Two-stage network DEA with convex hull in intermediate products

Two-stage Malmquist Productivity Index with Intermediate Products

Two-stage DEA models with undesirable input-intermediate-outputs

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still l...

Finding Common Weights in Two-Stage Network DEA

In data envelopment analysis (DEA), mul-tiplier and envelopment CCR models eval-uate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of...

Measuring Interval Efficiency in Convex Hull of Data Using DEA

Two-stage network DEA: when intermediate measures can be treated as outputs from the second stage

UT HO R CO PY Two-stage network DEA: when intermediate measures can be treated as outputs from the second stage Sonia Aviles-Sacoto, Wade D Cook*, Raha Imanirad and Joe Zhu Doctoral Program in Engineering Sciences, ITESM-Monterrey, Mexico; Schulich School of Buisness, York University, Toronto, Canada M3J1P3; Doctoral Program, Harvard Business School, Soldiers Field, Boston, MA 02163; and Intern...