选择性偏差 / selection bias

「释义」

选择性偏差是指人们常常根据自己对特定事件的代表性观点，来估计某些事件发生的概率。这样人们可能错误地相信了“小数定律”，将一系列的负相关归因于一个确定的和独立分布的随机过程，从而出现偏差。

「应用场景」

你在网上写过评价吗？如果写过，当时为什么决定这么做？研究显示，用户往往会因为消费体验决定是否写评价。有些网站，消费者在获得满意体验时，更可能留言评价，有些则只在极度满意和极度不满的情况下，才会写评价。无论哪种情况，都会因选择性偏差，影响最终评分。这样的评价也许无法准确展现该产品用户体验全貌。比如，如果只有对产品满意的顾客留下评价，产品评分就会虚高。如果企业只鼓励满意的客户评价，选择性偏差的影响会更明显。

Have you ever written an online review? If so, what made you decide to comment on that particular occasion? Research has shown that users’ decisions to leave a review often depend on the quality of their experience. On some sites, customers may be likelier to leave reviews if their experience was good; on others, only if it was very good or very bad. In either case the resulting ratings can suffer from selection bias: They might not accurately represent the full range of customers’ experiences of the product. If only satisfied people leave reviews, for example, ratings will be artificially inflated. Selection bias can become even more pronounced when businesses nudge only happy customers to leave a review.

eBay在2011年遭遇过选择性偏差问题，发现卖家评分高得可疑：多数卖家的好评率超过99%。公司在经济学家克里斯·诺斯克和斯蒂文·泰迪利斯的帮助下，发现用户在获得满意体验后，更有可能写评价：在网站已完成的约4400万项交易中，只有0.39%获得差评或负分，但实际出现“争端”的人有两倍之多（1%），7倍以上（3%）的交易显示，买家曾联系卖家抱怨产品质量。实际上相比卖家得分，买家是否给卖家写评价的决定，能更好预测未来买家是否会投诉卖家，也能更好体现产品质量。

EBay encountered the challenge of selection bias in 2011, when it noticed that its sellers’ scores were suspiciously high: Most sellers on the site had over 99% positive ratings. The company worked with the economists Chris Nosko and Steven Tadelis and found that users were much likelier to leave a review after a good experience: Of some 44 million transactions that had been completed on the site, only 0.39% had negative reviews or ratings, but more than twice as many (1%) had an actual “dispute ticket,” and more than seven times as many (3%) had prompted buyers to exchange messages with sellers that implied a bad experience. Whether or not buyers decided to review a seller was in fact a better predictor of future complaints—and thus a better proxy for quality—than that seller’s rating.

以上文字选自《哈佛商业评论》中文版2019年12月刊《设计更优化的网络评价体系》

杰夫·唐纳克（GeoffDonaker）金炫进（Hyunjin Kim）迈克尔·卢卡（Michael Luca）丨文

马冰仑 丨编辑