Environmental degradation, predominantly driven by greenhouse gas (GHG) emissions, poses a significant threat to ecological stability. In response, the Glasgow Climate Act requires economic stakeholders to prioritize decarbonisation. India aims to reach net-zero carbon emissions by 2060 using renewable energy and innovative technology. Attaining this ambitious goal necessitates addressing a complex interplay of contributing factors. This study advances the existing body of knowledge by applying symmetric and asymmetric autoregressive distributed lag (ARDL) models to analyze the effects of foreign remittances, green growth, green technological innovation, and unemployment asymmetry on India's decarbonization trajectory over the period 1990–2022. The methodological framework is anchored in the STIRPAT model, which systematically examines the influence of population, affluence, and technology through regression analysis of stochastic variations. Furthermore, the study draws theoretical grounding from sustainable innovation theory, the Environmental Phillips Hypothesis, and the Environmental Kuznets Curve (EKC) hypothesis. The findings indicate that green growth and innovative technologies can significantly reduce CO2 emissions. For each 1

Recent challenges in climate variation have emerged as a substantial concern for international communities. Presently, climate finance (CF) has emerged as a viable solution for mitigating climate change. CF, as a distinctive form of international support, seeks to foster sustainable development while concurrently enhancing CO 2 emissions. Therefore, the present study aims to estimate the impact of CF, green technological innovation (GTECH), economic policy uncertainty (EPC), and business freedom (BFD) on environmental sustainability (ES) from 2000 to 2023 for the N11 states (excluding South Korea due to unavailable data). Moreover, the moderation models are inspected for CF, GTECH, EPC, and BFD. However, theoretical support has aligned with the sustainable innovation perspective and the Sustainable Development Goals (SDG 9 and SDG 13). However, the integrated econometric estimates are carried out using the cross-sectional auto-regressive distributive lag technique, the methods of moments of quantile regression, and robustness verification via FMOLS and DOLS estimates. The findings showed that CF (−0.008) aids ES in the short term, while existing CF aids (0.019) are insufficient for supporting long-term ES. In parallel, GETCH (−0.077) and BFD (−0.183) contribute to enhancing ES. Similarly, EPC benefits the short term, but has destructive impacts on ES (1.510) in the long term. Interestingly, the moderation effects of CF*GTECH and CF*BFD aid ES at both short and long spans, while CF*EPC degrades ES. Consequently, a robust policy mechanism is required to regulate CF, and CF aid needs to be increased for developing states that benefit ES in the long term.

The increasing worldwide apprehension about climate change triggered by the emanation of greenhouse gases from transportation has inspired global economies to embrace alternative fuel technologies. However, the conventional transportation mechanism highly consumes fossil energy and heavily deteriorate the environment. Fossil fuel vehicles pose several challenges for Pakistan, affecting energy security, economic stability, and environmental health. Dependence on obsolete and inefficient vehicles results in increased fuel consumption and import expenditures, burdening the national economy. Therefore, electric vehicles (EVs) are promoted as a realistic, environmentally friendly technology that can transform a sustainable transportation system. Furthermore, a critical gap exists in evaluating the key barriers to adopting EVs through technological transformation. Hence, this investigation intends to implement the multi-criteria decision-making approach to assess the challenges in the adoption of EVs aligned with sustainable development goals (SDG-11 & SDG-13). The research strategy begins with a comprehensive examination of existing literature and consultations with specialists to identify potential hindrances. Thus, a novel Spherical Fuzzy Analytical Hierarchical Process was employed to prioritize the main and sub-barriers. This study evaluated the four key obstacles related to EVs in emerging economies like Pakistan. The expert’s evaluation indicated that the infrastructure barrier (34.99%) ranked first, the financial barrier (27.92%) was prioritized second, and technology was the third main barrier (20.99%). Furthermore, public infrastructure, the effect on the electricity grid, and the lack of maintenance workshops are the top three sub-barriers. Hence, the government of Pakistan needs urgent action to enhance the technological and financial capability for the implementation of EVs.

Achieving sustainable development depends significantly on identifying sustainable energy sources. Therefore, prioritizing sustainable Biomass Energy sources (BES) for energy production is a strategic decision that requires a robust decision support system (DSS). Two critical problems, meanwhile, have not yet been adequately resolved. The criteria for assessing BES in terms of sustainability have not been systematically structured. Second, the state-of-the-art in BES evaluation generally ignores the constrained rationality of decision-makers. In order to address the issues above and offer a more systematic and understandable framework for assessing BES, this research presents different developments pertaining to the following: (1) Develop a novel robust DSS system based on an in-depth investigation of the sustainable aspects (2) The DSS consists of a two-phase procedure that integrates the primary methods of Multi-Criteria Decision Making (MCDM), specifically the utility-based and the out-ranking approach. (3) The DSS uses spherical fuzzy (SF) information due to its comprehensive structure and ability to model hesitation in a decision process (4) Phase I employs the SF-AHP to weight the sustainability criteria (5) Phase II is composed of three stages, where SF-VIKOR and the SF-WSM methods are employed as utility-based approaches, and the SF-PROMETHEE is employed as an out-ranking approach. The model indicates that the economic factor is the most significant criterion, with forest residue identified as the optimal BES. A case study on BES evaluation, along with a feasible assessment, component analysis, and discussion, proves the practicality of the proposed DSS and the impact of parameter modifications on the outcomes.

The expansion of wind energy is crucial for sustainable development, yet its growth is hindered by multiple barriers, particularly in developing countries. Effective policy interventions are essential to address these challenges and facilitate wind energy integration. However, limited research has explored systematic approaches to identify and prioritize these obstacles. This study employs the Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) integrated with the novel Spherical Fuzzy Multi-Attributive Border Approximation Area Comparison (SF-MABAC) algorithm to assess key barriers and proposes a strategic solution. The findings indicate that the category of financial obstacles (0.2429) exhibits the highest ranking. On the contrary, the comprehensive global rankings reveal that limited government subsidies (6.9296 %), lack of wind power policy (5.9361 %), and unbalanced feed-in-tariff (5.1176 %) are the three most significant sub-obstacles amongst the remaining twentyfive obstacles within various categories. The study further identifies "securing adequate financial support" as the optimal strategy for overcoming these barriers. The outcomes of the sensitivity and comparability assessments indicated that the rankings derived from the method employed are legitimate and reliable. The findings contribute to the efficient implementation of wind energy projects, particularly in Pakistan, where strategic interventions are necessary to enhance sustainability and energy security.

There has been an increase in the number of discussions concerning carbon neutrality in order to address the problem of climate change and the damage to the environment. Therefore, nature warns societies to limit emissions and live eco-friendly due to rising temperatures and abrupt climate change. The regional comprehensive economic cooperation (RCEP), the world's foremost trading union, represents nearly one-third of the global economy and population and accounts for 30% of global trade and gross domestic product. This study observed the RECP economies from 1990 to 2021 to determine the connection between income inequality, risk components, renewable energy (RE), information communication, and technology (ICT) on environmental sustainability. However, limited research has investigated the association between such factors and ecology. To fill this gap, our research makes a unique contribution by exploring four specific econometric models to examine composite risk, financial risk, economic risk, political risk, and income inequality. The empirical study includes cross-sectional dependence, slope heterogeneity, augmented panel unit root test, Westerlund cointegration, second-generation cross-section augmented autoregressive distributed lags, and panel causality test. In addition, the augmented mean group estimation is used as a robustness check. The short-run findings demonstrate that an increase of 1% in income inequality and the utilization of RE significantly decrease (0.1786%) and (0.2024%) CO2 emissions. In the long run, the income inequality coefficient (- 0.4316) and the utilization of RE coefficient (- 0.9085) states that increasing income inequality and the utilization of RE by 1% reduces CO2 emissions in the environment by (0.4316%) and (0.9085%). Moreover, the risk components and ICT positively affect CO2 emissions and deteriorate environmental quality. The study concludes that in RECP economies, governments and regulators should prioritize preserving stable income inequality and incentivizing businesses to use renewable energy sources. These nations require stringent environmental regulations, governmental stability, robust institutions, and effective law enforcement to reduce CO2 emissions and achieve carbon neutrality.

The deliberate release of carbon dioxide (CO2) is a key factor contributing to climate change and other environmental problems. In order to determine how socioeconomic and technological variables influence emissions, this study employs the STIRPAT framework in conjunction with linear and non-linear (symmetric and asymmetric) autoregressive distributed lag models. This analysis explores the impact of smart grid technology (SMGD), renewable energy (RE), institutional quality, and urbanization on CO2 emissions from 1995 to 2021. The research aligns with the sustainable innovation theory and institutional theory. The results show that using RE sources and SMGD significantly cut down on CO2 emissions. Conversely, urbanization and institutional quality continue to exacerbate environmental degradation. The results are consistent across numerous estimation methods, including fully modified least squares, dynamic ordinary least squares, and canonical cointegrating regression. The study adds to the literature by presenting empirical evidence on the interconnection of technology, socioeconomic variables, and environmental impacts. It emphasizes how crucial it is to match economic and environmental initiatives with policies that incorporate technology innovation. Policymakers can decrease CO2 emissions and improve long-term sustainability by encouraging the deployment of SMGD and RE sources, as well as by optimizing institutional quality and regulating urbanization. This study provides vital information for accomplishing sustainable development objectives and promoting global climate action.

Renewable energy communities (RECs) serve as a highly promising stance to endorse the growth of sustainable and decentralised energy systems. Although previous studies have predominantly concentrated on the advantages and incentives for participating in RECs, there has been insufficient focus on the significant hurdles encountered by stakeholders in emerging economies. The study addresses the gap by identifying and ranking the primary barriers to REC implementation and proposing concrete strategies to improve stakeholder participation and effectiveness. Furthermore, a novel aspect of this research is the combination of two existing methods: the Spherical Fuzzy Analytic Hierarchy Process for assessing the importance of obstacles and the Triangular Fuzzy Multi-Attributive Border Approximation Area Comparison for prioritising the best strategies. The findings indicate that regulatory and bureaucratic (33.28%) barriers and financial (27.44%) constraints are the most significant. The TF-MABAC method reveals that streaming and support are essential for addressing obstacles. To overcome these obstacles, authorities need to encourage cooperation among stakeholders, simplify regulations, and offer financial incentives. This study improves methodological approaches in REC research by utilising sophisticated multi-criteria decision-making methodologies. The research immediately enhances global sustainability initiatives by promoting the shift to clean energy, therefore aligning with the aims of SDG-7 and SDG-13.

Deforestation in various economies caused tremendous disintegration and crumbling effects on environmental sustainability and loss of forest habitats. However, developing economies face higher environmental degradation due to large-scale deforestation for urbanization. Therefore, our research is based on four separate models to investigate the effects of greenhouse gases (CO 2 , CH 4 , and N 2 O) and ecological footprint on deforestation, urbanization, economic growth, globalization, and agricultural land in Pakistan. Hence, research data are grabbed from authentic sources like World Bank indicators, the Global Footprint Network, and the Swiss Economic institute. Further, the econometric methodology is employed to get long- and short-run dynamics through the autoregressive distributed lag model from 1990 to 2017 for Pakistan. Our empirical evidence suggests that carbon emissions expressed a significant positive linkage for deforestation, agriculture land, globalization, and urbanization that prompts long-term environmental degradation. Additionally, in the long run, ecological footprint developed a significant and positive bridge between deforestation, agriculture land, and economic growth. Moreover, the long-term findings concluded that methane gases surge deforestation, agriculture land, economic development, and globalization. However, a small ratio of nitrous oxide indicated a negative linkage between deforestation and agriculture land but a positive connection with economic growth, urbanization, and globalization. Moreover, the variance decomposition analysis and impulse response function examine the causality among the variables. For practical implications and policies, the government should formulate strict control on deforestation acts to save the environment and ecology. It should need to redesign urbanization policies with city and town planning. Policymakers should focus on advancements in the agriculture sector’s productivity. For emerging countries like Pakistan, besides reducing CO 2 emissions, policymakers should consider the reduction of methane and nitrous emissions.

The expansion of renewable energy (RE) technology could be assisted by energy policies that tackle significant barriers. Several obstacles have slowed the RE sector’s growth in developing nations, leading to less-than-ideal development in this area. Moreover, exploring potential alternate strategies to surmount these constraints has received limited attention. It is essential to identify the barriers preventing the use of RE technologies before proposing an adequate replacement to tackle these issues appropriately. Hence, the present research aspires to identify and prioritize the obstacles currently impeding the advancement of RE technologies in developing countries, using the spherical fuzzy analytical hierarchy approach. The results suggest that the “Policy and political” category (0.1769) has the highest ranking among the main groups, followed by “Economic” (0.1647), “Administration regulatory” (0.1640), and “Technology” (0.1438), respectively. The market barriers, with a weight of (0.1333), exhibit the lowest weight among the various factors considered. Similarly, the geographical and ecological barriers, with a weight of (0.1170), and the social and cultural barriers, with a weight of (0.1003), all have relatively lower weights. In contrast, the comprehensive global rankings of sub-obstacles indicate that the lack of a sufficient market base (0.05419), transportation problems (0.04375), and a lack of local entrepreneurship (0.04243) are the three most notable sub-obstacles among the remaining thirty-five obstacles across diverse categories. Moreover, recommendations are provided for the eradication of the obstacles. Furthermore, it is essential to consider the possible advantages of devising approaches to indorse the effective execution of RE projects in developing nations.

Due to the adoption of more financial inclusion (FI), energy utilization with sustainability became a challenge for world economies. Our research examines whether FI symmetrically and asymmetrically affects environmental sustainability in Pakistan. Six proxies are indexed for the FI data through principal component analysis (PCA). In the present research explanatory variables are, energy usage, industrialization, urbanization, and human capital during from 1975 to 2018. Our study engaged the Stochastic Impact by Regression on Population, Affluence, and Technology Approach (STIRPAT). Additionally, the econometric strategy is adopted for the empirical analysis to acquire the symmetric and asymmetric outcomes. The empirical result validates the asymmetric association of FI and carbon dioxide (CO2) emanations in short and long lags. Besides, fossil energy utilization, industrialization, and urbanization smoothen the path of environmental pollution. However, human capital significantly aids in reducing carbon pollution in the short and long terms. The policy makers can practically implement the research to utilize FI effectively to improve environmental sustainability and develop policies that discourage fossil energy utilization. Moreover, we pointed out the alarming situation of dealing with harmful emissions from urbanization and industrialization.

Renewable energy was the only source available for the generation of energy since the ancient time. However, after the discovery of fossil fuels (initially as coal, after that crude oil and lately gas) it has lost ground in the 19th and 20th centuries in most industrialized countries majorly for heating and transportation purposes. Renewable sources such as biomass (In wood form) for heating, cooking, and lighting; then wind energy for navigation and for driving mills; lastly hydropower, also for driving mills; were only sources of energy available prior to the introduction of fossil fuels. From the late 20th century, renewable energy has become much popular because fossil fuels are depleting and have a serious negative impact on the environment; globally new policies and measures are widely implemented now to encourage its use but still it is a difficult to find the right support mechanism for the development of renewable energy, since technologies and costs are evolving exponentially. The present investigation is aimed to study the present situation and to forecast the future of renewable energy in the various sectors such as industrial, automobile, electricity generation and also focuses on how the consumption of fossil fuels can be brought down.

Biomass has the dual benefit of promoting economic expansion and protecting the environment. Sugarcane bagasse, animal manure, and kitchen waste are some of the sources of biomass waste that are abundant in Pakistan. However, achieving renewable energy goals while relying on Pakistani road plans is riddled with difficulties. In contrast, there is a significant research gap in examining the barriers to biomass energy development using the multiple‐criteria decision‐making technique. This study aims to fill a knowledge gap by applying the Pythagorean fuzzy analytic hierarchy process to the problem of how to overcome the barriers to expanding Pakistan's biomass power generation. The results reveal that the political and policies/institutions are the most noteworthy obstacle with a weight of 0.2281 and follow the economics and financial, meteorological, technology and infrastructure, and cultural and behavioural hurdles stand second to fifth places, respectively. In addition, the analyses demonstrate that political instability is the most important sub‐obstacle, possessing a global weight of 0.0471. According to the study's outcome, it is suggested that decision‐makers, stakeholders, and regulatory agencies coordinate their efforts to ensure the availability of appropriate incentives, boost feedstock supply, and offer locals training to speed up the Pakistan biomass industry's presently sluggish growth.

Adopting suitable energy policies that consider the existence of main obstacles could make the development of solar energy systems much smoother. Several obstacles have been placed in the way of solar energy development in Pakistan, which has prevented its growth from reaching a satisfactory level. In order to tackle these issues, it is necessary first to recognize the obstacles that stand in the way of implementing solar energy. So, this research aims to find and rank the obstacles to the expansion of solar power in Pakistan using a novel spherical fuzzy analytical hierarchy process. The results revealed that the economic obstacles category (21.46%) ranks highest among major categories. In contrast, the overall global ranking of sub-obstacles showed that budget constraints (4.68%), lack of access to credit/capital (4.52%), political instability (4.51%), high investment risk and operation cost (4.42%), and partnership issues (4.37%) are the more critical five sub-obstacles than the rest of the twenty-one obstacles within different categories. In addition, recommendations are made for the elimination of the obstacles. The current study has policy implications for policymakers, researchers, and practitioners involved in the solar sector in the country. Furthermore, it may help develop strategies for the smooth deployment of solar energy in Pakistan.

Extreme environmental events surging across the globe are the consequences of the human's race for attaining rapid economic growth driven by cheap energy sources. However, the consequences of such achievements are far beyond the benefits of the growth which severely affect environmental quality resulting in the rise of average global temperature, and various factors linked with changing climate. The current analysis takes into account a panel of Chinese provincial data from 2000 to 2020 to empirically examine the impact and the magnitude of GDP, renewable energy, imports of high technology, green financing strategies, and quality of institutions on the provincial emissions of carbon in China. The panel is tested for several diagnostic tests and a long-run cointegrating connection is confirmed among the factors under examination. The advanced technique of Method of Moment Quantiles Regression (MMQREG) confirms that GDP is detrimental, whereas, renewable energy, green finance, import of high technology, and institutional quality depict heterogenous impacts on carbon emissions. Furthermore, the robustness check of the Augmented Mean Group, Fully-Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) validates and supports the earlier findings of MMQREG. Based on the outcomes it is revealed that except for the GDP, the explanatory factors effectively cut provincial carbon emissions in China, nevertheless, the magnitude of the green financing strategies raised a valid question which depicts a decreasing trend across the quantiles. According to the findings, it is proposed that the country should first prioritize green and sustainable finance and upgrade the domestic industrial technology with the help of import of high-technology that will relive burden on the environmental quality. Secondly, quality institutions will play an important role in coordination among various green financial institutes that will further maximize the gain from deployment of renewable energy sources.

Small and Medium-sized Enterprises (SMEs) are more adaptable because of their size and straightforward structure; they will be better able to take advantage of changes and innovation. SMEs are common in the nation and have significantly increased Pakistan’s GDP. To achieve and guarantee these SMEs’ effective performance, they must improve the quality of their services. For this reason, the current study has looked into the significance of Supply Chain Integration (SCI). The present research has adopted a “quantitative research design” to conduct the study. Concerning the research framework, the independent variable is supplying chain logistic issues that impact SME service quality through the mediation of supply chain integration. There are two methods adopted for the data analysis. Firstly, the statistical package for social sciences (SPSS) is employed for the demographic outcomes. Secondly, regression, reliability and validity analysis are carried through the Structural Equation Model (SEM). The results of the study indicated the six linkages. Firstly, the association of High Cost of Information Technology (HCI) positively impacts Coordination and collaboration. Secondly, Quality Logistic Personnel (QLP) is positively and significantly associated with Commitment and competence. Thirdly, HCI indicated a positive link with Coordination and collaboration. Fourthly, QLP expresses a positive and significant relationship with Coordination and collaboration. Fifthly, QLP demonstrated a positive and significant association with Creativeness and customisation. Finally, QLP showed insignificant negative results with Coordination and collaboration. The present study holds greater significance in this regard. The study provides valuable insights to the employees or workforce of SME businesses to supervise or rationally monitor their supply chain performance. The service quality of SMEs has been measured through commitment and competence, creativity and customization, and coordination & collaboration of sales logistic personnel.

In a challenging environment, renewable energy (RE) entrepreneurs promote and encourage the enactment of new technologies and concepts, but they face several hurdles in promoting them. A basic research gap exists in investigating the ecopreneurship obstacles to RE development by using multiple-criteria decision-making (MCDM) approaches under uncertainty in a comprehensive study, this research thus intends to fill a research gap with the fuzzy MCDM approach to tackle the entrepreneurial obstacles to emerging economies' power generation growth, which can be divided into two parts. Firstly, a literature survey and discussion with experts were used to identify prospective obstacles. Secondly, a novel Spherical Fuzzy Analytical Hierarchical Process was used to finalize obstacle weights. The results showed that the 'Inadequate government or policy support' category, with a final weight of (0.2093), is the most essential among the major categories, and 'inadequate access to institutional finance' becomes the second rank. Compared with Pythagorean fuzzy AHP, our suggested technique incorporates more details considering the uneasiness of the decision-making atmosphere. In contrast, the overall global orders of obstacles revealed that 'Accessing credit', with a final weight of (0.0737), is more important than the other twenty-six obstacles.

A slew of economic, environmental, and social concerns has pushed policymakers and governments to embrace renewable energy (RE) technologies in order to ensure a sustainable energy future. RE technologies have a beneficial effect on the environment and social well-being. Therefore, this study presents a method for systematically determining and ranking the benefits of adopting RE technologies in remote areas and possible solutions. The present analysis is structured into four distinct levels. The benefits of RE technologies were identified through a comprehensive review of relevant literature. The Delphi technique was employed to reach a consensus and classify the advantages. Fourteen benefits were determined and classified according to seven primary criteria. Furthermore, the Fuzzy Analytic Hierarchy Process was employed to determine the weights and rankings. The Fuzzy VIekriterijumsko KOmpromisno Rangiranje method was ultimately used to evaluate the potential alternatives. The integrated method result significantly reveals that the environmental criteria are the most critical factor, with a weight of (0.1727), and are followed by the quality of energy aspect, with a weight of (0.1617). Moreover, the global weights show that Sustainability is ranked highest, followed by Skill development, then the other sub-benefits within different categories. These two benefits have relative weights of (9.9164%) and (9.4924%), respectively. Furthermore, the most effective solution facilitating local and foreign investors was the most promising among the four recommended alternatives. The quote has proven that it benefits the government and policymakers in deploying RE technologies and resolving energy challenges in remote areas of developing nations like Pakistan.

Greenhouse gas emissions are a major hazard to the planet's ecosystem and humanity and contribute to global warming. Consequently, it's critical to investigate China's emission-inducing elements' core functions. To that end, the dynamic effects of renewable energy, foreign remittances, globalization, financial development, and economic growth on carbon intensity in China are explored in this research. The study analyzed data spanning from 1990 to 2020 and employed the linear Autoregressive Distributed Lag (ARDL) technique and various diagnostic tests. The findings of the linear ARDL methodology reveal that renewable energy mitigates the destruction of the environment; however foreign remittances, globalization, financial development, and eco-nomic growth exacerbate environmental deterioration in China. Furthermore, the outcomes specify that renewable energy has a negative short-and long-term impact on environmental erosion. Renewable energy sources are a tremendous tool for supporting China's initiatives to protect energy independence while reducing climate change. Additionally, concrete actions need to be taken by the Chinese government to minimize CO2 emissions to boost social prosperity and sustainability.