Purpose: Considering the importance of pro-environmental behaviors in achieving Sustainable Development Goals, this paper examines and strengthens the understanding of how green rewards shape employees’ sustainable actions by integrating Stimulus-Organism-Response theory with Social Cognitive Theory. This paper explores the interplay between green rewards and pro-environmental behaviors. Specifically, this paper highlights the role of environmental passion as an internal mediating mechanism, and also analyzing the moderating influence of AI literacy as a critical capability in the digital era. Methods: This paper employed the Partial Least Squares Structural Equation Modeling combined with Artificial Neural Network analysis to capture both linear and nonlinear patterns in employee behaviors. The questionnaire respondents were from employees across various manufacturing and service sectors in China, with a total of 445 valid responses. Results: The results revealed that green rewards not only motivate pro-environmental behaviors but also foster positive environmental passion, which further enhance sustainable actions. Moreover, AI literacy significantly strengthens the positive influence of green rewards, amplifying their impacts on both environmental passion and pro-environmental behaviors. In addition, Artificial Neural Network analysis consistently identifies green rewards as the most influential predictor for both pro-environmental behaviors and environmental passion. Conclusion: These findings provided empirical support for the Stimulus-Organism-Response theory and the Social Cognitive theory. Results demonstrates that external incentives and internal psychological states jointly shape sustainable employee behaviors. To effectively promote pro-environmental behaviors, policymakers and managers should design targeted, sector-specific incentives and boost AI literacy.

In an era characterized by mounting ecological challenges, tertiary education establishments confront the imperative to execute Sustainable Development Goal 4. The potential of education fiscal investments in driving environmental development and preservation has emerged as a focal point in contemporary policy discourse. This research plans to analyze the interrelationship between tertiary education systems and environmental sustainability, with particular emphasis on how educational policy moderates the connection between carbon emissions and key educational parameters, including infrastructure, student enrollment, and resource allocation. Partial least squares structural equation modelling is employed alongside a panel autoregressive distributed lag model and fixed effects regression with Driscoll–Kraay standard errors for robustness testing. The findings reveal that tertiary educational student enrollment and infrastructure are linked to reduced carbon emissions over time. In contrast, increased tertiary educational resource allocation aligning with policy is positively associated with carbon emissions in the short term. Educational policy plays a dual role, either reinforcing or mitigating these effects depending on its design and enforcement. This study contributes to the literature by clarifying the dynamic interplay between education systems and environmental outcomes. It offers practical guidance for policymakers, emphasizing the need to align education policies with environmental goals. Specifically, integrating sustainability into campus development and leveraging student engagement is critical to advancing both SDG 4 and SDG 13.

Environmental tax systems serve as a particularly effective mechanism for governments in mitigating ecological damage and achieving sustainable development. OECD countries account for nearly 70% of global energy-related CO2 emissions in 2024. Considerably high emissions underscore the ongoing necessity for OECD economies to examine environmental sustainability. A comprehensive investigation into the environmental taxation frameworks across OECD member states would provide insight into whether their tax policies reasonably promote their energy or technological innovations, thereby enhancing the efficacy of environmentally oriented tax regimes. This research primarily seeks to investigate how environmental related tax interacts with digital transformation processes and renewable energy utilization patterns to shape consumption-derived carbon dioxide emissions throughout OECD nations. This paper employs the Feasible Generalized Least Squares (FGLS) and Panel-Corrected Standard Error (PCSE) analytical models to examine the moderating role of environmental taxation on how digital technologies and renewable energy consumption in influencing carbon emissions in OECD economies. The empirical analysis draws upon longitudinal macro-panel datasets encompassing 32 OECD member countries over a two-decade period spanning from 2001 through 2021. The empirical evidence robustly demonstrated the regulatory effectiveness of environmental taxation mechanism, as it consistently exhibited a negative and statistically significant effect on emissions across various model specifications. Effective environmental related taxes can augment the ability of digital technology to foster environmental efficiency. In addition, environmental related taxes may increase emissions when applied concurrently with renewable energy consumption. Comprehensive policy strategies that include environmental taxation, digital transformation, and robust institutional frameworks are crucial for achieving significant environmental advancements and ongoing economic growth. Governments should consistently advocate for digital innovation and renewable energy consumption, but these initiatives must be supported by more optimal environmental tax policies.

Environmental tax systems serve as a particularly effective mechanism for sustainable fiscal performances as well as the efficient and environmentally responsible behaviors. In OECD countries, the effectiveness of environmental tax revenue depends not only on economic structure but also on institutional quality and ICT development. However, empirical evidences on how institutional quality, economic complexity, and ICT development jointly influence environmental tax revenue remains limited. This paper aims to analyze the moderating role of ICT in influencing relationships between institutional quality, economic complexity, and environmental tax revenue capacity. Using 28 OECD member countries’ data spanning from 2002 to 2022, this paper employs the fixed-effects model with clustered standard errors model and cross-sectional augmented autoregressive distributed lag test these relationships. Control variables related to macroeconomic conditions and structural characteristics are included to ensure robustness of estimation, including gross domestic product, foreign direct investment, inflation rate and trade openness. The results indicate that institutional quality and economic complexity both have positive effects on environmental tax revenue. ICT development is found to strengthen the positive relationship between economic complexity and environmental tax revenue. However, ICT development weakens the positive effect of institutional quality on environmental tax revenue. This negative moderating suggests that ICT development may reduce the taxable base by improving environmental efficiency and compliance. Although ICT expansion improves the environmental-tax capacity of complex economies, it can substitute the institutional channel through the promotion of emission reduction and cleaner production. These findings imply that OECD government officials need to more closely coordinate digital governance mechanisms with environmental tax plans in order to reconcile their fiscal objectives and environmental performance.

Environmental taxes have received considerable attention as a fundamental policy for environmental regulation and sustainable development. However, empirical evidence found the contradictory relations between environmental taxation and emissions among OECD countries. This paper is aimed to analyze whether environmental taxation moderate the net effect of the shadow economy, AI adoption, and ICT penetration on CO2 emissions in OECD countries. Limited by the availability of dataset, this paper chose 20 OECD countries and employed the fixed-effects model with clustered standard errors model and cross-sectional augmented autoregressive distributed lag model to check their relationships. Findings show that environmental taxes consistently reduce environmental emissions, underscoring their effectiveness as a policy tool for OECD economies. In contrast, the shadow economy worsens environmental performance, although its interaction with environmental taxes demonstrates that tax policy can partially offset the distortions caused by informality. AI adoption increases environmental quality, and interaction with environmental taxes further strengthens this effect, suggesting that AI can strengthen tax effectiveness. ICT shows no significant direct impact on environmental performance. However, its interaction with environmental taxes could reduce the emissions, indicating that tax outcomes vary with technological structure. This interaction indicates that ICT yields environmental benefits only when supported by strong fiscal frameworks. These results highlight that environmental taxation play a key role in reaching emission targets as a conditional policy tool rather than a universally effective instrument. Its performance depends on tax design, enforcement capacity, and the broader structural context, including informality and technological development. It contributes to the literature by offering empirical evidence on double dividend hypothesis and showing how fiscal instruments and technological progress interact with each other in reducing environmental emissions. The results imply that tax design should be aligned with country-specific and technological conditions to enhance policy effectiveness. Integrating environmental taxes with digital transformation strategies is important for mitigating environmental emissions of OECD countries.