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- W2904798144 abstract "Prior research has shown that both advice generated through algorithms and advice resulting from averaging peers’ input can impact users’ decision-making. However, it is not clear which advice type is more closely followed and if changes in decision-making should be attributed to the source or the content of the advice. We examine the effects of algorithmic and social advice on decision-making in the context of an online retirement saving system. By varying both the advice’s message and the attributed messenger, we assess what it is about the advice that people follow. We find that both types of advice have a positive effect on users’ saving performance, and that users follow advice presented as coming from an algorithmic source more closely than advice presented as crowdsourced. Our results shed light on how people view and follow online advice, and on information systems’ persuasive effects under conditions of uncertainty." @default.
- W2904798144 created "2018-12-22" @default.
- W2904798144 creator A5007172071 @default.
- W2904798144 creator A5012800294 @default.
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- W2904798144 date "2018-10-02" @default.
- W2904798144 modified "2023-10-14" @default.
- W2904798144 title "The Persuasive Power of Algorithmic and Crowdsourced Advice" @default.
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- W2904798144 doi "https://doi.org/10.1080/07421222.2018.1523534" @default.
- W2904798144 hasPublicationYear "2018" @default.
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