Decoding User Intentions Towards AI Chatbot Services Under the Impact of Social Influences
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Artificial intelligence chatbot services (AICSs) have become more popular than ever in the current scenario despite much debate about their positives and negatives. This study aims to explore the links between social influences (SIs) related to community views, opinions, and the environment that affects individuals' transformation of their hedonic motivation (HM) and expectations (CEs), shedding light on their intention to continue using AICSs. Via a deductive approach and mixed methods, a cross-sectional study was conducted to evaluate the measurement and structural models with the participation of 332 university students in South Vietnam through an online survey (using Google Forms). Partial least squares structural equation modelling (PLS-SEM) was applied in this study. Research findings show that social influence (SIs) have positive impacts on HM, CEs (including performance and effort expectations), and behavioural intention toward AICS usage (BI). CEs and HM play intermediary roles in the relationship between SIs and BI. Notably, customer habit (HBT) has adverse moderating effects on relationships such as “SI and CEs” and “HM and BI,” clarifying customer experience about their intention to continue using AICSs in the current context. As a result, the research findings are expected to provide significant theoretical and practical implications for AI service managers and developers.
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