The Asia Pacific, led by the resource-dependent ASEAN-5, is the largest carbon contributor, yet its firms exhibit critically low transparency. This study examines the relationship between voluntary Sustainability Assurance (SA) and carbon disclosure transparency using 875 firm-year observations (2018–2022). Applying panel regression and several robustness tests, we find that SA adoption has a positive relationship with the magnitude of disclosed carbon emissions, indicating enhanced transparency. This positive relationship is significantly more pronounced in firms with high environmental performance and greater property, plant, and equipment (PPE) efficiency, suggesting SA aligns with genuine sustainability efforts rather than symbolic reporting. Furthermore, SA increases the likelihood of disclosing the complex Scope 3 emissions. However, the effectiveness of SA is conditional: its transparency benefit is statistically significant only within mandatory sustainability reporting (SR) regimes and in non-environmentally sensitive industries, highlighting crucial variations across regulatory and industrial contexts within ASEAN-5. This research provides evidence on the role of SA in emerging markets, extending Agency Theory by demonstrating its function as a credibility signal that reduces information asymmetry. We offer practical guidance for managers seeking market differentiation, and for regulators aiming to align voluntary SA with IFRS S1/S2 to enhance disclosure quality.

This study investigates the moderating effect of mergers and acquisitions (M&A) on the relationship between credit risk and bank value. Using moderation analysis, robust panel regressions, and an objective credit risk metric, it addresses limitations of prior research that relied on event study methods prone to bias or discretionary risk metrics, offering a comprehensive framework for analyzing credit risk and value creation in the context of M&A in the banking industry. The findings reveal a significant negative association between credit risk and bank value, a direct positive effect of M&A on value, and a moderating effect whereby M&A exacerbates the adverse impact of credit risk. These results provide actionable insights for investors, practitioners, and policymakers, who should be especially mindful of credit risks in M&A contexts.

This research examines the macroeconomic determinants of inflation in Cambodia with an ARDL cointegration analysis. The results demonstrate a long-run negative association between inflation and exchange rates, tax revenue, and broad money. In the short run, growth in tax revenues dampens inflation, while money supply growth boosts it. Looking at the results, we can infer that expansionary fiscal policy (in particular, tax effort) and prudent monetary policy can control Cambodia’s currency and inflation. Policymakers should take into account the system of relationships among these macroeconomic variables to design such policies, which can cause price stability and long-term growth in the economy.

Financial markets evolve through recurring phases of stability, turbulence, and structural transformation. Standard Hidden Markov Models (HMMs) assume fixed transition probabilities, which limits their ability to capture such higher-order changes in market behavior. This study introduces an Adaptive Hierarchical Hidden Markov Model (AH-HMM), where regime transitions depend on an unobserved meta-regime that reflects the broader macro-financial environment. Each meta-regime defines its own transition matrix across market states such as bull, bear, and turbulent phases. In this way, the model adapts dynamically to structural changes arising from crises, policy shifts, or variations in investor sentiment. Using weekly data for major equity indices, aggregated from daily prices, together with macro-uncertainty indicators, we show that the AH-HMM identifies key turning points including the Global Financial Crisis, the COVID-19 shock, and the post-2022 tightening cycle. In our empirical application, where we approximate the latent structural layer by low- and high-uncertainty environments defined from the VIX, the adaptive model attains a higher in-sample likelihood and delivers competitive out-of-sample forecasts and Value-at-Risk coverage relative to conventional HMMs and time-varying transition alternatives. Overall, the results highlight a mechanism of structural learning within market regimes and offer tools for risk management and policy analysis under uncertainty.

Credit cards play a central role in household financial behavior by combining payment and short-term financing functions shaped by socioeconomic, cognitive, and attitudinal factors. This study examines the determinants of credit card use and repayment behavior in Ecuador, focusing on purchasing power, financial literacy, and institutional trust. A quantitative, cross-sectional, and explanatory design was applied to a probabilistic sample of 550 credit card users from Quito and Santo Domingo. Multivariate analyses and Partial Least Squares Structural Equation Modeling (PLS-SEM)—including formative and hierarchical constructs—were used to validate the proposed behavioral framework. The results show that higher income is associated with more responsible repayment, while financial literacy and trust mediate this relationship through cognitive and attitudinal mechanisms. Moderate R2 values and small-to-moderate f2 effect sizes align with patterns observed in other Latin American credit markets. Behavioral differences also emerge across age, gender, and household composition, underscoring the heterogeneity of financial capability in the region. The findings demonstrate that responsible credit card indebtedness depends not only on economic capacity but also on financial knowledge and institutional trust, offering practical implications for financial inclusion policies and targeted education programs in emerging economies.

Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government Regulations and Cryptocurrency Performance on Cryptocurrency Prices, while Government Regulations and Cryptocurrency Performance partially mediate the effect of Bitcoin halving. These findings highlight that Cryptocurrency Prices are shaped by the interplay of technical, policy, and psychological factors, with strategic implications for investors, regulators, and developers.

Taxation on cryptocurrency is becoming critical in global fiscal governance as digital assets adapt to the modern reality of existing outside of traditional regulatory constructs. Theoretical and practical understanding of cryptocurrency taxation is quite new, and so a systematic review was designed to present the most recent empirical research evidence on the legal, fiscal and behavioral aspects of cryptocurrency taxation from across the globe. Using the PRISMA-2020 guidelines, a structured search was applied to the Scopus database on 21 May 2025, with the search terms “crypto-currency”, “cryptoasset” and “taxation.” The inclusion criteria consisted of original research articles published between the years of 2020 and 2025 in English or Spanish, that could be accessed via institutional library support, and that were related to taxation, legal regulation and/or compliance. Out of the original identified 224 records, 36 met the eligibility criteria after screening and verification through seven different stages of review. Socially, five themes were produced by the findings: legal ambiguity surrounding fiscal treatment, limited tax literacy and compliance issues, macroeconomic and monetary issues, application of digital technologies for fiscal tracking, and environmental repercussions from crypto mining. Many countries do not have any coherent tax frameworks to govern the risk that emerges from cryptocurrency taxation, creating uncertainty for both regulators and investors. The findings outlined in this systematic review point to the urgent need for creating a coherent approach to cryptocurrency taxation based on definitions, digital approaches to traceability, and tax literacy compliance strategies. In order to create effective cryptocurrency taxation, there must be a base balance between ensuring innovation, fiscal responsibility, transparency, equity and sustainability in the developing digital economy.

Implementing enterprise risk management (ERM) helps organizations identify, assess, and manage emerging risks. As global ecosystems face intensifying environmental, social and governance (ESG) pressures—including climate risks, regulatory demands for sustainability reporting and stakeholder expectations for ecosystem protection —the internal audit function (IAF) plays an increasingly critical role in helping organizations monitor and respond to these risks. Internal auditors’ expertise supports risk identification and assessment, though management maintains responsibility for risk management and control. Using the Committee of Sponsoring Organizations’ (COSO) ERM framework, we review 77 studies across 23 journals published between 2004 and 2024. Prior research primarily examines internal audit’s assurance and consulting roles, with considerably less attention given to activities that compromise independence. While evidence suggests that internal audit quality enhances risk management effectiveness, uncertainty remains about boundaries for consulting activities and technology-enabled assurance. Our synthesis highlights limited empirical insight into internal audit’s strategic partnership role in ERM and identifies future research opportunities for scholars, practitioners and standard setters.

The scope of this topic stems from the change in insurance companies and the subsequent transition to IFRS 17. The new code came into force on 1 January 2023. Therefore, the purpose of this article is to compare the two standards in terms of methodology and process logic. To highlight the new aspects of the new standard and to present the author’s view that IFRS 17 provides more opportunities for timely action and intervention by company management in the processes and improvement of results compared to IFRS 4. To examine how the application of the standard has affected the strategy for recognising, measuring, and reporting liabilities under insurance contracts, as well as financial results in the insurance sector in China. The study uses a mixed approach, combining a comparison of IFRS 4 and IFRS 17 with examples illustrating actual practice in the sector to examine differences in accounting treatment. It cites examples from European and Asian traders to assess how things will develop in practice. Contribution: This study adds new evidence on the impact of IFRS 17 on value and profit management. Our study found that the new standard introduces a single model for measuring insurance contracts, which significantly increases transparency and comparability in financial statements. Furthermore, one of its most important findings is that, with the equalisation of the margin on contractual services and the recognition of profits over the entire term of insurance contracts, the balance sheets for all years will show more consistent reports of profits and losses. It also calls for attention to the challenges insurers met in developing cash flow discounting methods or putting the general measurement model into effect. Overall, the report found that search engine IFRS 17 has made comparability and transparency better while making suggestions to industry stakeholders about what problems came out when they were discovered afterwards.

In the context of green transformation, climate change and its economic implications are attracting increasing attention. Based on the Trade-off Theory framework, this study examines how climate risk affects firms’ shadow banking activities in emerging markets. This study focuses on emerging market economies, using a panel dataset of Chinese A-share non-financial listed firms from 2007 to 2023 to systematically examine the relationship between climate risk and shadow banking activities, that is, financing conducted outside the formal banking system. The empirical findings reveal that climate risk significantly dampens the shadow banking activities of non-financial firms. Further mechanism analysis suggests that this effect operates through two key channels: the weakening of corporate resilience and adjustments in capital structure decisions. Moreover, the analysis uncovers heterogeneous impacts of climate risk on shadow banking, depending on the quality of information disclosure, industry characteristics, and the degree of financing constraints. This research provides new insights into the evolution of corporate financial behavior under climate risk and offers empirical evidence to support firms in optimizing their financial strategies and enhancing their financial risk management capabilities.