In the wake of the 2015 Paris Agreement, green finance has emerged as a pivotal mechanism for addressing environmental challenges and achieving sustainable development goals (SDGs). This study employs a combined meta-analysis and bibliometric analysis to assess the evolving research landscape of green finance with a comparative lens on developed and developing economies. Based on 51 studies from Scopus (1990–2024) for bibliometric analysis and 17 studies for meta-analysis, the findings highlight distinct research patterns. Developing economies, particularly China and India, exhibit a rising trend in green finance research, emphasizing practical environmental solutions, whereas developed economies, including the United States, Sweden, and South Africa, focus on long-term strategies and foundational policy frameworks. The meta-regression analysis indicates that integrating green finance with financial development and renewable energy investments significantly enhances carbon reduction efforts. Model 2 results show that fintech and renewable energy investments contribute to emission reductions by 84% and 92%, respectively, at a 1% significance level. Moreover, interaction effects suggest that these investments yield greater benefits in developing economies, reducing emissions by 56% and 118%, respectively, at the 1% significance level. This study underscores the importance of Green Finance policies tailored to the specific economic contexts of nations to maximize environmental sustainability.

This research aims to examine how different generations in India adopt fintech services, considering the main barriers and demographic factors that influence these patterns. Based on a survey of 278 banking customers in Punjab and Jammu and Kashmir, it is evident that Generation Z and millennials have embraced fintech services more than Generation X, with key obstacles including a lack of technical skills, concerns about cybersecurity, and strict regulations. The findings suggest that implementing measures tailored to each generation will be essential in promoting digital financial services and bridging the gap between those who can access these services and those who cannot. Although fintech companies are increasingly recognised in the payments industry, the primary challenges to the rapid growth of the fintech ecosystem in India include "lack of technical know-how," "low security (fraud messages, calls, etc.)," regulatory and compliance laws, "documentation and formalities," and "emotional attachment to cash." Governments, financial institutions, regulators, and Indian fintech firms must collaborate to address these structural issues from the ground up, expand their reach, enhance consumer satisfaction, and make digital channels more accessible.

The contemporary workforce is being radically transformed by the emergence of Generation Z and the explosive growth of the gig economy. Gen Z differs from other generations in valuing flexibility, autonomy, and purposeful work more than the long-term employment model. Their technological literacy has redefined work standards, with freelancing, temporary contracts, and remote work becoming the new norm. While this trend is beneficial in the sense that it provides work-life balance and diversified sources of income, it has challenges in employment security, mental well-being, and career advancement. HR practitioners need to shift by embracing innovation, technology, and flexibility. The old model of employment does not suit Gen Z's needs anymore, calling for dynamic practices such as on-demand learning, customized benefits, and AI-enabled talent management. Yet, aligning digital evolution with a people-centric strategy continues to be the key.

The AI predictive analytics-based tool has broken the silence by prompting them to adopt proactive ex-ante risk management strategies as opposed to the previous schemes. predictive analytics permits the SME to anticipate imminent disturbances, form the trend, and detect anomalies in real-time through its application of machine learning algorithms and advanced data analytics techniques. Such methods can consequently be expected to cease or avert impacts created by the following: anticipated supply chain disruptions, possible financial vulnerabilities, and operational inefficiencies. Indeed, challenges abound in adopting AI solutions. Notwithstanding these challenges, SMEs have proved vibrant in adopting AI tools to enhance their risk mitigation frameworks and resilience against crisis events such as recession or global pandemics, as borne out by case studies. This review paper critically examines the different theoretical aspects and future prospects of AI-powered predictive analytics in the context of SME adoption.