Systematic Literature Review: The Use of SEM in Business and Social Sciences – Insights from ABAC Journal 2021–2024

Kittipong Napontun, Worawalan Sophachit, Prarawan Senachai — Fri, 23 May 2025 00:00:00 +0000

Structural Equation Modeling (SEM) is a crucial analytical instrument in business and social sciences, allowing researchers to examine intricate correlations between observable and latent variables while reducing measurement errors. This study conducts a systematic literature review (SLR) of SEM-related research published in the ABAC Journal from 2021 to 2024. The review classifies research articles according to their application domains, estimating techniques, software utilization, theoretical frameworks, and geographical study sites. Research indicates that SEM is mostly employed in marketing, management, travel and tourism, finance, human resource management, education, accounting, and economics. Maximum Likelihood Estimation (MLE) is the predominant method, followed by Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Integrated Generalized Structured Component Analysis (IGSCA). AMOS and SmartPLS are identified as the favored SEM software. The research underscores the growing utilization of hybrid SEM methodologies, which combine factor-based and component-based models to enhance analytical flexibility. These findings offer significant insights for researchers and practitioners, assisting them in choosing suitable SEM approaches according to research aims and data attributes. Future research should investigate the use of IGSCA and conduct comparative assessments of various SEM estimate techniques across varied data situations to improve methodological progress in business and social science research.

PM2.5 Pollution, Retail Trading, and Stock Market Returns

Anya Khanthavit — Sat, 24 May 2025 00:00:00 +0000

PM_2.5 is a dangerous airborne pollutant. Its induced health and economic losses affect investors and stock markets worldwide. This study applies mediation analyses to examine the relationship of Bangkok’s PM_2.5 pollution with Thai stock market returns, where retail trading serves as a mediator. Investors are unaware of the actual PM_2.5 level, therefore, the PM_2.5 level is a perceived level, not an actual level. Perception is measured by Google’s relative search volume index on “PM 2.5”. It is decomposed into correct perception (actual PM_2.5 level) and misperception (regression residual of the full perception on the correct perception). Using a daily sample from August 1, 2016, to December 28, 2023, the generalized method of moments regression uncovered a negative and significant relationship. The main contributor was found to be the mediating effect of retail net buying volume induced by misperception. Further investigation suggests that this relationship is consistent with the noise-trader-risk explanation.