A stochastic model for optimizing crowdfunding campaign success

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-05-07 DOI:10.1016/j.orl.2025.107303

Sylvie Chaddad , Yezekael Hayel , Vineeth S. Varma

引用次数: 0

Abstract

Crowdfunding is popular among entrepreneurs who aim to bypass classical funding channels and directly address the crowd via Internet-based Crowdfunding platforms. This work introduces a model to enhance crowdfunding by strategically managing friends and family (F&F) investments. It studies the impact of timely F&F funds on total raised amounts, employing offline and online policy strategies. The offline method aims at maximizing expected investment, while the online uses Markov Decision Processes (MDPs) to improve success probability.

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优化众筹活动成功的随机模型

众筹受到企业家的欢迎，他们希望绕过传统的融资渠道，通过互联网众筹平台直接面向人群。这项工作引入了一个模型，通过战略性地管理朋友和家人（F&；F）投资来增强众筹。本文采用线下和线上两种策略，研究了及时融资对总融资额的影响。离线方法以期望投资最大化为目标，在线方法利用马尔可夫决策过程（mdp）提高成功概率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.