy (2003). Dalkirs (2005) integrated life cycle model and Heisigs (2009) examination of 160 KM frameworks are also reviewed for their contribution. Building on these models and prior work by Evans and Ali (2013), the Knowledge Management Cycle (KMC) model is proposed. Finally, sample KM initiatives, activities, and technologies are mapped to the seven non‑sequential KMC model phases (i.e., identify, store, share, use, learn, improve, and create) to illustrate its practical use. The main contribution of the KMC model is that it provides a holistic view of the knowledge life cycle, by building on previous life cycles models and Heisigs (2009) analysis of KM frameworks. It further extends previous models by including different knowledge forms, integrating the notion of second order or double loop learning, and associating some facilitating initiatives and technologies for each of its phases.
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