In this paper, we explore the design of web-based advice robots to enhance users' confidence in acting upon the provided advice. Drawing from research on algorithm acceptance and explainable AI, we hypothesise four design principles that may encourage interactivity and exploration, thus fostering users' confidence to act. Through a value-oriented prototype experiment and value-oriented semi-structured interviews, we tested these principles, confirming three of them and identifying an additional principle. The four resulting principles: (1) put context questions and resulting advice on one page and allow live, iterative exploration, (2) use action or change oriented questions to adjust the input parameters, (3) actively offer alternative scenarios based on counterfactuals, and (4) show all options instead of only the recommended one(s), appear to contribute to the values of agency and trust. Our study integrates the Design Science Research approach with a Value Sensitive Design approach.
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In this paper, we explore the design of web-based advice robots to enhance users' confidence in acting upon the provided advice. Drawing from research on algorithm acceptance and explainable AI, we hypothesise four design principles that may encourage interactivity and exploration, thus fostering users' confidence to act. Through a value-oriented prototype experiment and valueoriented semi-structured interviews, we tested these principles, confirming three of them and identifying an additional principle. The four resulting principles: (1) put context questions and resulting advice on one page and allow live, iterative exploration, (2) use action or change oriented questions to adjust the input parameters, (3) actively offer alternative scenarios based on counterfactuals, and (4) show all options instead of only the recommended one(s), appear to contribute to the values of agency and trust. Our study integrates the Design Science Research approach with a Value Sensitive Design approach.
DOCUMENT
Firms increasingly use social network sites to reach out to customers and proactively intervene with observed consumer messages. Despite intentions to enhance customer satisfaction by extending customer service, sometimes these interventions are received negatively by consumers. We draw on privacy regulation theory to theorize how proactive customer service interventions with consumer messages on social network sites may evoke feelings of privacy infringement. Subsequently we use privacy calculus theory to propose how these perceptions of privacy infringement, together with the perceived usefulness of the intervention, in turn drive customer satisfaction. In two experiments, we find that feelings of privacy infringement associated with proactive interventions may explain why only reactive interventions enhance customer satisfaction. Moreover, we find that customer satisfaction can be modeled through the calculus of the perceived usefulness and feelings of privacy infringement associated with an intervention. These findings contribute to a better understanding of the impact of privacy concerns on consumer behavior in the context of firm–consumer interactions on social network sites, extend the applicability of privacy calculus theory, and contribute to complaint and compliment management literature. To practitioners, our findings demonstrate that feelings of privacy are an element to consider when handling consumer messages on social media, but also that privacy concerns may be overcome if an intervention is perceived as useful enough.
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