Chatbots in the frontline: drivers of acceptance

Abstract

PurposeBy extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.Design/methodology/approachBy using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.FindingsFindings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.Practical implicationsThe study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.Originality/valueThis is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.

Modeling Students’ Perceptions of Chatbots in Learning: Integrating Technology Acceptance with the Value-Based Adoption Model

“…Other studies have yielded similar results, such as [28,35,36,60,61,74]. In addition, Kumar and Silva [55] found that perceived ease of use (expected effort) positively affects students' attitudes toward accepting the use of chatbots in learning, as did many other studies [16,35,52,60,61,74]. Regarding the factor of attitude, several studies indicate that students' attitudes toward chatbots are a main predictor of their acceptance and use behavior [22,35,52,56,59,75].…”

“…For example, Chen et al [31] confirm in their study that the perceived usefulness (expected benefit) of chatbots positively affects students' attitudes toward chatbot acceptance and use behavior in learning. Other studies have yielded similar results, such as [28,35,36,60,61,74]. In addition, Kumar and Silva [55] found that perceived ease of use (expected effort) positively In the context of chatbot use in education, the TAM is by far the most used model for investigating both students' and teachers' perceptions of chatbot use in learning [31,62].…”

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