To be precise (imprecise) in utilitarian (hedonic) contexts: Examining the influence of numerical precision on consumer reactions to artificial intelligence‐based recommendations
通过四项实验发现，当AI推荐使用精确（不精确）数字时，消费者在功利（享乐）消费情境中更可能做出积极反应，且这一匹配效应受推荐者类型和消费者对AI与人类推荐者的朴素信念调节。
Abstract The precision of artificial intelligence (AI)‐generated information has been suggested in the past as a method of nudging consumers' evaluations and intentions, but little is known about whether such effects are also context‐sensitive. Based on four studies, we find a matched condition under which consumers are more likely to make a positive response when precise (imprecise) numbers presented by AI recommenders are used in a utilitarian (hedonic) consumption context (Study 1). Additionally, we show that consumer conceptual fluency also mediates this matching effect on consumer purchase decision‐making (Studies 2). We further show the matching effect is moderated by the recommender type (Study 3) and consumer lay beliefs about the AI and human recommenders (Study 4). This study shows that when consumers' lay belief changes from “AI performs objective tasks well” and “Human performs subjective tasks well” to “AI performs subjective tasks well” and “Human performs objective tasks well,” it can change the difference in the matching relationship between human and AI recommenders.