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Improving green productivity (GP) is critical for achieving global sustainable green development. Yet, past efficiency studies on the African continent have ignored Africa's GP, estimation, and driving factors. Specifically, the role of sovereign debt vulnerability, environmental entrepreneurship, and institutional quality in ensuring Africa's green productivity development is lacking. Therefore, this study built a meta‐frontier biennial weighted modified data envelopment analysis (DEA) model to evaluate green productivity across resource‐intensive and non‐resource‐intensive African countries from 2010 to 2019. Further, the study adopted the global Malmquist‐Luenberger productivity index (GML) to investigate the dynamic changes in African green productivity growth. The results suggest that only a few African countries are efficient, implying more room for improvement for the other countries. The heterogeneity of green productivity across the resource's classification exhibits significant disparity. The technology gap also prevails among the two resource classifications of African countries. The GML index indicates that Africa's green productivity is mainly explained by technical change instead of efficiency change. The bootstrap truncation regression suggests an inverted U‐shaped nexus between growth and green productivity in Africa and resource‐intensive countries (RIC). Green environmental entrepreneurship positively affects green productivity in Africa. On the components of institutional quality, we observed that the rule of law positively influences green productivity in non‐resource‐intensive countries (NRIC) and the whole of Africa. In contrast, political stability, government effectiveness, voice and corruption negatively affected green productivity in NRIC. Also, foreign direct investment (FDI) and sovereign debt vulnerability negatively correlate to green productivity in Africa as a whole and NRIC, respectively. The findings of this study aid in raising awareness of green productivity in developing countries, which is crucial in boosting global green development. [ABSTRACT FROM AUTHOR]

Evaluation of green development is crucial for policy analysis and decision‐making. To address the research gap on green development assessment systems, this study first presents the Super‐efficiency Bounded Adjusted Measure model to gage the green growth index and economic growth index. This analysis involves evaluation of the coupling coordination degree. Through the analysis of the coordination between green growth and economic growth leads to recommendations for each region under consideration in regards to promotion of the components of the sustainable growth. This study presents the model that melds the objectives of the green and economic growth and uses the results for constructing the sustainable development Lorenz curve and Gini coefficient for the analysis of the differences in the sustainable development levels across the regions. The empirical case is presented to show the possibilities for application of the proposed approach. [ABSTRACT FROM AUTHOR]

Transition towards low‐carbon and carbon‐neutral society requires multiple technological solutions. Thermal power generation is the main source of power generation in China and contributes to a large portion of carbon emission. Under the goal of "carbon peak", thermal power generation efficiency will become an important factor affecting industrial development. Based on the directional distance function, this article assumes energy used as inputs and power generation as an output. Then, energy‐oriented and energy‐generation oriented power generation efficiency analysis models are proposed. The carbon emission is treated as an undesirable output to analyze the regional power generation efficiency with and without industrial transfer. The application focuses on panel data of three regions in China over the period 2013–2017, accounting for three energy inputs: solid, oil and gaseous fuel. The results show that in regard to the factors improving power generation efficiency, pure efficiency and scale efficiency change is positive for the eastern and central regions, while pure technical efficiency change is positive for the western region. By further analyzing the power generation potential, the results also show that the eastern region exhibits potential savings in gaseous fuel, the central region has potential in three fuels, but all not prominent, and the western region has potential in solid and oil fuels. Accordingly, the article puts forward policy recommendations from the perspective of technological innovation, differentiated development, and collaborative communication. [ABSTRACT FROM AUTHOR]

Through their consumption behavior, households are responsible for more than 70% of total global greenhouse gas emissions. Therefore, the GHG emission reduction potential due to the household behavior is very high. Energy consumption is the main source of the GHG emission in households. There are two main ways to reduce GHG emissions in households: use of renewable energy, energy efficiency improvement, and energy conservation due to changes in the energy use patterns. The highest energy saving potential in households is linked with building renovation, followed by the use of energy efficient appliances (including lighting). Renewable energy microgeneration technologies in households also provide opportunities for GHG emission reduction. Although there have been many policies developed to reduce GHG emissions from energy consumption in households, they still need to be more effective. This paper aims to assess willingness of Lithuanian households to reduce GHG emissions from energy consumption in households by embarking on energy renovation of buildings, use of energy efficient appliances and use of renewable energy technologies. The willingness to pay for these GHG emission reduction measures allows to compare household preferences with respect to available support measures and assess the adequacy of such measures. The paper also discusses household attitudes toward the main policies and measures for GHG emission reduction. The results show the highest willingness to pay for energy efficient appliances, followed by renewable energy technologies. The willingness to pay for energy renovation is the lowest one and such s measure requires significant state support. [ABSTRACT FROM AUTHOR]

Creation of the climate‐smart agriculture requires efficient resource use and mitigation of the environmental pressures among other objectives. Therefore, it is important to assess the energy efficiency and productivity growth in the European Union's agriculture. This paper analyses the sample of the selected European Union member states. The productive technology including the energy consumption and the resulting greenhouse gas (GHG) emission is constructed. The measurement of the energy efficiency and productivity change relies on the slacks‐based measure and Luenberger productivity indicator. The productivity growth was decomposed with respect to the input/output variables and the sources of growth (i.e., efficiency change and technical progress). The average annual productivity growth of 0.79% was obtained for the selected countries during 1995–2016. The highest productivity gains were observed in Lithuania, Denmark, Belgium and Romania (1.27%–1.94% per year). The productivity growth related to GHG emission dominated the contributions by the input/output variables in Lithuania, Denmark, Belgium, Romania, Poland, Austria, France, the Netherlands, Hungary and Estonia. [ABSTRACT FROM AUTHOR]

The gains in corporate sustainability are important for business development under the increasing competition and climate change. The importance of the green and sustainable supplier selection has increased due to the environmental concerns and regulations. The information for business decisions is often vague and imprecise. Therefore, this paper develops a fuzzy methodology for sustainable supplier selection based on fuzzy information. Single‐valued neutrosophic set (SVNS) is a very popular tool for processing potentially uncertain information provided by decision‐makers. Thus, SVNS is considered as a useful extension of the existing methods in uncertain complex situations. In order to facilitate the multi‐attribute decision‐making (MADM), this paper develops a new similarity measure for the SVNSs and explores its application possibilities. For achieving the aim, a single‐valued neutrosophic (SVN) hybrid weighted similarity (SVNHWS) measure is presented to reflect degree of similarity of SVNSs more effectively. Moreover, a method based on the SVNHWS and entropy measures is constructed for handling SVN MADM problems, in which, the entropy measure is used to derive the unknown weights information of attributes. Finally, an illustrative mathematical example dealing with the sustainable supplier selection is provided. The reliability of the proposed technique is tested by means of the comparative analysis. [ABSTRACT FROM AUTHOR]

The G7 and Brazil, Russia, India, China and South Africa (BRICS) nations have committed to greenhouse gas emission reduction according to targets set out in the Paris Agreement and Copenhagen Accord. The objective of this paper is to develop an index decomposition framework and apply it for comparison of the drivers behind carbon dioxide emission. The impact of economic and technological development on greenhouse gas emissions is assessed by applying the Kaya identity. The index decomposition analysis is carried out by applying the Shapley value. In this paper, we seek to compare the two groups of countries—G7 and BRICS—in regard to the underlying trends in the energy‐related carbon dioxide emission during 1990–2015. The comparison of these two groups for countries draws some light on the pathways of decarbonization of the economies in developing and developed countries. The time period covered spans over the sub‐periods of economic growth and decline. Energy intensity appeared as the major factor pushing the carbon dioxide emissions down in the developed countries (i.e., G7 group). The latter effect was much lower for the developing countries (i.e., BRICS group) and was offset by the affluence effect. Further development of the renewable energy is important for the developing countries in order to start exploiting the carbon factor effect. [ABSTRACT FROM AUTHOR]

The implementation of bioeconomy is important in seeking to achieve the Sustainable Development Goals. Thus, in recent years, more attention is focused on sustainable bioeconomy. Referring to weak and strong sustainability approaches, many authors stated that bioeconomy is related only to weak sustainability, but this study provides a framework for policy makers that allows the definition and implementation of the bioeconomy based on the strong sustainability approach. Furthermore, researchers evaluating bioeconomy implementation conventionally encompassed the economic, social, and environmental dimensions of the impact of bio‐products; however, they did not consider the strong sustainability approach. Strong sustainability additionally requires not crossing ecological thresholds and, thus, implies consideration of planetary boundaries. Therefore, the inclusion of land footprint and biocapacity measures in the bioeconomy strategy, verifying that the land footprint does not exceed the level of biocapacity, is essential for the creation of a strongly sustainable bioeconomy. This study embarks on the definition of the bioeconomy based on strong sustainability and contributes to the discussion about bioeconomy implementation in the context of sustainable development. [ABSTRACT FROM AUTHOR]

External environmental factors play a significant role in the agricultural production of smallholder farmers. This is especially the case in developing countries where production is less technologically intensive. These factors are mainly exogenous and affect both the farmers' input choices and the final output levels. However, previous studies of technical efficiency of smallholder agricultural production either ignore these factors or assume separability between environmental factors and input choice, which is often not the case in developing counties. Using data on smallholder farmers in Ethiopia, we relax this separability assumption and investigate the importance of external environmental factors in farmers' performance and efficiency variation across regions. The empirical analysis is based on a non‐parametric conditional order‐m estimation method that relaxes some of the traditional strong assumptions in efficiency modeling and, more importantly, the separability between environmental factors and the choice of physical inputs. Using data from four major agricultural regions of Ethiopia, we show the extent that environmental factors contribute to the technical efficiency and the significance of environmental factors in farmers' performance. [ABSTRACT FROM AUTHOR]