User Behaviors, Engagement, and Consequences

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Paper Number

1186

Paper Type

Completed

Description

The increasing application of Conversational Agents (CAs) is rapidly changing the way customers access services. In practice, however, CAs are frequently flawed, such as they often misinterpreting users’ requests. Even through future advancements in technology, it remains unlikely that a CA will be flawless and error-free. Thus, understanding how to design CAs so that users are more willing to overlook errors constitutes an important area of research. In this regard, our study positions the human-like design of CAs as a potential way to ensure service satisfaction when errors occur. We examined the effect of human-like designed flawed CAs by conducting a two-condition experiment with 421 participants, analyzing its effect on users’ emotional state and service satisfaction. Our results show that the human-like design of flawed CAs leads to more positive emotions, which improve users’ service satisfaction. Therefore, designers should adopt a human-like design to prevent dissatisfaction with flawed CAs.

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Dec 12th, 12:00 AM

“Even the Wisest Machine Makes Errors” – An Experimental Investigation of Human-like Designed and Flawed Conversational Agents

The increasing application of Conversational Agents (CAs) is rapidly changing the way customers access services. In practice, however, CAs are frequently flawed, such as they often misinterpreting users’ requests. Even through future advancements in technology, it remains unlikely that a CA will be flawless and error-free. Thus, understanding how to design CAs so that users are more willing to overlook errors constitutes an important area of research. In this regard, our study positions the human-like design of CAs as a potential way to ensure service satisfaction when errors occur. We examined the effect of human-like designed flawed CAs by conducting a two-condition experiment with 421 participants, analyzing its effect on users’ emotional state and service satisfaction. Our results show that the human-like design of flawed CAs leads to more positive emotions, which improve users’ service satisfaction. Therefore, designers should adopt a human-like design to prevent dissatisfaction with flawed CAs.

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