The Need for a New Energy Performance Balance in Japan: Combination of an Adjusted-Improvement Model with a CCR Model

Abstract

This chapter aims to present an application result of the Adjusted-Improvement (AI) approach to DEA for generating an appropriate efficiency-improvement projection model. We propose a Target-Oriented (TO) DFM model that allows reference points that remain below the efficiency frontier. Our TO-DFM model specifies a Target Efficiency Score (TES) for inefficient DMUs. This model is able to compute an improvement projection based on an input reduction value and an output increase value in order to achieve a TES. However, in reality, these values may represent an infeasible case; for example, a Networking Rate may be required of more than 100% in the improvement projection, but this would exceed a physical limit. Therefore, we propose an Adjusted-Improvement (AI) approach based on the TO-DFM model. The AI approach specifies an adjustment in input/output items based on the absence or presence of a DMU’s improvement limit. This approach can compute an input reduction value and an output increase value in order to achieve a TES that maintains an improvement limit condition. This chapter evaluates the efficiency of new energy in Japan based on DEA and the abovementioned Adjusted-Improvement TO-DFM model to produce a realistic efficiency-improvement projection. The focus will be on three input cost criteria (cost of power generation, energy payback time, and CO2 emissions) and one output performance criterion (Networking Rate). Based on the results of the performance analysis and the efficiency-improvement projection of new energy performance needs in Japan, we offer a quantitative contribution to efficiency rise in energy-environment policy in Japan.