Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review

Scientific research input and output efficiency evaluation of universities in Chengdu-Chongqing economic circle based on data envelopment analysis

The study takes 10 urban agglomerations in China as the research object, focusing on the Chengdu-Chongqing urban agglomeration, and applies Data Envelopment Analysis (DEA) to measure and compare their scientific input and output efficiency of universities. First, this paper analyzes the input and output of scientific research in universities in major provinces in China in detail. Second, according to the construction principles of the indicator system, using qualitative interview to construct evaluation indicators of university research efficiency. Third, using DEA method, first analyze the input and output profile of some urban agglomeration universities such as Chengdu-Chongqing economic circle, measure and compare their research input and output efficiency, then compare and analyze the research efficiency of research-type sample universities within Chengdu-Chongqing economic circle, and conduct a projection study of non-DEA effective sample universities. The main conclusions are as follows: first, the average efficiency of scientific research in universities in Chengdu-Chongqing and other urban agglomerations in 2020 has slightly increased compared with that in 2016, but the gap between urban agglomerations is prominent, and the innovation level of scientific research in higher education institutions in urban agglomerations needs to be improved. Second, there is a mismatch between the themes of research, funding and human resources in research-oriented universities in the Chengdu-Chongqing economic circle. Third, there is considerable room for improvement in research efficiency, and the influence of scale on overall efficiency is weak. We found that excessive investment in scientific research in universities is the main reason for the non-effect.

Comprehensive performance evaluation of coordinated development of industrial economy and its air pollution control

Exploring coordinated pathways that can promote not only the sustainable development of the industrial economy but also air quality is of great significance for the prevention and control of air pollution in China. Currently, the joint development pathways of the industrial economy-environment nexus remain unclear and poorly evaluated. In this study, we proposed a comprehensive performance evaluation combining objective and subjective weighting to identify industrial enterprises' economic-environment nexus benefits. It would be one of the most important steps to explore the coordinated pathways. Based on data envelopment analysis (DEA), the proposed method integrated with the index integration was used to evaluate the comprehensive performances of 41 industrial sectors in China's 13th five-year plan (2016-2020). Evaluation results showed that the comprehensive performances of the economy-environment nexus of the industrial sectors varied significantly, with the five-year average comprehensive technical efficiency (TE) of 0.11-1. Overall, the best two performances were realized by the industries of equipment manufacturing and living consumption, whereas the worst one belonged to the industry of bulk raw materials, with average comprehensive TE values of 0.50, 0.43, and 0.19, respectively. The results of the quantitative evaluation were consistent with those of the qualitative analysis in terms of the developmental status of the industrial sectors. According to the analyses of pure technical efficiency and scale effect, the proposed method identified the industrial sectors with the highest developmental value and with the highest need to control air pollution. Compared with those of the original DEA model, the results of the proposed method showed pronounced differences in terms of the performances of industrial sectors with high energy consumption and high particulate matter (PM) emissions and with low energy consumption and low PM emissions. The proposed evaluation method combining the weighting was suitable for identifying the comprehensive performance of the industrial economy-environment nexus and provides the basis for the prevention and control of air pollution.

Evaluating the total-factor efficiency of E3 in oil-producing countries, with emphasis on education

Global warming is one of the greatest challenges of the contemporary world. Overcoming this problem requires a global determination in energy management and a significant reduction in the use of fossil fuels worldwide. The objectives of this article are to investigate the role of education in economic growth and to evaluate the total-factor energy, economic and environmental efficiency (E3) of oil-producing countries and productivity changes between 2000 and 2019. These countries were divided into two categories of middle- and high-income ones. The panel data model was used to estimate the role of education in the countries' economic growth, and the data envelopment analysis (DEA) method was used to measure their total-factor efficiency (E3). The findings indicate that education has a positive role in economic growth. In general, Norway proved to be efficient in all indicators of e1, e2, e3, and E3. The worst performance in e1 belonged to Canada (0.45) and Saudi Arabia (0.45); in e2, to Algeria (0.67) and Saudi Arabia (0.73); in e3, to the USA (0.04) and Canada (0.08); and in E3, to Canada (0.46), Saudi Arabia (0.48), and the USA (0.64). The average total-factor efficiency of all indicators for the selected countries was low. Average changes in total-factor productivity and technological changes for all the selected countries had decreased in e1 and e3 but improved in e2 and E3 during the studied period. The changes in technical efficiency also decreased during the period. Moving towards a low-carbon economy, developing creative and environment-friendly technologies, more investment in clean and renewable energy, and creating diversity in production, especially for OPEC and countries with single-product economies, are some of the ways suggested for improving E3 efficiency in the countries.

Energy efficiency evaluation, changing trends and determinants of energy productivity growth across South Asian countries: SBM-DEA and Malmquist approach

Energy efficiency is widely regarded as the most efficient means of supplying additional energy to meet the rising demand. However, extensive energy consumption causes greenhouse emissions, environmental destruction, and a decrease in energy efficiency (EE). This study investigates the role of energy efficiency and productivity growth in the ecological improvement of South Asia. Moreover, it evaluates the determinants (efficiency change or technology change) of energy productivity change across different SA (South Asian) countries. To estimate the energy efficiency and productivity change, we employed SBM-DEA and Malmquist Productivity Index methods with three inputs (capital stock, labor, and energy consumption), a single desirable output (gross domestic product) and a single undesirable output (CO2 emissions) on the well-extended dataset (2001-2019) for 6 South Asian countries. Furthermore, to check the impact of energy policy (2010) over the study period, the statistical significance of the change in mean scores for energy efficiency and productivity over two time periods (2001-2010 and 2011-2019) and six countries was examined using the Mann-Whitney U and Kruskal-Wallis tests. Results reveal that the average EE score of all 6 SA countries for the study period is 0.7278. This score shows that SA countries still have the potential of 27.22% to improve their energy efficiency to minimize the inputs to get the optimum output level with the least emissions. The primary determinant of energy productivity growth is technological change instead of efficiency. The average energy efficiency level is significantly different for two time periods, 2001-2010 and 2011-2019. Results conclude that energy efficiency and productivity in SA declined over the period, and potential causes are an inefficiency in the energy conversion process, extensive utilization of inputs, and less output growth.

Comprehensive Environmental Assessment Index of Ecological Footprint

This paper aims to contribute to the growing body of research literature on assessing environmental efficiency by introducing a new key performance indicator (KPIs) in more complete and dependable aspects of ecological footprint indices. For this purpose, the DEA model considering three inputs (energy consumption, labor force, and capital stock), one desirable output (GDP), and different undesirable outputs (CO₂ emissions, ecological footprint indicators) are applied to 27 OECD countries from 2000 to 2017. According to the results, Norway, Luxemburg, and United Kingdom are the most environmentally efficient countries in terms of environmental efficiency and ecological footprint efficiency. On the other hand, the lowest environmental and ecological footprint efficiencies were in countries like Lithuania, Slovak, Czech, Estonia, and the USA. In addition, these nations fare poorly regarding their carbon footprint and farmland efficiency. In further detail, Lithuania, South Korea, Portugal, and Spain have a critical status in fishing ground efficiency, while the forest area efficiency is very acute in Estonia, Latvia, Lithuania, and Czech.

A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability

Safeguarding natural resources and energy is essential to ensure food security for future generations. Given the increase of published papers in the agricultural field applying Data Envelopment Analysis (DEA), this review seeks to address the special requirements of this methodology when implemented in the agricultural sector as well as to classify papers under sustainability aspects (economic, environmental, social). More specifically, 120 papers from Scopus and Web of Science databases were included in this review by using PRISMA methodology, and they were tested in the following groups (i) General information, (ii) DEA implementation, (iii) DEA extensions, (iv) Data type, (v) Data collection and processing, and (vi) Sustainability dimensions. Results indicate that there is a great need for weights use when performing DEA in the agricultural sector, to acquire results with greater explanatory power. Moreover, systematic data collection of multiple factors could lead to the implementation of complex methodologies, providing feasible solutions to the involved stakeholders. Lastly, the social aspect is the least represented dimension out of the three aspects of sustainability, indicating the need for the integration of social factors in such analyses, especially when DEA is used to create a policy framework in a specific area.

Impact of "Three Red Lines" Water Policy (2011) on Water Usage Efficiency, Production Technology Heterogeneity, and Determinant of Water Productivity Change in China

This research evaluates the effects of the Three Red Lines policy on water usage efficiency (WUE), production technology heterogeneity, and water productivity change in 31 Chinese provinces between 2006 and 2020. SMB-DEA, Meta-frontier analysis, and Malmquist-Luenberger index (MLI) techniques were employed for estimation. Results revealed that the mean WUE (2006-2020) in all Chinese provinces was 0.52, with an improvement potential of 48%. Shanghai, Beijing, Shaanxi, and Tianjin were the best performers. The WUE scores before (2006-2011) and after (2012-2020) water policy implementation were 0.58 and 0.48, respectively; on average, there was more than a 9% decline in WUE after the implementation of the water policy. The eastern region has the most advanced water utilization technology as its technology gap ratio (TGR) is nearly 1. The average MLI (2006-2020) score was 1.13, suggesting that the MLI has increased by 12.57% over the study period. Further technology change (TC) is the key predictor of MLI growth, whereas efficiency change (EC) diminished from 2006 to 2020. The mean MLI score for 2006-2011 was 1.16, whereas the MLI Score for the period 2012-2020 was 1.10, indicating a modest decline following the implementation of the water policy. All three Chinese regions experienced MLI growth during 2006-2020, with TC the main change factor.

A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends

DEA, incepted in 80s, has emerged as a popular decision-making technique, for determining the efficiency of similar units. Due to its simplicity and applicability, DEA has gained the attention of scientists and researchers working in diverse areas, which has contributed towards a rich literature both in terms of theoretical development as well as different applications. This paper tries to bring together the near 40 years of existence of DEA in a concise format by discussing the popular DEA models, their advantages and shortcomings, and different applications of DEA. It also provides a brief bibliometric analysis to highlight the development of DEA over the years in terms of publication trends, highly cited papers, journal citation, etc.

Measuring the Efficiency of Energy and Carbon Emissions: A Review of Definitions, Models, and Input-Output Variables

The importance and urgency of improving energy and carbon emissions efficiency in mitigating climate change and achieving carbon neutrality have become an increasingly relentless focus in recent years. Assessing the performance of energy saving and carbon emissions reduction is a significant necessity to achieve sustainable economic development. Therefore, from the perspective of production economics, this paper presents a review of the definition, models, and input-output variables for measuring total-factor energy efficiency and total-factor carbon emissions efficiency. Relevant literature in this field, published between 2006 and 2021, has been systematically analyzed using CiteSpace software, which includes a quantitative and visual review of a large body of published literature. This review found that the current definitions of total-factor energy efficiency and total-factor carbon emissions efficiency are confusing and misleading. Furthermore, future research on energy saving and carbon emissions reduction should incorporate subject areas such as economics, energy, and ecology.

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.

By-production of electricity and particulates: efficiency of Indian thermal power plants revisited

Purpose

This paper studies the efficiency of Indian coal-fired thermal power plants (CTPPs) in by-production of electricity and particulates also known as Suspended Particulate Matter (SPM).

Design/methodology/approach

A non-radial directional distance function is optimized using data envelopment analysis to enumerate the overall inefficiency of CTPPs and its components in recent times. Further, second-stage regression analysis is conducted to identify factors that affect the inefficiency of plants.

Findings

The low inefficiency score for electricity generation suggests that most CTPPs operate close to the good output frontier. A high degree of emissions inefficiency is a challenge for Indian CTPPs. Ever-rising coal use inefficiency is a hindrance to control SPM emissions. The second stage regression analysis concludes that factors like ownership and capacity utilization play vital roles in determining a plant’s inefficiency level. Privately owned CTPPs have performed better in terms of technical inefficiency and emission inefficiency than plants owned by Central and State governments.

Originality/value

To the best of the authors’ knowledge, this study is one of the few published works that benchmark the productive and environmental performance of Indian CTPPs.

Evaluating the Context-Dependent Total-Factor Energy Efficiency of Counties and Cities in Taiwan

This paper applies the context-dependent total-factor energy efficiency (CD-TFEE) to determine the multi-layer disaggregate energy efficiency frontiers of twenty administrative regions in Taiwan for the year of 2016. The CD-TFEE overcomes the shortcoming of conventional TFEE index that TFEE is not able to find the “closest target” for each inefficient region in the short run. Furthermore, the CD-TFEE scores here deal with four types of energy inputs (electricity for production, electricity for household and non-household lighting, diesel sales, and gasoline sales), illustrating that multi-layer TFEE frontiers for each energy input in the case of Taiwan can be computed. Empirical results indicate that there are three levels of TFEE frontiers for electricity for production and four levels for other types of energy inputs. In addition, New Taipei City, Taipei City, Keelung City, and Penghu County are at the top level of TFEE frontier for all four energy inputs. This paper also demonstrates that the CD-TFEE procedure generates results different from the CD-DEA introduced by Seiford and Zhu (2003).

The Effect of Marshallian and Jacobian Knowledge Spillovers on Jobs in the Solar, Wind and Energy Efficiency Sector

The purpose of this paper is to establish if Marshallian and Jacobian knowledge spillovers affect job creation in the green energy sector. Whether these two effects exist is important for the number of jobs created in related fields and jobs pushed away in other sectors. In the analysis, the production efficiency, in terms of jobs and job spillovers, from inventions in solar, wind and energy efficiency, is explored through data envelopment analysis (DEA), based on the Malmquist productivity index, and tobit regression. A panel dataset of American and European firms over the period of 2002–2017 is used. The contribution to the literature is to show the role of the spillovers from the same technology sector (Marshallian externalities), and of the spillovers from more diversified activity (Jacobian externalities). Since previous empirical evidence concerning the innovation effects on the production efficiency is yet weak, the paper attempts to bridge this gap. The empirical findings suggest negative Marshallian externalities, while Jacobian externalities have no statistical impact on the job creation process. The findings are of strategic importance for governments who are developing industrial strategies for renewable energy.

Dual Efficiency and Productivity Analysis of Renewable Energy Alternatives of OECD Countries

This paper examines the dual efficiency of bioenergy, renewable hydro energy, solar energy, wind energy, and geothermal energy for selected OECD countries through an integrated model with energy, economic, environmental, and social dimensions. Two questions are explored: Which renewable energy alternative is more dual efficient and productive? Which renewable energy alternative is best for a particular country? Data envelopment analysis (DEA) is used for the efficiency evaluation, and the global Malmquist productivity index is applied for productivity analysis. Results indicate bioenergy as the most efficient renewable energy alternative with a 20% increase in average efficiency in 2016 compared to 2012. Renewable hydro energy, wind energy, and solar energy show a 17.5%, 16%, and 11% increase, respectively. The average efficiency growth across all renewable energy alternatives signifies major advancement. Country performance in renewable energy is non-monolithic; therefore, they should customize their renewable energy portfolio accordingly to their strengths to enhance renewable energy efficiency. Renewable hydro appears to have the most positive productivity change in 2016 compared to 2012, while solar energy regressed in productivity due to its scale inefficiency. All renewable energy alternatives have relatively equal average pure efficiency change. The positive trend in efficiency and productivity provides an incentive for policy makers to pursue further development of renewable energy technologies with a focus on improving scale efficiency.

A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy

This paper presents the use of multi-criteria decision-making (MCDM) for the evaluation of smart cities. During the development of the method, the importance of the decision-making approach in the linear ordering of cities was presented. The method of using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was proposed for the preparation of ranking. The method was verified by the application in the measurement of energy performance in smart cities. The authors conducted a literature review of research papers related to urban energy and MCDM published in the period from 2010 to 2020. The paper uses data from the World Council on City Data (WCCD). The research conducted allowed for the identification of the most popular MCDM techniques in the field of urban energy such as TOPSIS, AHP and DEA. The TOPSIS technique was used to organize and group the analyzed cities. Porto took the top position, whereas Buenos Aries was the last.

Energy Efficiency Management across EU Countries: A DEA Approach

We examine energy efficiency in the European Union (EU) using an integrated model that connects labor and capital as production factors with energy consumption to produce GDP with a limited amount of environmental emissions. The model is a linear output-oriented BCC data envelopment analysis (DEA) that employs variables with non-negative values to calculate efficiency scores for a sample of 28 EU member states in the period 2010–2018. We assume variable returns to scale (VRS) considering the natural inclination of countries to adopt technologies that allow them to produce higher outputs over extended periods of time, which we observed through the trends of increasing labor productivity and decreasing energy intensity over the analyzed period. The average EU inefficiency margin in the sample period is 16.0%, with old member states being significantly more efficient (4.2%) than new member states (29.5%). Energy efficiency management does not improve over time, especially in new member states that had substantially worse efficiency by 2018 than in 2010. New member states could increase energy efficiency through the liberalization of the energy market, the support of energy-saving and technologically advanced industries, and the introduction of measures aimed at increasing the productivity levels in the economy.

Environmental Efficiency Evaluation in the Top Asian Economies: An Application of DEA

Sustainable development has become a global catchphrase in the recent development age. This leads to the growth of various methodologies in evaluating environmental efficiency, such as the Data Envelopment Analysis (DEA) method. The purpose of this study is to propose an extended DEA model, i.e., the undesirable output model, in measuring the relative eco-efficiency scores across nations. The study collected the data of inputs, namely bad outputs and good outputs of the top 20 Asian economies in the period of 2005–2019, and then estimated the environmental efficiency of each country and classified them. The results have shown that there are four nations having higher average environmental efficiency than others. Japan is a good example of sustainable development that simultaneously balances economic development and environmental protection. The study has also discussed possible solutions for improvement to the group of nations with low environmental efficiency. Contributing to applying a novelty extended DEA model, this work recommends a more precise model, taking the weight of outputs into account for further studies.

Yangtze River Economic Belt environmental remediation efficiency based on an input-output optimization analysis

Although the Yangtze River Economic Belt (YREB) has been metaphorized as China's "arrow" to the world as it generates nearly half of the nation's gross domestic product, the region has also suffered immense environmental degradation during its development process. This paper uses environmental data from 2003 to 2013 of the YREB's nine provinces and two municipalities and investigates environmental remediation efficiency for the region. Results illustrate that (1) the efficiency of the YREB is very low as over the study period, only three provinces had mean environmental remediation values that could be classified as "effective," leaving the remaining six provinces and two municipalities as "ineffective"; (2) environmental efficiencies of the studied provinces and municipalities became increasingly polarized; (3) from 2003 to 2013, environmental efficiencies in the region have deteriorated; (4) the principal reason for environmental remediation ineffectiveness was due to a combination of redundant resource investments, excessive pollutant discharge, low industrial waste comprehensive utilization ratios, and non-municipal environmental remediation standards. To illuminate development pathways for the ineffective provinces and municipalities of the YREB, essential factors in the optimization of economic management investments are proposed.

Performance Assessment of Japanese Electricity and Gas Companies during 2002–2018: Three DEA Approaches

This study has compared Japan’s major electricity and gas companies in terms of their corporate performance measures from 2002 to 2018 using three types of Data Envelopment Analysis (DEA) approaches. We develop a new type of efficiency measures and indexes for DEA and then compare the performance of major electric power companies and city gas companies by examining a recent data set that include years after the Fukushima Daiichi Nuclear Power Plant accident. The data set incorporates the number of patents as an output that represents companies’ capability for technology innovation to investigate intertemporal changes of efficiency through index measures. The results provide us with two important findings. First, the electricity industry has experienced long-term difficulty due to the nuclear plant disaster; while the gas industry experienced less difficulty from the accident. Second, both industries have been gradually improving performance measures in recent years. However, the gas industry has outperformed the electricity industry. From the results, this study discusses important policy implications for Japan’s energy utility industry and academic research on the industry.

Energy Efficiency in OECD Countries: A DEA Approach

This paper deals with energy efficiency examined through an integrated model that links energy with environment, technology, and urbanisation as related areas. Our main goal is to discover how efficiently developed countries use primary energy and electricity (secondary energy). We additionally want to find out how the inclusion of environmental care and renewable energy capacity affects efficiency. For that purpose, we set up an output-oriented BCC data envelopment analysis that employs a set of input variables with non-negative values to calculate the efficiency scores on minimising energy use and losses as well as environmental emissions for a sample of 30 OECD member states during the period from 2001 to 2018. We develop a couple of baseline models in which we find that countries have mean inefficiency margins of 16.1% for primary energy and from 10.8 to 13.5% for electricity. The results from the extended models show that taking care about environment does not affect efficiency in general, while the reliance on energy produced from renewable sources does slightly reduce it.

Regional Diversification of Potential, Production and Efficiency of Use of Biogas and Biomass in Poland

Energy obtained from renewable sources is an important element of the sustainable development strategy of the European Union and its member states. The aim of this research is, therefore, to assess the potential and use of renewable energy sources and their effectiveness from the regional perspective in Poland. The research covered the years 2012 and 2018. The diversification of production and potential of renewable energy sources was defined on the basis of biogas and biomass. Calculations made using the data envelopment analysis (DEA) method showed that, in 2012, only three voivodeships achieved the highest efficiency in terms of the use of biogas and biomass resources; in 2018, this number increased to four. Comparing the effective units in 2012 and 2018, it can be seen that their efficiency frontier moved upwards by 56% in terms of biogas and 21% in terms of to biomass. Despite a large relative increase in the production of heat from biogas by 99% compared to the production of heat from biomass by 38%, the efficiency frontier for biogas did not change considerably. It was found that the resources of solid biomass are used far more intensively than the resources of biogas. However, in the case of biogas, a significant increase in the utilization of the production potential was observed: from 3.3% in 2012 to 6.4% in 2018, whereas in the same years, the utilization of solid biomass production potential remained at the same level (15.3% in 2012, 15.4% in 2018). It was also observed that, at the level of voivodeships, the utilization of biogas and biomass production potential is negatively correlated with the size of this potential. The combined potential of solid biomass and biogas can cover the demand of each of the studied regions in Poland in terms of thermal energy. The coverage ranges from 104% to 1402%. The results show that when comparing biomass and biogas, the production of both electricity and heat was dominated by solid biomass. Its high share occurred especially in voivodeships characterized by a high share of forest area and a low potential for biogas production (Lubuskie Voivodeship, Zachodniopomorskie Voivodeship).