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      Managing the academic talent void: Investigating factors in academic turnover and retention in South Africa

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          Abstract

          ORIENTATION: Globally, the demand for academic staff in higher education is expected to continue to increase. The South African situation is exacerbated by the so-called 'retirement swell' and turnover and retention problems; measurements to diagnose these factors remain limited. RESEARCH PURPOSE: This study aimed to investigate the factors that influence turnover and retention of academic and to validate the developed talent retention diagnostic tool for use in South African higher education institutions. MOTIVATION FOR THE STUDY: Limited research currently exists on the retention factors of academic staff in the South African context. RESEARCH APPROACH, DESIGN AND METHOD: Using an investigative quantitative research approach, the tool was administered to a convenience sample of academics (n = 153) in 13 higher education institutions. MAIN FINDINGS: The results showed an array of distinguishing turnover and retention factors and proved the tool to be a valid and reliable measure. Over half the respondents indicated slight to strong dissatisfaction with compensation and performance management practices. Significantly, 34% indicated that they considered exiting their academic institution, citing unhappiness about compensation, as the most likely reason, whilst 74.5% have previously looked for another job. PRACTICAL/MANAGERIAL IMPLICATIONS: The research highlights key areas (i.e. compensation, emotional recognition, a bonus structure that reflects employee contribution, performance management systems, mentorship and career development opportunities) that higher education should attend to if they want to retain their key and talented academic staff. CONTRIBUTION/VALUE-ADD: The results contribute to new knowledge on the factors that contribute to turnover and retention of academic staff and present a valid and reliable measure to assess these retention factors.

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          Multivariate Data Analysis

          For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. This text provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques. :Pearson New International Edition.
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            The Impact Of Human Resource Management Practices On Turnover, Productivity, And Corporate Financial Performance

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              AN UNFOLDING MODEL OF VOLUNTARY EMPLOYEE TURNOVER.

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                sajip
                SA Journal of Industrial Psychology
                SA j. ind. Psychol.
                AOSIS Publishing (Cape Town )
                0258-5200
                January 2014
                : 40
                : 1
                : 01-14
                Affiliations
                [1 ] University of Pretoria South Africa
                [2 ] North-West University South Africa
                Article
                S2071-07632014000100009
                10.4102/sajip.v40i1.1117
                acc84576-9034-42f8-ba35-9f86b3db2972

                http://creativecommons.org/licenses/by/4.0/

                History
                Product

                SciELO South Africa

                Self URI (journal page): http://www.scielo.org.za/scielo.php?script=sci_serial&pid=2071-0763&lng=en
                Categories
                Industrial Relations & Labor
                Psychology
                Psychology, Applied

                Labor & Demographic economics,Clinical Psychology & Psychiatry
                Labor & Demographic economics, Clinical Psychology & Psychiatry

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