This study investigates the potential of digital financial inclusion to reduce regional poverty in China, an issue that has received varying opinions from the academic community. Using panel data from 31 provinces, municipalities, and autonomous regions (2011–2020) and employing the system GMM, this paper analyzes the dynamic relationship between regional poverty and the growth of digital financial inclusion, as measured by the ‘Peking University Digital Financial Inclusion Index’. Controlling for factors such as the Gini coefficient, industrial structure, financial support for agriculture and education, and economic openness, this research finds that digital financial inclusion has a marked ability to reduce poverty rates. Moreover, our results indicate an intergenerational transmission characteristic in poverty, where prior levels significantly influence current poverty incidence. The study concludes that the recent acceleration of digital financial inclusion can be harnessed for meaningful poverty reduction. This study’s policy recommendations highlight the need for financial development to foster industrial and social growth and stress the importance of financial education for low-income populations. Additionally, it calls for increased management and oversight of inclusive and agricultural digital financial products and services.

This paper studied the impact of education investment on regional poverty alleviation of Yunnan’s poor counties, especially the dynamic constraints and marginal benefits of education input. This paper takes 30 poor counties in Yunnan province from 2007 to 2020 as the research object. A double fixed effect model, a systematic GMM model, and a quantile regression model are used to study the effect of education investment on regional poverty alleviation from static and dynamic levels. The results show that education investment has a significant positive effect on regional poverty alleviation at both static and dynamic levels. At the same time, under different poverty levels, the effect of education investment on poverty alleviation shows a law of diminishing marginal effect. As for the current situation of poor counties in Yunnan Province, the effect of education investment on poverty alleviation is increasing at a decreasing rate. The research object of this paper has achieved the goal of getting rid of absolute poverty, so the conclusion of this paper has more reference value.

Confronted with challenges such as escalating demand, expanding energy consumption, and emissions, China’s manufacturing sector stands at a pivotal juncture on its path towards sustainable development. Against the backdrop of a new wave of technological revolution and industrial transformation, exploring how the digital economy can foster growth in green total factor productivity (GTFP), particularly amidst technological diversification, holds significant importance for realizing sustainable development objectives. This study employs the system generalized method of moments (System GMM), encompassing 30 provinces in China, to delve deeply into the notable and dynamic correlation between the development index of the digital economy and GTFP. The findings reveal that the advancement of the digital economy significantly influences GTFP, underscoring its direct and enduring impact on green productivity. Key mechanisms through which the digital economy promotes green productivity are identified, including resource optimization, green technological innovation, data-driven decision making, and the transformation of environmentally sustainable behaviors. By bridging gaps in existing literature, this study integrates economic and environmental perspectives, emphasizing the necessity for formulating digital innovation policies aligned with environmental objectives. It provides richer insights into the role of the digital economy in enhancing GTFP, accentuating the potential of digital technologies in driving green transformation. With its holistic approach, this study combines economic efficiency with environmental sustainability, offering crucial guidance for policymakers and industry stakeholders in crafting sustainable development strategies.

As organizations strive to balance environmental stewardship with economic competitiveness, understanding the performance implications of Green Innovation (GI) has become increasingly important. Although the nexus between Green Product Innovation (GPI), Green Process Innovation (GPrI), and organizational outcomes has attracted sustained scholarly attention, empirical evidence remains inconclusive. To reconcile these inconsistencies and delineate boundary conditions, this study synthesizes data from 48 empirical investigations (2012–2025) via a random-effects meta-analysis with the Hartung–Knapp adjustment and trim-and-fill procedures to strengthen statistical inference. Results reveal significant small-to-moderate positive associations between GI and environmental (r = 0.172), financial (r = 0.191), and innovation performance (r = 0.143). Notably, moderator analyses demonstrate a synergy premium, where Integrated GI measures significantly outperform isolated GPI or GPrI approaches (r = 0.353). Substantial heterogeneity exists (I² = 91.2%), which is significantly moderated by innovation type, industry pollution intensity, geographic region, and research design. Our findings reinforce the Natural-Resource-Based View (NRBV) and the Dynamic Capabilities framework, highlighting that strategic returns depend on asset orchestration and contextual factors. We conclude that firms should adopt a holistic approach, integrating both product and process innovations to enhance competitive advantage in an incremental and context-contingent manner, while interpreting innovation-performance results cautiously given the limited evidence base.