The network structure of knowledge sharing among physicians

The network structure of knowledge sharing among physicians This paper applies social network analysis in order to model knowledge sharing among hospital physicians. Drawing on the literature on the diffusion of innovation and cooperation in clinical settings, it aims to furnish better understanding of knowledge sharing in two directions: describing how knowledge flows and identifying individual and contextual factors which facilitate its spontaneous spreading. Used to address these issues is a link- tracing sample of about 800 Italian hospital physicians, potentially involved in prescribing a new drug. The paper represents knowledge sharing about the innovation as a network. It therefore specifies Exponential Random Graphs (ERG) or p* models to reconstruct the network structure of knowledge sharing and to test the effect of exogenous factors on the tendency to take action in the network. The results show that knowledge flows informally, exploiting mutual information-seeking relationships, and, consistently with previous studies, locally, with physicians tending to cluster in small groups of proximate and similar peers. Moreover empirical evidence is provided that the propensity to share information with colleagues is greatly affected by individual-specific characteristics, mainly by the experience in the field and the attitude toward the innovation, and by exposure to commercial communication. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

The network structure of knowledge sharing among physicians

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Publisher
Springer Netherlands
Copyright
Copyright © 2011 by Springer Science+Business Media B.V.
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-011-9494-1
Publisher site
See Article on Publisher Site

Abstract

This paper applies social network analysis in order to model knowledge sharing among hospital physicians. Drawing on the literature on the diffusion of innovation and cooperation in clinical settings, it aims to furnish better understanding of knowledge sharing in two directions: describing how knowledge flows and identifying individual and contextual factors which facilitate its spontaneous spreading. Used to address these issues is a link- tracing sample of about 800 Italian hospital physicians, potentially involved in prescribing a new drug. The paper represents knowledge sharing about the innovation as a network. It therefore specifies Exponential Random Graphs (ERG) or p* models to reconstruct the network structure of knowledge sharing and to test the effect of exogenous factors on the tendency to take action in the network. The results show that knowledge flows informally, exploiting mutual information-seeking relationships, and, consistently with previous studies, locally, with physicians tending to cluster in small groups of proximate and similar peers. Moreover empirical evidence is provided that the propensity to share information with colleagues is greatly affected by individual-specific characteristics, mainly by the experience in the field and the attitude toward the innovation, and by exposure to commercial communication.

Journal

Quality & QuantitySpringer Journals

Published: Mar 26, 2011

References

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