Dominant cognitive frames and the innovative power of social networks

In this paper, we illustrate the link between social network structures, dominant cognitive frames on network purpose and the innovative power of a network, through a mixed-method comparative analysis of two Knowledge Translation Networks (KTNs)in the English National Health Service (NHS). Our findings illustrate several challenges for networked forms of organization linked to different manifestations of social networks (centralized/decentralized) and dominant cognitive frames (polarizing/loosely clustered). Our paper contributes a better understanding of how dominant frames on network purpose emerge alongside the development of network structure itself, and explores how this interplay between dominant frames and social networks impacts upon the collaborative work that supports the networks’ innovative power

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

<p>Abstract</p> <p>Background</p> <p>Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions.</p> <p>Objectives</p> <p>Our specific aims include: To collect social network data among staff in two long-term care (LTC) facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports.</p> <p>Methods and design</p> <p>In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports.</p> <p>Discussion</p> <p>This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building theory to design such interventions.</p

What is Social Network Analysis?

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. This book introduces the non-specialist reader to the principal ideas, nature and purpose of social network analysis. Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals. Social network theory maps these relationships between individual actors. Though relatively new on the scene it has become hugely influential across the social sciences. Assuming no prior knowledge of quantitative sociology, this book presents the key ideas in context through examples and illustrations. Using a structured approach to understanding work in this area, John Scott signposts further reading and online sources so readers can develop their knowledge and skills to become practitioners of this research method. A series of Frequently Asked Questions takes the reader through the main objections raised against social network analysis and answers the various queries that will come up once the reader has worked their way through the book

Social network analysis: a primer on engaging communities on climate adaptation in New South Wales, Australia

A network is a group or system of interconnected people or things. Social networks connect people. Those connections provide advantages to members of the network through access to private information, diverse skills and power, which makes the understanding of networks important for the formulation and communication of policy. The Adaptive Communities Node used a network analysis methodology to understand the formal and informal knowledge channels that communicate climate change adaptation policy throughout regional communities (Harman et al, 2016; Harman et al 2015a; Harman et al 2015b). The results of case studies in these communities (centred on Shoalhaven, Bega and Orange) have been published through the UTS:ISF NSW Adaptation Research Hub (https://www.uts.edu.au/research-and-teaching/our-research/institute-sustainable-futures/our-research/climate-change/nsw). This primer serves as a companion document to those reports

UNDERSTANDING INDIVIDUAL LEVEL ERP ASSIMILATION FROM A SOCIAL NETWORK PERSPECTIVE: A MULTI-CASE STUDY

Prior research on ERP assimilation has primarily focused on influntial factors at the organizational level. In this study, we attempt to extend our understanding of individual level ERP assimilation from the perspective of social network theory. We designed a multi-case study to explore the relations between ERP users´ social networks and their levels of ERP assimilation based on the three dimensions of the social networks. We gathered data through interviews with 26 ERP users at different levels in five companies. Qualitative analysis was used to understand the effects of social networks and individual interactive learning. We found that user social networks play a significant role in individual level ERP assimilation through interactive learning behaviours among users. We also found five key factors that facilitate users´ assimilation of ERP knowledge: homogeneity (age, position and rank), tie content (instrumental and expressive ties), tie strength, external ties, and centrality. Our research has significant implications for managing assimilation of ERP systems and improving users´ ERP assimilation level in organizations

Inter-organisational knowledge sharing by owners and managers of tourism and hospitality businesses of the Bournemouth, Poole and Christchurch conurbation, United Kingdom: an analysis of the motives, information content and networking.

This research study relates to knowledge management within the tourism sector and makes a contribution to the subject matter of inter-organisational knowledge sharing. The tourism sector has been slow to adopt the principles of knowledge management (Cooper, 2006; Cooper and Sheldon, 2010) and there has been focus on knowledge transfer (Shaw and Williams, 2009) rather than on knowledge sharing. Knowledge sharing is a social practice. This research study makes a contribution towards understanding the motives, information content and networking practices of inter-organisational knowledge sharing in the tourism sector. Theoretical contributions have been made which include: (1) the choice of a model which can be used to show knowledge sharing activities, the knowledge creation theory (Nonaka and Toyama, 2003) and relating the concept of information richness with the I-Space concept (Boisot, 1998); (2) a review and synthesis of a body of social network related theories in regard to embeddedness, structural influence and the innovative characteristics of social networks; (3) an explanation of the systemic features of shared knowledge through social networks as supported by systems, social systems and structuration theories; (4) the integration of theories and concepts regarding knowledge sharing and social networks with a view to better understanding the inter-organisational knowledge sharing practices of tourism businesses. The research approach combined both attribute and relational data in the same piece of work. Data were collected using a structured questionnaire and survey method. Interorganisational knowledge sharing relationships were mapped using social network analytical techniques (Wasserman and Faust, 1994). Data were analysed using frequencies, central tendency, inferential, Principal Components Analysis (PCA) and social network measurements.Empirical contributions were revealed through the discovery of why, how and what business people benefited from, overall and differently, and the examination of the different types of networking practices. As a result, the initial conceptual framework was revised and highlights several knowledge management concepts including: knowledge domain, knowledge specialists, knowledge diffusion, knowledge scanning, knowledge acquisition and knowledge dissemination. Motives were associated with two constructs: Cl) social network; and (2) knowledge sharing, and these components enable and facilitate interorganisational knowledge sharing practices within tourism destinations. Information content and networking were distinguished, network outcomes determined and structural processes measured in terms of embeddedness, structural influence and innovation regarding their potential knowledge sharing capability

Policy-driven EU Research Networks: Impact on the Greek S&T System

This paper focuses on the impact of EU-funded collaborative research networks at a national level using a combined method approach, social network analysis and in-depth case study work. First, it examines the participation intensity and role of the Greek organizations in the research network established through the Information Society Technologies priority of the European Community’s 4th, 5th and 6th Framework Programmes. Furthermore, it attempts to assess the impact of the IST research network on the diffusion and deployment of innovation in Greece. Some interesting results with significant policy implications arise: a) Greece exhibits high participation intensity in the EU-funded IST network, b) there are Greek organizations that have assumed an influential role in the network through time, in addition, they are also critical to the connectivity of the more peripheral Greek actors to the IST network, c) the value of the network, lies for the most part in indirect or ‘behavioural’ effects than in immediate project outputs measured in terms of commercialized products or services, d) however, while the knowledge obtained through the network assists organizations to gain better understanding of the market and identify future deployment opportunities this is not always possible due to the lack of sufficient infrastructure and national policies to support market introduction.

Consultation and illness behaviour in response to symptoms: a comparison of models from different disciplinary frameworks and suggestions for future research directions

We all get ill and social scientific interest in how we respond – the study of illness behaviour – continues unabated. Existing models are useful, but have been developed and applied within disciplinary silos, resulting in wasted intellectual and empirical effort and an absence of accumulation of knowledge across disciplines. We present a critical review and detailed comparison of three process models of response to symptoms: the Illness Action Model, the Common Sense Model of the Self-Regulation of Health and Illness and the Network Episode Model. We suggest an integrated framework in which symptoms, responses and actions are simultaneously interpreted and evaluated in the light of accumulated knowledge and through interactions. Evaluation may be subconscious and is influenced by the extent to which the symptoms impose themselves, expectations of outcomes, the resources available and understanding of symptoms' salience and possible outcomes. Actions taken are part of a process of problem solving through which both individuals and their immediate social network seek to (re)achieve ‘normality’. Response is also influenced by social structure (directly and indirectly), cultural expectations of health, the meaning of symptoms, and access to and understandings of the legitimate use of services. Changes in knowledge, in embodied state and in emotions can all be directly influential at any point. We do not underestimate the difficulty of operationalising an integrated framework at different levels of analysis. Attempts to do so will require us to move easily between disciplinary understandings to conduct prospective, longitudinal, research that uses novel methodologies to investigate response to symptoms in the context of affective as well as cognitive responses and interactions within social networks. While challenging such an approach would facilitate accumulation of knowledge across disciplines and enable movement beyond description to change in individual and organisational responses

What is Social Network Analysis?

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. This book introduces the non-specialist reader to the principal ideas, nature and purpose of social network analysis. Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals. Social network theory maps these relationships between individual actors. Though relatively new on the scene it has become hugely influential across the social sciences. Assuming no prior knowledge of quantitative sociology, this book presents the key ideas in context through examples and illustrations. Using a structured approach to understanding work in this area, John Scott signposts further reading and online sources so readers can develop their knowledge and skills to become practitioners of this research method. A series of Frequently Asked Questions takes the reader through the main objections raised against social network analysis and answers the various queries that will come up once the reader has worked their way through the book

MAPPING AND EXPLORING INFORMAL NETWORK IN ORGANIZATIONAL AND COMMUNITY LEADERSHIP

Work often happens through informal interactions and relationships. Formal networks and vertical channels no longer enough for the organizational and community capacity to adapt to the rapid social changes and disruptions. Just as the network knowledge is an asset for any organization in the disruptive era, understanding people’s connections and network’s approach is critically important in the cultural transformation of the leadership in the community and organization. The purpose of this article is to review and investigate how Social Network Analysis (SNA) could visualize and analyze the informal networks in organizational and community leadership’s studies. This study introduces a model that combines organizational leadership and community leadership as a social relations category in a micro- sociological perspective. By applying social network approach to evaluating leadership network, the organization or community can more efficiently scale and accelerate their development as well as solves their leadership problems. This method is useful for those who are seeking to influence policy, disseminate new ideas, and mobilize resources towards a common or a specific goal. SNA provides a set of theories, tools, and processes for understanding the relationships and structures of a network. SNA will determine the particular measures, from simple to complex rules, which need to be applied to derive insights from the network and how the network system is structured and evolved with time. The results of this review could help leaders to diagnose, measure, and evaluate their informal network structures and dynamics which are connected through shared interests, work, experiences, and collaborations.