Scope, Strategy and Structure: The Dynamics of Knowledge Networks in Medicine

The objective of this paper is to analyse the dynamics of networks in which new knowledge emerges and through which it is exchanged. Our conjecture is that the structure of a network cannot be divorced from the dynamics of the knowledge underpinning its activities. In so doing we look beyond studies based on the assumption of exogenous networks and delve into the mechanisms that stimulate their creation and transformation. In the first part the paper adopts a functional perspective and views networks as constructs aimed at the coordination of knowledge; accordingly, network structure is an emerging property that reflects the employment of an agreed strategy to achieve a collective scope. In the second part these themes are articulated in relation to the dynamics of medical innovation and enriched by an empirical study on the long-term evolution of medical research in Ophthalmology. This exercise highlights the connection between changes in scientific and practical knowledge and the reconfigurations of the epistemic network over a forty-year period. By mapping different network structures we capture variety in the gateways of knowledge creation – that is, the network participants – as well as in the pathways – that is, the inter-organisational collaborations. Our goal is to analyse how these patterns of interaction emerge and transform over time.Innovation, Network analysis, Inter-organizational Relationships

Knowledge, understanding and the dynamics of medical innovation

This paper investigates the processes by which scientific knowledge is created and legitimized. It focuses on scientific developments in a branch of medicine and explores the pathways through which the growth of knowledge enables advances in medical science and in clinical practice. This work draws conceptually on evolutionary approaches to technological change. The empirical part presents a longitudinal analysis of a database of scientific publications in the field of ophthalmology over a period of 50 years. Such an exercise allows us to identify pathways of shared understanding on a disease area, and to map out distinctive trajectories followed by the ophthalmology research community. The paper also contributes to general understanding of the innovation process by supporting the notion that knowledge coordination is a distributed process that cuts across and connects complementary areas of expertise.

Scope, Strategy and Structure: The Dynamics of Knowledge Networks in Medicine

The objective of this paper is to analyse the dynamics of networks in which new knowledge emerges and through which it is exchanged. Our conjecture is that the structure of a network cannot be divorced from the dynamics of the knowledge underpinning its activities. In so doing we look beyond studies based on the assumption of exogenous networks and delve into the mechanisms that stimulate their creation and transformation. In the first part the paper adopts a functional perspective and views networks as constructs aimed at the coordination of knowledge; accordingly, network structure is an emerging property that reflects the employment of an agreed strategy to achieve a collective scope. In the second part these themes are articulated in relation to the dynamics of medical innovation and enriched by an empirical study on the long-term evolution of medical research in Ophthalmology. This exercise highlights the connection between changes in scientific and practical knowledge and the reconfigurations of the epistemic network over a forty-year period. By mapping different network structures we capture variety in the gateways of knowledge creation – that is, the network participants – as well as in the pathways – that is, the inter-organisational collaborations. Our goal is to analyse how these patterns of interaction emerge and transform over time

Knowledge, understanding and the dynamics of medical innovation

This paper investigates the processes by which scientific knowledge is created and legitimized. It focuses on scientific developments in a branch of medicine and explores the pathways through which the growth of knowledge enables advances in medical science and in clinical practice. This work draws conceptually on evolutionary approaches to technological change. The empirical part presents a longitudinal analysis of a database of scientific publications in the field of ophthalmology over a period of 50 years. Such an exercise allows us to identify pathways of shared understanding on a disease area, and to map out distinctive trajectories followed by the ophthalmology research community. The paper also contributes to general understanding of the innovation process by supporting the notion that knowledge coordination is a distributed process that cuts across and connects complementary areas of expertise

Scope, Strategy and Structure: The Dynamics of Knowledge Networks in Medicine

The objective of this paper is to analyse the dynamics of networks in which new knowledge emerges and through which it is exchanged. Our conjecture is that the structure of a network cannot be divorced from the dynamics of the knowledge underpinning its activities. In so doing we look beyond studies based on the assumption of exogenous networks and delve into the mechanisms that stimulate their creation and transformation. In the first part the paper adopts a functional perspective and views networks as constructs aimed at the coordination of knowledge; accordingly, network structure is an emerging property that reflects the employment of an agreed strategy to achieve a collective scope. In the second part these themes are articulated in relation to the dynamics of medical innovation and enriched by an empirical study on the long-term evolution of medical research in Ophthalmology. This exercise highlights the connection between changes in scientific and practical knowledge and the reconfigurations of the epistemic network over a forty-year period. By mapping different network structures we capture variety in the gateways of knowledge creation – that is, the network participants – as well as in the pathways – that is, the inter-organisational collaborations. Our goal is to analyse how these patterns of interaction emerge and transform over time

Measuring the contribution of higher education to innovation capacity in the EU:Study

There has been a massive expansion of higher education in recent decades as part of attempts to create workforces with the skills to be able to compete successfully in the context of the knowledge based economy. At the same time, there is widespread unrest that universities are failing to respond to these new demands and are continuing to act as ‘ivory towers’ outside of rather than driving forward society. A key challenge for European policy-makers is therefore distinguishing the extent to which universities are realising their potential to contribute to the emergence of the knowledge-based economy. In this working paper we try to provide evidence on the key factors determining the contribution of higher education institutions (HEI) to innovation capabilities and expand the understanding of this contribution beyond traditional measures of the role of HEI on innovation capabilities. In this sense, we focus on the relevance of spill-overs through knowledge-transfer mechanisms as well as through human capital mechanisms

Measuring the contribution of higher education to innovation capacity in the EU

The general goals of the study include the provision of evidence on the key factors determining the contribution of higher education institutions (HEIs) to innovation capabilities and expand the understanding of this contribution beyond traditional measures of the role of HEI on innovation capabilities. In this context, the general objective of the study could be verbalised as “to develop a more comprehensive model of the contribution of higher education to innovation capacity”. This objective has been operationalised into the following five specific objectives which define in detail the purpose of the study:  Specific Objective 1: Completion of a comprehensive literature review of existing means and methodologies used for capturing, interpreting and also applying data and evidence related to the contribution of higher education systems to innovation capacity;  Specific Objective 2: Critical assessment of the existing literature, including an identification of gaps and an assessment of the merits of different approaches used;  Specific Objective 3: Development of a new approach, that provides an alternative set of indicators to measure the contribution of HEIs to innovation capacity;  Specific Objective 4: Implementation of the prototype set of alternative metrics;  Specific Objective 5: Discussion of the feasibility of developing new proxies or metrics for capturing the contribution of higher education systems to innovation capacity at the EU level. In general, the objective of the project and its research tools is therefore to propose a set of indicators for future measurements of the innovation impacts of HE that is validated through the opinions of the different stakeholders in the field (through interviews, case studies and a survey)

Measuring the contribution of higher education to innovation capacity in the EU. Executive Summary

There has been a massive expansion of higher education in recent decades as part of attempts to create workforces with the skills to be able to compete successfully in the context of the knowledge based economy. This emerging context demands new kinds of skills and approaches from workers to feed into industries that are evolving rapidly. Economic strength in the knowledge-based economy is driven by innovation, taking existing resources and assets and using them to do new things better and increase overall welfare levels. Whilst innovation is necessary across government, business, and civil society, universities are at the heart of attempts to improve the overall knowledge capital endowments that provide the feedstock for innovation as well as a proving ground for future innovators. At the same time, there is widespread unrest that universities are failing to respond to these new demands and are continuing to act as ‘ivory towers’ outside of rather than driving forward society (Galan-Muros, 2016). Particular concern lies on perceptions that universities have tended to expand their existing activities rather than to create new courses, pedagogies, and learning environments that best meet these needs. Where universities contribute effectively to innovation, then they can create whole new industries and sectors, and transform the fortunes of particular places. But at the moment, these conflicting narratives make it hard for policy-makers to determine whether universities (and indeed, which kinds of universities) are a boost to or a drag upon innovation capacities. A key challenge for European policy-makers is therefore distinguishing the extent to which universities are realising their potential to contribute to the emergence of the knowledge-based economy. By distinguishing which institutions are and are not realising this potential, policy-makers can developed a more nuanced set of engagement stimuli that can help to maximise this contribution and optimise the returns that European societies receive for their substantial public investments in higher education. This means that are providing the necessary education and knowledge base to deliver the ambitions of Europe 2020 and support Europe’s transition towards a successful, just and sustainable economy. This requires dealing with the uncertainty of the extent to which universities’ contribute to supporting the development of the emerging knowledge economy. Here we define ‘innovation’ as the result of the set of activities by which different kinds of knowledge are combined to create solutions and interventions to solve problems, ultimately making society a better place (a form of Schumpeterian perspective). Those societal improvements may be through: (a) raising competitiveness and creating new markets and sectors, (b) improving the delivery of public services, particularly to vulnerable social groups, or (c) reducing our environmental impacts. We seek to understand the extent to which universities are supporting ‘innovation’ as here defined to distinguish between good and bad performances, as the first step in a process by which policy-makers actively intervene to improve the performance of universities overall