EXAMINING DIGITAL MARKETERS’ INTENTION AND USAGE OF GEN AI IN INDONESIA WITH UTAUT FRAMEWORK
Description
Using extended UTAUT framework, this study aims to explore factors which influence digital marketers’ intentions to use Gen AI, as well as its actual usage, particularly in Indonesia. By examining the relationships between performance expectations, effort expectations, social influence, facilitating conditions, perceived threat of job, technology self-efficacy, and perceived risk on digital marketers' intentions to use Gen AI, this study aims to provide a comprehensive understanding of the elements shaping Gen AI adoption in digital marketing in Indonesia. We gathered 246 respondents from which are digital marketers from big cities in Indonesia (mostly domiciled in Java Island), with convenient sampling as our method. Our specific criteria is employees who handle digital marketing jobs and at least have used Gen AI for their work, from various industries in Indonesia. Questionnaires are spread with the help of social media and researchers connections. The proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The questionnaire utilizes a five-point likert scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree) to assess key variables. Specifically for Gen AI usage, the scale will be used with 8-point likert (1 = Never, 2 = Once a month, 3 = Several times a month, 4 = Once a week, 5 = Several times a week, 6 = Once a day, 7 = Several times a day, 8 = Once an hour, 9 = Several times an hour, 10 = All the time). Following the principles from the sampling and measurement design framework, this scale provides an interval level of measurement, allowing statistical testing of the hypothesized relationships within the UTAUT framework. Based on the results, Behavioral Intention (BI) has the strongest total effect on Gen AI Usage (GU) with coefficient of determination 0.509, confirming that intention is the main predictor of actual Gen AI use among digital marketers. In addition, Performance Expectancy (PE), Social Influence (SI), Perceived Threat of Job (PJ) and Technology Self-Efficacy (TS), and Perceived Risk (PR) give weaker but still considerable effect with coefficient of determination > |0.1|. On the other hand, Effort Expectancy (EE), Facilitating Condition (FC), Perceived Risk (PR), and moderation of Voluntary Usage (VU) give insignificant effects.
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Institutions
- Binus UniversityJakarta, Jakarta