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Psychosocial Conditions for Knowledge Sharing in Healthcare Research Centers: A Qualitative Comparative Analysis.

Authors :
Gonçalves, Tiago
Curado, Carla
Balle, Andrea
Source :
European Conference on Knowledge Management; 2019, Vol. 1, p415-424, 10p
Publication Year :
2019

Abstract

Knowledge sharing is a complex psychosocial phenomenon often considered the main component of knowledge management. The literature in the healthcare sector is shifting, adopting a people-centered approach while still struggling with old-fashioned managerial practices. Healthcare research centers are knowledge-intensive environments dealing with the fragmented nature of knowledge, therefore increasing the need of collaboration between scientific peers (Zhang et al., 2017). This study uses the social psychology approach of the Theory of Reasoned Action to examine the impact of psychosocial factors as antecedents of knowledge sharing between scientific peers in healthcare. We follow a qualitative design and use a sample of 150 healthcare researchers to study the relation among the perceptions of a social network, shared goals, social trust, and knowledge sharing. We use a fuzzy-set qualitative comparative analysis (fsQCA) to identify configurations that lead to the intention to share knowledge and its absence and to the knowledge sharing behavior and its absence. The findings show evidence of the proposed antecedents of the intention to share knowledge and their effect on knowledge sharing. Additionally, we offer and discuss configurations of causal conditions leading to the presence or absence of the intention to share knowledge and the knowledge sharing behavior considering tacit and explicit knowledge separately, aiming for a larger framework whose discussion can provide more insight of the phenomenon in the deployment of knowledge management practices. The theoretical contribution of this work is possible due to the methods used that adds to the literature in a unique and original way only possible by using fsQCA, since traditional quantitative statistical methods only offer a single estimated solution for each dependent variable and do not estimate solutions for the absence of variables (Rihoux and Ragin, 2009). The small sample size is considered as a limitation of the study. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20488963
Volume :
1
Database :
Complementary Index
Journal :
European Conference on Knowledge Management
Publication Type :
Conference
Accession number :
138854295
Full Text :
https://doi.org/10.34190/KM.19.092