Chatbots in the frontline: drivers of acceptance

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 pur...

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Published in:Kybernetes 2023-09, Vol.52 (9), p.3781-3810
Main Authors: Aslam, Wajeeha, Ahmed Siddiqui, Danish, Arif, Imtiaz, Farhat, Kashif
Format: Article
Language:English
Subjects:
Acceptance
Artificial intelligence
Automation
Chatbots
Consumers
Customer services
Motivation
Privacy
Robots
Service industries
Service robots
Technology
Technology Acceptance Model
Technology adoption
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cited_by cdi_FETCH-LOGICAL-c350t-b012b70c8f52711d732717dae605a332fb364a3e5f4e052c2d5f256f2c4428b03
cites cdi_FETCH-LOGICAL-c350t-b012b70c8f52711d732717dae605a332fb364a3e5f4e052c2d5f256f2c4428b03
container_end_page 3810
container_issue 9
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container_title Kybernetes
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creator Aslam, Wajeeha
Ahmed Siddiqui, Danish
Arif, Imtiaz
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description 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.
doi_str_mv 10.1108/K-11-2021-1119
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subjects Acceptance
Artificial intelligence
Automation
Chatbots
Consumers
Customer services
Motivation
Privacy
Robots
Service industries
Service robots
Technology
Technology Acceptance Model
Technology adoption
title Chatbots in the frontline: drivers of acceptance
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