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Abstract This study aims to analyze the innovation strategies for the green supply chain management with QFD (quality function deployment) multidimensionally. The novelty of the study is to define the criteria of green supply chain for each stage of QFD and propose a hybrid model by IVIF (interval-valued intuitionistic fuzzy) DEMATEL (decision making trial and evaluation laboratory) and IVIF MOORA (Multi-Objective Optimization by Ratio Analysis) respectively. The results demonstrate that understanding the customer expectations with customer relation management is the most important innovation strategy for the green supply chain management in energy industry with the consecutive stages of QFD whereas benchmarking the competitive market environment has relatively the last seat in the ranking. Hence, it is recommended that energy companies should have an effective customer relationship management. In this context, these companies should make a detailed analysis to learn what their customers directly expect from them. With the help of this issue, these companies should generate their product and services based on these expectations. Additionally, it is also stated that new service and product development is also essential for energy companies to improve their innovativeness. For this purpose, a research and development department should be created, and the qualified people should be employed. Additionally, different opinions should be collected from various parties, such as customers, employees, and suppliers. Since customers who are satisfied will prefer these companies, the energy companies can catch the opportunity to increase their market share.

Wind energy projects provide clean energy so that they should be increased to reach the sustainable development goals of the countries. However, current decision-making process should be improved for the effectiveness of these projects. Thus, critical factors should be considered to understand the significant indicators of the performance of the wind energy projects. This article aims to determine the factors that should be considered when deciding on wind energy investments. In this context, 9 different criteria belonging to 3 dimensions (project, firm, market) are determined based on literature review. Later, an analysis is carried out by using hesitant interval-valued intuitionistic fuzzy (IVIF) Decision Making Trial and Evaluation Laboratory (DEMATEL) to identify the most important factors. Furthermore, 4 different investment strategies in Boston Consultancy Group (BCG) matrix have been determined as alternatives. To determine which of these strategies is suitable for wind energy investments, the hesitant IVIF multi-objective optimization on the basis of ratio analysis (MOORA) method has been considered. Additionally, a comparative evaluation is also performed by using technique for order preference by similarity to ideal solution (TOPSIS) methodology. Similarly, sensitivity analysis is also made by considering 9 different cases. The analysis results of different methodologies are quite similar which shows the coherency and reliability of the findings. It is concluded that firm-based factors play the most significant role. It is also identified that technical development, financial performance and organizational effectiveness are the most significant criteria to make investment decision on wind energy projects. Furthermore, due to the market growth potential, it is recommended that wind energy investors increase their investments and strengthen their position in the market.

Climate change and rising global temperatures pose significant challenges for natural resource management. While developed economies have made progress in addressing these issues, emerging economies are still striving to achieve carbon neutrality, sustainable resource use, and environmental sustainability. This research aims to identify the factors driving carbon emissions in emerging economies over the past three decades. The study establishes a long-run relationship among the factors under investigation by employing various panel diagnostic methods. Non-parametric approaches are used to account for the non-symmetric distribution of panel data. The findings reveal that natural resource components have asymmetric impacts on carbon emissions, with oil rents reducing emissions and mineral rents increasing them. Economic growth and agricultural value added are identified as significant contributors to carbon emissions in the region. On the other hand, renewable energy consumption plays a crucial role in achieving carbon neutrality targets. Gross capital formation exhibits a mixed influence on carbon emissions, being positive and significant in lower quantiles and significantly negative in upper quantiles. These estimates are robust and align with existing literature. The study recommends sustainable resource abstraction and utilization, renewable energy production and consumption improvements, and enhanced capital formation. By providing empirical evidence and policy recommendations, this research contributes to understanding the relationship between these factors and their impact on carbon emissions, facilitating effective strategies for sustainable development and environmental preservation. Xinyang Normal University

AbstractIn the wake of the growing threats to humanity from climate change, we analyzed the information and communications technology (ICT)/education—environmental nexus from three distinct blocs including BRICS, MINT, and the G7 economies between 1990 and 2020. Two models were examined to reach the study's objectives. The first model evaluates whether education and ICT are essential for environmental sustainability via potential reduction in carbon emission. On the other hand, the second model fills an existing gap in extant studies by examining the prospect of education and ICT in influencing citizens on the importance of transition to renewable energy usage. Driscoll and Kraay estimator was employed as a panacea tool for cross‐sectional dependence and slope homogeneity while the fixed effect approach provides sufficient robustness checks on the findings. While some outcomes vary per bloc, others are relatively similar across the three blocs. Education level in school enrollment perspectives shows a negative significant pollution reduction effect across the three blocs, while only the G7 bloc performed better from human capital perspectives. The combined sample bloc shows that ICT also significantly reduces carbon emission, however, an individual bloc analysis refutes this stance for the MINT bloc. Additionally, while renewable energy cushions emissions in all the blocs, rapid urbanization, shows a positive CO2 emission impact except in the G7 bloc. Last, ICT and education significantly boost renewable energy usage only in the G7. Hence, governments and stakeholders in the blocs should gravitate toward greater investments in quality education and greener ICT infrastructures for a sustainable environment.

Abstract Urban transformation is vital to global sustainable development as humans increasingly come to dwell in cities. Within cities, the mobility sector promises the highest potential of carbon emission reduction. The disruptive business innovation brought about by the advent of app-based smart-sharing systems is emancipating collaborative consumption of mobility at larger and deeper scales, ranging from car-pooling, expanded electric vehicle (EV) use to bike-sharing. Synchronizing the existing yet under-realized low-carbon transport modes in cities, such as public transport, with emerging and diversifying app-based sharing mobility business models, offers huge potential to transform urban mobility toward sustainability. Yet, the rapid business expansion and innovation of the sharing mobility companies have profoundly challenged existing socio-economic relationships, knowledge systems and physical infrastructures in cities. This study explores the synergy between the social-ecological innovation in the sharing economy and the sustainable development of urban systems, using empirical data from three business cases in the emerging sharing mobility sector – in modes of ride-sharing, EV-sharing and bike-sharing - of Shanghai, China. It indicates that there is a strong co-evolution mechanism between the transformation towards more sustainable city at the macro-level and the business ecosystem innovation towards greener and smarter transport at the meso-level. We argue that the two level transformations, triggered by the disruptive innovation of the sharing economy and led by urban transformation towards sustainability, mutually influence each other and re-enforce sustainable values and practices in the fast changing urban context and business innovations in Shanghai.

There are some risks in renewable energy investments, such as legal, technology and financial issues. Hence, appropriate actions should be taken to minimize these risks. However, each of the measures to be taken for the management of risks creates new costs for businesses. Therefore, to ensure the financial sustainability of the projects, measures for the most important risks should be taken at the first stage. Because of this situation, it is vital to make a priority analysis for the risks faced by renewable energy projects so that it can be possible to increase the effectiveness of risk management. Accordingly, in this study, it is aimed to examine the risks and rewards regarding sustainable investment decisions for renewable energy projects. In this scope, a novel model is generated by integrating different techniques. In this process, the evaluations of six different experts are taken into consideration. First, missing evaluations for the sustainable investment decisions in renewable energy are estimated with neuro decision-making and collaborative filtering. Secondly, the weights of the risk factors of sustainable energy investments are computed with neuro quantum spherical fuzzy (QNSLF) DEMATEL with golden cut. Thirdly, reward alternatives for sustainable decision making are analyzed with Neuro QNSLF TOPSIS with golden cut. This study contributes to literature by determining the most important risks for renewable energy projects by an original decision-making model. Another important novelty of this study is that a new technique called neuro decision-making has also been developed. In this technique, the facial expressions of the experts who evaluate are taken into consideration. It is defined that technological changes have the greatest significance. Additionally, governmental incentives are found as the most essential reward to improve sustainable investments in renewable energy. Thus, for the effective management of these risks, appropriate actions should be taken. It is also obvious that the competitiveness of companies that fall behind this new technology will decrease. In this context, these enterprises need to take the necessary measures to manage the technology risk to be sustainable in the long term.

Abstract With drastic fossil fuel depletion and environmental deterioration concerns, a move towards a more sustainable bioenergy-based economy is essential. Lately, the application of microwave (MW) irradiation for waste processing has been attracting interest globally. MW-assisted heating possesses several advantages such as the provision of high microwave energy into dielectric materials with deeper penetration for internal heat generation, showing beneficial features in improving the heating rate and reducing the reaction time. Consequently, the most recent literature regarding the applications of MW-assisted heating for biomass pretreatment as well as biofuel and bioenergy production was reviewed and consolidated in this study. An impressive increase in the product yield and improvement of the product properties are reported, with the use of MW-assisted heating in several conversion routes to produce biofuels. Despite being a promising technology for biofuel production, some major fundamental data of MW-assisted heating have not been comprehensively identified. Therefore, the feasibility of this technology for large-scale implementation is still subpar. Understanding the interaction between the feedstock and the microwave electromagnetic field, and the optimization of several operational and mechanical parameters are the two main keystones that would propel the industrialization of MW heating in the near future. This provides key insights leading to increased feasibility and more advanced application of MW heating.

Abstract The framework of this study is to weight 8 selected determinants and rank energy alternatives for hydrogen investments. For this purpose, different criteria that are based on two dimensions are identified with supported literature and interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) with alpha cuts is considered to measure the significant criteria. Additionally, renewable and non-renewable energy alternatives are ranked regarding the appropriateness for hydrogen energy investments with the help of IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and IT2 fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) with alpha cuts. It is concluded that the weights of the criteria are quite similar for different alpha cuts. Also, ranking results of different energy alternatives are almost the same for both IT2 fuzzy TOPSIS and IT2 fuzzy VIKOR. Thus, it can be concluded that the analysis results are reliable and coherent. The principal results indicate that cost-efficiency and reserve adequacy play a key role in hydrogen investments since they have the highest weight (0.129). Moreover, it is also found that technological capacity also plays a critical role in this regard with the weight of 0.127. However, legal regulation has the lowest importance weight (0.121) in comparison with other factors. Additionally, the weights of personnel competency (criterion 3) and storage (criterion 4) are also low (0.122). The major conclusion show that renewable energy alternatives are more suitable to generate hydrogen energy in comparison with non-renewable ones. Within this context, it is identified that solar and geothermal energies are more appropriate alternatives for hydrogen production whereas coal and nuclear are on the last rank. Hence, the main strategy should be lowering the costs by following up-to-date technological developments. Another important issue is that it becomes more logical to produce hydrogen in renewable energy sources that will not be consumed forever so that sustainable production of the hydrogen can be provided.

Achieving environmental sustainability has become a global concern amidst increasing climate change threat. Using quarterly frequency data for the case of Russia from 1992 to 2018, the present study explores the interaction between disaggregated energy consumption (renewable energy and non-renewable energy), trade flow and economic growth on a broader measure for environmental degradation (ecological footprint). The choice of the variables draws strength from initiative of the United Nations Sustainable Development Goals (UN-SDG, 7, 8 11 and 13) for responsible energy consumption and clean energy consumption while mitigating climate change issues. The study applied the quantile-on-quantile regression (QQR) and nonparametric causality-in-quantiles to capture these associations. The outcomes from the QQR disclosed that in the majority of the quantiles, trade openness and renewable energy use contribute to environmental sustainability, while nonrenewable energy amplifies ecological footprint. Furthermore, growth in Russia escalates its ecological footprint. Moreover, in the majority of the quantiles, all the exogenous variables can predict ecological footprint. Given the outcomes of this study, it outlines the need for a paradigm shift for alternative and clean energy consumption in Russian energy mix amidst its economic growth trajectory while accounting for green-development approaches. Pathways to fully achieve the sustainability targets are carefully outlined in the concluding section.

Continuing economic progress with less environmental damage and achieving a sustainable environment require switching from fossil fuels to green energy. However, alleviating environmental damage of growth has become a major challenge for BRICS where economic progress amidst rising urbanization pollutes the environment. In this context, the fight against climate change and actions towards environmental sustainability are greatly affected by rising economic policy uncertainty. Hence, this study assesses the role of green energy, urbanization, and economic growth in CO2 emissions in the presence of economic policy uncertainty in BRICS (excluding South Africa) from 1997 to 2020. The study used the cross-sectionally augmented auto-regressive distributive lag technique for revealing the short- and long-run effects of the analyzed variables on environmental quality. The empirical evidence suggested that the environmental Kuznets curve exists according to the recent framework of Narayan and Narayan Energy Policy 38:661-666, (2010) because even though economic growth increases CO2 emissions, its long-run effect is less than the short-run effect. Economic policy uncertainty boosts CO2 not only in the short-run but also in the long-run, evidencing that a sustainable environment requires decreasing the levels of policy uncertainty. For BRICS, switching towards green energy is a vital option to decrease environmental deterioration owing to the negative connection between green energy and CO2. The findings indicated that rapid urbanization is among the causes of high CO2. Furthermore, economic policy uncertainty influences both green energy and economic growth levels. Finally, policies are recommended to mitigate environmental deterioration.