Operational Performance Evaluation of Korean Ship Parts Manufacturing Industry Using Dynamic Network SBM Model

The purpose of this study is to analyze the efficiency and productivity of the Korean ship parts manufacturing industry. To this end, the manufacturing process was divided into two stages (operating activities, financial activities), and the Dynamic Network SBM model and Malmquist Productivity Index were used. We collected analysis data from KIS-VALUE, and analyzed 40 companies from 2014 to 2020. As a result of the analysis, from 2014 to 2017, the average operating efficiency was 0.7825, the average financial efficiency was 0.5208, and the average total efficiency was 0.4537. It was found that improving efficiency requires improving both activities simultaneously, rather than focusing on a specific activity. Operating activities DMI was 1.0025, financial activities DMI was 0.9236, and OMI was 0.9464. In order to improve OMI, it is necessary to improve the financial activities DMI, which is the cause of the decrease in productivity. In order to improve financial activities DMI, government policy or technology change to improve DFS was found to be necessary. Finally, the effect of environmental factors on efficiency was analyzed by tobit regression. It was found that Firm Size had a negative (−) effect on efficiency, and Firm Age had a positive (+) effect on efficiency. The analysis results of this study will help to understand the relationship between input and output, which has been treated as a black box in the manufacturing industry, in two stages; and this will serve as a guideline for those working in Korea’s ship parts manufacturing industry to establish policies.

Benefit Evaluation of Real Estate Industry Based on SBM Model

According to the situation of real estate industry in different provinces and cities, the benefit is different, and the benefit of real estate industry in some regions is low. Based on the statistical data of real estate industry in various regions, this paper selects nine indicators, such as the number of enterprises, the average number of employees, the land purchase area (10000 square meters) in this year, to evaluate and analyze the benefit of real estate industry in 31 regions of China by using two-stage super efficiency model. The results show that the input-output of the real estate industry in 17 regions is effective, and the remaining 14 regions are DEA ineffective. The reasons for the inefficiency of the input-output are analyzed, and some suggestions to improve the efficiency are given.

Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis

The concept of eco-efficiency has recently become an issue of great importance due to the growing trend of environmental degradation, and many approaches based on Data Envelopment Analysis (DEA) are used in the literature to evaluate the environmental performance of economic systems. However, research to date has paid little attention to the possibility of extending the DEA approach to the problem of measuring the economic feasibility of eco-efficiency improvement. The main aim of this study is to evaluate the efficiency of investments focused on improving the eco-efficiency of the regional economy in Russia using the DEA approach. The various types of costs for environmental protection measures are considered as inputs and the annual decrease in specific environmental impacts of the regional economy are considered as outputs of DEA models. This is different from previous research, which generally focused on environmental efficiency only, omitting the integration of economic aspects in eco-efficiency measures. This study compares three different modifications of basic DEA models in the context of technical complexity and practical feasibility. The results show that the efficiency of regional environmental management in many Russian regions has a great potential for improvement. From a practical point of view, the Slack-Based Measure (SBM) model provides the most accurate results for policy applications. Unlike other ratings, the DEA-SBM model may stimulate an optimization of environmental protection spending and the introduction of technological and organizational eco-innovations.

Influencing Factors Analysis on Provincial Difference of Rural Energy Efficiency in China Employing Super Efficiency SBM Model and Global Malmquist-Luenberger Index

Given the current circumstance of increasingly severe resource and environmental deterioration, the progress of Chinese rural energy efficiency has a remarkable impression on Chinese future high-quality development. Energy consumption in rural areas accounts for a considerable proportion, so it is imperative to make a specific and accurate assessment of rural energy efficiency. This paper abandons the traditional method of regional division and separates China into eight economic zones. First of all, this paper applies Super-SBM model to calculate the rural energy efficiency and constructs a Global Malmquist-Luenberger (GML) Index based on 2008–2018 panel data. Subsequently, GML is decomposed into technical efficiency change index (GMLEC) and technological progress change index (GMLTC) to analyze green total-factor productivity (GTFP) in rural areas. Eventually, the GML and its decomposition terms of eight economic zones are explained by practicing a cumulative multiplication method from 2008 to 2018. The consequences of employing panel data of region prove that: (1) There is a severe regional imbalance of Chinese rural energy efficiency. (2) The rural energy efficiency in the northwest and southwest (western region) is higher than the Middle Yangtze River and the Middle Yellow River (central region). (3) GMLTC has a significant impact on GTFP.