Application of Markov Chain Model in Career Progression Of University Academic Staff:A Case Study of the Moi University - Eldoret, Kenya.
Abstract/ Overview
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.
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