Facet analysis on BCC model in DEA using artificial DMUs

This paper discusses a new amendatory suggestion for frontier of BCC model in Data Envelopment Analysis (DEA). The BCC model frontier may contain some weak efficient parts in input or output orientation, and Decision Making Units (DMUs) which are compared with these parts of frontier or placed on them take a bias efficiency. Here, using estimation of returns to scale for each efficient DMUs, allowable supporting hyperplanes replaced by weak parts of frontier. Computational testing with real world data sets with up to 40 decision making units, indicate the employing of this modification.