Knowledge sharing motivation among external and internal IT workers

Noam Koriat, Roy Gelbard

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


This paper extends a previous study that proposed an integrated model to test knowledge sharing (KS) motivation among information technology (IT) workers. While the previous study focussed on the differences in KS between internal and external IT workers, the perspective of the current paper is broader; it proposes additional hypotheses, and uses both inferential statistics and data mining techniques to detect further practical aspects of the integrated model findings. Because data mining techniques are useful in extracting patterns and gaining insights from data, they are implemented here alongside inferential statistics. The present study also looks into the employment-contract factor, to better capture the differences between internal and external IT workers. The study reveals that external workers score significantly lower than internal workers in almost every component of the integrated KS model. This gives rise to five practical implications of knowledge management (KM) and employment policies, including factors and practises that should be taken into consideration while employing external workers, to help motivate collaborative behaviour in IT departments.

Original languageEnglish
Article number1850026
JournalJournal of Information and Knowledge Management
Issue number3
StatePublished - 1 Sep 2018

Bibliographical note

Publisher Copyright:
© 2018 World Scientific Publishing Co.


  • IT workers
  • data mining
  • external workers
  • insourcing
  • internal workers
  • knowledge management
  • knowledge sharing
  • outsourcing


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