Journal of Business Administration and Languages (JBAL)

The Impact of Share Repurchases on Stock Returns and Financial Ratios: Evidence from SET100 Companies, January 2024–June 2025

Namporn Sathirakul — 2026-08-28

This study examines the effects of share repurchase announcements on stock returns and financial ratios of firms listed in the SET100 index during January 2024 to June 2025, a period in which the Thai stock market significantly underperformed global markets. An event study methodology is employed with an event window of 15 trading days before and after the announcement date (t–15 to t+15) and an estimation window of 120 trading days prior to the announcement.

The results indicate that share repurchase announcements are associated with statistically significant positive abnormal returns in the short period surrounding the announcement date (t+0 and t+1), as well as during certain pre-announcement periods. However, cumulative abnormal returns do not provide evidence of sustained value creation over the event window.

The analysis of financial ratios—earnings per share (EPS), return on equity (ROE), debt-to-equity ratio (D/E), and price-to-book value ratio (P/BV)—based on paired t-tests and Wilcoxon signed rank tests reveals no statistically significant changes, except for a marginal decline in the P/BV ratio. Overall, the findings suggest that share repurchases by SET100 firms during a market downturn primarily function as a short-term signaling mechanism rather than a tool for long-term value creation. This study contributes to the literature by providing evidence from an emerging market context and offers implications for investors, corporate managers, and capital market regulators.

Influence of Entrepreneurship, Organizational Culture and Learning Organization on Innovation of Small and Medium Agricultural Processing Businesses in Thailand

Nuchsara Nanthoe — 2026-08-28

This research objective of studying the influence of entrepreneurship, organizational culture, and learning organization on innovation in small and medium-sized agricultural processing businesses in the country. The study population consists of 1,319 entrepreneurs from small and medium-sized agricultural processing businesses, with a sample size of 382 individuals. The example uses a simple random sampling method, assuming that every unit in the population has an equal chance of being selected. This is done by drawing names of businesses and then randomly selecting without replacement and questionnaires were the analysis tool. The statistics used include inferential statistics such as confirmatory factor analysis, path analysis, and structural equation modeling.

The research findings indicate that (1) Entrepreneurship, organizational culture, learning organization, and innovation have observed variables that are consistent with empirical data. The highest-impact dimensions for each factor are: competitive capability in entrepreneurship, participation in organizational culture, knowledge sharing in learning organizations, and innovation processes. (2) Entrepreneurship and learning organizations have both direct and indirect influences on innovation in medium and small-sized agricultural product processing businesses. (3) Learning organizations also act as a mediating variable between organizational culture and innovation in medium and small-sized agricultural product processing businesses.

The Development Guidelines of Luxury Café to Enhance Customer Loyalty

Tissana Limwudtikaijirat — 2026-08-28

This research aims to extend the concept of customer loyalty to the luxury café business context. It integrates fundamental service research factors—namely, service quality, product quality, and Physical Environment —with a contemporary factor, technology-driven service innovation, to examine the antecedents influencing customer loyalty in the modern era. This quantitative study collected data via a questionnaire from a sample of 515 customers with experience visiting luxury cafés in Chiang Rai province. The samples were selected through convenience sampling. Data were analyzed using descriptive statistics, and hypotheses were tested using Multiple Regression Analysis. The findings revealed that store environment had the strongest positive influence on word-of-mouth, followed by service quality and technology-driven service innovation. Conversely, product quality was found to have no significant impact on word-of-mouth. Furthermore, regarding repurchase intention, service quality was identified as the most significant positive predictor, followed by store environment, product quality, and technology-driven service innovation. The results indicate that luxury customers prioritize experiential and emotional factors over functional factors when building loyalty to luxury cafés. These findings offer practical guidelines for luxury café businesses seeking to enhance customer loyalty and create differentiated service experiences, thereby strengthening their competitive advantage and ensuring long-term business sustainability.

Predicting the Success of Games on Steam Platform

Duangruthai Preedanon — 2026-08-28

This study aims to identify key factors influencing the success of video games on the Steam platform and to develop a statistical model for predicting a game’s likelihood of success. It serves as a tool to support entrepreneurs in making comprehensive business decisions, enhancing their competitive advantage. Data covering 47,557 video games released between 2018 and 2023 were collected from VGInsights and SteamDB. A logistic regression model was employed to examine the relationships between game success and independent variables: genre, subgenre, price, release month, and publisher quality. The findings revealed that Casual and Sports genres demonstrated a significantly positive impact on success across multiple years. Subgenres such as 2D Platformer, Survival Horror, Shoot ’Em Ups, VR, and FPS also exhibited consistently positive influences. Game pricing showed a significantly positive effect on success annually, with exceptionally high odds ratios ranging from 38 to 196. Conversely, release months such as February, March, August, September, and October displayed a negative impact across multiple years. Furthermore, games categorized as Indie demonstrated a significantly positive effect during 2018–2020, reflecting strong market attention toward indie games during that period before the market became highly competitive. These results provide valuable insights and practical predictive tools for developers and publishers to enhance strategic decision-making in the game industry.

Mediating Effects of Trust in Leaders and Supervisor Support on the Soft Skills of Hotel, Airline, and Tourism and Service Business Workers’ Job Performance

Tippawan Jantamaneechot — 2026-08-28

This study focused on exploring how soft skills influence job performance and investigating the role of trust in leaders and supervisors support from among hotel, airline, and tourism and service industry employees based on affective event theory. Using a quantitative method, data was collected from 420 participants who were working in hotel, airline, and tourism and service businesses located along Thailand’s Andaman coast using quota sampling, which represents an 84.5% response rate to the online questionnaires distributed for data gathering. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), this research highlights the direct and indirect effects of trust in leaders and supervisors’ support on soft skills’ effects on job performance. The results indicate a significant impact by soft skills on job performance, trust in leaders, and supervisors’ support. The findings showed that trust in leaders and supervisor support significantly mediated the impact soft skills on job performance. Soft skills, trust in leaders, and supervisor support are currently viewed as an essential element for workers, especially in the tourism and hospitality sector, to enhance their job performance. Yet, there have been few studies intended to determine the influences of soft skills on workers’ job performance, trust in leaders, and supervisor support separately in the contexts of hotel, airline, and tourism and service businesses. Thus, this research intended to eliminate the research gap in making academic originality and present useful contributions of the related suggestions based on the findings.

Content Consumer Segmentation form Importance Feature Selection for Service Cancellation Using Hybrid Clustering

Chakkarin Santirattanaphakdi — 2026-08-28

This research aims to develop a consumer segmentation model for churn prediction using hybrid clustering techniques and feature selection, addressing limitations in traditional methodologies that rely on demographics or single clustering methods, which often struggle with high-dimensional and non-linear data. The analysis involved 10,983 YouTube Premium users in the Bangkok metropolitan area. The methodology integrates stepwise feature selection via ANN, XGBoost, and LightGBM, alongside the creation of derived behavioral risk variables. Consumer segmentation was executed using GMM, HDBSCAN, and Spectral clustering, with performance assessed through Silhouette scores, DBI, and CHI. The results identify key predictors such as tenure (Period), contract type, watch time, content count, subscription count, payment issues, and support tickets. These findings align with brand loyalty and customer journey theories, where positive engagement increases switching costs, while issues with service recovery accelerate churn decisions. Derived features—including WatchTime_per_Content, Subscribed_Ratio, SupportTickets_per_Period and Churn_Risk—further enhanced classification granularity. Analysis showed that HDBSCAN provided the most balanced clustering (DBI = 1.782), while Spectral Clustering identified the highest-risk group (average Churn_Risk = 0.699). This research contributes to the field by synthesizing ensemble learning and hybrid clustering, expanding churn analysis to the streaming platform context, and providing a robust framework for proactive customer retention.

Does ESG Performance Affect the Cost of Debt of Listed Firms in ASEAN Countries?

Wanrapee Banchuenvijit — 2026-08-28

This study examines the effect of ESG performance on the cost of debt of 307 listed firms in ASEAN countries, namely Indonesia, Malaysia, Philippines, Singapore, and Thailand, during 2017–2023 with the total sample of 1,003 firm-year observations. This study employs random-effects panel regressions to test the impact of the overall ESG performance as well as its individual pillars, including environmental, social, and governance, on the borrowing costs of firms. In addition, the moderating role of firm size is also investigated. The empirical results show that, among ESG performance measurements, only lagged governance pillar score negatively affects the cost of debt at the statistical significance level of 0.05, indicating that creditors in ASEAN selectively incorporate ESG information into lending decisions by emphasizing more on governance than on environmental and social performance. Regarding control variables, foreign direct investment positively associates with the borrowing costs at 0.01 significant level, demonstrating that extensive foreign direct investment inflows may lead to greater competition for financial resources. Consequently, the cost of debt financing is higher. Moreover, country dummy variables and the cost of debt are significantly related at 0.01 level. Firms in Indonesia experience higher interest rates than comparable firms in Thailand (the reference country), whereas firms in Singapore encounter lower interest rates than comparable firms in Thailand. This finding shows that country-level institutional environments are still important factors in determining corporate borrowing costs in ASEAN. Furthermore, firm size does not moderate the relationship between ESG performance and the cost of debt, representing that the influence of ESG performance on borrowing costs does not differ between large and small firms. This study not only adds to the existing sustainable finance literature by investigating the cost of debt in ASEAN countries, but also encourage managers, lenders, and policymakers in emerging markets to execute sustainable financing practices.

The Development of a Potential Model for Digital Industry Executives to Enhance Competitiveness in the Artificial Intelligence Era

Jutamas Thanthikul — 2026-08-28

The objectives of this research were to study the essential components, develop a potential model, and establish a development manual for the potential of digital industry executives to enhance competitiveness in the Artificial Intelligence (AI) era. This study employed the real-time Delphi technique 3 round and focus group discussions as the primary research methodologies. The target groups included 22 experts in digital business management, alongside two specialized panels: 1) a group of 14 experts for the focus group evaluation of the model, and 2) a group of 5 experts for the manual assessment. Qualitative data were analyzed using content analysis, while quantitative data were processed using median and interquartile range (IQR) statistics. The research findings revealed that the developed potential model for digital industry executives consists of 4 dimensions and 12 core components. Dimension 1: Knowledge (K) includes 3 components: K1) Digital and AI Technology, K2) Digital Organization Management, and K3) Strategic Management. Dimension 2: Skill (S) includes 3 components: S1) Strategic Decision-Making, S2) Leadership, and S3) Application. Dimension 3: Attribute (A) includes 3 components: A1) Adaptability and Resilience, A2) Ethics, Morality, and Human Relations, and A3) Innovative Thinking. Dimension 4: Management (M) includes 3 components: M1) Resource Management, M2) Strategic Planning, and M3) Digital Organizational Management and Communication. The results of the model evaluation by the 14 experts indicated that the model is highly appropriate. Furthermore, the development manual, which consists of 4 development guidelines, received unanimous approval from the 5 evaluating experts, confirming its suitability and practical applicability for the professional development of digital industry executives.