Brahim Bergougui

The convergence of Industry 4.0 and global sustainability goals presents a critical paradox: while automation drives efficiency, its net impact on comprehensive environmental, social, and governance (ESG) performance remains contested. This study investigates the relationship between industrial robot and country‐level ESG performance across 63 countries over the period 2010–2024. We construct a novel entropy‐weighted composite ESG index integrating 60 indicators across ESG dimensions. The results demonstrate that industrial robots enhance ESG performance. Mediation analysis reveals that this effect operates not only through direct operational efficiency but through two transmission channels: innovation and human capital. Crucially, threshold regression uncovers nonlinear dynamics: using climate actions—measured through climate change adaptation and mitigation—as threshold variables, we find that the robotics–ESG relationship is negative or negligible under weak climate actions but amplifies substantially once countries surpass critical policy thresholds—a pattern consistent with policy‐dependent regime switching. Spatial analysis further reveals a distance‐decay effect, whereby ESG gains from automation are concentrated among countries proximate to major robotics innovation hubs (Japan, the United States, and Germany) and attenuate with geographic distance. Heterogeneity analysis identifies digital infrastructure maturity as the most powerful conditioning factor, with digitally advanced countries experiencing nearly fourfold greater ESG returns from robotics, while countries with limited digital capacity exhibit negative returns. These findings suggest that realizing the sustainability potential of industrial automation requires integrated policy frameworks that synchronize climate governance, innovation ecosystems, human capital investment, and digital infrastructure development.

Economies around the world are currently facing the significant challenge of balancing economic growth with ecological sustainability. While this is a global issue, emerging economies, because of their substantial environmental, demographic, and economic influence, deserve urgent attention. In light of the above, this study examines the factors shaping environmental sustainability (proxied by consumption-based carbon emissions) in emerging seven economies (E7) from 2004 to 2021. The study deployed the novel Method of Moment Quantile-based Regression (MMQR) and revealed that natural resources have negative effects on ecological sustainability by increasing consumption-based carbon emissions (CCO ₂₎ in E7 economies across all quantiles. Conversely, financial inclusion, financial globalization and the adoption of renewable energy decrease CCO ₂ thereby improving performance. In other words, the study established that higher dependence on resource endowment intensifies ecological harm whereas financial inclusion, renewable energy deployment and financial globalization strengthens ecological quality. Given these discoveries, the study underlined the criticality of enhancing resource governance to effectively guarantee that resources are exploited responsibly, catalyzing the uptake of green energy to delink growth from resource-based emissions and encouraging financial institutions to offer sustainable financial instruments. These strategies can bolster environmental well-being while also promoting inclusive economic development.

This paper examines the relationship between industrial robotics adoption and ecological capacity, measured by biocapacity, using panel data from 50 countries over the period 2000–2024. We investigate the transmission mechanisms, non‐linearities, spatial spillovers, and heterogeneity characterizing this relationship. Our empirical analysis yields five principal findings. First , industrial robotics demonstrates a positive effect on biocapacity. Second , mechanism analysis reveals that robotics strengthens ecological capacity through two primary transmission channels: institutional flexibility via reduced transaction costs and accelerated green‐biased technological progress, with the latter representing the dominant pathway. Third , threshold regression models identify a three‐regime non‐linear relationship: Robotics exhibits modest positive effects at low levels of industrial upgrading, counterintuitively adverse effects during the intermediate transition phase, and substantially amplified positive effects at advanced stages of industrial upgrading. Fourth , spillover analysis shows that ecological gains from robotics are significantly larger in countries with geographic proximity to Japan, the global robotics innovation hub, while trade‐based heterogeneity reveals substantially amplified effects in high‐trade economies and significant effects exclusively in countries with deep global value chain integration. Fifth , heterogeneity analysis demonstrates that robotics' environmental benefits are greater in high‐income countries, those with advanced digital infrastructure, and high‐population‐density economies, while effects are attenuated or negative in low‐income and digitally‐limited contexts. The results imply that policy sequencing—combining robotics deployment with structural upgrading, institutional strengthening, skills and infrastructure investments, and strategic trade integration—is essential to secure sustained improvements in ecological capacity.

Algeria's hydrocarbon-dependent economy faces significant challenges in diversifying its energy mix to achieve sustainability and reduce vulnerability to global energy market fluctuations. Despite abundant natural resources, the country's heavy reliance on fossil fuels has hindered progress toward energy diversification, as measured by the energy diversification index. This study investigates the asymmetric impacts of institutional quality, green technologies, and natural resources on Algeria's energy diversification from 1995/Q1 to 2022/Q4, addressing a critical literature gap. Using the Fourier nonlinear autoregressive distributed lag model, the study explores long-term equilibrium relationships and asymmetric dynamics between these variables and energy diversification. The analysis reveals that positive shocks in institutional quality lead to substantial increases in energy diversification, underscoring strong governance's crucial role in promoting energy transitions. Conversely, negative institutional shocks significantly reduce energy diversification, highlighting the detrimental effects of declining governance quality. Similarly, positive green technology shocks enhance energy diversification, while negative shocks diminish it. Natural resources exhibit dual effects: positive shocks result in modest energy diversification increases, suggesting resource revenues can support renewable projects; however, negative shocks lead to decreases, emphasizing fiscal volatility's destabilizing impact on energy diversification. These findings confirm asymmetric relationships, as positive and negative shocks significantly influence Algeria's energy diversification differently. Policy implications underscore the need for continuous governance reforms, enhanced anti-corruption measures, and transparent regulatory frameworks to attract renewable energy investments. Strategic reallocation of hydrocarbon revenues—through mechanisms similar to Norway's sovereign wealth fund model—could mitigate fiscal risks and support green transitions, providing actionable insights for transforming Algeria's energy landscape.

The European Union’s commitment to achieving climate neutrality by 2050 requires sustainable economic models that address both environmental degradation and energy security. While renewable energy technologies are recognized solutions to climate change, the relationship between circular economy principles and clean energy transition remains underexplored empirically. This study investigates the asymmetric relationship between circular economy implementation and clean energy development across 27 EU economies from 2010–2023. Using Method of Moments Quantile Regression to capture distributional heterogeneity, we reveal pronounced asymmetric effects of circular economy shocks on clean energy adoption. Positive circular economy shocks demonstrate amplified benefits in high-performing clean energy economies, with elasticity coefficients increasing across quantiles, indicating that nations with established renewable infrastructure optimally capitalize on circular economy improvements through synergistic effects. Conversely, negative shocks manifest heterogeneous impacts: lower-performing countries experience significant clean energy contractions, while advanced economies exhibit resilience, suggesting adaptive mechanisms that enable resource reallocation toward alternative sustainability pathways. These findings provide policymakers with an analytical foundation for optimizing circular economy strategies to accelerate EU climate-neutrality objectives while accounting for heterogeneous national circumstances and transition pathways.