Event schedule

About the Course

This winter course is focused on the building of knowledge in the field of business performance evaluation and management using frontier techniques. Its aims are to enable participants, including PhD students and other advanced study cycles, as well as practitioners from different areas of technical and scientific expertise, to acquire and extract knowledge for performance evaluation using frontier techniques from non-parametric (Data Envelopment Analysis - DEA) and parametric (Stochastic Frontier Analysis - SFA) methods and their application in a diversity of business contexts, using software such as R studio and Stata, among others.

A large part of the course will be devoted to Data Envelopment Analysis (DEA), a non-parametric method that evaluates the efficiency of similar decision-making units (DMUs) with multiple inputs and outputs. By contrast with parametric methods, Stochastic Frontier Analysis (SFA), the DEA method avoids prior assumptions about functional form or distribution. It establishes an empirical production frontier using observed DMU data, representing the multiple input-output relationship. Each DMU is evaluated against this frontier to determine efficiency, handling multiple inputs/outputs, benchmarking potential and flexibility in addressing efficiency issues such as cost, production and allocative efficiency.

Taking a strong theoretical and practical approach, the entire programme has been structured to showcase, discuss and use both classic approaches and new developments in frontier analysis applied to different organisational contexts in a meaningful way. In practical terms, throughout the programme participants are exposed to real-life case studies, with varying degrees of complexity, for which they are required to design, test and evaluate models capable of extracting valuable knowledge and providing support for decision-making based on proactive and data-driven efficiencies, such as the outcomes and inputs used in the performance frontier.