This study provides a comprehensive examination of the development, contemporary challenges, and future directions of business education in Taiwan. Integrating global benchmarking, historical analysis, institutional data, and interviews with senior scholars, the study compares Taiwanese business schools with leading institutions in North America, Europe, and the Asia Pacific region. The analysis shows that while Taiwan’s business education system broadly aligns with global priorities such as experiential learning, artificial intelligence and digital literacy, sustainability and ESG integration, internationalization, and lifelong learning, it faces distinct structural constraints. These include demographic decline, institutional rigidity, limited resources, uneven international visibility, and challenges in faculty development for emerging interdisciplinary fields. Historical analysis traces the evolution of business education in Taiwan from its dual track origins through postwar expansion, massification, and accreditation-driven quality enhancement. Insights from expert interviews identify ten systemic challenges related to curriculum design, governance, industry collaboration, internationalization, and research translation, and propose corresponding reform directions. The study concludes that Taiwan’s business schools must pursue strategic differentiation, deepen practice-oriented and interdisciplinary education, strengthen global engagement, and enhance research to practice integration in order to remain competitive and to contribute effectively to national economic and societal development.
The companies’ resources comprise the basics for business operations. Their qualifications and configuration significantly influence the operational results. Operations continuity and results, on the other hand, are significantly influenced by revenue management, investment, and finance policies. Traceability of this pattern and analysis of the sustainability of the operations-finance nexus are therefore important from the perspective of financial acumen. In this research, the operations-finance nexus and its role in business sustainability are analyzed with the financial data of one of the 30 leading transportation companies via path model analysis. Autonomous tests via three intra-model parameters of intensity ratios are realized at three levels. According to the analysis findings, the model is validated in three operation segments (shipping, trucking, multimodal) and in all tercile intervals of insourcing, investment, and liquidity intensities, the model generated significant results.
This study investigates real activities manipulation to meet earnings benchmarks across corporate life cycle stages. Focusing on prioritization, magnitude, and mechanisms, we show that growth and mature firms focus on avoiding earnings decreases, while declining firms prioritize avoiding losses. The magnitude of real activities manipulation follows a U-shaped pattern, peaking in the introduction and decline stages. While both utilize sales manipulation, motives diverge: introduction firms signal growth, whereas declining firms aim for survival. Integrating earnings distribution and regression analyses, this research provides novel insights into the dynamic evolution of earnings management throughout the corporate life cycle.
This study investigates how digital technology-driven dynamic capabilities (DDC) influence the formation of a sustainable and smart auditing ecosystem (SUSMAE) in public sector organizations (PSOs). It also examines the direct effect of cyber forensic accounting intelligence (CYFAI) on SUSMAE and its moderating role in the relationship between DDC and SUSMAE. Data were collected from accountants working in multiple PSOs in Southern Vietnam through a structured questionnaire survey. Partial Least Squares Structural Equation Modeling was employed using SmartPLS 4.1.0.3 to evaluate the proposed relationships. The results indicate that DDC is positively and significantly associated with SUSMAE. CYFAI is also positively associated with SUSMAE and strengthens the relationship between DDC and SUSMAE. These findings suggest that the development of SUSMAE in PSOs depends not only on DDC but also on accountants CYFAI. Practically, the study highlights the need for PSOs to strengthen digital technology-driven capabilities and develop accountants cyber forensic accounting intelligence in order to support more transparent, secure, and data-informed auditing practices. These efforts can help public organizations improve audit-related data sharing, enhance responsiveness to cyber-related financial risks, and foster the development of sustainable and smart auditing ecosystems.
This study examines the dynamics of bank deposit flows in the United States during a period of banking sector uncertainty and rising interest rates following the COVID-19 pandemic. We analyze deposit movements from the first quarter of 2022 through mid-2023, a timeframe that includes the failures of Silicon Valley Bank and Signature Bank. We find that approximately $1 trillion in deposits left the banking system during this period, with outflows particularly pronounced from larger institutions. Results suggest that uninsured deposits exited relatively safer banks, indicating that risk aversion was not the primary driver of these outflows. At the same time, approximately $700 billion flowed into money market funds, with retail investors seeking higher yields in prime retail funds and institutional investors prioritizing liquidity in government funds around the time of the bank failures.
Analyzing 3,492 Japanese individuals during the COVID-19 pandemic, the empirical study found that financial education, particularly financial education received at the school or workplace, can increase one’s financial literacy. In addition, those individuals who received financial education at the school/workplace were less likely to experience a decline in income and financial assets during the pandemic, and were more satisfied with their financial conditions as of March 2022. Women benefited from financial education to a greater degree than men. The results suggest that financial education can be a venue for reducing the gap in income and wealth.
This paper uses the stochastic volatility with contemporaneous jumps model to extract risk premium (RP) components and term structures. The sample data includes the daily returns and options of the S&P 500 and 30 large-capital firms from 1998 to 2016. The RP components and term structures reflect investors’ expectations regarding market trends. The findings reveal that in the S&P 500 index, the diffusion component of the variance RP (VRP) is the most essential factor in forecasting S&P 500 excess returns; moreover, the jump component of the VRP and its term structure explain the short-term excess returns. The firm-level findings reveal that the averages of RPs are not significantly related to future stock excess returns.
The research investigates the role of the leader in the effectiveness of operational risk management (ORM) at commercial banks based on the Basel Committee on Banking Supervision (BCBS). A quantitative method is utilized through the scale reliability analysis, exploratory factor analysis, confirmatory factor analysis and regression with a dataset of 300 observations. The respondent is bank staff with at least 3 years of experience working in the risk management department of Vietnamese commercial banks. The research results imply that the leadership’s perspective and contingency business plan profoundly influence the commercial bank’s ORM. In addition, other factors such as organizational structure, implementation of the ORM process, IT system, training and communication strongly impact the effectiveness of ORM in the banking business. One of the highlight points is to demonstrate the impact of leadership’s perspective on the effectiveness of ORM. These findings play an important role in theoretical and practical aspects, demonstrating the decisive role of the leader in ORM. On that basis, the study recommends enhancing ORM in Vietnamese commercial banks.
This study explores the empirical relationship between retail investors’ investment behavior and the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), with a focus on age and gender as moderators. Using a structured questionnaire and convenience sampling, data were collected from 500 respondents. Results show significant associations between investment behavior and extroversion, openness, and neuroticism. Age moderates the relations between neuroticism and investment behavior, while gender moderates the relationship between agreeableness, extraversion and investment behavior. Financial planners can guide investors to stable stock market behavior by considering their personality traits and demographic factors.
This study examines the impact of Environmental, Social, and Governance (ESG) scores on business operating performance, using data from 2,137 publicly listed Taiwanese firms between 2016 and 2023. Operating performance is assessed using both traditional labor productivity ratios and Data Envelopment Analysis (DEA). The empirical findings indicate that the ESG dimensions influence operating performance asymmetrically: the Environmental (E) dimension has a negative effect, while the Governance (G) dimension has a positive effect. In contrast, the Social (S) dimension does not show a consistent impact on operating performance. Moreover, the relationship between ESG and performance is moderated by industry and firm size. Mediation analysis using the Sobel test further reveals that operating performance partially mediates the effect of ESG on both financial and market performance, measured by Return on Assets (ROA) and Tobin's Q, respectively. Social and governance strategies are most effective when they emphasize human capital as a mediating channel.
This study examines the effectiveness of incorporating investor sentiment into machine learning models based on decision trees- specifically, Random Forest, XGBoost (Extreme Gradient Boosting), and LightGBM (Light Gradient Boosting Machine) - for option pricing in the Taiwan market. The empirical results demonstrate that these machine learning models significantly outperform the traditional Black-Scholes model in pricing accuracy. Notably, adding investor sentiment enhances the models' pricing performance, especially for at-the-money and in-the-money options, where pricing errors are reduced by 4 times and 2.6 times, respectively. The Random Forest model exhibits the best performance overall.
US federal regulators impose enforcement actions on banks when they discover breaches of fiduciary duty. We find that short sellers anticipate enforcement actions 6 months before issuance, regardless of the state of the economy. After the infractions are settled, short selling decreases for banks with certain characteristics. Further, we find that large banks face less scrutiny from short sellers ahead of enforcement actions, a potential benefit of being Too Big to Fail. These findings may suggest that short interest serves as a signal for declining bank quality ahead of a formal investigation and improving conditions after the settlement.
This paper reviews the literature on Securities and Exchange Commission (SEC) Comment Letters. The economic significance of Comment Letters may be relevant to public policy considerations and the evaluation of related research. La Porta et al. [(2006). What works in securities laws? The Journal of Finance, 61(1), 1-32] cast doubt on the value of public regulation enforcement. SEC review limitations and the institutional setting likely limit the impact of 10-K/10-Q Comment Letters. Severe resolutions are infrequent, and market impact evidence is limited. Recurring filing reviews may deter substandard reporting, and IPO Comment Letters offer a powerful setting, but neither has received much research attention. Empirical challenges are also examined.
This study investigates the impact of country-level peacefulness on the liquidity of cross-listed stocks traded on the New York Stock Exchange (NYSE) from 2008 to 2019. Our empirical analysis reveals that stocks from more peaceful countries exhibit enhanced liquidity, characterized by narrower spreads and reduced information-based trading. Among the global peace index's sub-indices, the safety and security measure shows the strongest and most consistent relationship with stock liquidity. We further explore the direct, indirect, and mediating effects of peace-related factors on market liquidity, employing change and instrumental variable regressions to validate our results. The findings remain robust, demonstrating that improvements in a country's peacefulness can significantly boost the liquidity and market quality of its cross-listed stocks, offering key insights for investors and policymakers.
This paper examines whether Moody's 2000 IPO compromised its independence as a credit rating agency. Using synthetic controls, we construct a counterfactual rating trajectory for Berkshire Hathaway-affiliated firms - Moody's largest post-IPO shareholder - and compare it to actual ratings. Results show significant rating inflation for these firms, peaking at nearly two notches by 2005 and fading thereafter. This effect exceeds prior difference-in-differences estimates. Placebo and robustness tests affirm significance. Findings underscore concentrated ownership's influence in reputation-sensitive industries and highlight conflicts of interest in credit ratings. The study advances literature on rating inflation and shareholder activism by revealing how large shareholders can distort incentives and market information.
Our study tests the role that industry concentration (IC), corporate innovation activities (as measured by a firm's research and development expense (RD)), and life-cycle stage play in determining the Tobin's Q ratios of Taiwanese firms. We find that all three variables play a key role. To further investigate the relation between IC and RD, we conducted a generalized method of momentum (GMM) and a Granger noncausality test. Both tests indicate a unidirectional effect from RD to IC. We conclude that a firm's industry structure, innovation activities, and life cycle stage are important factors when developing corporate strategy, making investment decisions, or setting government policy.
This paper tests the adaptive market hypothesis for the Saudi Arabian stock market. By applying the automatic portmanteau and variance ratio tests, the degree of time-varying return predictability of market and sectoral indices are evaluated, in comparison to that of the oil market. Using daily data from 2010, we find that the Saudi Arabian stock market has been mostly efficient over time, showing a low degree of return predictability. Furthermore, we find that this degree of efficiency is closely related to that of the oil market. However, in contrast to the stock market, the oil market is found to be relatively inefficient with a higher degree of return predictability. Finally, we find that the degree of stock return predictability is partly driven by macroeconomic variables such as inflation and interest rates.
The purpose of this research is to examine how volatility spillover operates in Indian agricultural spot and futures markets. The MGARCH-BEKK model for Multivariate Generalized Autoregressive Conditional Heteroscedasticity, Baba, Engle, Kraft, and Kroner was employed in this investigation. To investigate the spillover effects of five of the most liquid agricultural commodities traded on the National Commodity and Derivatives Exchange (NCDEX) and Multi-Commodity Exchange (MCX). Futures and spot markets have mutual spillover effects, according to the MGARCH Volatility test results. The volatility spillovers between spot and futures of jeera indicate that own spillovers are present and are more in the case of spot, both in the long term and short term. The cross-market volatility spillovers are more from spot to future in the short term and long term. As a result, one might argue that the Indian futures market is more effective in deciding agricultural commodity prices. These insights can help market players hedge risk and policymakers design futures contracts to improve the efficiency of the agricultural commodity derivatives market.
This study examines whether corporate social responsibility (CSR) report readability affects the ability of analyst recommendations to predict future returns, as well as the analysts' information environment. The results indicate that easy-to-read CSR disclosure improves the return predictability of analyst recommendations. Furthermore, we show that the effect of CSR report readability on analysts' information environment is driven entirely by reducing uncertainty, not by reducing information asymmetry among analysts, and this result is more pronounced for firms with relatively low CSR performance. Additionally, we demonstrate that one possible channel through which more readable CSR reports may enhance the return predictability of analyst recommendations is by aligning these recommendations with valuation estimates from the residual income model.
