Inverse data envelopment analysis for operational planning: The impact of oil price shocks on the production frontier

Abstract

Inverse data envelopment analysis (DEA) is a useful planning tool, especially when it is combined with frontier changes that accurately reflect reality. This paper proposes an inverse optimization model for operational planning by taking into account frontier changes in conjunction with environmental factors. The aim is not only to present a computational procedure of a new measure to properly capture the effective frontier changes, but more importantly to demonstrate how frontier changes observed in the past can be utilized to provide insights into estimation of the future production frontier. In essence, the proposed model is intended to help establish realistic goals for operational planning practices. The model is applied to the Korean natural gas industry as an empirical demonstration.