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. © 2011 Springer Science+Business Media B.V.
Zappa, P. (2011). The network structure of knowledge sharing among physicians. QUALITY & QUANTITY, 45(5), 1109-1126 [10.1007/s11135-011-9494-1].
The network structure of knowledge sharing among physicians
ZAPPA, PAOLA
2011
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. © 2011 Springer Science+Business Media B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.