Predicting Lecturers Promotional Mobility Using Markov Chain Model

Abstract

Stochastic mobility models are probabilistic descriptions of how movements take place from one class to another. The main objective of the study was to forecast the number of members of University of Ghana (UG) academic staff in various categories or states of a system. In the literature, a stochastic mobility model for an open system has been developed. This work adopts this preexisting stochastic model to forecast promotion patterns for UG academic staff over specified periods. This is done through the generation of a probability transition matrix for academic staff promotions (open system) from 2001 to 2014. The findings of the study indicate that the total expected size of the university increased steadily over the period under consideration. A member of academic staff recruited to the position of a lecturer who wishes to rise through the ranks and to retire as a professor is likely to spend 27 years in the service (10.3 years as lecturer, another 7.5 years as senior lecturer, 5.6 years as associate professor and 3.6 years as full professor). A member of academic staff of UG recruited into the entry point as a lecturer has a 78.78% chance of becoming a senior lecturer, a 45.56% chance of becoming an associate professor and a 26.51% chance of becoming a full professor.