经济观察报 记者 陈月芹 2025年9月12日20时，苹果iPhone17系列开启预售。同一时间，拼多多推出百亿补贴活动，用户每逢整点抢券，使用优惠券下单苹果新品最多可减900元。 9月13日，不少用户在社交媒体上发帖"iPhone17被砍单"，称收到拼多多方的退单退款通知，依据为"该商品为限购商品，此订单因账号或收货信息被系统判 定不符合发货条件，已全额退款"。 消费者完成网购支付后，商家或平台单方面取消订单的行为，会被消费者形容为"砍单"，常由商品缺货、价格异常、风控系统判定风险等因素引发。 据经济观察报了解，为了打击"黄牛"等批量下单百亿补贴限购商品，让更多用户享受优惠福利，保障用户合法权益，拼多多内部有一套算法模型用于识别异 常账户。针对部分可能被系统"误伤"的用户，拼多多已协调客服与用户作进一步沟通。 "下单成功"不意味着购买成功 一名被"砍单"的消费者称，自己使用常用的拼多多账户、常用的收货地址下单，只买一台自用，付款成功12小时后仍被强制取消订单。他多次咨询拼多多官 方客服"不符合发货条件"的具体依据是什么，客服仅回复"由于咨询量较大，将尽快安排专员处理"。 受优惠券驱动，9月12日晚，有消费者 ...

Core Viewpoint - The rapid growth of e-commerce platforms has led to an increase in fraudulent activities, exposing vulnerabilities in information sharing, rule design, and technical defenses of these platforms [1][2]. Group 1: Fraudulent Activities - Criminals have exploited e-commerce platform loopholes through various scams, including "buy new, return old" schemes and "high-priced listings" for fake transactions [1][2]. - A specific case involved individuals purchasing luxury goods, marking them up, and then using the platform's return policy to profit from the price difference [1][2]. - The Shanghai People's Procuratorate reported that these fraudulent activities occurred over a hundred times, resulting in significant financial losses [1]. Group 2: Platform Vulnerabilities - The return review mechanism of the platforms is inadequate, allowing users to exploit the "worry-free return" policy for profit [2][3]. - Criminals have shown sophistication in their methods, including researching legal loopholes and collaborating to manipulate platform rules [2][3]. - The platforms rely heavily on automated systems for return processing, which lack strict scrutiny of product quality and model, leading to undetected fraudulent activities [3][4]. Group 3: Recommendations for Improvement - The procuratorial authorities have suggested implementing a dynamic monitoring system using big data and AI to identify suspicious high-priced listings and unusual return behaviors [4][5]. - Recommendations include optimizing return policies, setting limits on return frequencies, and enhancing credit rating systems for high-frequency return accounts [4][5]. - Establishing an information-sharing mechanism between platforms to track product flow and ensure the authenticity of transactions is also advised [5].