Assessing Performance of Organizations Under Uncertainty: An Application in Higher Education

Data envelopment analysis (DEA) is an established approach to measure the efficiency of a group of firms. Amongst many existing DEA models, enhanced Russell measure (ERM) has received some attention and it minimises the ratio of average input reduction to average output increase. In the original ERM, observations are assumed to be precise but in reality, it is always true. This paper presents a class of robust optimisation models to deal with uncertainty with a high degree of robustness in the ERM models. In addition, this study leverages the Monte-Carlo simulation to give an appropriate range for the budget of uncertainty approving the highest level of conformity for the ranking of units. An application on the Master of Business Administration (MBA) programmes is presented.