This thesis explores the relevance of Bio Data verses Personality for predicting Cultural Competence among Industrial and Organisational Psychology and Human Resource Management professionals and students in New Zealand. It also explores the relevance of the model (D.W. Sue, 2001) of Cultural Competence currently in use by the New Zealand Psychologists board and also the relevance of a four factor model of Cultural Intelligence (Early & Ang, 2003). The sample consisted of 113 participants drawn from a population of Industrial and Organisational Psychology, and Human Resource Management professionals and students. A questionnaire which measures the predictors of the Big Five Personality Factors (Goldberg, 1999), and Bio Data, and the criterion variables of Cultural Intelligence (Earley & Ang, 2003) and questions constructed specifically for this thesis was distributed online. The criterion variables were based on an existing three part (Awareness, Knowledge and Skills) Multidimensional Model for Developing Cultural Competence by D.W. Sue (2001). The results of this research were obtained through exploratory factor analysis and subsequent multiple regression analysis. A new model was constructed to represent the tested predictor and criterion relationship. Results suggest that overall Personality is a better predictor of Cultural Competence, with the Personality Factor of Agreeableness being the highest weighted Personality Factor. D.W Sue’s (2001) Multidimensional Model for Developing Cultural Competence maintained its three part structure in the analysis and consequently seems relevant to the unique socio-cultural, organisational and professional setting of the tested group. Ang and colleagues (Ang, Van Dyne, Koh, Ng, Templer, Tay & Chandraseker, 2007) Cultural Intelligence Scale maintained its four part factor structure and was reliable for this thesis.
| Identifer | oai:union.ndltd.org:ADTP/269420 |
| Date | January 2009 |
| Creators | Williams, Tania Marie |
| Publisher | Massey University |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
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