Options
Disentangling Trust in Voice Assistants - A Configurational View on Conversational AI Ecosystems
Journal
Annual Meeting of the Academy of Management (AOM)
Type
conference paper
Date Issued
2023
Author(s)
Research Team
IWI6
Abstract
Voice assistants’ (VAs) increasingly nuanced and natural communication via artificial intelligence (AI) opens up new opportunities for the experience of users, providing task assistance and automation possibilities, and also offer an easy interface to digital services and ecosystems. However, VAs and according ecosystems face various problems, such as low adoption and satisfaction rates as well as other negative reactions from users. Companies, therefore, need to consider what contributes to user satisfaction of VAs and related conversational AI ecosystems. Key for conversational AI ecosystems is the consideration of trust due to their agentic and pervasive nature. Nonetheless, due to the complexity of conversational AI ecosystems and different trust sources involved, we argue that we need a more detailed understanding about trust. Thus, we propose a configurational view on conversational AI ecosystems that allows us to disentangle the complex and interrelated factors that contribute to trust in VAs. We examine with a configurational approach and a survey study, how different trust sources contribute to the outcomes of conversational AI ecosystems, i.e., in our case user satisfaction. The results of our study show four distinct patterns of trust source configurations. Vice versa, we show how trust sources contribute to the absence of the outcome, i.e., user satisfaction. The derived implications provide a configurative theoretical understanding for the role of trust sources for user satisfaction that provides practitioners useful guidance for more trustworthy conversational AI ecosystems.
Language
English
Keywords
Voice Assistants
Conversational AI Ecosystems
Trust
Agentic Information
Systems
HSG Classification
contribution to scientific community
Publisher place
Boston, Massachusetts, USA
Event Title
Annual Meeting of the Academy of Management (AOM)
Event Location
Boston, Massachusetts, USA
Event Date
04-08 Aug 2023
Subject(s)
Division(s)
Eprints ID
270063