I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents

•This study proposes an analytical framework combining the expectation-confirmation model (ECM), information system success (ISS) model, TAM, and the need for interaction with a service employee.•Analysis of data reveals that information quality and service quality positively influence consumers’ sa...

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Veröffentlicht in:Telematics and informatics Jg. 54; S. 101473
Hauptverfasser: Ashfaq, Muhammad, Yun, Jiang, Yu, Shubin, Loureiro, Sandra Maria Correia
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.11.2020
Elsevier Science Ltd
Schlagworte:
Artificial intelligence
Chatbots
Client satisfaction
Consumers
Continuance intention
Conversation
Customer satisfaction
Customer service
Customer services
Data quality
ECM
Employees
Human-computer interaction
Information
Intelligence tests
ISS model
Job satisfaction
Quality of service
Satisfaction
Service industries
TAM
The need for interaction
Usefulness
User satisfaction
The need for interaction
TAM
Continuance intention
Satisfaction
Chatbots
ISS model
ECM
ISSN:0736-5853, 1879-324X
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Zusammenfassung:•This study proposes an analytical framework combining the expectation-confirmation model (ECM), information system success (ISS) model, TAM, and the need for interaction with a service employee.•Analysis of data reveals that information quality and service quality positively influence consumers’ satisfaction, and that perceived enjoyment, perceived usefulness, and perceived ease of use are significant predictors of continuance intention.•The findings further show that the need for interaction with a service employee moderates the effects of perceived ease of use and perceived usefulness on satisfaction. Chatbots are mainly text-based conversational agents that simulate conversations with users. This study aims to investigate drivers of users’ satisfaction and continuance intention toward chatbot-based customer service. We propose an analytical framework combining the expectation-confirmation model (ECM), information system success (ISS) model, TAM, and the need for interaction with a service employee (NFI-SE). Analysis of data collected from 370 actual chatbot users reveals that information quality (IQ) and service quality (SQ) positively influence consumers’ satisfaction, and that perceived enjoyment (PE), perceived usefulness (PU), and perceived ease of use (PEOU) are significant predictors of continuance intention (CI). The need for interaction with an employee moderates the effects of PEOU and PU on satisfaction. The findings also revealed that satisfaction with chatbot e-service is a strong determinant and predictor of users’ CI toward chatbots. Thus, chatbots should enhance their information and service quality to increase users’ satisfaction. The findings imply that digital technologies services, such as chatbots, could be combined with human service employees to satisfy digital users.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0736-5853
1879-324X
DOI:10.1016/j.tele.2020.101473