Citation

Frough, Eid Mohammad (2026) Understanding customer perceptions of AI chatbots in Malaysian F&B SMES: Trust, use, and satisfaction. PhD thesis, Multimedia University.

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Abstract

Artificial Intelligence (AI) chatbots are increasingly transforming customer engagement strategies in the food and beverages industry. Despite their growing prevalence, there is limited understanding of the factors influencing their adoption in the food and beverage sector in Malaysia, particularly among cafes and coffee shops, and how this adoption affects customer satisfaction. This research aims to investigate the factors that drive or inhibit the adoption of AI chatbots in Malaysian coffee shops and to assess the impact on customer satisfaction. Adapted by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Privacy Calculus Model, this study examines constructs such as trust, perceived usefulness, privacy concerns, behavioral intention, actual use, and customer satisfaction. A quantitative research method is employed, utilizing a structured survey distributed to customers in cafes and coffee shops across Malaysia. The study surveyed customers in Malaysia using a nonprobability sampling method. A total of 595 valid responses collected. The collected data was analyzed using descriptive and Partial Least Squares Structural Equation Modeling (PLS-SEM). The novel contribution of this study lies in the structural integration of the UTAUT2 and Privacy Calculus models through trust as a mediating mechanism, extending the traditional adoption model to incorporate actual use and customer satisfaction within the context of Malaysian F&B SMEs. The analysis of the results shows that except Facilitating Conditions to Behavioral Intention, each proposed relationship is significant. Performance Expectancy, Effort Expectancy, Hedonic Motivation, Habit, Perceived Benefit, and Trust positively affected customers' behavioral intention, and Perceived Privacy Risk negatively affected trust. Behavioral Intention and Actual Use were significantly predictive of Customer Satisfaction. Moreover, variables such as Age and Experience were not supported as hypothesized, meaning that users who were young and more experienced were more amenable to using the chatbots.

Item Type:	Thesis (PhD)
Additional Information:	Call No.: HD45 .F76 2026
Uncontrolled Keywords:	Artificial intelligence—Business applications
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD45-45.2 Technological innovations. Automation
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	05 Oct 2026 04:33
Last Modified:	05 Oct 2026 04:33
URII:	http://shdl.mmu.edu.my/id/eprint/16870

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