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The influence of different types of system feedback on the trust and acceptance of voice assistants

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Application possibilities of voice assistants are rapidly increasing. However, users interact with voice assistants primarily for simple, low-risk tasks, such as setting timers, checking the weather forecast and retrieving the daily news. For high-risk or more resource consuming tasks, such as online shopping and hotel bookings, users still prefer graphical user interfaces. Meanwhile, smart speakers with screen components, such as the Echo Show, are also available. This master thesis studies the influence of various feedback types (acoustic, dual) on the trust and technology acceptance in the context of voice assistants. This research is based on a mix of methods, including literature research, online survey, and usability test. Examining usage preferences, trust in different feedback types and the intention to use voice assistants, this work in particular focusses on the comparison of Echo Dot and Echo Show. The study indicates that when using voice assistants, the level of risk involved in the task is likely to have a higher impact on trust than the type of feedback. Exclusively when performing high-risk tasks, a visual feedback component shows beneficial influence on the level of trust. A coherence between the type of feedback and technology acceptance cannot be observed. However, the results of this study suppose a correlation between the level of trust and the intention to use voice assistants.
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