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ORIGINAL RESEARCH

How Does Interactivity Shape Users’ Continuance Intention of Intelligent Voice Assistants? Evidence from SEM and fsQCA

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Pages 867-889 | Received 04 Sep 2023, Accepted 12 Feb 2024, Published online: 04 Mar 2024
 

Abstract

Purpose

With the rapid expansion in the use of intelligent voice assistants (IVAs) in people’s daily lives, how to improve users’ continuous intention is crucial for the sustainable development of intelligent voice technology. Utilizing the stimulus-organism-response (S-O-R) framework, we propose a theoretical model to examine how three dimensions of interactivity (ie, two-way communication, responsiveness, perceived control) impact individuals’ affective reactions (ie, psychological ownership, subjective well-being) and continuance intention of IVAs and how that effect differs technology readiness.

Methods

To validate the proposed model, 412 valid samples were collected in China and underwent analysis using a comprehensive approach that incorporated partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA).

Results

The findings from the PLS-SEM analysis indicate that three dimensions of interactivity have significant impacts on affective reactions to varying degrees, thus affecting users’ continuance intention. Among these dimensions, responsiveness is the strongest predictor of affective reactions. Additionally, the impact of subjective well-being on continuance intention is stronger when users with high technology readiness. Finally, the results from fsQCA support the PLS-SEM findings and provide three configurations with different combinations of antecedents that sufficiently explain high continuance intention.

Conclusion

Our findings reveal the internal mechanisms through which the three dimensions of interactivity impact users’ continued usage of IVAs. This study is among the first to examine the effects of dimensions of interactivity on behavioral intentions, utilizing both symmetric (PLS-SEM) and asymmetric (fsQCA) methodologies to identify the most significant dimensions of interactivity and determine sufficient combinations of dimensions to predict users’ intention to continue using IVAs. These findings offer valuable and fresh insights for both theoretical understanding and practical application.

Ethics Statement

This study involving human participants has been approved by the ethics committee at Chongqing University, China. We confirm that all participants were provided with comprehensive information about the purpose and procedures of the study before their involvement and gave informed consent in line with the principles outlined in the Declaration of Helsinki. Confidentiality and anonymity were maintained for all participants, and their data was protected throughout the study.

Acknowledgments

The authors thank the editor and the reviewers for their constructive feedback through the review process. We gratefully acknowledge the support received for this work from the National Natural Science Foundation of China (Grant Nos, 72110107002 and 71974021), and the National Social Science Foundation of China (Grant Nos. 23AGL042 and 21BGL246).

Author Contributions

All the authors have collectively made substantial contributions to the research project. This includes contributions in areas such as conceptualization, study design, execution, data acquisition, analysis, and interpretation. All authors were actively involved in drafting, revising, and critically reviewing the article. They have provided final approval for the version that will be published and have agreed on the target journal for submission. Furthermore, all authors accept responsibility for the entirety of the content presented in the work.

Disclosure

The authors report no conflicts of interest in this work.