There is a significant need to change people’s travel mode from personal cars to public rail, because rail transport is a more environmentally friendly travel mode. Over the past decade, the number of rail passengers has reduced because of service quality problems. Thus, this study aims to propose guidelines for precise service quality (SQ) improvements of intercity rail services in Thailand. Data were collected from 615 train passengers by distributing questionnaires at train stations in six provinces, covering all regions of Thailand. Cluster analysis (CA), factor analysis (FA), and importance-performance analysis (IPA) were applied in this research, which were used based on gap analysis. As a result of CA and FA, the 45 quality indicators were grouped into four factors, namely, vehicles, staff, services, and infrastructures/stations. The FA results seem more appropriate than those of CA in terms of providing factor loadings that indicate the importance of each indicator. The results of IPA show that the seven indicators that were analyzed fell into the “concentrate here” quadrant. To summarize the current policy, the factor most in need of rapid improvement in order to increase the quality of the intercity rail service in Thailand is that of the train car variables group; on the other hand, the main strength of the current services relates to the services provided by staff.

The aviation industry has grown rapidly worldwide and is struggling against intense competition. Especially in Thailand, the compound annual growth rate of passengers traveling by air has increased continuously over the past decade. Unfortunately, during the past two years, the ongoing COVID-19 pandemic has caused severe economic crises for nearly all businesses and industries, including the aviation industry and especially for passenger airlines whose number of customers has decreased astoundingly due to travel restriction. To maintain business stability, therefore, airlines must build customer loyalty to survive in times of crisis. This study thus examines critical factors’ impact on airline loyalty by using a Bayesian network (BN) derived from a structural equation modeling (SEM). The study integrates the SEM and BN to refine causal relationships between critical factors, identified as critical pathways. Findings reveal that customer satisfaction and customer trust, followed by perceived value, dramatically influence customer loyalty and so are considered priorities for building airlines’ customer loyalty. This study also recommends practical strategies and policies to improve customer loyalty amid the competitive airline business during and after the COVID-19 era.

This study explores the influence of Thai government policy perceptions on the adoption of electric vehicles (EVs). Transitioning to EVs is vital for reducing greenhouse gas emissions and combating climate change, aligning with global sustainability goals. This study addresses gaps in understanding how multidimensional perceptions of government policies influence EV adoption intentions in emerging markets, particularly in Thailand. A questionnaire was distributed to 3770 respondents across Thailand between January and March 2024. The survey assessed multiple dimensions of government policy, including commitment and efficiency, welfare, communication, policy effectiveness, and tax benefits. Using statistical techniques such as Exploratory Factor Analysis (EFA), second-order confirmatory factor analysis (CFA), and structural equation modeling (SEM), this study validated the constructs of government support perception and examined their influence on EV adoption intentions. The findings highlight that tangible government policies, particularly those improving EV infrastructure and providing clear regulatory support, alongside effective communication about these policies, significantly influence public willingness to adopt EVs. The results also emphasize the critical role of perceived government commitment and fiscal incentives in shaping consumer decisions. Based on these insights, this study recommends prioritizing the expansion of EV infrastructure, enhancing the visibility of government commitment, and improving direct financial incentives to accelerate EV adoption. These findings contribute to the growing body of knowledge on EV adoption in emerging markets and offer practical implications for policymakers seeking to promote sustainable transportation solutions.