Environmental Performance Evaluation of the Korean Manufacturing Industry Based on Sequential DEA

Abstract

This study’s aim is to examine the environmental performance of the South Korean manufacturing industry and suggest performance-oriented policies. The manufacturing industry is classified into seven sub-sectors based on individual sectoral differences among firms. For this purpose, a sequential generalized directional distance function and the Sequential Malmquist-Luenburger (SML) index are used with the assumption of no deterioration in technology over time. The SML is decomposed into two indices: efficiency change (EC) and technical change (TC). The empirical results showed an average increase of 0.3% in environmental productivity measured by the SML over the whole period. Although the overall average value is low, it showed a 0.8% increase after 2015, implying that ETS policy has enhanced environmental productivity. From the decomposition of the SML, it was also found that the EC index (−1.1%) was comparatively lower than the TC index (1.5%) over seven years, implying that the innovation effect leads the environmental productivity of the Korean manufacturing industry. With regard to individual sectors, the seven sub-sectors showed quite different patterns in their performance. Therefore, not only should firms in each sector make an effort to enhance their performance, but the government also needs to support specialized measures to enhance firms’ overall competitiveness.

The Effects of Environmental Regulations on the Manufacturing Industry’s Performance: A Comparison of Green and Non-Green Sectors in Korea

“…Previous research using Korean data includes that by Kang and Lee [27], Kim and Ha [9], Kang and Jo [28], Jung [29], and Lee and Choi [30]. According to Kang and Jo [28] the enforcement of the Indoor Air Quality Control Act enabled about 652 people to find jobs during 2015-19.…”

“…The GHG Inventory and Research Center was also established to construct GHG data and manage emissions according to Article 45 [2,31]. Lee and Choi [30] show that ETS implemented in 2015 promoted technical changes in the manufacturing industry, but this top-down approach by the government may have limits in enhancing environmental efficiency. Jung [29] suggests that LCGG was based on economic growth rather than ecological modernization and green jobs were only created in traditional environmental protection and pollution reduction areas.…”

A Study of the Feasibility of International ETS Cooperation between Shanghai and Korea from Environmental Efficiency and CO2 Marginal Abatement Cost Perspectives

“…The speed of CO 2 emissions increase of Korea ranked second among the OECD countries after Turkey's (50.5%). According to the analysis, South Korea's high dependence on coal is the main reason for its high carbon dioxide emissions, as well as the main cause of air pollution and haze [23]. In 2009, the Korean government enacted a "low-carbon green growth" national carbon emissions reduction policy.…”

Evaluation of Enterprise Learning Performance in the Process of Cooperation Innovation Using Heronian Mean Operator

“…Moldavska and Welo [29] proposed a new method to assess the sustainability of manufacturing enterprises and thought that enterprise sustainability assessment in manufacturing industry is a tool framework to guide organizations towards sustainable practices. Lee and Choi [30] decomposed the sequential Malmquist-Luenburger index into two indicators, efficiency change and technology change, and evaluated the environmental performance of Korean manufacturing industry using Malmquist-Luenburger index and generalized directional distance function. In addition, the above traditional performance evaluation methods including AHP [11], BSC [31], and EVA [32] mostly assume that attributes are independent of each other.…”

“…In the process of enterprise cooperative innovation, the evaluation results of learning performance have an important impact on the adjustment of cooperation mode, cooperation content, and cooperation strategy. The application of reasonable method is one of the important guarantees for the accuracy and rationality of the performance evaluation results [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Therefore, it is necessary to further study the practical application of the evaluation of enterprise learning performance in the process of cooperative innovation by considering the interaction between attributes and determining a scientific and reasonable sequential weight vector.…”