Causal Relationship of Integrated Marketing Communications and Technology Acceptance Model Influence on Purchase Intention of Digital Lottery Tickets via the Paotang Mobile Financial Transaction Application of Krung Thai Bank - Jonburee, Chiraborn; Khlaikhaek, Saringkhan (Ph.D. in Social Sciences Journal, 2026)
This research article aimed to (1) study the direct influence of integrated marketing communication on the purchase intention of digital lottery tickets via the Paotang application through Krungthai Bank. and (2) study the direct influence of the technology acceptance model on the purchase intention of digital lottery tickets through the Paotang application via Krungthai Bank. This study employed a quantitative research approach using questionnaires to collect data from 213 consumers aged 20 years and above who purchased digital lottery tickets through the Paotang mobile application via Krung Thai Bank financial transaction services. The sample was selected using multi-stage sampling. The statistical methods used for data analysis consisted of descriptive statistics, including frequency, percentage, mean, and standard deviation, and inferential statistics, including factor analysis, path analysis, and structural equation modeling (SEM). Findings are as follows: integrated marketing communication (IMC) had a positive and statistically significant direct effect on consumers’ intention to purchase digital lottery tickets at the .001 significance level, with a standardized path coefficient (β) of .456, thereby supporting Hypothesis 1 (H1). In addition, the Technology Acceptance Model (TAM) exerted a positive and statistically significant direct effect on purchase intention at the .001 significance level, with a standardized path coefficient (β) of .473, thus supporting Hypothesis 2 (H2). Collectively, integrated marketing communication and the Technology Acceptance Model explained 72.1% of the variance in consumers’ intention to purchase digital lottery tickets (R² = .721). Furthermore, the hypothesized structural model demonstrated a good fit with the empirical data. The model fit indices were as follows: χ² = 35.4, df = 28, p = .159, χ²/df = 1.26, CFI = .998, TLI = .993, NFI = .989, SRMR = .027, and RMSEA = .035.