AI-based Conversational Agents for Customer Service – A Study of Customer Service Representative' Perceptions Using TAM 2
Autor(en): | Sonntag, Martin Mehmann, Jens Teuteberg, Frank |
Stichwörter: | artificial intelligence; Conceptual research; conversational agents; customer service; Customer service representatives; Customer-service; Empirical studies; empirical study; Research models; Sales; Subjective norm; Survey data; TAM 2; Technology acceptance model; Technology acceptance model 2 | Erscheinungsdatum: | 2022 | Herausgeber: | Association for Information Systems | Journal: | 17th International Conference on Wirtschaftsinformatik, WI 2022 | Zusammenfassung: | This study aimed to identify the various factors that may influence customer service representatives' perceptions of artificial intelligence (AI)-based conversational agents (CAs) for customer service. By analyzing 180 publications, a conceptual research model is developed for identifying the factors that may influence customer service representatives' perceptions of AI-based CAs for customer service. The underlying conceptual research model comprises ten factors. The study is grounded in the application of the Technology Acceptance Model 2 (TAM 2) approach. The research model is empirically evaluated with survey data from 128 participants. Our results show that the direct positive effect of subjective norm on customer service representatives' perception of using AI-based CAs in customer service decreases with increasing experience. Moreover, our results reveal new insights regarding trust. The results of this study provide an overview of the predominant characteristics of the influencing factors of customer service representatives' perceptions of AI-based CAs for customer service. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved. |
Beschreibung: | Cited by: 2; Conference name: 17th International Conference on Wirtschaftsinformatik, WI 2022; Conference date: 21 February 2022 through 23 February 2022; Conference code: 191912 |
Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129945960&partnerID=40&md5=6e165c56248a36e3e0b9eedce0dba464 |
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