Impact of input substitution and output transformation on data envelopment analysis decisions

Abstract

Data envelopment analysis (DEA) can aid managerial decision-making because it offers an opportunity to measure organizational performance in a holistic manner, aggregating data from partial indicators into a single comprehensive measure. However, there are some methodological hazards associated with the use of DEA that are especially relevant to managerial decisions, but which have been largely ignored in the literature. Herein, we identify and show the impact of a ubiquitous methodological hazard in DEA modelling – the economic assumptions regarding input substitutions and output transformations.