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Title: Factors influencing decision making in internal management : evidence from private sector organisations in Saudi Arabia
Author: Abunar, Malak M.
ISNI:       0000 0004 5988 893X
Awarding Body: Brunel University London
Current Institution: Brunel University
Date of Award: 2016
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Talent management has grown considerably in the last decade as organisations have made it a top priority issue around the world. A shortage of talent has emerged as one of the critical challenges that face organisations worldwide as they seek successful operations on a global scale. This has resulted in anxiety among organisations and thus created pressure on human resource management to maintain the competencies needed to achieve organisational goals. Thus, this challenge is motivating organisations to accurately identify and manage talents effectively to include them in the organisational talent pool. In order to address what influences the likelihood of an individual being labelled as ‘talent’, this research seeks to investigate the decision-making processes involved in the identification of talent. This study makes an important contribution to the conceptual and empirical understanding of the nature of decision-making within talent management, which has suffered from a dearth of research. Thus, the aim of this study is to determine and examine the contextual and cultural factors that influence and shape the perceptions and the experience of managerial decision-making and its effect on the fairness of talent decisions. To date, there are a number of factors that have largely been examined separately in the literature. This study is the first to attempt to investigate these factors collectively to develop a comprehensive model to address the nature of talent decision-making. Furthermore, this study is one of a handful of studies that responds to the well-established call to emphasise the importance of decision-making in talent management literature. A quantitative approach was deemed best suited to test the proposed model. A cross-sectional survey was conducted for primary data from diverse managerial levels. Data were collected from private organisations in the oil and banking sectors in Saudi Arabia. Because data collection is seriously challenging in Saudi Arabia, convenience and snowball sampling were believed to be the most appropriate in terms of satisfactory responses. Using an online and paper-based survey strategy, a total of 1960 questionnaires were distributed, 486 were returned, and 470 completed responses were used for final analysis. Exploratory and confirmatory factor analyses were employed to validate the reliability and dimensionality of the integrated scales of the talent identification process. The results of a structural equation analysis supported the hypotheses. The findings of the empirical research identified three categorical variables that influence decision-making in talent identification processes; i.e., cultural, organisational, and societal factors. Further, decision-making style has a significant relationship with the fairness of talent decisions. The key theoretical contribution of this research is the development of a robust, multi-dimensional model that explains the promising phenomenon of the talent identification process, and demonstrates the factors that have a definite impact on talent decision-making. Unlike previous studies, this study measures the multi-dimensional model of the talent decision-making process, at the aggregate level which is considered as a methodological contribution in the area of talent management research. Pragmatically, the proposed model offers decision-makers a new perspective for adjusting and dealing with talent identification processes in order to ensure equity in talent decisions. This study extends the notion of talent decision-making in the talent identification process and creates avenues for further research.
Supervisor: Ali, Maged Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Talent management ; Decision making ; Saudi Arabia