Adoption of ChatGPT in Thailand: Exploring the Impact of Service Quality and Technology Acceptance on Workplace Stress Using Hybrid Artificial Neural Network and Structural Equation Modelling

The rapid adoption of AI technologies such as ChatGPT has generated significant discussions regarding their applications and implications across various sectors. In developing countries like Thailand, the integration of such technologies is still in its early stages. This study explores the factors influencing ChatGPT adoption in Thailand, focusing on service quality and Technology Acceptance Model (TAM) constructs using a hybrid approach combining Artificial Neural Network (ANN) and Structural Equation Modeling (SEM). The research examines how service quality dimensions (tangibility, reliability, responsiveness, assurance, and empathy) impact user attitudes, perceived usefulness, perceived ease-of-use, and the intention to use ChatGPT. Understanding how to effectively use ChatGPT in the workplace can help reduce stress levels. Employees familiar with its capabilities can enhance productivity, streamline workflows, and feel more confident in their responsibilities, alleviating anxiety about adapting to new tools and minimizing fears of technology replacement. The study addresses key gaps in the literature by focusing on a developing country context, where empirical research on AI adoption is limited. Data from 530 ChatGPT users in Thailand were collected through online surveys using snowball sampling. The findings reveal that user attitudes significantly mediate the relationship between service quality and the intention to use ChatGPT. Service quality also directly influences perceived usefulness and perceived ease-of-use, which subsequently affect user attitudes and behavioral intentions. The hybrid analytical approach of combining ANN with SEM improves the predictive accuracy of the model, offering nuanced insights into AI adoption. This research contributes theoretically by expanding the TAM framework to incorporate service quality dimensions, presenting a comprehensive model for AI-driven service adoption. Practically, it provides actionable recommendations for policymakers and service providers in Thailand and similar developing contexts to improve service quality and user engagement. Future research could explore cultural factors and adopt mixed-method approaches to gain deeper insights into user experiences with AI technologies like ChatGPT.