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This paper aims to investigate the motivating factors for Malaysian governmental agencies (MGAs) to embrace chatbot technology.

Based on the technology-organisation-environment (TOE) framework, using purposive and snowball sampling techniques, 262 online data from the MGA top management were gathered. Smart PLS4 was employed to test the hypotheses of the study.

The findings demonstrated positive relationships between technological readiness (TR), big data analytics (BDA), organisational readiness (OR), organisational learning capabilities (OLC) and governmental policies (GP) concerning chatbot adoption intention and also the relationship GP with OR. A mediating effect was also observed, which indicated the OLC role in positively mediating BDA, the OR role in positively mediating OLC and the OR role in positively mediating GP with OR and OLC as sequential mediators in the relationship between BDA and chatbot adoption intention. Furthermore, the presence of citizen demand (CD) strengthened the relationship between TR, OR and chatbot adoption intention.

This study was limited to Malaysian federal government agencies who still not adopting Chatbots.

The findings offer valuable insight into factors affect the adoption of chatbots among Malaysian government agencies. Stakeholders, including department heads, can use these findings to strategically enhance counter service by promoting chatbot adoption.

The study demonstrated that the TOE framework was effective in identifying the factors contributing to the decision-making process for adopting chatbots across MGAs. Organisational readiness and organisation learning capability was found to sequentially mediate the relationship between big data analytic and intention to adopt chatbot. Citizen demand was found to have moderation effect on the relationship between organisational readiness and technological readiness towards the intention to adopt a chatbot.

There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise in demand for products from the gourmet industry, little is known regarding the factors that inspire customers to order from online FDAs, subsequently influencing customers’ satisfaction. Considering the knowledge gap, this study utilizes the stimulus-organism-response (S-O-R) model to conceptualize the factors: stimuli (eWOM, online reviews and online deals as external stimuli, and late-night craving and convenience as internal stimuli) that determine the organism level (i.e. customers’ inspiration) to subsequently generate the response (i.e. customers’ satisfaction).

We collected the data from 388 users and analyzed it via partial least squares – structural equation modeling (PLS-SEM).

The results reveal that online reviews, deals, late-night food cravings and convenience positively determine customers’ inspiration and satisfaction. In contrast, eWOM fails to impact customers’ inspiration directly and indirectly, affecting customers’ satisfaction through inspiration. Besides, customers’ inspiration positively mediates the relationship between stimuli (e.g. online reviews, online deals, late-night cravings and convenience) and customers’ satisfaction.

This study is novel in that it explores the impact of internal (late-night craving and convenience) and external (eWOM, online reviews and online deals) stimuli on customer inspiration and subsequently predicts customer satisfaction. We also expand prior studies on food delivery apps by studying customer inspiration as a mediating mechanism between internal and external stimuli and customer satisfaction.