New Approaches to Decision-Making Models for University Management Using a Default Probability Ranking Based on Population Simulations

Abstract

　 In Japan, the number of universities confronting management crises is continuously increasing. This is caused primarily by the decline in the numbers of the 18-year-old cohort. Many universities have already begun to tackle this sociodemographic problem. However, identifying the management policy which is most appropriate and best suited to their individual circumstances is invariably a difficult issue. In fact, some universities have been unsuccessful in formulating and implementing countermeasures and have ended up in financial trouble.

　 The core aim of this paper is thus to propose a new approach to help universities find the most suitable and effective management policy. In order to achieve this, the procedure adopted is the following. Firstly, all universities (national, public and private) are ranked on the basis of the School Basic Survey data, Center of Excellence and Global COE data, and Grant-in-Aid for Scientific Research data, and are then divided into 7 clusters. Secondly, by using an originally developed simulation model, which takes uncertainty factors into consideration, an estimate is made of the number of potential applicants for the next 100 years, and of how much time each university cluster has before the advent of the era of free college admissions. Thirdly, management policies which can be implemented during the grace period are carefully selected and assigned to each cluster.

　 In conclusion, the findings are: 1) universities that belong to the 6^th and 7^th clusters are likely to experience free admissions within a few years; 2) universities that belong to the 4^th cluster are at a critical point, so they must make a rapid decision about what kind of management policy is best suited to their circumstances; while 3) universities that belong to the 1^st and 2^nd clusters are in a very secure position for the next several decades. Based on these findings, the paper proposes a number of approaches to the problem of how to tackle university management issues in conditions of uncertainty.