The Evolution of the Communities of Practice Approach:Toward Knowledgeability in a Landscape of Practice—An Interview with Etienne Wenger-Trayner

Since its introduction by Jean Lave and Etienne Wenger in Situated Learning: Legitimate Peripheral Participation in 1991, the concept of communities of practice has been widely adopted by researchers and practitioners in different fields. This has been accompanied by continuous expansion and development of the theory behind the concept. In this interview, Professor Etienne Wenger-Trayner discusses the evolution of the theory of communities of practice in his own work over the past two decades. He talks about the origins of communities of practice as a theoretical approach, identifies three phases through which this theory has evolved, and reflects on his professional trajectory as a theorist and consultant. Using his career as an example, Wenger-Trayner elaborates on the notion of knowledgeability as a relationship individuals establish with respect to a landscape of practice that makes them recognizable as legitimate actors in complex social systems

The ‘disconnect’ between science and innovation within Scotland

The science base in Scotland has traditionally been strong, with world- leading universities driving the development of science – a fact that is shown in a number of studies (Scottish Science Advisory Council, 2009)1. The contribution of the science community has been significant in the past and current trends suggest that Scotland is geared to produce high-quality research in the future. Particularly significant is the contribution of scientists to the fields of agriculture, biological sciences, biochemistry, and immunology, where Scotland stands amongst the top five countries in the world, in terms of publication numbers per million head of population.However, data suggests that this excellence in the science base has not translated well into innovation. One of various indicators of poor translation is the patent record, which is relatively poor for Scotland (Figure 1). For instance, with 68.5 patents per million head of population, Scotland generates four times fewer patents than Finland (281.5 patents per million head), significantly fewer than countries like Sweden, Japan, Germany and US (294, 226, 209, and 132.5 patents per million, respectively) and even fewer than the UK average (with 84 patents per million)

Development of absorptive capacity over time and across boundaries: The case of R&D consortia

Absorptive capacity (AC) has been identified as the ability of firms to acquire, assimilate, and apply external knowledge, and thus as a pre-condition for learning from knowledge environment. However, extant literature has focused on AC as (1) a static and (2) a firm-centred concept. In particular, there is little conceptual framing and empirical evidence of how AC develops over time and across boundaries. Taking R&D consortia as the unit of analysis and based on insights from three in-depth case studies of collaborative R&D, our contribution is a framework for AC development over time and across inter-organizational, intra-organizational, and practice boundaries at different stages of collaboration in R&D consortia. Using this framework, we identify a set of mechanisms which enable the development of AC and we discuss the preconditions for these mechanisms. For R&D managers, our research implies that in order to enhance effectiveness of knowledge transfer and learning in R&D consortia they need to develop a strategy that (1) supports learning and AC development throughout the whole cycle of the collaboration, not only by focusing on intra-firm capabilities, but in particular by providing flexible interfaces for overcoming a variety of interaction and learning boundaries between heterogeneous R&D partners, and (2) enables the integration of created and acquired knowledge within the organization once the collaboration is over

Understanding Communities of Practice:Taking Stock and Moving Forward

This paper provides a comprehensive, integrative conceptual review of work on communities of practice (CoPs), defined broadly as groups of people bound together by a common activity, shared expertise, a passion for a joint enterprise, and a desire to learn or improve their practice. We identify three divergent views on the intended purposes and expected effects of CoPs: as mechanisms for fostering learning and knowledge-sharing, as sources of innovation, and as mechanisms to defend interests and perpetuate control over expertise domains. We use these different lenses to make sense of the ways CoPs are conceptualized and to review scholarly work on this topic. We argue that current debate on the future of work and new methodological developments are challenging the received wisdom on CoPs and offer research opportunities and new conceptual combinations. We argue also that the interaction between the lenses and between CoP theory and adjacent literatures might result in new theory and conceptualizations

Algorithmic routines and dynamic inertia: How organizations avoid adapting to changes in the environment

Organizations often fail to adequately respond to substantive changes in the environment, despite widespread implementation of algorithmic routines designed to enable dynamic adaptation. We develop a theory to explain this phenomenon based on an inductive, historical case study of the credit rating routine of Moody’s, an organization that failed to adapt to substantial changes in its environment leading up to the 2008 financial crisis. Our analysis of changes to the firm’s algorithmic credit rating routine reveals mechanisms whereby organizations dynamically produce inertia by taking actions that fail to produce significant change. Dynamic inertia occurs through bounded retheorization of the algorithmic model, sedimentation of assumptions about inputs to the algorithmic model, simulation of the unknown future, and specialized compartmentalization. We enable a better understanding of organizational inertia as a sociomaterial phenomenon by theorizing how—despite using algorithmic routines to improve organizational agility—organizations dynamically produce inertia, with potentially serious adverse consequences

Algorithmic routines and dynamic inertia: How organizations avoid adapting to changes in the environment

Organizations often fail to adequately respond to substantive changes in the environment, despite widespread implementation of algorithmic routines designed to enable dynamic adaptation. We develop a theory to explain this phenomenon based on an inductive, historical case study of the credit rating routine of Moody’s, an organization that failed to adapt to substantial changes in its environment leading up to the 2008 financial crisis. Our analysis of changes to the firm’s algorithmic credit rating routine reveals mechanisms whereby organizations dynamically produce inertia by taking actions that fail to produce significant change. Dynamic inertia occurs through bounded retheorization of the algorithmic model, sedimentation of assumptions about inputs to the algorithmic model, simulation of the unknown future, and specialized compartmentalization. We enable a better understanding of organizational inertia as a sociomaterial phenomenon by theorizing how—despite using algorithmic routines to improve organizational agility—organizations dynamically produce inertia, with potentially serious adverse consequences