AN APPLICATION OF GOAL PROGRAMMING TO ACADEMIC RESOURCE ALLOCATION PLANNING

Abstract

Since the last decade, universities in Nigeria have been experiencing a progressive decline in required inputs, like funds, materials and academic staff. In spite of this, there has been a continuing rise in the demand for their services, as shown by rising student enrolment figures (Nigeria, 1981). Confronted with such a problem, universities require more than ever before, formal decision models for planning the allocation of their scarce resources as efficiently as possible. This study applies goal programming for planning the academic resource allocation--a major input--of the University of Ibadan for 1982/83-l986/87. The goal programming model used modifies that of Schroeder (1974) by defining explicitly a student enrolment goal and introducing an academic staff level goal, which is designed to cater for academic staff advancement, at least according to the historical rate in each faculty. Furthermore, it redefines the academic rank distribution goal to incorporate the controversial 30%-40%-30% rank distribution ratios introduced in 1981. The study seeks principally to determine the distribution of academic staff by rank, in each faculty/college, over a five-year period and recommend the planning implications of such a distribution. In addition, it attempts to find the effects of dropping the controversial rank distribution goal on the model solution. The model was solved using the Revised Simplex Goal Programming Algorithm developed by Kang (l980) on an I.B.M. VM 370 computer in the University of Nebraska-Lincoln, U.S.A. The analysis of the model solution: suggests that from a purely theoretical point of view, it is desirable to use a rank distribution goal, for an optimization model of the type used in the study; otherwise, the model will select least cost allocation alternatives only and such a solution cannot be used effectively for planning. However, the distributional ratios to be used should not be rigid like the controversial ones of 1981, but should reflect the historical advancement rates in the respective faculties. The result of solving such a model should be, used for indicative planning only; -confirms the fear that the use of fixed rank distribution ratios might inhibit promotion rate; -indicates that the Faculty of Agriculture and Forestry appears to be operating very much below the minimum level of academic staff requirement to meet the student enrolment goal of that faculty as of now; -suggests that by the beginning of 1986/87, the University of Ibadan will require a minimum of 1,133 academic staff of various ranks to meet its student enrolment goal. This is over 60% above the minimum requirement at the beginning of 1982/83; -recommends that the University should pursue a vigorous Staff Development Programme in which the training of the best of its graduates--through a type of Junior Fellowship Programme--will be the core, as one approach of augmenting the supply of academic staff normally obtained through recruitment; -corroborates the findings of Kang (1980) that CPU time of the Revised Simplex Goal Programming Algorithm, tends to increase with increasing negative deviational variables in the objective function.