ABSTRACT Ecological pressures associated with industrialization, energy use, and resource‐intensive production have intensified the need to identify strategies capable of strengthening ecological capacity, particularly in major emerging economies such as China. This study examines how green supply management (GSM), renewable technological innovations (RTI), and energy prices (EP) influence China's ecological capacity over the period 1990Q1–2024Q4. Ecological capacity is measured using the Load Capacity Factor (LCF), while the Quantile Autoregressive Distributed Lag approach captures heterogeneous short‐ and long‐run dynamics. The results confirm long‐run cointegration among the variables and highlight distributional heterogeneity across different quantiles of LCF. GSM exerts a positive long‐run effect on ecological capacity, whereas RTI does not generate a consistent ecological payoff, indicating the importance of effective diffusion and adoption. EP exhibits a negative long‐run association, underscoring the limitations of price‐based mechanisms. The findings provide policy‐relevant insights for advancing SDG 9 through greener supply chains, effective innovation diffusion, and sustainable infrastructure development in China.
ABSTRACT Tourism intermediaries are expected to contribute to sustainable development, yet research often stops at policies, intentions or reported practices. This review examines how far studies trace intermediary influence from organisational leverage and action to adoption by another actor and to sustainable outcomes. The corpus includes 113 Scopus and Web of Science reports published between 1997 and July 2026. The review was not prospectively registered. Design‐specific appraisal produced 20 higher, 41 moderate and 52 lower confidence ratings. Evidence is concentrated on tour operators and travel agencies; platforms and destination‐level effects remain underexamined. Orchestration appeared in 59 reports (52.2%), while translation and selection each appeared in 48 (42.5%). Most reports (97/113; 85.8%) stopped at or before intermediary action, whereas only 16 (14.2%) followed the chain to another actor's response or a measured sustainability outcome. The framework clarifies where evidence weakens and what future research should observe directly.
ABSTRACT Energy poverty, associated with SDG 7, remains pervasive in sub‐Saharan Africa (SSA) and is closely linked to sustainability (SDG 13), yet prior evidence is fragmented and often limited to a single indicator. This study re‐examines the energy poverty–environment nexus adopting three different environmental metrics and allowing impacts to vary across space and time. Using an SSA panel (1990–2023 and 30 countries), the Geographically Neural Network Weighted Regression (GNNWR) is applied to model load capacity factor (LCF), CO 2 emissions, and ecological footprint (EF) as functions of energy poverty (POV), GDP, urbanization, globalization, renewable energy use, and natural‐resource rents; robustness is assessed with Geographically and Temporally Neural Network Weighted Regression (GTNNWR). Diagnostic tests indicate a strong fit ( R 2 ≈0.81–0.93) and spatiotemporal non‐stationarity. POV is associated with higher CO 2 emissions, while it significantly reduces LCF, implying weaker ecological carrying capacity. Conversely, POV is linked to a lower EF, consistent with constrained access dampening consumption‐based pressures even as pollution and biocapacity dynamics worsen. Renewable energy consumption improves environmental quality by lowering EF and increasing LCF. GDP growth increases CO 2 and EF, whereas urbanization shows mixed effects (higher CO 2 and LCF but lower EF). Globalization raises CO 2 and EF but has a weak effect on LCF. Spatial diagnostics show that adverse POV effects cluster in Southern and Western SSA. GTNNWR confirms the main results. Policy should treat POV as an environmental risk and couple electrification and clean‐cooking access with accelerated deployment of renewables and region‐targeted measures where impacts are strongest.
ABSTRACT Amid an accelerated energy transition and growing regulatory and competitive pressures, this study analyses how energy and environmental constraints condition industrial productivity in the EU‐27 (2014–2024) and what role innovation plays in this process. It pursues two objectives: (i) to identify whether energy and emissions intensities constitute necessary conditions for high productivity; and (ii) to assess whether business innovation effort moderates their relationship with productivity and whether this effect is homogeneous across European economies. The analysis combines Necessary Condition Analysis, which identifies structural thresholds, with bias‐corrected dynamic fixed‐effects panel models, which allow productivity persistence and interaction effects to be analysed. Results show that energy and environmental pressures operate not as transitory costs but as structural constraints on industrial performance. From an economic policy perspective, this implies that the green transition requires considering energy and environmental constraints jointly with business innovation effort, taking into account structural differences across European economies.
ABSTRACT Global climate change and mounting pressure from environmental degradation necessitate a multidimensional examination of the determinants of the carbon footprint in rapidly growing economies. This article analyses the long‐term effects of the sustainable development index, foreign direct investment, the economic complexity index, and financial freedom on the carbon footprint within the context of the Next Eleven (N‐11) countries. Taking data availability into account, data for the period 1995–2022 were used for nine N‐11 countries. In the methodological process, tests for cross‐sectional dependence, homogeneity, and multicollinearity were first applied, followed by the CADF unit root test, and the Durbin–Hausman cointegration test. Long‐run coefficients were obtained using the DOLSMG and CupFM estimators. According to the estimation results from both DOLSMG and CupFM, the findings indicate that, across the panel, the sustainable development index, and foreign direct investment reduce the carbon footprint, whilst the economic complexity index, and financial freedom increase it. Country‐level results reveal that these effects vary significantly across the N‐11 countries. Consequently, carbon reduction policies should be designed not through a one‐size‐fits‐all approach, but by taking into account each country's production structure, energy mix, investment profile, and level of financial liberalization.
