Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure

Abstract

Improving energy efficiency has been widely regarded as one of the most cost-effective ways to improve sustainability and mitigate climate change. This paper presents a sequential slack-based efficiency measure (SSBM) application to model total-factor energy efficiency with undesirable outputs. This approach simultaneously takes into account the sequential environmental technology, total input slacks, and undesirable outputs for energy efficiency analysis. We conduct an empirical analysis of energy efficiency incorporating greenhouse gas emissions of Korean power companies during 2007-2011. The results indicate that most of the power companies are not performing at high energy efficiency. Sequential technology has a significant effect on the energy efficiency measurements. Some policy suggestions based on the empirical results are also presented.

The Economic Efficiency of Urban Land Use with a Sequential Slack-Based Model in Korea

“…Data envelope analysis (DEA) was used to analyze the complex process of land transformation policies, because DEA can deal with multiple inputs and outputs simultaneously and does not require any prior information on the theoretical frame of the production function [1,36]. In general, DEA models assume an efficiency gap between optimal and actual resource allocation, which is called the slack variable, implying the output shortage or input surplus in the decision making unit (DMU) [1,36].…”

“…In general, DEA models assume an efficiency gap between optimal and actual resource allocation, which is called the slack variable, implying the output shortage or input surplus in the decision making unit (DMU) [1,36]. Since the traditional radial DEA models do not consider these slack variables in the objective function, it can produce inaccurate results in efficiency evaluations.…”

“…Since the traditional radial DEA models do not consider these slack variables in the objective function, it can produce inaccurate results in efficiency evaluations. In order to overcome this difficulty, a new approach called the non-radial and non-parametric slack-based measure (SBM) model has been developed [1,36], incorporating the slack variables directly into the objective function. Considering the dynamic change of production technology during the research period, the sequential slack-based measure (SSBM) model will be introduced to incorporate the concept of sequential production technology over time.…”

“…Based on Zhang's and Xie's approaches on SSBM [1,36], we try not only to consider industrial wastewater and industrial sulfur dioxide as undesirable outputs, but also to add noise status to analyzes factors influencing ULUEE in Korea, and the feasibility of the deregulation policies on the green belts. Suppose for N Decision Making Units (DMUs), every DMU demands M inputs (x) for J desirable outputs (y) with K undesirable outputs (b) as well.…”

Measuring the Performance of Industrial Green Development Using a Non-Radial Directional Distance Function Approach: A Case Study of Jiangxi Province in China

“…Industrial capital data could not be obtained from the China Statistical Yearbook. Thus, we compute the data using the perpetual inventory method following Zhang and Kim (2014) [26]:…”