讲座题目：Purchase-choice Algorithmic Recommendation in a Distribution Channel
主讲嘉宾：朱思远
时间：2025年10月27日（星期一）下午14:00—16:00
地点：商学院109会议室
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江南大学商学院
2025年10月21日
主讲嘉宾简介
朱思远，2024年2月加入江苏大学，讲师。研究方向：信息设计、平台运营。2023年6月毕业于中国科学技术大学管理学院，获得管理学博士学位，华盛顿大学（西雅图）联合培养博士。主持国家自然科学基金一项、江苏省社会科学基金一项。论文发表在European Journal of Operational Research (ABS4星)、International Journal of Electronic Commerce (ABS3星)、 Journal of the Operational Research Society (ABS3星)、Computers & Industrial Engineering (ABS2星)、Electronic Commerce Research and Applications (ABS2星)、Managerial and Decision Economics(ABS2星)等领域内国际主流期刊。
讲座主要内容
Digital platforms increasingly sell visibility and personalized exposure through sponsored listings and paid recommendations, making an algorithmic recommendation not only an information device but also a costly strategic instrument for retailers. This practice motivates our study of how paid recommendation interacts with pricing, consumer beliefs, and welfare in a distribution channel. We develop a two-stage model in which a retailer first commits to a price schedule and a recommendation rule, and then, after quality is realized, decides whether to buy a costly, type-specific recommendation that alters consumers’ posteriors. The analysis shows that adoption follows a quality threshold: the retailer purchases a recommendation only when product quality is high enough. When a recommendation is adopted, pricing becomes type-dependent, and in some regimes the retailer charges lower prices to high-preference buyers while charging higher prices to marginal buyers, a pattern of reverse price discrimination. Profit and welfare effects are non-monotonic: retailer and manufacturer profits improve only when quality and placement costs lie in favorable ranges, while consumer surplus changes unevenly across segments. These findings provide a tractable framework to study the strategic role of paid recommendation and offer practical insight for retailers deciding when to invest in recommendation services in a distribution channel.
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