A forecasting methodology for academic manpower requirements in a small sized technical university (original) (raw)

Manpower Planning for Demand Forecasting of Faculty Members using Trend Analysis and Regression

International Journal of Academic Research in Business and Social Sciences, 2015

Employing adequate manpower is one of the major concerns of modern organizations. As Faculty members having specific characteristics, they are not available when necessary and this requires planning in order to predict their demand in time. In this research, using trend analysis as one of the quantitative method for estimation, first the predictive variables including BA,MA and PhD students also the published articles are predicted for five years, then by using regression equations models, the faculty members by rank, age and gender are forecasted. The findings showed that associate professors, aged 46 to 55 years are the most necessary manpower to be employed. Also the percentage of female faculty members shows significant growth.

Prediction of educational institution using predictive analytic techniques

Education and Information Technologies, 2018

An educational institution is a place where people of different ages gain an education. In Pakistan, it includes primary, middle, high schools, inter colleges, technical and vocational institutions, degree colleges and universities. They provide a large variety of learning environments and learning spaces. This article figures out educational institutions development prediction, using the model of linear regression. This study has analyzed the development of a number of educational institutions using statistical analysis and predicts the future development of educational institutions yearly. The data is taken from BHandbook of statistics on Pakistan economy^ time series data from 1970 to 2016. The population was affected by limited numbers of educational institutions; the female institutions at every level is less than male, and the ratio of institutional development is lower as compared to increasing population (like the third world countries). The results suggest a need of further development of educational institutions at every level, for male and female, especially the female institutions because the female population in Pakistan is 52% of total population.

Using Regression Analysis to Forecast the Factors Affecting the Enrollment of a Tertiary School

Asia Pacific Journal of Multidisciplinary Research, 2014

The development of the enrollment forecast was done using three models: the logit model (for demographic profile), the percentage, base and rate concepts (for price), and Markov analysis (for quality and convenience). The variables and the relationships among them were analyzed using the models. Enrollment forecast, based from the mathematical models, revealed that males are less likely to attend school by 23% than females. As they grow older the likelihood of attending school also decreases by 57.5%. With regards to age, results of the study shows that for every one year increase in the age, the likelihood of attending school decreases by 27.5%, and it even decreases further by 57 percent as they grow older. In terms of per capita income and remittance, as their values increases the probability/likelihood to pay tuition fee higher than the suggested tuition fee of the region (P29,579.00) increases.

Prediction of academic manpower system of a Polytechnic institution in Nigeria

This study is on makovian approach in studying the behaviour of the academic staff grade transition of a Polytechnic institution in Nigeria. The objective of this study is to determine the proportion of staff recruited, promoted and withdrawn from the various grade levels in the institution over the years and also forecast the expected manpower structure of the institution for 2014/2015 session. Secondary data obtained from the

Forecasting approaches in a higher education setting

Education and Information Technologies, 2021

Forecasting the enrollments of new students in bachelor's systems became an urgent desire in the majority of higher education institutions. It represents an important stage in the process of making strategic decisions for new course's accreditation and optimization of resources. To gain a deep view of the educational forecasting context, the most used machine learning and statistical approaches are discussed and analyzed. These methods were applied over student data collected from the enrollment of new students in the faculty of literature and Human sciences between 2003 and 2019. The main result of this study is the development of a forecasting model that provides the most accurate values with a minimum of errors.

The use of RAS in manpower forecasting: A microeconomic approach

Economic Modelling, 1996

This paper deals with the use of FL%3 in manpower forecasting. The starting point is a microeconomic allocation model of the firm in which the optimal employment by education is determined. Two restricting hypotheses, dealing with the uniformity of wage changes and technologies over industries, are formulated. Several variants of the allocation model, differing with regard to accepting these hypotheses, are investigated. It is shown that these variants can all be rearranged to obtain the RAS structure. The performances of the FLU variants indicate the validity of the hypotheses. It is concluded that neither hypothesis can be rejected.

Forecasting of Future Supply in Strategic Human Resources Planning Process: External Analysis

Ataturk Universitesi Iktisadi Ve Idari Bilimler Dergisi, 2005

Bu çalı ma, Türkiye'nin en büyük 200 sanayi i letmesinde gerçekle tirilmi tir.Ara tırmanın konusu, stratejik insan kaynakları planlaması sürecinin önemli bir unsuru olarak, dı analiz uygulamasını de erlemektir. Çalı mamızın temel sonucuna göre, ara tırma kapsamındaki stratejik insan kaynakları planlamasını gerçekle tiren i letmeler, dı analiz a amasını göz önüne almamaktadırlar.

The effects of type of forecasting model and aggegation procedure on the accuracy of managerial manpower predictions

Behavioral Science, 1978

This article examines the &ciency of Markov chain models in the prediction of future needs for managers in a particular organization. It compares the accuracy of predictions made using a Markov chain model to predictions obtained by regression methods using data on personnel movementa during 13 years in a large corporation. T w o methods for estimating the transition probabilities between the different levels of the organization were presented and the a m m y of the respective Markovian models was compared. The effects of aggregating the employees into different hierarchical groups on the accuracy of prediction wae ale0 examined. The Markov chain models yielded, in general, more accurate predictions than the regression models. The predictions that were obtained based on transition probabilities estimated from past movementa between levels were more accurate thaa those based on transition probabilities estimated from time series of the number of employees at each level. The accuracy of all models, however, depends on the forecasting of new employees entering the firm at each leveL The results also suggest that higher aggregation leads to more accurate predictions. The utility of using Markovian vs. regression models from both the accuracy aspect and the availability and costs of data are discussed.

The History of Manpower Forecasting in Modelling Labour Market

2008

The manpower forecasting approach (MFA) was one of the first attempts in educational planning purposes. Manpower planners attempted: 1) to calculate the demand for manpower classified by occupation; 2) to convert this classification of demand by occupation into demand by educational attainment; 3) to devise plans and policies aimed at equating projected demands and probable supplies. The paper recalls the basic principles of the MFA from the perspective of the history of the economic thought and attempts to clarify why there was a virtual failure in MFA during the 1960s.