One major concern about foreign direct investment (FDI) is the potential negative environmental impact due to increased CO₂ emissions. However, there is a possibility that FDI mitigates CO₂ emissions through green innovation and creates a cleaner environment. In the existing literature, there is no significant empirical evidence on the linkage among FDI, green innovation and CO₂ emissions in the context of BRICS countries. Hence, this study aims to analyze the impact of FDI and green innovation on the environmental quality of BRICS economies for 1990–2014. The study employed Augmented Mean Group (AMG) estimators for empirical data analysis. The study’s findings depict that foreign direct investment, energy use, and economic growth have a significant and positive impact on the CO₂ emissions of BRICS economies. Moreover, green innovation has a significant inverse impact on CO₂ emissions. The results show bidirectional causalities between CO₂ emissions and green innovation, trade openness and CO₂ emissions, energy use and CO₂ emissions, and urbanization and CO₂ emissions. Additionally, the findings reveal a one-way causality from CO₂ emissions to GDP and CO₂ emissions to urbanization. This study offers essential policy recommendations for the environmental sustainability of BRICS countries through green innovation.

Purpose: In the era of knowledge economy, the significance of intellectual capital has been increasing globally. Similarly, recent studies have focused on the importance of green intellectual capital in mitigating environmental degradation. However, only a few studies have analysed green intellectual capital and its impacts in the specific case of Pakistan. Hence, this study aims to investigate the effects of green intellectual capital on green innovation adoption in Pakistan’s manufacturing small and medium-size enterprises (SMEs).Design/methodology/approach: We used a data sample of 235 SMEs, gathered from the four manufacturing sectors of Pakistan including: textile, chemical, pharmaceutical and steel and analysed using a multiple regression analysis approach.Findings: The empirical results of this research indicate that green human capital and green structural capital significantly increase green innovation adoption. However, it must be noted that green relational capital has a positive but insignificant impact on green innovation adoption in manufacturing SMEs in Pakistan.Originality/value: The findings and recommended policy measures of this study are important for the managers of manufacturing SMEs and policymakers to mitigate environmental destruction and achieve sustainable development through green intellectual capital.

Purpose: Recent research validates an increasing knowledge of environmental concerns in manufacturing small and medium enterprises (SMEs). However, only a few studies maintain that green human resource management (HRM) practices and corporate social responsibility (CSR) play an important role, especially in the case of developing economies. Thus, this study aims to examine the direct and indirect relationship between green HRM practices and environmental sustainability (ES) through the mediation of CSR in SMEs in Pakistan.Design/methodology/approach: The cross-sectional design of this study considers the mechanism by which green HRM practices affect ES through CSR in the context of Pakistani SMEs. The authors collected data from 320 manufacturing SMEs and used the partial least squares structural equation modelling (PLS-SEM) technique to examine the relationship between variables.Findings: The empirical findings of this study suggest green HRM practices have a positive and significant impact on ES. Further, the second hypothesis is not supported. In addition to the direct impact, the indirect effect of green HRM practices on CSR is positive and significant. Finally, the authors determine that green HRM practices affect ES through the partial mediation of CSR.Originality/value: To date, this study is the first to use CSR as a mediator between green HRM practices and ES in the context of Pakistani SMEs. The study has important implications for HRM and government policy makers, suggesting they should improve strategies in favour of the green economy. Furthermore, developing countries could design similar studies with different future sustainability factors.

Purpose: In light of the shift in focus from information communication technology (ICT) access (access divide) and skills (skills divide) to the tangible impacts of ICT use (impact divide), a growing number of scholars have called for further investigation into the inter-territorial and multi-dimensional aspects of the digital divide in China. This study aims to address these gaps by examining the disparities across 31 provinces, particularly emphasizing the transition from the traditional access and skills divides to the impact divide.Design/methodology/approach: Multivariate regression analysis extensively investigates the transition from the access and skills divides to the impact divide across 31 provinces. Additionally, ArcGIS software is used to analyze spatial agglomeration and the auto-correlation (Moran-i) and predict mapping patterns in the data corresponding to all three levels of the digital divide.Findings: According to the study's findings, poverty is a significant factor in the digital divide between different regions in China. The research shows that provinces with advanced administrative systems, such as Guangdong, Shanghai, Beijing, Jiangsu, Shandon and Zhejiang, have high scores on the digital development index (DDI). However, regions with poverty-ridden and rural areas, primarily located in southwest, central and western China, tend to have lower DDI scores.Originality/value: This study offers a novel contribution to the literature by presenting an innovative conceptual framework that explores the impact divide within China's provinces. The authors also address this lacuna in the literature by developing and testing two dimensions to examine the relationships statistically under a wide range of socioeconomic and ICT indicators.