Journal of Scientific Papers

ECONOMICS & SOCIOLOGY


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ISSN 2071-789X



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  • General Founder and Publisher:


    Centre of Sociological Research

  • Publishing Partners:

     
     
    University of Szczecin (Poland)


    Mykolas Romeris University (Lithuania)

     

     
     
    Alexander Dubcek University of Trencín, Faculty of Social and Economic Relations (Slovak Republic)



     
    University of Entrepreneurship and Law, (Czech Republic)

     

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Exploration Knowledge Sharing Networks Using Social Network Analysis Methods

Vol. 10, No 3, 2017

 

Győző Attila Szilágyi,

 

Óbuda University,

Doctoral School on Safety and Security Science,

Budapest, Hungary,

E-mail: szilagyi@strategiakutatas.hu

 

EXPLORATION KNOWLEDGE SHARING NETWORKS USING SOCIAL NETWORK ANALYSIS METHODS

 

 

 

 

 

 

 

Abstract. Knowledge sharing within organization is one of the key factor for success. The organization, where knowledge sharing takes place faster and more efficiently, is able to adapt to changes in the market environment more successfully, and as a result, it may obtain a competitive advantage. Knowledge sharing in an organization is carried out through formal and informal human communication contacts during work. This forms a multi-level complex network whose quantitative and topological characteristics largely determine how quickly and to what extent the knowledge travels within organization. The study presents how different networks of knowledge sharing in the organization can be explored by means of network analysis methods through a case study, and which role play the properties of these networks in fast and sufficient spread of knowledge in organizations. The study also demonstrates the practical applications of our research results. Namely, on the basis of knowledge sharing educational strategies can be developed in an organization, and further, competitiveness of an organization may increase due to those strategies’ application.

 

Received: December, 2016

1st Revision: March, 2017

Accepted: June, 2017

 

DOI: 10.14254/2071- 789X.2017/10-3/13

JEL Classification: D82, D83, D85

Keywords: knowledge sharing, social network, network theory.