The development of a knowledge sharing construct to predict turnover intentions

The objective of this paper is to discuss the development of a knowledge sharing questionnaire and the role of knowledge sharing in predicting turnover intentions of registered professional nurses.

A literature study was conducted to determine the concepts and activities linked to knowledge sharing in order to compile a questionnaire. The questionnaire was factor analysed in order to determine the factor structure of the instrument. Thereafter, the construct of knowledge sharing was introduced together with organisational culture and various proposed mediating variables, namely organisational commitment, organisational citizenship behaviour and job satisfaction, as well as various demographic variables to develop a predictive model of turnover intentions through applying general linear modelling. A cross‐sectional field survey design was used with a sample of 530 registered professional nurses in South Africa.

A knowledge‐sharing questionnaire was developed that yielded a high reliability coefficient. A significant negative relationship was found between knowledge sharing behaviour and turnover intentions. Furthermore, knowledge sharing interacted with organisational culture in a final model where all the selected mediating and demographic variables were simultaneously entered into the equation to predict turnover intentions.

More attention should be given to improve the content validity of the knowledge‐sharing questionnaire. The development of more knowledge sharing measures in different industries is also important.

Employers should know that retention strategies of professional nurses can be built around opportunities to share knowledge if they manage the organisational culture in such a way that people are willing to share what they know. This emphasises the importance of the human being in effective knowledge management.

The development of the knowledge‐sharing questionnaire contributes to fill a gap of existing measures. It also focuses on the importance of tacit knowledge and that knowledge resides in the human minds of people. The value of a thorough literature overview in compiling questionnaires and applying general linear modelling in compiling predictive models are highly recommended.