Predicting the Influence of Network Structure on Trust in Knowledge Communities: Addressing the Interconnectedness of Four Network Principles and Trust pp41-54
The goal of this paper is to explore the emergence of trusting relationships within Communities of Practice. It has been argued that trust can be viewed as an organizing principle (McEvily, Perrone, and Zaheer, 2003). However, the focus of this paper is on the view that trust is an essential pre‑condition for the sharing of knowledge. The goal of the paper is to discuss possible connections between social networking principles, network structure, and trust within Communities of Practice. This paper will define and subsequently analyze the concept of trust and develop arguments relating to the existence and strength of trusting relationships within Communities of Practice. The theoretical arguments propose relationships between the characteristics of trusting relationships and four network characteristics: homophily; closure; brokerage; and the small‑world problem. The general research question that underpins this paper is: To what extent do network principles determine the level of trust among members within a social network (i.e. a Community of Practice)? The analysis focuses on a specific type of social network which has been termed a Community of Practice. Communities of Practice have been argued to be critical elements in the creation, refinement and sharing of knowledge (Dugid, 2005; Wenger, 1998; Wenger, McDermott, and Snyder, 2002).
Keywords: network structure, trust, knowledge communities, knowledge sharing, homophily, closure, small worlds, brokerage
Abstract: 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). Dalkir’s (2005) integrated life cycle model and Heisig’s (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 Heisig’s (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.
Keywords: Keywords: Knowledge management, KM life cycle, KM framework, initiatives, technology, knowledge, knowledge assets, tacit, codified, encapsulated