2016
DOI: 10.1177/0170840615613374
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Dominant Cognitive Frames and the Innovative Power of Social Networks

Abstract: (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.

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Cited by 33 publications
(12 citation statements)
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References 72 publications
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“…Qualitative in-depth case studies with 3 CLAHRCs and 3 similarly networked innovation initiatives in the USA and Canada. Semi-structured interviews with key participants across CLAHRC cases (phase 1, n = 67; phase 2, n = 42) and North American cases (phase 1, n = 67; phase 2, n = 42) Social network analysis via the use of survey instruments across two time points with CLAHRCs (phase 1, n = 261/367; phase 2, n = 211/333) and one time point with one North American case ( n = 39/77) Analysis of cognitions via the use of a cognitive mapping tool https://www.journalslibrary.nihr.ac.uk/hsdr/hsdr02130/#/abstract D’Andreta et al (2013) [ 21 ] D’Andreta et al (2016) [ 20 ] Evans and Scarbrough (2014) [ 22 ] HS&DR-09/1809/1072: Collective action for knowledge mobilisation: a realist evaluation of the Collaborations for Leadership in Applied Health Research and Care [ 13 ] 2010–2014 £600,000 PI: Prof Jo Rycroft-Malone Longitudinal realist evaluation involving hypothesis generation, refining, testing and programme theory specification. Data derived from in-depth case studies of 3 CLAHRCs over four phases of data collection.…”
Section: Resultsmentioning
confidence: 99%
“…Qualitative in-depth case studies with 3 CLAHRCs and 3 similarly networked innovation initiatives in the USA and Canada. Semi-structured interviews with key participants across CLAHRC cases (phase 1, n = 67; phase 2, n = 42) and North American cases (phase 1, n = 67; phase 2, n = 42) Social network analysis via the use of survey instruments across two time points with CLAHRCs (phase 1, n = 261/367; phase 2, n = 211/333) and one time point with one North American case ( n = 39/77) Analysis of cognitions via the use of a cognitive mapping tool https://www.journalslibrary.nihr.ac.uk/hsdr/hsdr02130/#/abstract D’Andreta et al (2013) [ 21 ] D’Andreta et al (2016) [ 20 ] Evans and Scarbrough (2014) [ 22 ] HS&DR-09/1809/1072: Collective action for knowledge mobilisation: a realist evaluation of the Collaborations for Leadership in Applied Health Research and Care [ 13 ] 2010–2014 £600,000 PI: Prof Jo Rycroft-Malone Longitudinal realist evaluation involving hypothesis generation, refining, testing and programme theory specification. Data derived from in-depth case studies of 3 CLAHRCs over four phases of data collection.…”
Section: Resultsmentioning
confidence: 99%
“…D’Andreta et al (2016) set the scene with a rich case-based analysis of two collaborative networks in the health services in UK. The focus of the paper is the dynamic interactions between dominant frames about the purpose of the network and network structure and the impact of this interaction on collaboration and innovation within the network.…”
Section: Orchestrating Network For Innovationmentioning
confidence: 99%
“…The special issue brings together six thoughtful and provocative papers that help advance our ability to conceptualize, measure, manage and advise network emergence and evolution within and across organizational boundaries, and seek to contribute to a growing understanding of the impact of such networks on organizations and society. One set of papers (D’Andreta, Marabelli, Newell, Scarbrough, & Swan, 2016; Corbo, Corrado, & Ferriani, 2016; Dagnino, Levanti, & Mocciaro Li Destri, 2016) debates the articulation between the organized and emergent dynamics of networks and its impact on knowledge exchanges and innovation. The second set of papers seeks to inform our understanding of the manifestations of power in network dynamics (Qureshi, Kistruck, & Bhatt, 2016; Parker, Halgin, & Borgatti, 2016; Maclean & Harvey, 2016).…”
mentioning
confidence: 99%
“…Healthcare professionals involved included surgeons, oncologists and radiation oncologists, within a multidisciplinary team approach (15). All team members ensured effective knowledge translation flows (16), employing tools like in-person meetings (17), electronic medical records (18), evidence-based methods (19), clinical cases and best practices (19) and self-assessment (20).…”
Section: Methodsmentioning
confidence: 99%