Environmental Efficiency Scores Research Articles

Global Energy Transition and the Efficiency of the Largest Oil and Gas Companies

The challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil and gas companies (OGC) are undergoing a gradual transformation into comprehensive energy corporations, aligning themselves with energy transition policies. This paper examines two types of efficiency measures—operational and environmental—for the 20 largest OGC during the period of 2010–2019. Secondly, this research aims to explore the effect of the global energy transition on both environmental and operational efficiency. Based on three estimation methods, two estimation steps are used in this research. In the first step, the True Fixed Effect (TFE) model and the Battese and coelli (1995) SFA model are applied to evaluate, measure and compare the environmental and operational efficiency scores. In the second step, the TFE model and GMM approach for the dynamic panel data model are used to explore, evaluate and verify the effect of global energy transition on the environmental and operational efficiency of the largest 20 OGC in the world. The results reveal that the average operational efficiency of major OGC measured using the BC.95 model and TFE model is 66% and 85%, respectively, and the overall average level of environmental efficiency for OGC over a 10-year period is 31% (based to B.C.95 model) and 13% (based to TFE model). Our findings reveal that biofuels, solar and hydropower contribute to promote the operational and environmental efficiency of the largest 20 OGC. However, the analysis suggests that while the global energy transition significantly influences and bolsters environmental efficiency, its effect on operational efficiency among these major OGC remains less pronounced and insufficient.

Non-farm income and environmental efficiency of the farmers: Evidence from India

In the face of various agro-climatic shocks when agricultural income becomes highly volatile, farmers often undertake multiple jobholding and engage in non-farm activities for income smoothing. The earnings from these activities are often used to purchase productivity enhancing agricultural inputs. In this context, the impact of non-farm income on intensification of agricultural inputs and the consequent impact on over-all farm efficiency is well documented in the literature. However, with a rapid rise in usage of agricultural inputs with environmentally detrimental impact, very little is known about whether non-farm income has any impact on farmers’ environmental efficiency-ability to reduce the amount of polluting inputs to the largest extent possible without reducing the amount of agricultural production. Our study fills the gap in the literature by analysing the impact of non-farm income on environmental efficiency of the farmers. We first estimate the environmental efficiency scores adopting the non-parametric data envelopment analysis (DEA) method and using a household level panel data from Village Dynamics of South Asia project on Indian states for a span of five years (2010–2014). We then estimate the impact of non-farm income on environmental efficiency using Instrumental Variable Tobit Model. Our results show that average environmental efficiency of the Indian farmers was 46 % during the study period indicating the fact that a reduction in polluting agricultural inputs by 54 % was possible without compromising the level of farm production. We also find that for 1 % increase in non-farm income, environmental efficiency of farmers rises by around 4 %. This reflects the environment friendly behaviour of farmers as a channel through which non-farm activities affect usage of environmentally linked inputs. These results provide vital policy insights in terms of how non-farm activities could be integrated with policies related to farming, in order to ensure sustainable agricultural practices.

Efficiency analysis and CO2 emission reduction strategies in the US forest sector: a data envelopment analysis approach

Industrial economic activities produce pollutants and environmentally sustainable production systems in forestry aim to minimize these undesirable outputs while maintaining high production and economic growth. In this contribution, we assume that in addition to plot-specific inputs and outputs, there are some contextual variables that may be exogenously fixed or may be under the control of the decision-makers. In this sense, we first propose a novel and practical approach to calculate environmental efficiency by reducing undesirable products. Then, we utilize an inverse data envelopment analysis (IDEA) model to effectively manage and reduce CO2 emissions. In doing so, the applied models have been utilized to evaluate the efficiencies of 89 forest plots in the USA. Given our estimations in a real application to the forest plots, the study revealed that the average environmental efficiency score is nearly 0.75 (out of 1). However, there is potential for improvement by adjusting the impacts of contextual factors, which could raise the score to approximately 0.8. Furthermore, the analysis indicates a positive correlation between ownership and environmental efficiency, suggesting that increased ownership leads to higher environmental efficiency. Conversely, temperature exhibits a negative correlation with environmental efficiency. Finally, the results obtained from the IDEA indicate that in order to reduce undesirable outputs by a specific level of 5–10%, it is necessary to decrease other inputs and outputs. This is because, under the assumption of weak disposability, reducing the level of undesirable outputs requires a reduction in certain factors that influence production capacity. In other words, achieving the desired reduction in undesirable outputs inevitably involves diminishing certain aspects of the production process. As the major conclusion, the emergence of IDEA as a powerful tool for sensitivity analysis, along with its flexible nature, offers exciting opportunities for research and practical applications in various fields, including forestry activities. It has the potential to enhance overall environmental efficiency and enable better control over GHG emissions levels.

Environmental efficiency in greenhouse tomato production using soilless farming technology

The environmental efficiency of agricultural production and the relationship between management type and monetary value of achieving environmental efficiency are important parameters to assess the competitiveness of farms. The objectives of the study were to (i) estimate the environmental efficiency of greenhouse tomato farms, (ii) explore the determinants of the environmental efficiency level of greenhouse tomato farms, and (iii) calculate the monetary value of providing less greenhouse gas emission (GHG) and effective waste management in greenhouse tomato farms. The research data were obtained from 42 professional and 55 semi-professional greenhouse farms producing tomatoes using soilless farming technology in Turkey by using questionnaires. The environmental impact of tomato production was assessed using Life Cycle Assessment (LCA). The environmental efficiency was estimated by using Data Envelopment Analysis (DEA), and the Tobit model was used to elicit the determinants of environmental efficiency. The results showed that 1.72 kg CO2-equivalents of GHG were emitted for 1 kg fresh tomatoes from the cradle to the farm gate, and 1753.1 tons of organic waste were generated. The average environmental efficiency score of the greenhouse farms was 0.86, while the score was higher for professional farms and glass greenhouses. The results also revealed that the monetary value of GHG reduction and composting of all organic wastes in the greenhouse tomato farms were 1037.14 and 5700 US dollars, respectively. The values were higher for the professional greenhouse farms and glass greenhouses. The variables of education level of farmers, the size of glass greenhouses, net income, waste recycling investment, environmental knowledge level of farmers, and presence of green production practices positively affected the environmental efficiency. The findings suggest that awareness, extension, and training activities should be organized to reduce the farm-level negative impact of environmental inefficiency. Shifting from a static cost impact paradigm to a dynamic environmental management paradigm in greenhouse tomato farms may improve environmental efficiency, especially in semi-professional farms, and increase the competitive power of greenhouse farms.

Favorable Fiscal Self-Sufficiency Enables Local Governments to Better Improve the Environmental Governance—Evidence from China’s Lower-Pollution Areas

With the rapid development of industrial economy, local governments in China have invested a large amount of financial funds in environmental protection. In the era of widespread use of clean energy, local governments have a greater responsibility to coordinate fiscal policies with industrial development policies to improve regional environment. Local governments with large fiscal surpluses would make more efforts to improve environmental efficiency, rather than attract heavily polluting industrial enterprises to develop their local economies, and more likely to promote the use of clean energy equipment and raise environmental awareness in government. This paper focuses on testing the impact of abundant fiscal revenue of local governments on the efficiency of regional environmental governance with the data in all prefecture-level cities of China’s Guangdong province from 2001 to 2020. We estimate local environmental governance efficiency score with super-efficiency SBM method, taking unexpected output into account. Then we find that fiscal affluence has significant positive effect on the efficiency of environmental governance and the environmental awareness of the government also has obvious help in improving local environmental efficiency. We hope that these findings will provide practical help for local governments to improve their fiscal policy agendas and the quality of environmental governance.

The influence of institutional quality on environmental efficiency of energy consumption in BRICS countries

It has been observed in the literature that efficient energy use reduces production cost and carbon emissions into the environment. This study further argues that institutional quality enhances environmental efficiency of energy consumption. Therefore, this study was carried out with the aim of exploring the influence of institutional quality on environmental efficiency of energy use in BRICS countries for the period from 2001 to 2020. A two-step procedure was carried out to achieve the objectives of this study. First, the environmental efficiency of energy consumption was estimated using the stochastic Frontier analysis (SFA) technique. The results of the SFA approach show that the average environmental efficiency of energy use in BRICS countries is 61%, ranging from 37.5 to 100%. Furthermore, there is 39% room for improvement in environmental efficiency of energy use in BRICS countries. Moreover, the SFA results also indicate that South Africa has the highest average environmental efficiency, and China has the lowest environmental efficiency score among BRICS countries. Second, this study employed the system GMM technique to explore the impact of institutional quality on environmental efficiency of energy consumption in BRICS countries. The results of the system GMM show that institutional quality plays a significant role in improving environmental efficiency of energy consumption in BRICS countries. Finally, this study recommends some policy measures based on the study’s findings to improve environmental efficiency of energy consumption.

Understanding water-energy nexus in drinking water provision: An eco-efficiency assessment of water companies

Understanding water-energy nexus in the provision of drinking water services is a challenge which has outstanding relevance in the current climatic emergency. Environmental efficiency and eco-efficiency assessment of water companies are two useful tools to address this challenge. In this study, we estimated hyperbolic and enhanced hyperbolic distance functions to compute the potential reduction in greenhouse gas (GHG) emissions and energy costs in the provision of drinking water. The empirical application focused on the English and Welsh water companies over 2011-2019. Average environmental efficiency and eco-efficiency scores were 0.920 and 0.962, respectively which indicates that water companies performed well but there is room for improvement. Moreover, due to the economies of scale, the cost of reducing GHG emissions was higher for water and sewerage companies than for water only companies. The results and conclusions of this study allow better understanding of the relationship between the provision of drinking water, energy costs and GHG emissions.

Evaluating sustainable efficiency of decision-making units considering undesirable outputs: an application to airline using integrated multi-objective DEA-TOPSIS.

Sustainable development has gained significant attention in the literature due to the increased global awareness of environmental sustainability during the last decade. Sustainable development has three aspects, including economic, social, and environmental. The challenge of sustainable development is to establish a balance between these three aspects. Assessing the efficiency of a company contributes comprehensive information to improve its overall performance. Despite numerous studies in this field, the literature lacks studies that simultaneously consider all three aspects of sustainable development, especially the social aspect. The main objective of this paper is to calculate the technical, social, and environmental efficiency scores. We also introduce a new efficiency called sustainable efficiency that merges all three sustainable development aspects in one efficiency score. This study applies two existing data envelopment analysis (DEA) models to evaluate technical, social, environmental, and sustainable efficiencies. These models, namely the three-step method and the modified three-step method, are computationally intensive. Also, this paper introduces two new DEA models, namely the common weight goal programming DEA and the common weight DEA, to assess the efficiencies with much fewer computations. Each model produces results that are different from one another. Therefore, the TOPSIS approach is applied to provide an overall result by integrating the results obtained from the four presented models. For this purpose, the implementation of four TOPSIS models is required. To illustrate the capability and validity of the developed models in efficiency calculation, a case of Iranian airlines is presented. The selected airlines are evaluated in different aspects, and final results are obtained by applying TOPSIS. The findings show that using TOPSIS to combine the results of several DEA models leads to a fully ranking of airlines in four aspects of technical, social, environmental, and sustainable efficiencies. Also, it is recommended to managers to probe pairwise comparison between different efficiencies of airlines in order to find and improve the weak ones.

Measuring technical, environmental and eco-efficiency in municipal solid waste management in Chile

ABSTRACT Moving towards a circular and sustainable economy requires improving the management of municipal solid waste (MSW) increasing recycling rates while minimising unsorted waste and operational costs. It is essential to evaluate the economic and environmental efficiency of MSW services. Previous studies focused on developed countries and employed radial parametric and non-parametric methods. By contrast, this study assessed the technical efficiency, environmental efficiency and eco-efficiency of several Chilean municipalities employing the non-radial range adjusted measure approach. A second stage of assessment was conducted to explore the influence of a set of environmental variables on efficiency scores. Results revealed that the evaluated Chilean municipalities performed poorly from a technical perspective since the average technical efficiency score was 0.484. By contrast, average environmental efficiency and eco-efficiency scores were 0.899 and 0.922, respectively. Nevertheless, the percentage of eco-efficient municipalities was lower than 1%. It was also found that tourism had a major and negative impact on all types of efficiency. By contrast, population density had a significant and positive impact on environmental efficiency. The assessment of three types of efficiency provides relevant information to policymakers to define specific strategies to improve MSW management according to sustainability and circular economic objectives.

Technical efficiency measurement of urban industrial water: a case study of cities in China

PurposeWith the rapid economic growth and urbanization development, regional environmental problems have attracted increasing attention. The study on analyzing cities’ capacity on resource utilization and environmental protection is practically significant because of the industrial agglomeration in an urban area. This study aims to measure environmental efficiency of urban industrial water utilization by comparing input, output and undesirable outputs variables of cities.Design/methodology/approachThis paper combines data envelopment analysis basic approach with regression to discover the environmental efficiency score of cities and their influence factors. A set of slack-based measure (SBM) model is constructed for calculating the environmental efficiency score by considering both desirable and unendurable outputs.FindingsThis paper analyzes the industrial water utilization efficiency for China from the city level by evaluating the performance for up to 200 mainland Chinese cities during 2012–2016 under SBM model. Then, 2C Tobit regression is used to measure the determining factors of industrial water utilization efficiency from the angle of natural, social, municipal and industrial structure factors. The empirical study results show huge room for improvement in industrial water utilization in China, while the average citizen efficiency scores maintain a level of about 0.5.Originality/valueSignificant differences exist in the regional efficiency in different cities in China. Per capita GDP, a total length of drainage pipe and whether the area is coastal or not have significant positive impacts on the water utilization efficiency, while the proportion of secondary industry to GDP has a significant negative influence. Specific recommendations are proposed based on the local industrial water utilization efficiency scores, such as improving urban infrastructure and adopting a more flexible water pricing system.

Measuring the environmental efficiency of the investment for offshore wind power site in Taiwan

Many of the studies is based on parameters with the requirement of pre-estimation and huge function clause format. But in the proposed method, no pre-estimation is required and there is no need to establish a functional relationship between the described and dependent variables. This research investigates the environmental performance and the factors affecting the environmental performance of offshore wind energy companies in Taiwan using super-efficiency data envelopment analysis (SE-DEA) and Tobit regression model, respectively. SE-DEA model was theoretically used in the first step of analysis, followed by Tobit model in the second step. The study was based on 2019 cross-sectional data obtained from seven locations of Taiwan including Songshan, Taoyuan, Nantou, Zhongzheng, Xinyu, and Changhua. It was found that offshore wind power companies in Taiwan had an average environmental efficiency score of 1.8953, which was very high. Moreover, this performance score could be further increased by improving the factors that affected the efficiency. Such factors included age of company, numbers of internal boards, number of shareholders, research and development, ISO 45,001, government policy, personnel quality, and wind speed. Increase in number of shareholders resulted in higher technical efficiency by a significant level at 1%. When the number of internal boards increased 2.20 %, the efficiency score increased up to 100 %. Amount of research and development factors increased by 12.16 %, the effective score was 100 %, with a 5% prioritization with a positive coefficient front sign. This shows how much the company has research and development relating to offshore wind power. Higher amount of research and development resulted in higher technical efficiency. When I.S.O 45,001 factor increased by 41.94 %, the effective score was 100 %, with a 1% significant level and a positive coefficient front mark. The government policy increased the technical efficiency by a significant level at 1%. When government policy increased to 36.54 %, the efficient score enhanced up to 100 %. The factor quality personnel showed positive signs. Increasing number of qualified personnel enhanced the technical efficiency, with the efficiency level at 25.23 %. The factor wind speed had a positive coefficient, corresponded with the hypothesis. Increase in wind speed leaded to higher technical performance score, with a focus of 5%. When wind speed rose to 2.98 %, the efficiency score increased up to 100 %. The best environmental performance was of Wpd Taiwan Energy Co., Ltd company which had the highest score of 3.2521, while the Copenhagen Infrastructure Partners Association company had the lowest score of 0.9136, indicating the worst environmental efficiency. Inefficient companies can improve their environmental efficiency based on their efficiency scores and ratings in order to be a leading offshore wind power facility in Taiwan.

Cooperation and competition among urban agglomerations in environmental efficiency measurement: A cross-efficiency approach

Environmental efficiency has become a key indicator in describing the capacity of regional resource utilization with consideration of the negative externality to nature. Notably, with the development of urban agglomerations all over the world, the role and strategy of efficiency measurement for cities should be reorganized to deal with the complex relationships among cities based on urban agglomerations. In this paper, we construct a set of data envelopment analysis (DEA) models based on a peer-evaluation mode with consideration to the cooperative relationships among cities within the same urban agglomeration together with the competitive relationships between different urban agglomerations. Then, this paper we analyze the environmental efficiency of 48 Chinese mainland cities belonging to the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA), Yangtze River Delta Urban Agglomerations (YRDUA), and Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA). This was accomplished during 2014 to 2019 by using four inputs, two desirable outputs, and two undesirable outputs. The results of efficiency scores indicate that the environmental efficiency trend increased during the time series from 2014 to 2019 while the difference on environmental efficiency among different cities and urban agglomerations are significant. The BTHUA is the best performing urban agglomeration with much higher environmental efficiency scores in all the years. Besides, this paper selected 11 influencing factors based on three different angles to analyze the internal and external environments to environmental efficiency scores for providing further inspiration to managers.

Measurement of Environmental Efficiency Based on Stochastic Directional Distance Function: A Metafrontier Approach

This study measures environmental efficiency (EE) based on CO₂ emissions for five groups of countries between 1998 and 2018, using the stochastic metafrontier directional distance function. The model estimates environmental efficiency scores for a panel of 163 countries using data on GDP and CO₂ emissions as economic growth and the consumption of fossil fuels lead to increased CO₂ emissions. Moreover, meta inefficiency and technical gap differences (TGD) are compared, and the findings indicate that most countries have higher mean TGDs than their group’s average inefficiency measures. Furthermore, except for the low-income group, the OECD group is closest to the meta environmental frontier, suggesting that the OECD countries have advanced technologies to govern the environment. Alternatively, the findings also showed that upper-middle-income countries have the worst meta efficiency, implying that this group of countries sustain a high pollution growth path. Finally, we compare the difference between the stochastic metafrontier method and the pooling method and show that the pooling approach underestimates the severity of environmental problems.

Environmental efficiency of electric vehicles in Europe under various electricity production mix scenarios

Decarbonizing residential transportation sector depends on the energy mix. A need for environmental efficiency of electric vehicles considering the life cycle impacts of electricity generation under different mix scenarios is essential. This research aims to present the first empirical analysis on the environmental efficiency of battery electric vehicles across 27 European countries, considering the average electricity mix, marginal electricity mix (2015–2020), and renewable energy-based electricity mix (2030–2040) scenarios. The midpoints environmental impacts per kWh electricity generation were estimated for each country using the latest ecoinvent v3.7 life cycle environmental impact data. Well-to-wheel environmental impacts of battery electric vehicles were calculated for each country based on a functional unit per km traveled. An input-oriented non-restricted and weight restricted frontier models using the panel-based weights obtained from the European Commission's Joint Research Center (JRC) survey was built to model the environmental efficiency. Finally, the footprint efficiency results related to different electricity production mix scenarios and future projections to improve the environmental efficiency of battery electric vehicles were suggested. The results reveal Finland and Netherland as the most environmentally efficient countries using BEVs for all the electricity mix scenarios. It is seen that average mixes cause lower environmental efficiency scores of battery electric vehicles than marginal mixes due to higher shares of renewable electricity sources in marginal mixes.

Exploring PM2.5 Environmental Efficiency and Its Influencing Factors in China.

In China, air pollution, especially fine particulate matter (PM2.5) pollution, has become increasingly serious with the rapid economic growth that has occurred over the past 40 years. This paper aims to introduce PM2.5 pollution as a constraint in the environmental efficiency research framework through the use of panel data covering the Chinese provinces from 2001–2018. PM2.5 environmental efficiency is measured with the slack-based measure (SBM)-Undesirable-variable returns-to-scale (VRS) model, and the results show that the average PM2.5 environmental efficiency score is 0.702, which indicates inefficiency, and is U-shaped over time. The PM2.5 environmental efficiency scores are unbalanced across the eight regions and 30 provinces of China. Additionally, the relationship between PM2.5 environmental efficiency and its influencing factors is examined with a tobit model, and the empirical findings indicate that the relationship between economic development and PM2.5 environmental efficiency is an inverted U, which is the opposite of the traditional environmental Kuznets curve (EKC). In addition, technological innovation, trade dependency, and regional development each have a significantly positive effect on PM2.5 environmental efficiency. However, environmental regulations, the industrial structure, and population density have significantly negative effects on PM2.5 environmental efficiency. Finally, this paper fails to prove that foreign direct investment (FDI) has created a PM2.5 “pollution haven” in China.

Holistic Impact and Environmental Efficiency of Retrofitting Interventions on Buildings in the Mediterranean Area: A Directional Distance Function Approach

The study focuses on the application of a nonparametric methodology for evaluating the sustainability of retrofitting interventions to be applied on different typologies of buildings and different climate zones of the Mediterranean area. The paper starts from the analysis of data collected through the HAPPEN project, that is a H2020 European project which proposes a holistic approach for a deep and sustainable renovation of the Mediterranean residential Building stock. Even if the European Commission allocated considerable funds for retrofitting interventions, the choice of the optimal solution is not always that easy because several variables have to be considered. The present manuscript proposes a methodology to compare different retrofitting solutions combining Life-Cycle Cost (i.e., LCC) estimations with the nonparametric Directional Distance Function approach (i.e., DDF). In detail, the literature suggests that the DDF can be effectively used for comparing different observations through efficiency scores. The main result of the paper is the definition of a hybrid methodology that, starting from estimates of LCC and applying a DDF technique, represents a simple method for evaluating the best retrofitting intervention. Results are represented by two scores where the former represents a holistic efficiency measure, while the latter shows an environmental efficiency score.

Environmental performance evaluation of European farms by assessing polluting factors in joint production

Measuring the environmental efficiency of firms using data envelopment analysis (DEA) has recently gained momentum due to the urgency of climate change. The existing literature on environmental efficiency ignores the internal structures of the production system and treats the production unit as a ‘black box’. Thus, it fails to identify the exact source of inefficiencies, which complicates course correction in a multi-stage production system. In response to these inadequacies, this study takes into account the amount of pollutants emitted, in addition to the classic input and output parameters in DEA, in each of the stages to measure the environmental efficiency of the overall system and decompose it into stage-level environmental efficiencies. Two separate models assign each country two separate efficiency scores for its environmental and technical performance. To demonstrate the applicability of the proposed framework, the environmental performance of farms in the European Union is measured. The numbers of efficient farms in technical and environmental approaches are 21% and 8% of the total 130 farms, respectively. The average environmental efficiency scores of the two stages (crop production and animal husbandry) across the farms are found to sharply increase and decrease, respectively in comparison to their corresponding technical efficiency. The study also reveals some interesting conclusions. For example, the environmental performance improves for inefficient farms when they try to achieve technical competence. To achieve overall environmental efficiency, all the stages need to be fully efficient. Based on the shadow prices of the polluting inputs and outputs obtained from the two models, we calculate the marginal rate of substitution for the inputs and marginal rate of transformation for the outputs which help one in carrying out comparative analysis. For instance, the results indicate that fertilizer and forage land are responsible for the majority of the environmental inefficiency. Production of cereal and meat is economically efficient; whereas dairy farming is both resource-intensive and environmentally harmful. Based on this analysis, we suggest important policy measures at both the farm and the country levels.

Assessing between and within Product Group Variance of Environmental Efficiency of Swiss Agriculture Using Life Cycle Assessment and Data Envelopment Analysis

Food production systems can contribute to the degradation of the environment; thereby endangering the very resource, they depend on. However, while overall large, the environmental impacts of individual agricultural products are disparate. Therefore, in order to gain a better understanding of the impact different food production systems have on the environment, we should start at the produce level. In this study, we combine life cycle assessment (LCA) methodology and data envelopment analysis to calculate environmental efficiency scores (i.e., agricultural output divided by environmental impacts) for eight product groups (Milk, Cattle, Pig fattening, Cereals, Beets, Potatoes, Vegetables, Fruits) in Switzerland. First, LCA is used to calculate “cradle to farm-gate” environmental impacts. These impacts are then used as inputs in a data envelopment analysis, with the amount of produced agricultural products as outputs. The resulting environmental efficiency scores reflect the relative efficiency (i.e., related to the best-observed performance) of the observed product groups. We find large differences in environmental impacts and environmental efficiency score distribution between the product groups. While we find some variability of environmental efficiency between farming systems (Organic and Proof of Ecological Performance) within a product group (difference in coefficient of variation between farming systems: Fruits = 48%, Vegetables = 13%, Cereals, Potatoes = 8%), we did not find any significant differences in environmental efficiency between organic and integrated farming systems for any of the considered product groups. Furthermore, we did not find a negative effect of multifunctionality of Swiss farms (i.e., multiple simultaneously produced product groups), but found a small positive effect for Milk in the presence of other product groups. However, the high within product group variance of environmental efficiency suggests the potential for improvements (notably >40% for Fruits and >30% for Cattle and Potatoes).

Assessing environmental efficiency of China’s industry system using two-stage range-adjusted measure model

PurposeThe purpose of this paper is to examine the industrial production efficiency, pollution treatment efficiency, total factor energy efficiency and water efficiency in China with the consideration of technological innovation. This study also explores the distribution proportion of technological innovation between industrial production substage and pollution treatment substage.Design/methodology/approachA nonparametric method, data envelopment analysis (DEA), is used as the model foundation of this study. Specifically, a novel two-stage range-adjusted measure (RAM-DEA) with shared inputs is constructed to analyze the China’s industrial system. In this study, the panel data of 30 provinces from 2008 to 2015 are used.FindingsThis study found that although the current environmental regulation reduced the efficiency of industrial production, it could significantly improve the pollution treatment level. However, the lack of pollution treatment capacity was still an obstacle for development of China's industrial system. Compared with the total factor energy efficiency, the total factor water efficiency had more room for improvement. The optimal distribution of technological innovation in the two substages performed little change and the distribution roughly followed the “three-seven principle”.Practical implicationsMore attention should be paid to improve the pollution treatment level and total factor water efficiency. And more R&D expenditure should be used in the industrial production substage in the eastern coastal areas, while in the inland areas, more R&D expenditure should be used in the pollution treatment substage.Originality/valueThis study proposed a model to environmental efficiency score with considering interval data under two-stage evaluation structure, which could strengthen the theory and expand the application scope of DEA approach.

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific.

This study employs super-efficiency DEA model with desirable inputs and an undesirable output in calculating environmental efficiency values in different regions in Asia-Pacific from 1990 to 2018. The study compares environmental efficiency index in South East Asia, South Asia and East Asia. The study also evaluates the determinants of environmental efficiency using truncated regression. The mean environmental efficiency score demonstrates that East Asia region is highly efficient whereas South East Asia is the least efficient. Results from the truncated regression established an inverted U-shape relationship between environmental efficiency and Technological Innovation (TI) in the main panel, and the three regions. Also, economic growth shows an inverted “U” shape link with environmental efficiency in the panels except in South East Asia. Human capital promotes environmental efficiency in the main panel and the rest of the regions. Moreover, while FDI promotes environmental efficiency in the main panel and East Asia, it reduces environmental efficiency in both South East and South Asia regions within the Asia-Pacific. In addition, an interaction effect between technological innovation and renewable energy use, advances environmental efficiency within the entire study countries. Based on the findings the study proposes several policy recommendations.