通过自适应广告排序优化用户粘性

IF 4 2区管理学 Q2 BUSINESS

Marketing Science Pub Date : 2023-09-01 DOI:10.1287/mksc.2022.1423

Omid Rafieian

引用次数: 0

摘要

本文开发了一个离线强化学习框架，用于识别和评估优化用户参与度的广告排序策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Optimizing User Engagement Through Adaptive Ad Sequencing

This paper develops an offline reinforcement learning framework that identifies and evaluate the ad sequencing policy that optimizes user engagement.

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来源期刊

Marketing Science BUSINESS-

CiteScore

8.60

自引率

10.00%

发文量

期刊介绍： Marketing Science is a publication of the Institute for Operations Research and the Management Sciences (INFORMS) publication (SSCI indexed). We invite authors to submit for peer review their best marketing-oriented research. We accept many types of manuscripts. Please consider us as an author-friendly outlet for your research. We are THE premier journal focusing on empirical and theoretical quantitative research in marketing. Marketing Science promises to provide constructive, fair, and timely reviews with the goal of identifying the best submissions for publication. Topics covered in Marketing Science include the following: -Advertising- Buyer Behavior- Channels- Competitive Strategy- Forecasting- Marketing Research- New Product Development- Pricing and Promotions- Sales Force Management- Segmentation- Services Marketing- Targetability.