ABSTRACT Despite growing scholarly attention on eco‐innovation as a strategic response to environmental sustainability challenges, limited understanding persists regarding how internal resources and external institutional pressures interact to shape firms' eco‐innovation practices. Anchored in the resource‐based view (RBV), institutional theory, and the dynamic capabilities perspective, this study investigates how organisational resources and institutional pressures influence eco‐innovation through a proactive environmental strategy, and how green agility strengthens this relationship. Using data from 187 technologically innovative firms collected through a two‐wave time‐lagged survey, Partial Least Squares (PLS) path modelling and Artificial Neural Networks (ANN) were employed to test the proposed model and validate its predictive performance. Results reveal that market demand, environmental capability, regulatory pressure and managerial concern significantly drive proactive environmental strategy, which in turn enhances eco‐innovation practices. Both PLS and ANN analyses converge on market demand as the most influential determinant. Moreover, green agility strengthens the effect of proactive environmental strategy on eco‐innovation, highlighting its function as an adaptive dynamic capability in rapidly changing environments. Cross‐validated predictive ability tests (CVPAT) further confirm the model's predictive robustness. This study advances theoretical understanding by integrating RBV, institutional and dynamic capabilities perspectives and offers practical insights for managers seeking to leverage strategic resources and agility to accelerate eco‐innovation.

ABSTRACT This study develops a mixed‐integer nonlinear optimisation model to jointly minimise PM 10 and CO 2 emissions from urban road transport in nine of Türkiye's most densely populated provinces, aligning with the targets of the Paris Agreement. The model is novel in its integration of environmental baselines (city‐level PM 10 and CO 2 levels), economic feasibility (GDP), and urban form variables (population density and land‐use ratios), creating a realistic and context‐aware decision framework. It applies three tiers of constraints: (i) 2023 regulatory emission ceilings, (ii) GDP‐based economic capacity thresholds, and (iii) nonlinear constraints reflecting how urban morphology influences policy adoption. A composite climate impact index—capturing post‐policy PM 10 , CO 2 , and their interaction—serves as the objective function to yield granular, city‐specific mitigation scenarios. Results indicate that cities like Ankara, Bursa, and Antalya can virtually eliminate PM 10 emissions, while Istanbul achieves the highest CO 2 reduction (87%), collectively delivering nearly 20 Tg CO 2 ‐equivalent reduction. Sensitivity analysis confirms that moderate increases in GDP can enhance mitigation outcomes by expanding feasible policy space. As the first model in the Turkish context to embed both urban planning and economic structure into dual‐pollutant optimisation, this framework offers not only predictive capacity but also prescriptive guidance for policymakers. It enables comparative assessment of emission‐reduction strategies—such as fleet electrification, low‐emission zones, and transit infrastructure investment—offering a robust and transferable tool for other rapidly urbanising regions aiming to simultaneously advance air quality, public health, and climate resilience.

ABSTRACT Effective management of natural resources is paramount for achieving sustainable economic growth while mitigating environmental degradation in resource‐rich regions. This study investigates the impact and spatial spillover effects of natural resources on economic growth and CO 2 emissions for 54 African countries. The data from 2005 to 2022 were collected from the World Development Indicators (WDI). Recognizing the endogeneity issues, the study utilized two‐stage least square estimation approaches, including panel 2SLS, Spatial Autoregressive (SAR), and Spatial Durbin Model (SDM) estimations to obtain both spatial and non‐spatial estimates. The non‐spatial results indicate a strong positive impact of natural resources, CO 2 emissions, FDI, and governance on growth, while reliance on renewable energy sources may temporarily lower GDP due to initial transition costs. Moreover, GDP growth, FDI, and governance positively affect CO 2 emissions, whereas natural resources and renewable energy inversely influence CO 2 emissions. In addition, the spatial analysis findings reveal that GDP growth in one country positively influences GDP growth in neighboring countries and neighboring countries' natural resources also have significant spatial spillover effects on the GDP growth in the region. Moreover, CO 2 emissions exhibit spatial interdependence with neighboring nations and the natural resources of neighboring countries exert significant spatial spillover effects on CO 2 emissions. This study contributes to the literature by providing a comprehensive spatial and non‐spatial analysis of the natural resource‐economic growth‐environment nexus in Africa. It provides novel insights into the spatial spillover effects that have been overlooked in prior research. The findings recommend boosting regional cooperation in resource management and emission reduction to get benefits on positive GDP growth spillover effects and mitigate CO 2 emissions across neighboring African countries.

ABSTRACT One of India's strategic goals is to boost the country's use of renewable energy; however, limited empirical insight exists on how the financial sector influences this transition. This study explores the intricate relationship between financial development and renewable energy generation, focusing on the differentiated roles of financial institutions and financial markets in India. Employing the Autoregressive Distributed Lag (ARDL) approach over the period 1990–2019, the study justifies its methodology due to the mixed order of integration revealed through unit root tests and the need to model both short‐run and long‐run dynamics. Additionally, a structural break in the data identified through the Chow test reinforces the appropriateness of using ARDL for robust inference. The results confirm the existence of a stable long‐run equilibrium relationship among the variables, as shown by the ARDL bounds F‐test. Empirical findings demonstrate that financial institutions exert a statistically significant and positive influence on renewable energy deployment in the short and long run. At the same time, financial markets also contribute positively, albeit to a lesser extent. These findings have significant policy implications: enhancing the depth and efficiency of financial institutions could accelerate India's renewable energy goals. In light of these results, the study advocates for targeted financial sector reforms, improved regulatory frameworks, and supportive investment mechanisms to bridge financial gaps in clean energy sectors. The insights offer valuable guidance for policymakers to align financial development strategies with India's sustainable development and energy transition objectives.

ABSTRACTThe present study endeavors to investigate whether there exists a trade‐off between banking profitability stemming from credit expansion activities and endeavors aligned with sustainable development goals (SDGs) in Vietnam. Spanning from 2000 to 2022, the study utilizes banking profitability data (ROA) retrieved from the WDI database, and SDG data, encompassing SD2, SD3, SD4, SD6, SD7, SD12, and SD13, sourced from SDG. Employing two combined non‐parametric methodologies, Quantile‐on‐Quantile regression and Wavelet coherence models, the research unveils compelling insights. Notably, concerning SDG2, SDG4, SDG6, SDG7, and SDG12, the support extended by banks toward these objectives indicates both positive and negative associations over the study duration. A robust negative correlation is discerned between SDG12 and ROA, implying that financing activities and projects aligned with SDG12 in Vietnam may entail disproportionately high costs relative to the profits accrued. Conversely, SDG13 manifests a positive correlation across quantiles, suggesting that banks in Vietnam endorsing endeavors aimed at addressing climate change could bolster their profitability. Moreover, intervals of positive correlation between ROA and SDGs (excluding SDG12) are notably pronounced in the 2015–2016 timeframe, following the SDG summit, underscoring the importance of SD‐focused initiatives and sending clear signals to economic actors, including banks, to rally behind these objectives.

ABSTRACTRecent evidence highlights China as the leading generator of waste in the Asia‐Pacific region, placing the nation under further scrutiny for environmental challenges beyond its carbon emissions profile. Although climate finance initiatives and recycling practices are recognized within SDGs 3, 6, 12, and 13 as potential strategies to curb this ecological burden, empirical studies focusing specifically on China remain limited. To address this gap, the present research delivers the first empirical assessment of both the symmetric and asymmetric impacts of waste management and financial development (FDV) on carbon emissions in China. A further contribution is the construction of a composite index for green policies, derived from three key elements—green technology, green finance, and renewable energy. The analysis also incorporates urbanization and affluence as control factors, using quarterly data spanning 1997Q1–2022Q4. Methodologically, the study employs autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) approaches, complemented by robustness checks using long‐run estimators. The findings show that improvements in waste management exert a positive influence on climate neutrality, whereas adverse shocks prove insignificant. By contrast, financial development displays negligible effects when positive but worsens environmental outcomes when negative. The green policy index and its components support climate neutrality, while affluence and urbanization act as impediments. Causality tests further indicate both unidirectional and bidirectional relationships, underscoring the predictive power of these parameters in shaping China's pathway toward climate neutrality. Based on these results, the study outlines policy measures aimed at reinforcing the pursuit of climate neutrality.

ABSTRACTPursuing sustainable development in the contemporary era necessitates a comprehensive understanding of the intricate dynamics between environmental factors and socio‐economic processes. This study scrutinizes how energy security risk, information and communication technologies, natural resource rents, and green innovation affect environmental quality in the United States. This research uses data from 1990 to 2020 and applies advanced methods, including Fourier‐based cointegration and long‐run estimators, to analyze the relationships between these variables and environmental outcomes. The study robustly indicates that energy security risk, information and communication technologies, and natural resource rents exert detrimental effects on ecological quality. Conversely, the analysis demonstrates that green innovation positively contributes to improving environmental quality. The findings highlight the balance between technology, resource use, and environmental sustainability, emphasizing the need for strategies to reduce negative effects and support sustainable development.

ABSTRACTEnvironmental concerns, such as carbon emissions, are critical to address for attaining sustainable development goals because they significantly impact climate change, public health, and the sustainability of ecosystems. This study is grounded in ecological modernization theory (EMT) and considers green factors—renewable energy consumption (GRNE), adjusted net savings (GANS), and forest area (GFAL)—and blue factors—aquaculture (BACP) and fisheries production (BTFP)—of the economy and foreign direct investment in addressing environmental concerns and mitigating their impact on carbon emissions in South Asia. The novel panel quantile regression technique is applied to data from 1992 to 2022. The results reveal significant heterogeneity in the impact of these factors across different levels of carbon emissions. GRNE demonstrates a strong negative effect on emissions, especially in higher quantiles, underscoring its role in mitigating environmental degradation. GANS shows a significant reduction in emissions in mid‐level quantiles, but its impact diminishes in the highest quantiles. Conversely, GFAL has a counterintuitive positive relationship with emissions across most quantiles, suggesting deforestation or forest mismanagement in the region. BACP consistently reduces emissions in lower quantiles, while BTFP exhibits a positive relation with emissions, particularly in middle quantiles, likely due to the carbon‐intensive nature of fisheries. Finally, CFDI is associated with higher emissions in the middle‐ and higher quantiles, indicating that foreign investments may be directed toward polluting sectors. The slope equality test confirms that the coefficients are unequal across the specified quantiles, while symmetric quantile tests endorse asymmetrical effects. This study offers critical insights into how South Asia's energy consumption and resource management impact carbon emissions, highlighting the effectiveness of the Sustainable Development Goals (SDGs) for 2030. Policymakers should consider these diverse/quantile specified effects when designing targeted strategies to reduce carbon emissions. Nevertheless, leveraging the strengths of green and blue factors in the economy and responsible investment practices can help attain the SDGs.

ABSTRACTOver the past three decades, Africa has been rapidly urbanizing. This urbanization has been fueled by a massive exodus of rural populations to urban centers in search of better living conditions. However, there is no consensus on the consequences of this rapid urbanization on the various development indicators. In this paper, we appreciate the effect of urbanization on happiness in Africa. To achieve this, we specify and estimate a panel data model from a sample of 34 countries over the period 2006–2019. The estimation is done by several techniques: the Ordinary Least Squares (OLS), the Fixed Effects (FE), the Random Effects (RE), and the Two Step Least Squares (2SLS) methods. Overall, our results show that urbanization, approximated by the rate of the population living in urban areas, significantly reduces happiness in Africa captured by the life ladder. This result remains robust when quantile regression (QR) is used as an alternative estimation technique, thus indicating improving the urban living environment through physical infrastructural development and environmental sanitation.