调查电商市场中引导向关联卖家的助推行为：以 Amazon 为例
Investigating Nudges toward Related Sellers on E-commerce Marketplaces: A Case Study on Amazon
AI总结：
本文审计 Amazon 四国市场的默认报价、卖家指标与展示特征，发现差异化绩效评估和评分数量会隐性助推顾客选择关联卖家，而修正指标可使其偏好近乎减半。
摘要：
电商市场为全球数百万卖家提供了商业机会。其中一些卖家因使用市场的附属服务（例如市场提供的履约和/或运输服务）而与市场存在特殊关系——我们将这类卖家统称为关联卖家（Related Sellers）。当多个卖家提出销售同一产品时，市场会通过以下方式帮助顾客选择（某个卖家的）报价：（a）默认报价选择算法；（b）展示每个报价及相应卖家的特征（价格、卖家绩效指标、卖家评分数量等）；以及（c）最终依据这些特征评估卖家。本文中，我们对上述机制如何在 Amazon 位于印度、美国、德国和法国的四个不同市场中把顾客助推向关联卖家进行了端到端调查。我们发现，在面对明确选择时，顾客偏好的报价与算法选择的报价可能存在显著差异。我们强调，Amazon 正对不同卖家采用不同的绩效指标评估政策，这可能使关联卖家受益。例如，此类政策导致关联卖家的实际绩效指标与展示给顾客的绩效指标之间出现明显差异。我们进一步观察到，在顾客可见的以卖家为中心的特征中，卖家的评分数量对其决策影响最大，但该特征未必反映卖家真实的服务质量，而是反映卖家的经营规模，从而隐性地引导顾客转向规模更大的关联卖家。此外，当向顾客展示不同卖家经过修正的指标时，他们对关联卖家的偏好几乎减半。
英文摘要：
E-commerce marketplaces provide business opportunities to millions of sellers worldwide. Some of these sellers have special relationships with the marketplace by virtue of using their subsidiary services (e.g., fulfillment and/or shipping services provided by the marketplace) -- we refer to such sellers collectively as Related Sellers. When multiple sellers offer to sell the same product, the marketplace helps a customer in selecting an offer (by a seller) through (a) a default offer selection algorithm, (b) showing features about each of the offers and the corresponding sellers (price, seller performance metrics, seller's number of ratings etc.), and (c) finally evaluating the sellers along these features. In this paper, we perform an end-to-end investigation into how the above apparatus can nudge customers toward the Related Sellers on Amazon's four different marketplaces in India, USA, Germany and France. We find that given explicit choices, customers' preferred offers and algorithmically selected offers can be significantly different. We highlight that Amazon is adopting different performance metric evaluation policies for different sellers, potentially benefiting Related Sellers. For instance, such policies result in notable discrepancy between the actual performance metric and the presented performance metric of Related Sellers. We further observe that among the seller-centric features visible to customers, sellers' number of ratings influences their decisions the most, yet it may not reflect the true quality of service by the seller, rather reflecting the scale at which the seller operates, thereby implicitly steering customers toward larger Related Sellers. Moreover, when customers are shown the rectified metrics for the different sellers, their preference toward Related Sellers is almost halved.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
