University Pierre and Marie Curie France
University of Tehran Iran, Islamic Republic of Department of Information Technology Management, Faculty of Management
The selection of best Information System (IS) project from many competing proposals is a critical business activity which is very helpful to all organizations. While previous IS project selection methods are useful but have restricted application because they handle only cases with precise data. Indeed, these methods are based on precise data with less emphasis on imprecise data. This paper proposes a new integrated Data Envelopment Analysis (DEA) model which is able to identify most efficient IS project in presence of imprecise data. As an advantage, proposed model identifies most efficient IS project by solving only one Mixed Integer Linear Programming (MILP). Applicability of proposed method is indicated by using data set includes specifications of 8 competing projects in Iran Ministry of Commerce.