International Journal of Asian Social Science

Determinants of AI technologies adoption in Bangladeshi accounting firms: A PLS-SEM analysis using the TOE framework

2026-01-14T21:56:56-06:00

Artificial intelligence (AI) developments have produced cutting-edge technologies that offer significant potential for corporate transformation. This study examines the key factors influencing the adoption of AI-based accounting technologies by Bangladeshi accounting firms. The proposed research model is grounded in the Technology–Organization–Environment (TOE) framework, which provides a comprehensive perspective for analyzing adoption drivers across various contextual dimensions. A quantitative research approach was employed to gather data from 160 accounting professionals through an online survey. The study utilized Partial Least Squares (PLS), a statistical technique based on structural equation modeling (SEM), to achieve its objectives. Empirical results indicate that the adoption of AI accounting technology in Bangladeshi accounting firms is significantly affected by factors such as relative advantage, complexity, employees’ capabilities, and customer pressure. Conversely, factors like cost, financial resources, rivalry pressure, management support, and vendor support did not demonstrate a substantial impact within this context. The research highlights the technological, organizational, and environmental factors that influence the integration of AI-based accounting tools. Practical implications suggest that policymakers, vendors, and professionals should focus on reducing barriers and enhancing readiness for adoption. Overall, the study provides both empirical evidence and practical strategies to promote AI adoption in emerging economies.

Chip in behaviour modification in primary year two hyperactivity kids through signal card and good behaviour game token

2026-01-14T22:05:55-06:00

The purpose of this action research is to reduce ‘chipping behavior’ and talking without permission among Year 2 hyperactive children in a primary school in Kedah, Malaysia. This behavior is identified as a main challenge in classroom management because it interrupts the smooth flow of teaching and learning and can negatively influence the involvement of other students. This research employed a mixed design involving five hyperactive students as qualitative observation samples and 33 teachers as quantitative survey respondents. Two interventions were applied over a two-week period: the Signal Card strategy and the Good Behavior Game Token system. The results indicate that both interventions were effective in reducing talking without permission and improving students’ self-control, concentration, attention span, and overall classroom engagement. The teachers found the practicability of the interventions easy to implement and suitable for Year 2 students. The study suggests that the consistency of using positive reinforcement interventions must be supported by both teachers and families to sustain behavioral improvements over time and ensure long-term success. These results offer valuable insights into behavior management practices for young hyperactive students and reveal that simple, structured interventions can foster a more encouraging learning environment. The findings also propose the possible adaptability of the interventions across different classroom situations.

Macroeconomic determinants of China’s electromechanical exports to ASEAN: A gravity model analysis

2026-01-14T23:04:03-06:00

This study investigates the macroeconomic determinants of China's electromechanical product exports to ASEAN countries, focusing on how economic scale, exchange rates, trade costs, and trade facilitation measures influence bilateral trade flows. An extended gravity model is applied using panel data from 2010 to 2019, covering seven ASEAN countries (Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam). The analysis incorporates bilateral GDP, RMB real effective exchange rate, average tariffs, distance-weighted transportation costs, and a Trade Facilitation Index derived from Global Competitiveness Report data through Principal Component Analysis. The results reveal that ASEAN countries' GDP is the dominant driver of export flows, with an elasticity coefficient of 1.191, indicating that demand for technology-intensive products grows more than proportionally with economic development. Exchange rate appreciation positively affects exports through quality signaling effects, while trade costs exhibit complex relationships with export performance. Trade facilitation measures strengthen export competitiveness through complementarities with traditional macroeconomic factors, though their effects are secondary to macroeconomic fundamentals. By extending gravity model applications to technology-intensive exports within regional integration contexts, this research provides insights into the interaction of macroeconomic variables in determining trade flows. The findings suggest that policymakers in China and ASEAN should prioritize supporting economic capacity building, stabilizing exchange rates for high-end market positioning, reducing tariffs and transport costs, and improving customs efficiency and logistics systems to enhance bilateral trade cooperation.

Regional GDP as a moderator between intellectual capital and marketing performance: Evidence from Chinese SMEs

2026-01-14T23:14:44-06:00

Intellectual capital is a crucial driver of competitiveness; however, its role in shaping the marketing performance of small and medium-sized enterprises (SMEs) across diverse regional contexts remains insufficiently understood. This study utilizes survey data from 78 Chinese SMEs and employs partial least squares structural equation modeling (PLS-SEM) to examine the effects of five dimensions of intellectual capital on marketing performance. Additionally, it investigates the moderating role of regional gross domestic product (GDP). The results indicate that informational and structural capital significantly enhance marketing performance, whereas regional GDP does not exert a moderating effect. These findings suggest that internal intangible resources are more critical than external economic conditions in driving SME marketing success. The study extends research on intellectual capital to include SME and regional contexts and offers practical insights for prioritizing intangible assets within marketing strategies.

AI customer service and hidden triggers of burnout: Evidence from Malaysia’s e-commerce sector

2026-01-14T23:28:22-06:00

This study examines employee burnout in AI-integrated customer service roles within the Malaysian e-commerce sector, focusing on the influence of task shifting, organizational support, and perceived AI monitoring, grounded in the Job Demands-Resources model. A quantitative cross-sectional design was adopted, drawing on survey data collected from 172 employees working in customer service and related functions in medium-to-large e-commerce organizations located in the Klang Valley. The data were analyzed using descriptive statistics, reliability analysis, Pearson correlation, and multiple regression to assess the relationships between AI-related job demands, organizational resources, and burnout outcomes. The findings show that task shifting and perceived AI monitoring are significantly and positively associated with employee burnout, indicating higher levels of emotional exhaustion, disengagement, and reduced personal accomplishment when AI implementation is poorly managed. In contrast, organizational support exhibits a significant negative relationship with burnout, demonstrating its protective role in mitigating the adverse effects of increased job demands. Employees who reported access to adequate training, clearer communication, and responsive managerial support experienced lower levels of burnout despite exposure to AI-driven changes. The study offers practical implications for e-commerce organizations implementing AI in customer service functions, highlighting the need for structured task redistribution, transparent and non-intrusive monitoring practices, and sustained organizational support mechanisms. By adopting a human-centered approach to AI integration, organizations can balance operational efficiency with employee well-being, reduce burnout risks, and promote sustainable service performance in technology-intensive environments.