A Markov model for prediction of academic manpower system in Nigerian colleges of education
Shamsuddeen Ahmad Sabo et al.
What the paper says
This research employed a Markov model to assess the progression of the academic staff workforce in Nigerian colleges of education, using Sa'adatu Rimi College of Education, Kano as a case study. The objective was to underscore the importance of effective workforce planning in mitigating staff shortages or surpluses. By analysing transition probabilities derived from college planning department data, the study constructed a transition probability matrix depicting staff flow over time. The Markov model's findings projected an estimated 568 academic staff members for the college in the 2024/2025 session, distributed across academic ranks. Notably, the forecasted staff structure skewed towards higher ranks. Furthermore, the study offered insights into new staff members' anticipated years of service at different academic ranks. The research underscores the pivotal role of workforce planning in educational institutions, highlighting the Markov model's value in guiding staffing and workforce management decisions.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.