Issue #1 (Volume 22 2025)

This research paper aims to explore the market efficiency of stock exchanges in of ASEAN-5 countries, Indonesia, Malaysia, Singapore, Thailand, and the Philippines, during the COVID-19 pandemic. Stock market efficiency is the degree to which stock prices reflect all available relevant information. In an efficient market, stock prices will immediately rise or fall to reflect new information released by a company. This study uses the Stochastic Frontier Analysis (SFA) method to determine the efficient value over time. Market efficiency generally refers to how well financial markets in these selected countries reflect all available information, particularly in the context of the COVID-19 pandemic. SFA is useful here as it can separate random errors from inefficiencies, allowing us to isolate the impact of COVID-19 on market efficiency levels across these countries. The results show that the stock markets of ASEAN-5 countries (Indonesia, Malaysia, Thailand, Singapore, and Philippines) are efficient during the COVID-19 pandemic. Based on the hypothesis test, for the overall period of 2021 and 2023, the average efficiency ranges from 0.68 to 0.72, and for the time period/per year the average efficiency ranges from 0.66 to 0.74. The efficiency of the Philippine stock market based on time period/per year shows the average maximum efficiency in 2021 (0.74) and 2023 (0.73). While the average efficiency of the Malaysian stock market shows the minimum level of efficiency in 2020 (0.66) and 2021 (0.68).

Acknowledgment
The authors would like to thank the Research and Innovation Institute (LRI), Universitas Muhammadiyah Surakarta, for the enormous financial support in writing this study.

This study aims to investigate the mediating effect of digital financial inclusion on the relationship between digital financial literacy and the financial well-being of Malaysian households, focusing on gender differences. Using quantitative research, a total of 210 responses, which contained 105 samples for each gender, were collected from households across Malaysia using a self-administered questionnaire. The research model was analyzed using Partial Least Square-Structural Equation Modelling techniques. The findings revealed significant relationships between digital financial literacy and digital financial inclusion, as well as between digital financial inclusion and financial well-being. Additionally, digital financial inclusion was found to significantly mediate the relationship between digital financial literacy and financial well-being, underscoring the importance of digital financial inclusion. The MICOM analysis results show that all constructs have good configural invariance, indicating the measures are consistent across groups. High correlations between males and females suggest similarities, but permutation tests indicate these similarities might be due to chance. Variance differences for digital financial literacy and digital financial inclusion are not significant. However, financial well-being shows a significant variance difference, suggesting less variability among males, supported by higher reliability scores for the financial well-being of males, indicating more consistent responses. Notably, the standardized beta for the digital financial inclusion – financial well-being path is higher among females, indicating a stronger influence of digital financial inclusion on financial well-being for this group. However, the direct relationship between digital financial literacy and financial well-being is insignificant for both genders.

Acknowledgment
This research was supported by the Ministry of Higher Education (MoHE) of Malaysia through the Fundamental Research Grant Scheme (FRGS/1/2022/SS01/UUM/02/10).

Rapid technological advances have made financial markets more accessible and encouraged individual investors to engage in investment decision-making actively. Generation Z, or Gen Z, characterized by higher levels of digital literacy, a high sense of curiosity, and acceptance of innovation, tends to make investment decisions quickly. This study aimed to analyze the effect of technological progress, financial literacy, and financial attitudes on investors’ investment decisions. There are 125 Gen Z investors in Jakarta, Indonesia, selected as research samples using the non-probability sampling method. The survey method was employed to collect data, and the study instrument was a questionnaire. For data analysis, Partial Least Squares version 4.0 was used. The study’s findings revealed that financial literacy and financial attitude positively influence Gen Z investment decisions. Technological progress does not affect Gen Z in determining investment in the financial market. Financial literacy and financial attitude are more dominant for Gen Z investors than technological progress in determining investment allocation. This finding implies that Gen Z must improve their understanding of correct financial literacy and financial attitudes that align with individual investors’ character. Further investigation needs to reveal the insignificance of technological progress in determining investment decisions. Technological progress and financial literacy likely have the same factor characteristics related to three dimensions: knowledge, skills, and attitudes. The attitude of Gen Z investors towards the progress of financial technology by investors is preceded by good financial literacy. Therefore, it is necessary to test the relationship between variables, both mediation and moderation, in investment decisions.

This paper investigates the multifractal behavior of the six largest African stock markets, including the Johannesburg, Casablanca, Botswana, Nigerian, Egyptian, and Regional Stock Exchanges. Despite the growing significance of these markets in the global economy, there is limited understanding of their underlying dynamics, particularly regarding their multifractal properties. This lack of knowledge raises concerns about the informational efficiency of these markets, as traditional models may not adequately capture the complexities of price movements. To achieve the goals of the study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method is applied to capture the multifractal dynamics, and shuffling and phase randomization techniques are performed to identify the sources of the multifractality of the six African stock markets. The empirical results, derived from the generalized Hurst exponents, Rényi exponents, and Singularity spectrum, show that all six stock markets display multifractal behavior, characterized by irregular and complex price movements that vary across different scales and timeframes. Additionally, the study finds that both long-term correlations and heavy-tailed distributions contribute to the observed multifractality. Long-term correlations lead to persistent price trends, challenging the Efficient Market Hypothesis (EMH), while heavy tails increase market unpredictability by raising the likelihood of extreme events like crashes or booms. The findings have significant practical implications for stakeholders in African stock markets, enabling investors and portfolio managers to enhance risk assessment and develop effective trading strategies while helping market regulators improve efficiency and stability through appropriate policies. Financial institutions can also refine risk management frameworks to better account for extreme events.

The study provides empirical evidence on the cost implications of socially responsible investing (SRI) in relation to Environmental, Social, and Governance (ESG) preferences. Specifically, it examines whether socially responsible investors incur higher costs to meet non-pecuniary goals and how government involvement can offer rewards to socially responsible investors in supporting the realization of the United Nations’ Sustainable Development Goals (SDGs). Using panel data regression, this study analyzes ESG scores and financial and return data of 1,450 firm-year observations in ASEAN-5 countries over the period 2015–2022. The findings reveal that firms implementing ESG practices experience an increase in their cost of capital (CoC), supporting the notion that ESG investment requires a sacrificial cost. Even firms with low operational risks face rising CoC when implementing ESG principles. However, the study also finds that firms located in countries with better government effectiveness and stronger control of corruption benefit from a reduction in CoC, despite ESG implementation. Conversely, country risks, particularly those related to environmental pollution, exacerbate the CoC for firms adhering to ESG criteria. Overall, the results suggest that while country-level governance can reward socially responsible investors by mitigating CoC, country risks such as pollution pose additional burdens, highlighting the need for government intervention to incentivize SRI and align it with global sustainability goals.

Acknowledgment
This research was funded by the Indonesian Ministry of Education, Research, and Technology (DRTPM), Fundamental Research Grant in 2024 [0609.10/LL5-INT/AL.04/2024,359/D.01/LPPM/2024].

Understanding the conditions leading to business failure and predicting them earlier is the best way for companies to overcome and minimize their harm, improve their performance, and avoid financial distress and bankruptcy. This paper aims to measure the level and trends of factors affecting financial distress in Vietnam – an emerging Southeast Asian economy, along with the managerial implications drawn from the research results. Research data were collected from 606 firms listed on the Vietnam Stock Exchange from 2018 to 2022. The Altman Z-score is used to determine the financial distress of these firms. The factors researched and tested in this study are all internal factors divided into two groups with distinct features. Non-financial factors belong to management characteristics; financial factors are typical indicators of a firm’s financial statements. The study uses OLS, FEM, and REM models to analyze the influence of financial factors (Total liability to Total assets, Sales growth, Firm size, and Firm age) and non-financial factors (Board size, CEO duality, Institutional ownership level, Independent member, and Foreign CEOs) on financial distress and GLS regression to overcome the model’s shortcomings. The results show that the factors in the research model significantly impact financial distress, of which six factors (Board size, CEO duality, Institutional ownership level, Foreign CEOs, Sales growth, and Firm age) are negatively correlated. Three other factors (Independent members, Total liability to Total assets, and Firm size) are positively correlated with financial distress.

Acknowledgment
The author thanks everyone who helped make this study possible.

This study examines the extent of environmental and community disclosures and evaluates how audit committee features influence such disclosures among listed firms in Bahrain and Kuwait, Gulf Cooperation Council (GCC) countries of emerging markets. The research employs an unweighted disclosure index comprising 18 items related to environmental and community disclosures, analyzing 432 firm-year observations across Bahrain and Kuwait covering a nine-year period (2015–2023). Three audit committee features (independence, number of meetings, and size) along with the number of other board committees are examined in this empirical investigation. Descriptive analysis indicates that the sampled firms offer 44.25% and 60.60% of environmental and community information, respectively, signaling a satisfactory disclosure level in Bahrain and Kuwait. This demonstrates progress compared to prior studies in GCC countries. Hierarchical Multiple Regression models demonstrate that all four models significantly describe the dependent variables. Regression model four exhibits the highest explanatory power in explaining community information. Audit committee independence and size emerge as determinants of community information, while only audit committee independence is associated with environmental information. The results of this study bear significant implications for governmental bodies and regulatory authorities aiming to strengthen disclosure regulations and promote corporate governance frameworks within GCC nations.

The study aims to analyze the co-movement between oil prices, BRICS nations’ exchange rates, and stock markets. Grasping these interrelationships is essential for understanding how global energy price shifts broadly affect the economies, particularly those of developing nations.
The study employs wavelet coherency analysis on daily data, examining the association between crude oil (Brent crude), exchange rates (Brazilian Real, Russian Rubble, Indian Rupee, Chinese Yuan, and South African Rand), and stock markets (BOVESPA of Brazil, Moscow Exchange of Russia, Nifty50 of India, Shanghai Composite of China, and JSE FTSE of South Africa) across both temporal and frequency domains.
This study reveals strong comovements, especially during periods of global economic instability, such as the impact of the COVID-19 pandemic and the Russia-Ukraine war. During such periods, oil prices and stock market indices tend to move in tandem, while oil prices and exchange rates show an inverse relationship. The study also reveals a decoupling of crude oil from both share markets and exchange rates during normal economic conditions. This decoupling suggests that outside of a chaotic period, the relationships weaken. However, the co-movements among the variables for China are notably weaker, even during economic upheavals, than in other BRICS nations. Understanding these relationships can aid in informed decision making and strategies in the face of global economic turmoil.

Acknowledgment
This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2025/R/1446).

The global adoption of Central Bank Digital Currencies (CBDCs) represents a pivotal shift in monetary systems, driven by technological advancements and economic imperatives. While a small number of official digital currencies are in circulation, many nations are launching pilot programs to address financial inclusion challenges and enhance economic resilience. This study aims to identify the determinants of digital currency adoption across 116 countries, using logistic regression to analyze the effects of economic, technological, institutional, and financial factors.
The results show that higher GDP levels significantly increase the likelihood of active CBDC adoption by 332.1 percent and pilot adoption by 212.6 percent, reflecting the role of economic development. Greater internet usage improves the odds of active adoption by 12.7 percent and pilot adoption by 13.4 percent, while financial inclusion indicators, such as account ownership, increase the likelihood of adoption by 59 percent for active initiatives and 141 percent for pilot projects. Monetary freedom positively influences active adoption by 31.1 percent, and higher interest rates increase the odds by 20.8 percent. Conversely, business freedom negatively affects active adoption by 27.5 percent and pilot adoption by 29.1 percent, suggesting that countries with strong private-sector digital payment solutions may rely less on CBDCs.
These findings represent the transformative potential of digital currencies to improve financial inclusion and economic participation. Policymakers should prioritize investments in digital infrastructure and financial inclusion initiatives to facilitate the integration of digital currencies into national economies and empower underserved populations globally.

Investor behavioral factors determine the investment decisions of individual investors in the stock market. The study investigated behavioral factors driving investment decisions in Nepal’s stock market, contributing to existing literature. The behavioral factors comprise heuristics, prospects, and herding as predictors and investment decisions as a response variable. Thus, the study adopted a descriptive and analytical research design to test the research hypotheses and resolve the research questions and issues. A survey was conducted among individual investors registered with Nepal’s trading management system (TMS). A total of 526 structured questionnaires were distributed to targeted respondents, and only 350 useful questionnaires (66.54 percent) were received. The survey data of cross-sectional type were encompassed with a random clustering sampling method for this study. Further, the study employed descriptive statistics to depict the characteristics of respondents’ profiles, correlation analysis to assess the association between predictors and response variables, and linear regression analysis to investigate the impact of predictors on response variables. Similarly, Cronbach’s alpha was tested to observe reliability in the study. The survey findings showed a positive and significant association between heuristics and investment decisions (β = 0.088, p < 0.05). The prospect is positively linked with the individual’s investment decision but found insignificant (β = 0.011, p > 0.05). Finally, herding found a positive and significant association with investment decisions (β = 0.235, p < 0.05). The findings of this study contribute to existing theory and can be a benchmark for decision-makers and policymakers, investors, and others.

Transfer pricing practices remain a challenge for tax authorities in various countries because they can be used to reduce tax payments. This study aims to explore the impact of ownership structure on transfer pricing practices, focusing on how board experience and executive characteristics act as moderating factors. Additionally, the study considers three control variables: company size, debt to equity ratio, and ROE. The analysis encompasses all publicly listed companies on the Indonesia Stock Exchange, utilizing panel data analysis and moderated regression techniques. The dataset comprises 2,480 entries from 310 companies over an eight-year span from 2015 to 2022. The findings indicate that concentrated ownership positively influences transfer pricing, whereas managerial ownership exerts a negative influence. Meanwhile, foreign, institutional, and family ownership show no significant impact on transfer pricing activities. The experience of the board of directors only moderates the effect of ownership concentration on transfer pricing, with no other significant moderating effects observed. In contrast, executive characteristics successfully moderate the impact of foreign ownership, managerial ownership, and ownership concentration on transfer pricing but not institutional or family ownership.

The study reviews the application of machine learning tools in financial investment portfolio management, focusing on cluster analysis for asset allocation, diversification, and risk optimization. The paper aims to explore the use of clustering analysis to broaden the concept of portfolio diversification beyond traditional volatility metrics. An open dataset from Yahoo Finance includes a ten-year historical period (2014–2024) of 130 actively traded securities from international stock markets used. Dataset selection prioritizes top liquidity and trading activity. Python analytical tools were employed to clean, process, and analyze the data. The methodology combines classical Markowitz optimization with clustering analysis techniques, highlighting variance-return trade-offs. Various asset characteristics, including annualized return, standard deviation, Sharpe ratio, correlation with indices, skewness, and kurtosis, were incorporated into the clustering models to reveal hidden patterns and groupings among financial assets. Results show that while clustering enhances insights into asset diversity, classical approaches remain historically superior in optimizing risk-adjusted returns. This study concludes that clustering complements, rather than replaces, classical methods by broadening the understanding of diversification and addressing many diversity factors, such as metrics of the technical, graphical, and fundamental analysis. The paper also introduces the diversity rate based on clustering, which measures the variance balance by all features within and between clusters, providing a broader perspective on diversification beyond traditional metrics. Future research should investigate dynamic clustering techniques, integrate fundamental economic indicators, and develop adaptive models for effective portfolio management in evolving financial markets.

Corporate structure decisions are the foundation of a company’s legal, financial, and operational framework, influencing diverse issues, from liability and tax obligations to growth potential and public perception. The paper aims to analyze the effect of firms’ financial performance on capital structure decisions. Firm size and corporate governance were taken as moderators and mediators, respectively. The study is based on 23 non-banking public firms listed on the Nepal Stock Exchange, adapting a causal-comparative research design. The moderated mediation model was tested using the Process Macro to assess the impact of corporate governance scores on the relationship between firm performance and capital structure. The result shows that firm performance positively and significantly impacts capital structure decisions. The results revealed no effect of corporate governance on capital structure decisions; however, the moderated mediation impacts of corporate governance and firm size have been reflected in the financing decision. This study extends previous research with the moderated mediation effects of corporate governance and the size of non-banking firms on their financing decisions. The results encourage managers to raise debt funds for those firms that observe the firm’s size, providing practical insights into business decisions. The study also has policy and theoretical implications.

Acknowledgment
We are grateful to everyone who contributed directly or indirectly to the research. We also appreciate the anonymous reviewers’ insightful feedback, which helped enhance the quality of the paper.

This study examines how perceived security and privacy influence user ratings of cryptocurrency applications, which are critical for adoption and satisfaction amid the growing popularity of blockchain technologies and rising concerns over information security in online platforms and mobile apps. The study focuses on mobile applications from the Android app market. It used text mining methods to investigate over 64 thousand text-based user reviews and star ratings of over 140 cryptocurrency-related mobile applications available in the Google Play store. Using a partially supervised machine learning approach, this study first identified reviewer sentiment related to privacy and security, then employed ordinal regression analysis to examine the data to reveal the relationship between perceived security threats, privacy concerns, and app ratings. This study found that crypto apps average 3.84 out of 55 stars, which is higher than Productivity apps (3.46) but lower than FinTech (4.29) and Banking (4.25) apps. Ordinal regression analysis revealed security and privacy threats negatively impact ratings, while robust security measures improve them, with a model Pseudo R² of 0.25. These results have implications for both cryptocurrency app developers and platform managers, offering insights for enhancing user experiences and informing future research endeavors in this domain. It contributes to the literature by integrating the Protection Motivation Theory with sentiment analysis and provides a structured framework for developing an understanding of user behavior in the context of cryptocurrency apps.

This study investigates the investment preferences of institutional investors in Indonesia, focusing on the factors influencing stock selection. A comparative analysis is conducted between pressure-sensitive and pressure-insensitive investor groups to explore how different factors such as corporate social responsibility, corporate governance, shariah-compliant stocks, and financial indicators, including profitability, liquidity, and risk, affect their investment decisions. Data from 938 observations across 253 manufacturing companies listed on the Indonesia Stock Exchange were analyzed using panel data regression. The period was chosen because it captures a stable economic period in Indonesia, allowing for an accurate assessment of investment patterns without major external shocks. The results reveal that institutional investors favor stocks listed on the Indonesia Shariah Stock Index (ISSI), perceived as low-risk investments. Pressure-sensitive investors, such as banks and insurance companies, prefer companies with close business affiliations, while pressure-insensitive investors, such as mutual funds and pension funds, prioritize financial performance and corporate governance. Additionally, the study finds that the debt-to-asset ratio and inclusion in the Shariah index significantly affect institutional ownership, indicating a preference for leveraged companies with ethical investment profiles. This study provides a deeper understanding of the varying preferences between institutional investor groups, highlighting the significance of ethical considerations, financial stability, and corporate governance in emerging markets.

Social media significantly influences investor behavior, particularly in emerging markets like the Egyptian stock market. This study examines its impact on trading frequency, herding behavior, and overconfidence among Egyptian investors. Data were collected through a structured survey of 300 active investors, distributed via two prominent Facebook pages: “The Popular Union of Investors in the Egyptian Stock Market” and “Investment in the Egyptian Stock Market.” The sample was determined using Cochran’s formula for large, undefined populations, achieving a 78% response rate from the 385 recommended respondents. A descriptive quantitative approach was employed, utilizing correlation tests and regression analysis to assess relationships between social media engagement and investor behavior.
Findings indicate that social media usage significantly increases trading frequency, as investors make more reactive decisions based on rapidly available information. Herding behavior is also positively associated with social media engagement, demonstrating that investors tend to follow market trends and decisions discussed in online communities. Additionally, social media exposure fosters overconfidence, leading to increased risk-taking behavior. These insights highlight the critical role of social media in shaping investor behavior, with practical implications for regulators, financial advisors, and individual investors. Regulators should promote investor education on the cognitive biases linked to social media engagement, while financial advisors must address its influence on client decision-making. Future research should explore platform-specific features, such as visual content and influencer-driven financial advice, to better understand their effects on investment strategies.

Acknowledgment
The authors are thankful to the Deanship of Graduate Studies and Scientific Research at University of Bisha for supporting this work through the Fast-Track Research Support Program.

The study aims to investigate the effect of research and development (R&D) capitalization on revenue-expense matching in the pharmaceutical and biotechnology industries, with particular attention to the moderating role of corporate governance and the influence of regulatory intervention. While capitalizing R&D expenditures enhances the relevance of financial information and positively impacts firm value, it also increases the risk of earnings management, potentially disrupting revenue-expense matching. Using a fixed-effects regression model, this study analyzes 1,350 firm-year observations from Korean listed firms in the bio-pharmaceutical sector from 2012 to 2022. The sample includes firms with financial statements, auditor data, and detailed disclosures on R&D expenditures, encompassing capitalized R&D costs, R&D expenses recognized in income statements, and those classified as manufacturing costs. The results indicate that R&D capitalization generally weakens revenue-expense matching in these industries. However, the adverse effects are mitigated by the effective implementation of corporate governance mechanisms. Additionally, the Financial Supervisory Service’s thematic supervision of R&D accounting practices has significantly improved revenue-expense matching. Prior to the supervision period (2012–2017), firms exhibited significant discretionary capitalization practices, undermining revenue-expense matching. Following the supervision (2018–2022), improved adherence to accounting standards has enhanced matching quality, underscoring the regulatory intervention’s effectiveness. These findings contribute to the literature by demonstrating that while discretionary R&D capitalization can impair revenue-expense alignment, strong corporate governance and adherence to accounting standards can offset these negative effects. The study provides valuable implications for future research and industry practices, particularly in navigating the trade-offs associated with R&D capitalization.

Acknowledgment
This study was supported by Chungnam National University.

This study examines how consumer, investor, and manager sentiment explain US stock excess returns over 23 years. Its novelty resides in integrating the sentiments of three different types of economic and financial agents. It also performs a segmented temporal analysis using rolling window techniques, to assess sentiment’s impact across different time horizons. The empirical analysis utilizes the Paris-Winsten and Newey-West estimators, along with the ARMAX model to address autocorrelation and heteroscedasticity in linear regression, providing robust standard errors and reliable statistical inferences. The autoregressive moving average models estimate excess return based on the past values, shocks, and external variables. Combining the Fama-French five-factor model with the sentiment factor enriches the analysis. The study’s findings indicate that higher consumer optimism negatively impacts excess returns, as investors may anticipate a future decline in the stock market due to an existing overheated economy. Investor sentiment exhibits mixed behavior, where higher uncertainty may increase stock returns due to previous oversold markets creating opportunities for investors or due to the closing of short positions, which will also increase stock demand. It is also related to decreased stock returns depending on the proxy used. As for managers’ sentiment, this work did not demonstrate a relevant relationship between this sentiment and stock returns. The study also reveals that the importance of sentiment determinants of those three agents changes over time. The findings support behavioral models of asset pricing, which incorporate both market fundamentals and the psychological characteristics (sentiment) of different market participants.

Acknowledgments
This work is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Ref. UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Instituto Politécnico de Viseu for their support.

This article examines the influence of networking capital, leverage, and profitability on a firm’s cash holdings. A firm’s level of cash reserves is a trade-off between financing, investment, and market climate. To achieve this trade-off, firms maintain cash reserves as a preservative motive. A firm with optimized working capital will have low working capital requirements, which will result in an increase in the firm’s cash reserves. In this context, the present study acquires data from 51 firms in the manufacturing sector registered on the TASI (Tadawul All Share Index) from 2014 to 2022. The study considers cash as a regressand, net working capital, profitability, and leverage as predictor variables, and firm size as a control variable. The study observed that the manufacturing firms in Saudi Arabia invest excess cash in profitable projects. The study wrapped up the results by using pooled regression and panel regression with fixed and random effects. Panel regression results report a negative and significant influence of net working capital on firms’ cash reserves with a coefficient of –0.09. Leverage positively influences the firms’ cash reserves with a coefficient of 0.05 and is significant, and profitability is positive and significant with a coefficient of 0.04. Further, firm size is positive and significant with a coefficient of 0.004.

Acknowledgment
The author acknowledges that the current project under research project number PSAU/2023/01/27013 was funded by Prince Sattam Bin Abdulaziz University.

This study investigates whether higher foreign shareholder equity improves labor investment efficiency in South Korean publicly listed firms. Labor investment, like capital investment, plays a crucial role in shaping corporate performance and value. It involves continuous cash outflows and poses challenges during restructuring, such as downsizing. Foreign shareholders are known to take on a monitoring role in Korean firms, potentially leading to more efficient labor investment decisions.
To assess the impact of foreign shareholder involvement on labor investment efficiency, regression analysis was conducted using data from 2,699 firm-year observations from firms listed on the Korean stock exchange during the pre-pandemic period (2016–2019). Labor investment inefficiency was measured as the absolute difference between actual and expected labor investment levels, considering both over- and under-investment as inefficiencies.
The analysis revealed a significant negative relationship between foreign ownership and labor investment inefficiency. Specifically, a regression coefficient of –2.220 (p-value: 0.027) indicates that higher foreign shareholder equity is associated with lower labor investment inefficiency. Further analysis, separating the sample into over-investment and under-investment groups, found that the coefficient for foreign ownership in the under-investment group was –1.920 (p-value: 0.055), significant at the 10% level. These findings suggest that foreign shareholders, through their monitoring role, help reduce information asymmetry, decreasing inefficiencies in labor investment decisions.

Prior research states that during extreme uncertainties stock prices deviate from their fundamentals. This study examines the cross-section of share price returns during the COVID-19 and pre-COVID periods to determine how investors’ reaction to prior earnings volatility is affected by the COVID-19-induced ambiguity. The sample consists of 840 firms listed on the New York Stock Exchange (NYSE) from January 1, 2020 to May 31, 2021. Consistent with the notion that ambiguity-aversion is not a universal phenomenon, COVID-period stock returns exhibit a positive (β = 0.23) and statistically significant relationship with prior earnings volatility. In contrast, the stable period returns show a very weak, if any, correlation with prior earnings volatility. The positive relationship is more pronounced for firms that experience greater information asymmetry. When comparing the results with previous research, it appears that different crises evoke varied levels of ambiguity-aversion possibly because of the ways in which each crisis’s features and anticipated outcomes influence how the market reacts. Thus, before crafting responses to a crisis, policymakers and firms should thoroughly examine the crisis and identify the underlying causes, dynamics, and possible effects on decision-makers’ ambiguity-aversion behavior.

Corporate governance has been widely applied in developed countries to promote accountability, transparency, and efficiency within corporations. In Vietnam, as the country transitions toward integrating international standards, corporate governance has become an emerging and critical area of focus. Therefore, this study aims to examine the relationship between corporate governance characteristics and corporate financial distress. The study utilizes the dataset of about 500 listed companies in the Vietnam stock exchange during 2014–2022. Feasible generalized least squares regression (FGLS) is employed to account for the heteroskedasticity and autocorrelation problems. Regression results show that frequent board meetings and more gender-diverse boards improve corporate financial health, while an increase in board members and duality roles have negative effects. Duality is often associated with increased agency problems, inefficient capital usage, and higher risk levels that reduce financial health. However, the impact is different in complex firms measured by book-to-market ratio and operating cycles. In complex firms, duality proves valuable by providing unified leadership and enabling active, clear management strategies. This can be explained by the fact that clear and flexible strategies outweigh the benefits of separation between the chairman and Chief Executive Officer.

Acknowledgment
The author gratefully acknowledges the financial support from the Banking Academy of Vietnam.

Under complex financial circumstances, individuals are empowered to improve financial decision-making by trusting financial advice and utilizing digital technology and resources. Though the extant research has explored numerous factors impacting financial well-being, the specific influence of financial advice and digital financial literacy remains underexamined in the Indian context. Thus, grounded on Social Cognitive theory, this study aimed to examine how insights gained from financial advice and digital financial literacy integrate into individual’s decision-making and, subsequently, influence their financial well-being. The data were collected using purposive sampling from Southern India, with 508 respondents recruited using social media platforms. The research hypotheses were empirically validated through hierarchical regression and mediation analysis using the Hayes Process Macro. The study’s findings reveal that financial advice positively predicted financial decision-making (β = 0.667; p < .000). Similarly, digital financial literacy has a positive impact on financial decision-making (β = 0.369; p < .000). Additionally, financial decision-making (β = 0.105; p < .065) positively predicted financial wellbeing. Thus, both factors emerged as transformative predictors of an individual’s financial well-being. Moreover, the findings reveal the mediating role of financial decision-making between financial advice, digital financial literacy, and financial well-being. Therefore, the study underscores that by leveraging the cumulative effect of professional financial advice and digital technologies, policymakers and government regulatory bodies can augment the critical ability of informed decision-making. Thus, these factors could navigate overcoming individual financial challenges and benefit the overall well-being of a diverse population.

From an accounting perspective, taxes reduce profits and are often perceived as diminishing shareholders’ rights. Consequently, government support through tax reductions plays a crucial role in enhancing the effectiveness of corporate strategies aimed at minimizing tax burdens. From the perspective of the Efficient Market Hypothesis (EMH), government tax incentive policies serve as vital signals to investors, shaping their expectations and influencing investment decisions. This study focuses on Indonesia’s tax incentive policy introduced at the onset of the COVID-19 pandemic on April 1, 2020, and continuing until September 30, 2023. To assess market efficiency during this period, portfolios were constructed from the top 21 firms listed on the IDX Quality 30 and IDX High Dividend 20 indices, categorized by their systematic risk and cost of equity. The findings indicate that portfolios with higher systematic risk and cost of equity exhibit more optimal returns, greater volatility, and better risk-return trade-offs. Conversely, portfolios with lower systematic risk and cost of equity tend to yield suboptimal returns due to their passive investment characteristics. Overall, the returns from all portfolios during the tax incentive period align with the weak form of the EMH, albeit showing negative autocorrelation instead of a purely random walk pattern. These findings imply that information regarding tax incentives influences prices primarily among firms with higher cost of equity or systematic risk. This study contributes to the understanding of the EMH by examining the impact of tax incentives during the pandemic while controlling for both the cost of equity and systematic risk.

Earnings forecasts by financial analysts are critical to guiding investment decisions and corporate valuations. This study examines how forecast sequence (disaggregation vs. aggregation) interacts with initial optimism (presence vs. absence) to shape the accuracy of earnings predictions. A 2×2 between-subjects experimental design was employed, involving 97 professional financial analysts from leading U.S.-based brokerage firms with extensive experience in equity research. These analysts, representative of the target population making critical market forecasts, were tasked with predicting the annual earnings per share (EPS) of a hypothetical global hospitality firm, Firm X, listed on the New York Stock Exchange. The sample was chosen to ensure high external validity by mirroring real-world practices and decision contexts in financial forecasting. Initial optimism was manipulated using “strong-buy” and “neutral” stock recommendations, while forecast sequence was adjusted by requiring updates either after each management announcement (disaggregation) or collectively (aggregation). Results demonstrate that disaggregation amplifies optimistic bias in the presence of initial optimism, resulting in inflated earnings forecasts. This effect is attributed to confirmation bias. In contrast, no significant differences in forecasts were observed between sequences in the absence of initial optimism. These findings offer practical insights into mitigating cognitive biases in financial analysis, emphasizing the dual-edged role of disaggregation. Future research may extend these findings across diverse industries and forecasting contexts to further refine strategies for enhancing decision-making accuracy and investor trust.

Indonesia’s mining sector was ranked as the third most vulnerable to fraud according to the Association of Certified Fraud Examiners (ACFE) survey in 2019. The advent of the COVID-19 pandemic further contributed to a 26.6% decline in sector investment in 2020 due to widespread project cancellations. Thus, this study analyzes fraudulent financial reporting and firm value from the perspective of fraud hexagon and firm size focusing on the mining sector industry in Indonesia. The panel data regression analysis was used to analyze data collected from the annual reports of mining companies in Indonesia from 2020 to 2022. The findings indicate that management pressure proxied by financial targets and measured through Return on Assets (ROA) has an effect on fraudulent financial reporting (FFR), as measured by F-Score. In addition, opportunities proxied by nature of industry affect FFR negatively. FFR also affects the value of a company as proxied by Tobin’s Q ratio. These results suggest that mining companies should set financial targets cautiously to avoid excessive pressure on management and uphold strong governance and control systems. Moreover, this study highlights the importance of raising awareness of fraudulent financial reporting, given its potentially adverse effects on a company’s going concern.

With the increasing global emphasis on responsible investing, this study explores the tradeoff between ESG and traditional financial metrics in shaping the investment decisions of retail investors in India. A within-subject experimental design was employed at Christ University, India, involving an initial sample of 75 participants, with 55 completing all three experiment rounds. The sample respondents evaluated masked stock profiles across three rounds, where updated financial and ESG information on masked stock was provided at each round. The results indicate that though ESG metrics are getting attention among retail investors, financial metrics are still the main determining factor for investment. It was found that ROE (52 responses), 3-year CAGR Net Profit (36 responses), and P/E ratios (48 responses) are the most influencing factors to make investment decisions. Similarly, ESG factors (Governance, Environmental, and Sustainability scores) are also frequently mentioned, with 74 citations. Retail investors mainly consider profitability and view ESG as risk-mitigating or neutralizing factors. While evaluating the ESG factors, retailers mainly look at the firm’s environmental concerns, followed by governance and social factors. This result contrasts with the previous studies in this domain, where the literature emphasized governance factors more than environmental factors. These results highlight the integration of ESG elements, as retail investors remain with favorable returns and sacrifice sustainability. Further, this study spots the need for better and quantifiable ESG performance reports to consider alternative data comparable to financial data for better investment decisions.

As financial technologies rapidly expand in developing countries like India, digital financial literacy plays a critical role in shaping how individuals interact with innovative financial services. This study evaluates the influence of financial literacy, digital literacy, and digital financial literacy on the adoption of Peer-to-Peer lending platforms. It also explores the distinct roles and interrelationships among these forms of literacy within the Peer-to-Peer lending ecosystem. Data were collected from 430 participants, exceeding the minimum sample size requirement calculated through G*Power. Participants, comprising borrowers and lenders, actively interacted on Peer-to-Peer lending platforms in cities like Delhi, Mumbai, Hyderabad, Bangalore, and Chennai, ensuring a holistic understanding of the ecosystem. Borrowers are individuals seeking financial assistance, while lenders provide funds, often in exchange for interest-based returns. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study reveals that while financial literacy and digital literacy significantly contribute to digital financial literacy, they do not directly impact the behavioral intention to adopt Peer-to-Peer lending platforms. Instead, digital financial literacy directly influences adoption intention, highlighting the importance of integrated literacy over isolated skills. The findings underscore the high proficiency levels of existing users in financial, digital, and digital financial literacy, reflecting the platforms’ appeal to skilled individuals. Expanding access to less proficient populations remains crucial. Moreover, platform managers can capitalize on user expertise by introducing advanced features tailored to sophisticated needs, thereby enhancing satisfaction and the overall user experience. These insights emphasize digital financial literacy’s pivotal role in fostering broader Peer-to-Peer lending adoption.

Acknowledgments
The first author thanks the Ministry of Education, Government of India, for providing financial assistance (fellowship) during her Ph.D.

This research investigates the relationship between the adoption of internal fintech solutions and the profitability of banks in Kosovo, leveraging the Technology Acceptance Model and Innovation Theory. The study analyzes the impact of mobile banking, e-banking, electronic payment systems, and data analytics on profitability using net interest margin (NIM) and return on assets (ROA) as key metrics. A mixed-method approach was adopted, combining audited financial report data from Kosovo’s commercial banks with survey data to ensure comprehensive analysis. To explore this relationship, a structured questionnaire was administered to 169 bank employees across 10 commercial banks in Kosovo. The sample included professionals from finance, technology, credit analysis, and customer service departments, chosen for their direct involvement in fintech adoption and its implementation. This selection ensured insights from individuals who actively engage with fintech tools and their impact on bank operations. Findings reveal that fintech adoption impacts profitability based on focus. Investments in operational efficiency negatively affect ROA (β = –0.079, p < 0.001), while fintech adoption targeting business opportunities, credit cost reduction, and customer understanding improves ROA and NIM. Business opportunities enhance ROA (β = 0.053, p < 0.01) and NIM (β = 0.098, p < 0.001), while customer understanding increases ROA (β = 0.143, p < 0.001). Mobile banking, digital lending, and bank age also show positive effects.

Fintech adoption drivers are relevant for tourism-supported culinary SMEs for a number of reasons, including sustainability, economic growth, and technological advancements. This study aims to confirm the fintech adoption drivers among tourism-supported culinary SMEs in West Sumatra, Indonesia. The study uses primary data collected through a survey. Forty-four experts from various relevant academic backgrounds were respondents to this study. Data were analyzed in multiple stages. First, data were analyzed using the univariate test by applying the Mann-Whitney U and Kruskal-Wallis tests. Second, data analysis proceeds to exploratory factor analysis to separate the drivers into several factors. Finally, confirmatory factor analysis was employed using a second-order structural equation model. The result shows that five of the thirteen drivers identified in the literature were deleted due to no expert agreement. Based on exploratory factor analysis, it was found that two factors were created as fintech adoption drivers: time reduction process and new customer attraction factor (factor 1), and ease of use, security, and cost reduction factor (factor 2). The third analysis using second-order smart_PLS indicates that the two factors were confirmed. It can be concluded that two factors drive fintech adoption: (i) time reduction process and new customer attraction factor, and (ii) ease of use, security, and cost reduction factor.

Acknowledgment
This research was funded by the Ministry of Education, Culture, Research and Technology, Republic of Indonesia (No. 186/E5/PG.02.00.PT/2023).
We acknowledge the directorate of higher education, the Ministry of Education, Culture, Research and Technology, Republic of Indonesia, for research funding (No. 186/E5/PG.02.00.PT/2023). Our thanks are also directed to the Rector of Universitas Bung Hatta and anonymous reviewers of this article for constructive suggestions.

The interplay between stock market performance and economic risk is a central concern in financial economics, as macroeconomic variables have a considerable impact on investment decisions and stock pricing. This relationship is particularly critical for bank stocks, as their performance is a key indicator of a country’s financial health. While extensive research has explored bank stock returns in developed economies, there exists a significant gap in understanding this dynamic within developing countries like India, particularly amid macroeconomic fluctuations underscored by the COVID-19 pandemic. Given the substantial investments in bank stocks by Indian investors, this study aims to examine the impact of macroeconomic factors on Indian bank stock returns. The study employs quarterly data from 2013–14 to 2022–23, with macroeconomic data sourced from the CMIE Economic Outlook and bank stock returns data obtained from the Bloomberg database. Using an Ordinary Least Squares regression model, the findings reveal that interest rate (β = 0.3069), inflation (β = 0.1644), GDP (β = 0.1928) and COVID-19 (β = 0.5737) exert significant positive effects on bank stock returns, while the exchange rate (β = –0.7440) has a substantial negative impact. The results highlight the sensitivity of bank stock returns to macroeconomic volatilities, with the pronounced impact of the COVID-19 pandemic further highlighting the effects of economic crises. The findings emphasize the need for incorporating these factors into the bank stock returns model, offering valuable insights for investors, banks, and financial regulators.

Acknowledgment
Aleena Joseph is a recipient of the Indian Council of Social Science Research Doctoral Fellowship. The article is largely an outcome of the doctoral work sponsored by ICSSR. However, the responsibility for the facts stated, opinions expressed, and the conclusions drawn is entirely that of the authors.

Economic informality remains a critical challenge in Latin America, affecting both sustainable development and tax equity. This study analyzes the relationship between tax culture and willingness to formalize among traders in Peru’s main wholesale food market. Using a quantitative, non-experimental, correlational and cross-sectional approach, 300 traders were surveyed using an expert-validated questionnaire with tested reliability (Cronbach’s alpha of 0.87 for tax culture and 0.83 for formalization). The findings show a significant positive correlation (rs = 0.914, p < 0.01) between tax culture and the probability of formalization. The dimensions of tax knowledge (rs = 0.681), tax awareness (rs = 0.701), and tax compliance (rs = 0.745) were also positively associated with the inclination to formalize. While 44.3% of respondents acknowledged that access to tax information strengthened their tax culture, only 30.3% claimed to regularly comply with their tax obligations. The study concludes that promoting formalization requires educational initiatives and public policies that strengthen the tax culture, simplify procedures and build institutional trust. It also highlights the need to integrate effective state and local tax systems and to develop legislation aligned with the realities of local government, thus promoting the inclusion of taxpayers in the tax system.

This study examines the connections between heuristic prejudices, risk perceptions, and investment decisions among stock market investors in Nepal. The study explores how prejudices such as overconfidence, representativeness, availability, and anchoring and adjustment shape investment choices, with a specific emphasis on the mediating influence of risk perception. Through a quantitative approach, data were collected from 404 respondents via a self-administered survey, and Structural Equation Modeling (SEM) was used for analysis. The findings reveal that risk perception significantly mediates the effect of these biases on investment decisions, highlighting the complex interplay between behavioral factors and investor behavior. By highlighting the necessity of taking risk perceptions into consideration when addressing behavioral biases in investment strategies, these results have practical consequences for investors, financial consultants, and legislators. This research pays attention to the understanding of behavioral finance, particularly within the context of Nepal’s capital market, and lays the groundwork for further studies on factors affecting investment decisions in real-world settings.

Considering the snakebite effect experience of investors and their decision-making in the era of robo-advisors, this study focuses on examining the mediating role of the snakebite effect between the value of robo-advisors and investment decisions and assessing the moderation of social-emotional well-being and resilience among active investors. The research process began with an exhaustive review of existing literature and the development of a structured questionnaire. A further survey was undertaken by collecting 361 responses from active investors residing in the region of South India using robo-advisors, and finally, the mediation and moderation were analyzed utilizing confirmatory factor analysis (CFA) to check the model fit and Structural Equation Modelling (SEM) to test hypothetical relationships. The results validate the intervening role of the Snakebite Effect in the relationship between the value of Robo-Advisors and investment decision-making. Further, social emotional well-being and resilience of investors significantly lessen the negative impact of the snakebite effect on investment decision-making. The role of social-emotional well-being and resilience is vital as high tendency leads to a low snakebite effect, better effectiveness of robo-advisors, and investment decision-making. This study provides various theoretical, practical, and managerial implications for improved robo-advisory services and increased adoption among diverse investor segments. In particular, the study emphasizes that financial institutions should focus on hybrid advisory models that combine the analytical capabilities of robo-advisors with the empathetic, personal touch of human advisors.

The impact of different types of capital flows on China’s economic growth has been widely studied to determine whether the type of capital significantly affects the Chinese economy. The purpose of this study is to investigate the relationship between long-term capital flows and economic growth in China, considering factors such as Foreign Direct Investment (FDI), portfolio equity, portfolio bonds, and external debt. All secondary data were collected from the World Bank database. The paper also investigates which type of capital flow has the most significant relation with the economic growth of China. A quantitative approach was chosen for the study. Moreover, to overcome the bias output of ordinary least squares, this paper deployed a Two-Stage Least Squares (2SLS) estimation method. This study has found a relatively stable positive relationship between FDI and growth, where the coefficient of 0.9699 indicates that a 1% increase in FDI is associated with a 0.97% growth in Gross Domestic Product (GDP). Similar to FDI, portfolio equity has a positive impact on GDP growth, with a coefficient of 2.1419. In contrast, portfolio bond and debts have a negative coefficient of –1.7752 and –0.2831. These findings contribute to a deeper understanding of China’s development experience, particularly regarding the role of capital flow. The paper explores two key limitations that need to be explored in the future, i.e., the causal relation between each type of long-term capital flow and economic growth, and the impact of COVID-19 on the economic growth relationship.