APPLICATION OF MARKOV CHAIN MODEL IN CAREER PROGRESSION OF UNIVERSITY ACADEMIC STAFF: A Case Study of the Moi University-Eldoret, Kenya.

Abstract

The use of Mathematical models for manpower planning has increased in recent times for better manpower planning quantitatively both in public and private sectors. In respect of organizational management, numerous previous studies have applied Markov chain models in describing title or level promotions, demotions, recruitment, withdrawals, or changes of different career development paths to confirm the actual manpower needs of an organization or predict the future manpower needs. The movements of staff within the grades or job group levels called transitions are usually the consequences of promotions or transfers between segments or wastage and recruitment into the system. In this study we determined and compared the transition rates of the academic staff of science and art faculties, the expected time taken before one attains the highest academic rank, and the absorption rates in the university. The data was collected from Moi University- Eldoret and the grades or job groups were: Tutorial Fellow, Lecturer, Senior Lecturer, Associate Professor, and full Professor. The study established that the transition rates are high at the Tutorial fellow and lecturer levels in both science and art with 67.09% and 86.31% and 86.00% and 97.53% respectively within the first ten years of employment. But it was low at 50% at senior lecturer and associate professor in the faculty of science and 63.51% and 88.69% for the same ranks in the faculty of arts. . It took academic staff 19.51 years and 22.74 years in science and art respectively to attain the rank full professor.

Keywords: Jobgroups, transitional rate, markov chain,absorption rate,expectation