This study contributes new insights into dividend policy by investigating how debt levels and firm size moderate the relationship between cash holdings and dividend payouts. Grounded in the MM theory of capital structure, the research challenges the traditional assumption of dividend irrelevance by incorporating real-world financial constraints and governance dynamics. The sample consists of 475 non-financial firms listed in Thailand, covering data from 2019 to 2023. Using Hayes’s PROCESS Macro for moderated moderation analysis, the findings reveal that cash holdings positively influence dividend payouts, and this effect is contingent upon both the firm’s leverage and size. Specifically, small firms with low debt levels tend to offer higher dividend payout, whereas large firms with below-average industry debt show diminished dividend payouts. This interaction presents a novel theoretical contribution by linking liquidity management, capital structure, and firm scale in explaining dividend behavior dimensions that have rarely been integrated in prior research. The study extends the existing literature on investment returns and corporate financial policy and provides practical implications for investors and corporate decision-makers operating in emerging markets.

Current understanding of the basic characteristics that affect the perceived quality of cruise destinations remains lacking. In order to create a set of perceived destination quality (PDQ) variables, this study intends to investigate and verify cruise destination attributes in both reflective and formative terms. Data was gathered using a questionnaire survey as part of the study’s quantitative research technique. The study sample comprised 350 participants, with GSCA Pro software version 1.1.8 being used to analyze the data that was gathered. The research results confirmed the essential components of perceived destination quality (PDQ), which were composed of the following six important categories as first-order constructs: natural and well-known attractions, the variety of tourist services and culture, the quality of general tourist atmosphere, entertainment and recreation, the general environment, and accessibility. The 23 observed variables in this study, which comprised important reflective and formative components, were used to evaluate these constructs. The study’s findings can serve as a reference for executives, cruise tourism managers, and port destinations as they create policies and plans to grow cruise tourism in the destination region. Meanwhile, researchers may use these sets of variables for consideration in conjunction with other elements in subsequent studies.

Various studies have debated how changes in dividend tax rate affect investment decisions. While some argue that dividend tax policies impact investment decisions, others have suggested that these taxes have no relevant influence on such decisions. This study examines how researchers from various countries investigate the relationship between dividend tax policies and investment decisions. Utilizing a bibliometric analysis approach, this study explores research trends in the area of dividend tax policies and investment decisions. Data were sourced from the Scopus database and analyzed using Bibliometrix R-package (Biblioshiny) tools and VOSviewer. The study aims to provide insights into publication trends, countries involved in research in this field, the most relevant journals, the most productive researchers, and recent and future theme trends. By doing so, this study offers a more complete overview of research developments on dividend tax policies and investment, and highlights potential directions for future research.

This study examines the connection between household debt and income disparity in Thailand, emphasizing the dynamic interaction between these two variables. The study utilizes annual data from 1980 to 2022, a period marked by significant structural changes in the economy. To address these changes, the study implements the Time-Varying Parameter Vector Autoregression (TVP-VAR) estimation method, which is well-suited for capturing dynamic structural shifts. After estimating the model, coefficients were used to generate the impulse response function. The results of the study indicate that a one standard deviation shock in income inequality, as measured by the Gini coefficient, results in a reduction in the household debt-to-GDP ratio across the short, medium, and long term, with the impact being most pronounced in the short term and diminishing over time. Furthermore, the study examines how a shock to income inequality influences consumption patterns. An increase in the Gini coefficient initially leads to a rise in short-term consumption, but this effect reverses in the medium and long term, when consumption declines. The study also explores the impact of household debt shock on consumption. The results indicate that an increase in the debt-to-GDP ratio is associated with a rise in short-term consumption, while in the medium and long term, consumption decreases. These findings highlight the complex and varying impacts of income inequality and household debt on economic indicators over different time horizons, emphasizing the importance of accounting for dynamic structural changes in economic analysis.

This research aimed (1) to analyze the effect of the taxpayer code of ethics and tax sanctions on the voluntary tax compliance of listed companies in the Stock Exchange of Thailand; (2) to analyze the effect of the taxpayer code of ethics and tax sanctions, mediated by tax morality, on the voluntary tax compliance of listed companies in the Stock Exchange of Thailand; and (3) to compare the general information of respondents in relation to opinions on taxpayer code of ethics and tax sanctions. This study employed a quantitative research design. Data were collected via questionnaire from 380 Chief Financial Officers (CFO) of listed companies in the Stock Exchange of Thailand. Hierarchical random sampling was used in order to select the sample. The collected data were analyzed using a structural equation model. The findings of the study indicated the following: 1) taxpayer code of ethics and tax sanctions have direct and indirect positive influences on voluntary tax compliance; 2) the willingness to pay taxes varies across industry groups, suggesting different perceptions of taxpayer code of ethics and tax sanctions; and 3) factors such as gender, age, level of education, and work experience, do not significantly influence opinions on taxpayer code of ethics or tax sanctions.

This study investigates the key drivers of digitalization and the impacts of digitalization on organizational resilience among Thailand’s top department stores. Targeting mid- to senior-level managers, IT professionals, and operational executives, the study involved collection of data from a sample of 400 respondents using purposive and quota sampling techniques. A pilot test with 40 participants was utilized to ensure the reliability of the questionnaire through Item-Objective Congruence (IOC) and Cronbach’s Alpha analysis. Data were analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). The findings reveal that innovation (β = 0.189, p < .001), human capital (β = 0.519, p < .001), and infrastructure and technology (β = 0.334, p < .001), significantly drive digitalization, while business model adaptation did not show a significant effect (β = 0.057, p = .313). Furthermore, digitalization was shown to have a strong influence on organizational resilience (β = 0.863, p < .001). These results highlight the critical role of investment in human capital, fostering innovation and enhancing technological infrastructure, to accelerate digital transformation and build resilience in a rapidly changing retail environment. The study offers practical insights for department store leaders seeking to strengthen their digital capabilities and adapt effectively to market disruptions.

The aim of this study was to construct a causal model that investigates the association between big data analytics capability (BDAC), supply chain agility (SCA), supply chain performance (SCP), and financial performance (FP), in the hotel industry. Additionally, it examines the mediator functions of SCA and SCP in the correlation between BDAC and FP. The study collected data from 324 hotel entrepreneurs who participated by completing online surveys. The gathered data were subsequently examined using PLS-SEM. The results demonstrate that BDAC has a direct favorable impact on SCA, SCP, and FP, while SCA also has a positive effect on both SCP and FP. Both SCA and SCP were found to significantly mediate the relationship between BDAC and FP. These findings indicate that hotel owners should utilize customer service data for thorough analysis to determine the most effective operational solutions and improve their BDAC. This method has the potential to enhance SCA, SCP, and eventually, yield superior financial performance. The study enhances our understanding of the function of BDAC in improving performance in hotel businesses. It also offers practical implications for hotel management.

Previous studies have shown that utilizing data sources such as historical or technical data along with deep learning approaches can increase the accuracy of forex price prediction. However, relying on a single data source, such as historical data alone, limits predictive performance as it fails to capture the entire complexity of the market. This study aims to demonstrate that merging financial data from four different sources can significantly improve prediction accuracy. This study proposes a hybrid LSTM-GRU-Attention deep learning model, leveraging historical, fundamental, technical, and sentiment data, to predict the closing price of the GBP/USD currency pair, which is actively traded on a global scale. QuantManager, Forexfactory, and DailyFX data were collected over three timeframes: 30-minute, 1-hour, and 1-day, from January 1, 2013 to December 31, 2023, respectively. The model’s performance was evaluated using MSE, RMSE, and MAE metrics. The proposed model with multi-source data demonstrated substantial error reductions compared to historical data only models from previous studies, achieving RMSE decreases from 17% to 89% and MAE reductions from 22% to 94% across 30-minute, 1-hour, and 1-day timeframes. The integrated multi-source data model outperformed models that integrated only historical data, across all timeframes, highlighting the benefits of improved forex prediction accuracy.

The COVID-19 pandemic significantly shifted global work patterns, accelerating the adoption of remote and hybrid work environments. Most theories and studies related to fundamental well-being variables have traditionally been grounded in fully offline work modes. This leaves gaps in understanding how these well-established concepts apply to online-related work environments. This study study aims to investigate the impact of online work mode on the foundations of personal well-being by exploring the relationships between resilience coping, life orientation, hope, and purpose in life across both online-related work and fully offline work settings. Data were collected from 469 participants, including 348 working in online-related roles and 121 in fully offline positions. Findings indicate that hope has the strongest influence on a sense of purpose across both work modes, followed by life orientation in offline work and resilient coping in online work. The results highlight the importance of resilience in managing isolation and self-management in online settings, while life orientation is more significant in offline environments, emphasizing interpersonal interactions. These findings underscore the need for updated theoretical frameworks and further research to address the evolving dynamics of work and employee well-being.

To keep pace with dynamic changes in the global financial sector, the Bank of Thailand has provided the opportunity for bank operators and investors to submit for approval to set up a virtual banking business in Thailand in 2025. As this type of bank will begin operating in Thailand for the first time in 2025 consumer adoption is likely to be very challenging. In this study, the TAM model was adopted to examine the factors influencing behavioral intentions to use virtual banking services, collecting data through a self-administered questionnaire from 600 bank customers aged between 20 and 60, and residing in Bangkok. Descriptive statistics such as frequency, percentage, mean, and standard deviation, were employed to describe the sample characteristics and the level of each factor in the model. Structural equation modelling (SEM), including confirmatory factor analysis (CFA), was used to determine the construct validity of the variables. Path analysis was used to test the model’s goodness of fit and the research hypotheses. The results showed that all hypotheses were supported and that factors such as corporate reputation, perceived safety of technology, personal innovativeness, and the perceived cost of technology indirectly influence behavioral intentions to use virtual banking services.