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Organizational dynamics: exploring the factors affecting knowledge sharing behavior.

Authors :
Obermayer, Nóra
Toth, Viktoria Erika
Source :
Kybernetes. 2020, Vol. 49 Issue 1, p165-181. 17p.
Publication Year :
2020

Abstract

Purpose: The purpose of this study is to identify the individual and organizational factors that influence knowledge sharing (KS) behavior within Hungarian organizations. Design/methodology/approach: The data were obtained from 238 completed questionnaires collected via the LimeSurvey system. The analysis is based on applied quantitative methodology, both descriptive and inferential statistics were used. The research investigated the relationships between individual and organizational characteristics and the KS behavior at individual and global levels. Findings: Among individual factors, significant relationships have been identified regarding the generation and position of individuals, and KS behavior, while gender and education do not seem to play a significant role. With respect to organizational factors, the size of the organization and the tenure of individuals are found to be significant. Research limitations/implications: The results of the analysis are limited because the data set was not large enough to investigate inter- and intra-industry variability. Practical implications: The outcome of this research can support the design of managerial and organizational processes and incentives that will potentially facilitate KS in a more efficient and effective manner. Such improved KS is likely to improve the overall performance of knowledge-intensive organizations. Originality/value: The original value of this research is that individual and organizational characteristics have been identified that influence KS behavior. The study focuses on a single country, Hungary, and provides relevant insight into the organizational dynamics of a specific national context. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0368492X
Volume :
49
Issue :
1
Database :
Academic Search Index
Journal :
Kybernetes
Publication Type :
Periodical
Accession number :
141295150
Full Text :
https://doi.org/10.1108/K-04-2019-0300