标题： 社会学习中的逆反动机：非从众偏好的信息级联 显示英文标题

标题： Contrarian Motives in Social Learning: Information Cascades with Nonconformist Preferences

摘要： 我们将非 conformism 的倾向嵌入到一个标准的 Bikhchandani-Hirshleifer-Welch 社会学习模型中。代理既重视正确性，也重视选择少数派行动（固定或基于比例的奖励）。我们研究了外生信号和内生获取，在一个高斯二次设定下，具有固定的进入成本和精确度的凸成本。反叛动机将均衡阈值从 1/2 移开，并扩大了信息被购买的信念区域，维持了有信息的动作；在投资的情况下，接近中心信念时选择的精确度较低。福利由一种权衡决定：轻微的反叛抵消了过早的从众，而强烈的反叛则使行动与有信息的社会信号相违背，并导致低价值的实验。一个易于处理的特征给出了闭式阈值、比较静态分析和透明的福利比较。应用包括科学优先竞赛和学术扩散，其中独特性产生租金，但过度的反叛会削弱信息聚合。 显示英文摘要

摘要： We embed a taste for nonconformism into a canonical Bikhchandani-Hirshleifer-Welch social-learning model. Agents value both correctness and choosing the minority action (fixed or proportion-based bonus). We study exogenous signals and endogenous acquisition with a fixed entry cost and convex cost of precision in a Gaussian-quadratic specification. Contrarian motives shift equilibrium cutoffs away from 1/2 and expand the belief region where information is purchased, sustaining informative actions; conditional on investing, chosen precision is lower near central beliefs. Welfare is shaped by a trade-off: mild contrarianism counteracts premature herding, whereas strong contrarianism steers actions against informative social signals and induces low-value experimentation. A tractable characterization delivers closed-form cutoffs, comparative statics, and transparent welfare comparisons. Applications include scientific priority races and academic diffusion, where distinctiveness yields rents yet excessive contrarianism erodes information aggregation.