Anne Buckett, Jürgen Reiner Becker and Gert Roodt
The purpose of this paper is to establish the extent of general performance factors (GPF) in assessment center (AC) exercises and dimensions. The study further aims to determine…
Abstract
Purpose
The purpose of this paper is to establish the extent of general performance factors (GPF) in assessment center (AC) exercises and dimensions. The study further aims to determine if larger GPF contributes to larger ethnic group differences across exercises and dimensions that are more cognitively loaded in an emerging market context.
Design/methodology/approach
The authors analyzed data across three independent AC samples (Sample 1: N=172; Sample 2: N=281; Sample 3: N=428). The Schmid-Leiman solution was used to determine the extent of GPF in AC exercises and dimensions. An independent samples t-test and Cohen’s d was used to determine the size of ethnic group differences across exercises and dimensions.
Findings
The results indicate that GPF is consistently large for the in-basket exercise. Furthermore, dimensions that are more cognitively loaded, such as problem solving, strategic thinking, and business acumen, seem to produce the largest ethnic group differences. Overall, the research indicates that larger GPF is associated with larger ethnic group differences in relation to specific AC dimensions and exercises.
Originality/value
The authors add to the literature by investigating the prevalence of a GPF in AC ratings across AC exercises and dimensions. A novel contribution of the research attempts to link the prevalence of a GPF in AC ratings to group membership in South Africa. The study offers an alternative statistical analysis procedure to examine GPF in AC ratings.
Details
Keywords
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
Details
Keywords
Howard Thomas, Michelle Lee, Lynne Thomas and Alexander Wilson
Howard Thomas, Michelle Lee, Lynne Thomas and Alexander Wilson