A preliminary model to identify low-risk MBA applicants

Abstract

Business schools throughout the world strive to admit “quality” students to their MBA programmes. To achieve this, various measures are employed during the selection processes.  These measures include various tests such as the General Management Admissions Test, Test of English as foreign language and the Common Admission Test, to name but a few.  Although these tests may be successful in indicating the quality of applicants, their predictive capabilities with reference to the academic performance in the discipline of management and leadership are unproven, while some researchers even regard these tests to be biased or unscientific across cultural boundaries.
This article attempts to provide a preliminary model that could be applied to applicants in order to predict their academic success on an MBA programme. To do so, the model makes use of historical academic performance of 729 MBA students who enrolled during the years 1999, 2000 and 2001 at the Potchefstroom Business School of the Northwest University.  These students graduated in the years 2001, 2002 and 2003.  A vast array of demographic, academic and historical variables is employed by discriminant analyses to categorise the applicants into 2 groups, namely:• “Low-to-no -isk” applicants for the MBA programme (most preferred applicants that should graduate within the minimum period of 3 years);• Applicants who did not complete their degree in 3 years.  This category contains two groups of students, namely those who extended their studies to 4 years, and those who failed and subsequently  dropped out of the MBA programme. Further analysis of this category identified:o “Medium-to-low-risk” applicants who are expected to complete their degree in 4 years (they need an additional year to complete the 3-year degree).  Although this category is less favourable, they do complete their studies. o “High-risk” applicants are those who are not expected to complete their degrees and would probably exit the programme without obtaining any qualification.  These applicants should not be allowed to enter into the MBA programme.
The reliability of the discriminant function rates favourably with 71% (MBA in 3 years), 62% (MBA in 4 years) and 83% (dropping out of the programme) being categorised correctly by the respective discriminant functions. Being a preliminary model, its predictive capabilities need to be verified in practice before it can  be implemented as tool to render assistance in MBA admissions.  The value of this research lies  in the fact that it constitutes a model that could be employed and improved as a predictive tool in an environment where very limited predictive tools exist.  Therefore, although it is by no means a tried and tested model, it sets the scene by supplying a scientific base from which incremental improvements could result.