This paper is a contribution to the ongoing debate on the benefits and drawbacks of bank revenue diversification. Revenue diversification may benefit banks if diversified activities are inherently less risky and possess high returns, while it may hurt banks if diversified activities are more risky and have low returns. Analyzing a panel dataset of 200 commercial banks from all South Asian countries, we found that overall revenue diversification into non-interest income has a positive impact on the profitability and stability of South Asian commercial banks. We further observed that different types of non-interest income-generating activities have different impacts on bank performance and stability. While fees and commission incomes have a negative impact on the profitability and stability of South Asian commercial banks, other non-interest income has a positive impact. Our results imply that banks can benefit from revenue diversification if they diversify into specific types of non-interest income-generating activities. Our findings are robust and relevant to the use of alternative measures of revenue diversification, profitability and stability.

The field of sustainable finance has grown rapidly in response to escalating climate and economic challenges, yet its intellectual landscape, especially the connectedness between green and traditional financial systems, remains underexplored. This paper aims to systematically map the evolution, thematic structure, and intellectual linkages of the sustainable finance literature with a specific focus on risk spillovers and connectedness across financial systems. This study employs a comprehensive bibliometric methodology to map 1261 Web of Science-indexed articles (1994–2024) on the connectedness of sustainable finance, using techniques such as citation analysis, bibliographic coupling, co-citation analysis, trend cartography, collaboration network, and keyword trend analysis. The study clarifies the field’s evolution and identifies its key themes, influential authors, institutions, and networks. The findings reveal an exponential surge in sustainable finance research after 2015, coinciding with policy milestones like the Paris Agreement and rising ESG investment interest. Notably, the review uncovers how research clusters have formed around topics such as green bond market spillovers, green technology innovation, and climate risk, highlighting both well-established areas and emerging fronts. The contribution lies in providing a roadmap for future research and policy: the study pinpoints knowledge gaps (e.g., systemic risk transmission between green and conventional assets) and suggests how policymakers and investors can leverage these insights to foster a resilient, sustainable financial system.

The rapid integration of FinTech and sustainability-oriented sectors is reshaping financial risk dynamics, particularly in emerging markets such as China. This study investigates tail-dependent spillovers among ten Chinese FinTech and sustainability-linked sectors from 2015–2024 using a factor-purged Quantile Vector Autoregression (QVAR) with generalized forecast error variance decompositions. By isolating idiosyncratic shocks, the framework uncovers how risk creation, transmission, and absorption vary across market states. Results show that (i) FinTech acts as a net transmitter of shocks in adverse (lower-tail) states, amplifying downside risk to clean energy and green innovations; (ii) policy-intensive sectors (environmental and atmospheric governance) switch roles across quantiles, revealing asymmetric regulatory spillovers; and (iii) diversification benefits compress in the tails, with cross-sector linkages intensifying during crises. These findings highlight the importance of quantile-specific stress testing for regulators and the design of state-contingent hedging strategies for portfolio managers.

Static concentration measures cannot show whether economically important trading relationships persist over time. This study constructs transaction-value-weighted measures of supplier and customer retention and incorporates them into a network-augmented model of firm productivity. Chinese value-added tax invoices and matched firm records from 2019 to 2025 yield an unbalanced panel of 443,506 firm–year observations. Supplier stability is the share of current purchases from suppliers retained from the preceding year, while customer stability is defined analogously using sales. Annual directed, weighted transaction networks are reconstructed from invoice flows, and DomiRank measures firms’ structural dominance. Total factor productivity is estimated using the Levinsohn–Petrin method. Firm and year fixed-effects estimates show negative relationships between both stability dimensions and productivity. Two-stage least-squares estimates using leave-one-out same-industry peer stability as instruments remain negative. Positive interactions with DomiRank indicate that stronger network positions attenuate these relationships. Potential operating-channel analyses associate stable ties with higher gross margins and asset turnover, but also with greater expenses, weaker operating profitability, slower inventory turnover, and longer operating cycles. Results are robust to alternative measures, matching, high-dimensional fixed effects, outlier treatment, lagged specifications, and industry–year stratified permutation tests. The findings show how longitudinal transaction statistics and network position jointly explain productivity heterogeneity among SMEs.