Determinants of Behavioral Intention to Use Mobile Applications in Thailand

Abstract

Background and Objectives: The objective of this study is to pinpoint and examine the major factors impacting intention to use mobile apps in Thailand by integrating insights from the Technology Acceptance Model 2 (TAM2), the Technology Acceptance Model 3 (TAM3), the Unified Theory of Acceptance and Use of Technology (UTAUT), and its extension UTAUT2. The key causes of Behavioral Intention (BI) to use mobile applications in Thailand are realized, focusing on Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Trust (TR), Hedonic Motivation (HM), Price Value (PV), and Habit (HB) as critical factors. The goal is to deliver actionable perceptions for developers and businesses to enhance their applications, thereby improving adoption rates and overall user satisfaction in the Thai market.

Methodology: This research used a quantitative methodology to assess the behavioral desire to utilize mobile apps in Thailand. Data were collected from 655 participants within Thailand’s tech-savvy community. Using a 5-point Likert scale to measure responses allowed for a thorough statistical analysis using Structural Equation Modeling (SEM). While the sample was concentrated in urban and tech-centric regions such as Bangkok and Chiang Mai, it also included participants from diverse geographic and demographic backgrounds, offering comparative insights into digital adoption across Thailand.

Main Results: The findings indicate that PE (β = 0.35), HM (β = 0.31), and FC (β = 0.28) were the best predictors of BI, while EE, TR, PV, SI, and HB also had statistically significant positive impacts. Additionally, the research confirms the significant effect of socio-demographic control variables—including gender, age, income, and education—with mobile app usage frequency exhibiting the highest coefficient (β = 0.32). The need for a multidimensional approach to mobile strategy is highlighted by these findings. The study contributes empirical evidence guiding developers and marketers to create targeted, intuitive, and secure applications that resonate with diverse user needs, thereby sustaining long-term engagement and strengthening adoption in Thailand's digital market.

Discussions: Thai users specifically favor applications that improve productivity, are user-friendly, and are influenced by social recommendations, highlighting the importance of peer influence and word-of-mouth. Trust in the app’s security and the availability of necessary resources also emerged as critical factors, particularly for mobile banking and e-commerce. Demographic analysis indicates that younger, more affluent users and students are more inclined to use mobile apps, with regular app engagement being strongly linked to the type of application (e.g., social media and e-commerce).

Conclusions: The inferences drawn from this research help to improve our understanding of mobile apps and their patterns of use in a fast-changing digital world, offering useful advice for companies and developers who want to improve user interaction and app design for Thai market. This research expands on the findings of earlier studies by highlighting the TR component of the UTAUT2 framework as a crucial factor, emphasizing its contextual significance in Thailand’s mobile application environment, which is constantly changing in response to worries about privacy and security.