Role of interaction quality and trust in use of AI-based voice-assistant systems

Abstract

PurposeThe rapid growth of artificial intelligence (AI)-based voice-assistant systems (VASs) has created many opportunities for individuals to use VASs for various purposes in their daily lives. However, traditional quality success factors, such as information quality and system quality, may not be sufficient in explaining the adoption and use of AI-based VASs. This study aims to propose interaction quality as an additional, yet more important quality measure that leads to trust in an AI-based VAS and its adoption. Design/methodology/approachThe authors propose a research model that highlights the importance of interaction quality and trust as underlying mechanisms in the adoption of AI-based VASs. Based on survey methodology and data from 221 respondents, the proposed research model is tested with a partial least squares approach. FindingsThe results suggest that interaction quality and trust are critical factors influencing the adoption of AI-based VASs. The findings also indicate that the impacts of traditional quality factors (i.e. information quality and system quality) occur through interaction quality in the context of AI-based VASs. Originality/valueThis research adds interaction quality as a new quality factor to the traditional quality factors in the information systems success model. Further, given the interactive nature of VASs, the authors use social response theory to explain the importance of the trust mechanism when individuals interact with AI-based VASs. Contribution to Impact

Inducing AI-powered chatbot use for customer purchase: the role of information value and innovative technology

“…Though these conceptions are quite distinct, they all suggest that AI is an attempt to create machines capable of executing intelligent tasks. AI is booming today (Lee et al , 2021) and is being touted as an efficient tool in different areas, namely, banking (Eren, 2021), human resource management (Kshetri, 2021), tourism and hospitality (Go et al , 2020) and online retailing (Chen et al , 2021).…”

Task type's effect on attitudes towards voice assistants

“…Naturally, researchers have attempted to identify the characteristics that enhance VAs' trustworthiness. Some notable characteristics include the ability to display emotions, personalities and social capabilities (Hamacher et al, 2016; Lee et al, 2021; Qiu & Benbasat, 2005).…”

A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures

“…As it stands, people report not using voice assistants for a broad range of tasks, even though they're technically capable of doing so [27]. Prior work has illustrated the importance of trust for continued voice assistant use [31,35], as trust is pivotal to user adoption of voice assistants [33,45] and willingness to broaden the scope of voice assistant tasks [27]. It is especially important to support trust-building between users and voice assistants as researchers continue to imagine and develop new capabilities for them, including complex tasks such as supporting healthcare tasks [41,55], giving mental health advice [52,66], and other high stakes decision-making [17].…”

“…Prior researchers have examined trust in machines in terms of people's confidence in a machine's ability to perform as expected, benevolence (well-meaning), and integrity to adhere to ethical standards [36] Broadly, past research has evaluated how various factors such as accuracy and errors affect people's trust in algorithms [19,20,67]. In the case of voice assistants, Nasirian et al [45] and Lee et al [33] studied how quality affects trust in and adoption of voice assistants, and found that information and system quality did not impact users' trust in a voice assistant, but interaction quality did. Interaction quality was captured based on a study by Ekinci and Dawes [22], in which Likert scale responses were captured regarding competence, attitude, service manner, and responsiveness of the voice assistant.…”