Sonia Valeria Aviles-Sacoto

Learn More
Data Envelopment Analysis (DEA) is amethodology for evaluating the relative efficiencies of a set of decisionmaking units (DMUs). The original model is based on the assumption that in a multiple input, multiple output setting, all inputs impact all outputs. In many situations, however, this assumption may not apply, such as would be the case in(More)
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,(More)
Data envelopment analysis (DEA) is a methodology used to measure the relative efficiencies of peer decision-making units (DMUs). In the original model, it is assumed that in a multiple input, multiple output setting, all members of the input bundle affect the entire output bundle. There are many situations, however, where this assumption does not hold. In a(More)
  • 1