INTERNATIONAL JOURNAL OF DATA ENVELOPMENT ANALYSIS
Year:2013 | Volume:1 | Issue:1|Papers Count:6

For efficiency evaluation of some of the Decision Making Units that have uncertain information, Rough Data Envelopment Analysis technique is used, which is derived from rough set theorem and Data Envelopment Analysis (DEA). In some situations rough data alter nonradially. To this end, this paper proposes additive rough–DEA model and illustrates the proposed model by a numerical example.

Performance evaluation of universities is an important issue between researchers. Classic data envelopment analysis (DEA) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. However, DEA with stochastic data are, rarely used to measure efficiency of universities. In this paper, input oriented model in stochastic data envelopment analysis is used to evaluate universities in Iran. In addition, super efficiency model is developed in stochastic DEA to rank stochastic efficient units. To obtain numerical results with stochastic data, a deterministic equivalent of each stochastic model is used which can be converted to a quadratic program. Thirty-three Iran universities have been considered in this study for which computational results of both classic and stochastic approaches are obtained.

In this paper, different input-oriented ratio-based DEA (DEA-R-I) models are proposed. By presenting the envelopment-additive-enhanced Russell model based on the DEA-R-I form, each decision making unit is evaluated and its efficiency score is calculated. Also, by presenting the central resource allocation model based on the DEA-R-I form, a suitable benchmark for all DMUs is proposed by solving a linear programming problem. Finally, the efficiency scores obtained for the data of 20 commercial bank branches by each of the proposed models are compared.

Over the years we have witnessed the growing importance of supply chain operations and supply chain management (SCM), as supply chains play a major role in every step of the product life cycle. Therefore, this paper will DEA-based performance evaluation approaches for overall supply chain can be categorized. Future perspectives and challenges are discussed.

Supplier selection is one of the critical activities for firms to gain competitive advantage and achieve the objectives of the whole supply chain. In this paper based on a DEA-TOPSIS method for MADM problems a flexible strategy for supplier selection is introduced.

Every country actively and initiatively takes all kinds of policy steps to improve the international competitiveness of its industries and therefore improve national integrated competitiveness for the purpose of gaining economic benefits under the context of economic globalization. Therefore, studies of moreover, projects launched by the cluster had to be endorsed by the growers and one criterion in the selection of projects was that the project would demonstrate to the growers the value of collaboration. Therefore, we develop a comprehensive performance measurement framework using the classical and two-stage Value Chain Data Envelopment Analysis models.