Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants

Artificial intelligence agents (chatbots), which are programs to communicate with users primarily in customer service contexts, are an alternative interaction channel supporting businesses in the digital environment and vital components in customer service. The present empirical paper, which is aime...

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Main Authors: Gatzioufa Paraskevi, Vaggelis Saprikis, Giorgos Avlogiaris
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Human Behavior and Emerging Technologies
Online Access:http://dx.doi.org/10.1155/2023/8859989
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author Gatzioufa Paraskevi
Vaggelis Saprikis
Giorgos Avlogiaris
author_facet Gatzioufa Paraskevi
Vaggelis Saprikis
Giorgos Avlogiaris
author_sort Gatzioufa Paraskevi
collection DOAJ
description Artificial intelligence agents (chatbots), which are programs to communicate with users primarily in customer service contexts, are an alternative interaction channel supporting businesses in the digital environment and vital components in customer service. The present empirical paper, which is aimed at identifying and discussing the factors motivating nonusers to adopt the specific technology in mobile contexts, proposes a comprehensive conceptual model, which combines the UTAUT 2 behavioral theory with variables of mobile service quality contexts, such as information quality, privacy concerns, interface, and equipment, as well as trust and mobility factors. Data analysis, based on the partial least squares structural equation modeling (PLS-SEM) statistical method, revealed that performance expectancy, facilitating factors, hedonic motivation, mobility, trust, and service quality positively affect nonusers’ behavioral intention to adopt chatbots. In addition, equipment, interface, and trust have a significant impact on users’ trust in the context of mobile chatbots. Personal data privacy issues also have a negative effect on trust, in contrast to effort expectancy, which positively affects performance expectancy. As mobile service quality factors have not been investigated before in the context of chatbots, the findings of the present research are expected to provide useful insights both to academia and the business industry.
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institution Kabale University
issn 2578-1863
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publishDate 2023-01-01
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spelling doaj-art-1887e091e6764be7a7fc3d4d139645df2025-02-03T05:57:01ZengWileyHuman Behavior and Emerging Technologies2578-18632023-01-01202310.1155/2023/8859989Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality DeterminantsGatzioufa Paraskevi0Vaggelis Saprikis1Giorgos Avlogiaris2Department of Management Science and TechnologyDepartment of Management Science and TechnologyDepartment of Statistics and Insurance ScienceArtificial intelligence agents (chatbots), which are programs to communicate with users primarily in customer service contexts, are an alternative interaction channel supporting businesses in the digital environment and vital components in customer service. The present empirical paper, which is aimed at identifying and discussing the factors motivating nonusers to adopt the specific technology in mobile contexts, proposes a comprehensive conceptual model, which combines the UTAUT 2 behavioral theory with variables of mobile service quality contexts, such as information quality, privacy concerns, interface, and equipment, as well as trust and mobility factors. Data analysis, based on the partial least squares structural equation modeling (PLS-SEM) statistical method, revealed that performance expectancy, facilitating factors, hedonic motivation, mobility, trust, and service quality positively affect nonusers’ behavioral intention to adopt chatbots. In addition, equipment, interface, and trust have a significant impact on users’ trust in the context of mobile chatbots. Personal data privacy issues also have a negative effect on trust, in contrast to effort expectancy, which positively affects performance expectancy. As mobile service quality factors have not been investigated before in the context of chatbots, the findings of the present research are expected to provide useful insights both to academia and the business industry.http://dx.doi.org/10.1155/2023/8859989
spellingShingle Gatzioufa Paraskevi
Vaggelis Saprikis
Giorgos Avlogiaris
Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
Human Behavior and Emerging Technologies
title Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
title_full Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
title_fullStr Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
title_full_unstemmed Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
title_short Modeling Nonusers’ Behavioral Intention towards Mobile Chatbot Adoption: An Extension of the UTAUT2 Model with Mobile Service Quality Determinants
title_sort modeling nonusers behavioral intention towards mobile chatbot adoption an extension of the utaut2 model with mobile service quality determinants
url http://dx.doi.org/10.1155/2023/8859989
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AT vaggelissaprikis modelingnonusersbehavioralintentiontowardsmobilechatbotadoptionanextensionoftheutaut2modelwithmobileservicequalitydeterminants
AT giorgosavlogiaris modelingnonusersbehavioralintentiontowardsmobilechatbotadoptionanextensionoftheutaut2modelwithmobileservicequalitydeterminants