隐藏在众目睽睽之下:动态定价和战略供应商

IF 4.8 3区 管理学 Q1 ENGINEERING, MANUFACTURING Production and Operations Management Pub Date : 2023-09-19 DOI:10.1111/poms.14064
Jiaru B. Bai, H. Sebastian Heese, Manish Tripathy
{"title":"隐藏在众目睽睽之下:动态定价和战略供应商","authors":"Jiaru B. Bai, H. Sebastian Heese, Manish Tripathy","doi":"10.1111/poms.14064","DOIUrl":null,"url":null,"abstract":"Abstract Many on‐demand service platforms employ surge pricing policies, charging higher prices and raising provider compensation when customer demand exceeds provider supply. There is increasing evidence that service providers understand these pricing policies and strategically collude to induce artificial supply shortages by reducing the number of providers showing as available online. We study a stylized mathematical model of a setting in which an on‐demand service platform determines its pricing and provider compensation policies, anticipating their impact on customer demand and the participation of strategic providers, who might collectively decide to limit the number of providers showing online as available. We find that collusion can substantially harm the platform and customers, especially when the potential demand is large, and the supply of providers in nearby regions is limited. We explore two pricing policies that a platform could employ in the presence of (potential) provider collusion: a bonus pricing policy that offers additional provider payments on top of the regular compensation and the optimal pricing policy that maximizes the platform's expected profit while taking strategic provider behavior fully into consideration. Both policies feature a compensation structure that ensures that total provider earnings increase in the number of providers available, thereby encouraging all providers to offer their service. We show that both policies can effectively mitigate the impact of potential provider collusion, with the bonus pricing policy often performing near‐optimally. As it might be difficult for a platform to accurately estimate the propensity of providers to collude, we numerically evaluate how platform profits are affected if the pricing policy is designed based on possibly incorrect estimates of the providers' propensity to collude. Our observations suggest that a platform should design its pricing policy under the assumption that all providers are strategic and consider collusion, as the losses associated with implementing such a policy in settings with minor risk of collusion are limited, while the potential losses from failing to consider rampant collusion can be significant.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"93 1","pages":"0"},"PeriodicalIF":4.8000,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hiding in plain Sight: Surge pricing and strategic providers\",\"authors\":\"Jiaru B. Bai, H. Sebastian Heese, Manish Tripathy\",\"doi\":\"10.1111/poms.14064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Many on‐demand service platforms employ surge pricing policies, charging higher prices and raising provider compensation when customer demand exceeds provider supply. There is increasing evidence that service providers understand these pricing policies and strategically collude to induce artificial supply shortages by reducing the number of providers showing as available online. We study a stylized mathematical model of a setting in which an on‐demand service platform determines its pricing and provider compensation policies, anticipating their impact on customer demand and the participation of strategic providers, who might collectively decide to limit the number of providers showing online as available. We find that collusion can substantially harm the platform and customers, especially when the potential demand is large, and the supply of providers in nearby regions is limited. We explore two pricing policies that a platform could employ in the presence of (potential) provider collusion: a bonus pricing policy that offers additional provider payments on top of the regular compensation and the optimal pricing policy that maximizes the platform's expected profit while taking strategic provider behavior fully into consideration. Both policies feature a compensation structure that ensures that total provider earnings increase in the number of providers available, thereby encouraging all providers to offer their service. We show that both policies can effectively mitigate the impact of potential provider collusion, with the bonus pricing policy often performing near‐optimally. As it might be difficult for a platform to accurately estimate the propensity of providers to collude, we numerically evaluate how platform profits are affected if the pricing policy is designed based on possibly incorrect estimates of the providers' propensity to collude. Our observations suggest that a platform should design its pricing policy under the assumption that all providers are strategic and consider collusion, as the losses associated with implementing such a policy in settings with minor risk of collusion are limited, while the potential losses from failing to consider rampant collusion can be significant.\",\"PeriodicalId\":20623,\"journal\":{\"name\":\"Production and Operations Management\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2023-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Production and Operations Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/poms.14064\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production and Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/poms.14064","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0

摘要

许多按需服务平台采用动态定价政策,当客户需求超过供应商供应时,收取更高的价格并提高供应商补偿。越来越多的证据表明,服务提供商了解这些定价政策,并在战略上串通起来,通过减少显示在线可用的服务提供商的数量,来诱导人为的供应短缺。我们研究了一个程式化的数学模型,其中一个按需服务平台决定其定价和供应商补偿政策,预测它们对客户需求和战略供应商参与的影响,他们可能共同决定限制在线显示可用的供应商数量。我们发现,合谋会对平台和客户造成实质性的伤害,特别是当潜在需求很大,而附近地区的供应商供应有限时。我们探讨了在存在(潜在)供应商勾结的情况下,平台可以采用的两种定价策略:一种是奖金定价策略,在常规补偿的基础上提供额外的供应商支付;另一种是最优定价策略,在充分考虑供应商战略行为的情况下,最大化平台的预期利润。这两项政策都以补偿结构为特色,确保供应商的总收入随着可用供应商数量的增加而增加,从而鼓励所有供应商提供服务。我们表明,这两种政策都可以有效地减轻潜在供应商勾结的影响,奖金定价政策通常执行接近最优。由于平台可能难以准确估计供应商的串通倾向,因此,如果定价政策是基于对供应商串通倾向可能不正确的估计而设计的,我们将从数字上评估平台利润是如何受到影响的。我们的观察表明,平台应该在假设所有供应商都是战略性的并考虑共谋的情况下设计其定价政策,因为在共谋风险较小的情况下实施此类政策所带来的损失是有限的,而不考虑猖獗的共谋所带来的潜在损失可能是巨大的。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Hiding in plain Sight: Surge pricing and strategic providers
Abstract Many on‐demand service platforms employ surge pricing policies, charging higher prices and raising provider compensation when customer demand exceeds provider supply. There is increasing evidence that service providers understand these pricing policies and strategically collude to induce artificial supply shortages by reducing the number of providers showing as available online. We study a stylized mathematical model of a setting in which an on‐demand service platform determines its pricing and provider compensation policies, anticipating their impact on customer demand and the participation of strategic providers, who might collectively decide to limit the number of providers showing online as available. We find that collusion can substantially harm the platform and customers, especially when the potential demand is large, and the supply of providers in nearby regions is limited. We explore two pricing policies that a platform could employ in the presence of (potential) provider collusion: a bonus pricing policy that offers additional provider payments on top of the regular compensation and the optimal pricing policy that maximizes the platform's expected profit while taking strategic provider behavior fully into consideration. Both policies feature a compensation structure that ensures that total provider earnings increase in the number of providers available, thereby encouraging all providers to offer their service. We show that both policies can effectively mitigate the impact of potential provider collusion, with the bonus pricing policy often performing near‐optimally. As it might be difficult for a platform to accurately estimate the propensity of providers to collude, we numerically evaluate how platform profits are affected if the pricing policy is designed based on possibly incorrect estimates of the providers' propensity to collude. Our observations suggest that a platform should design its pricing policy under the assumption that all providers are strategic and consider collusion, as the losses associated with implementing such a policy in settings with minor risk of collusion are limited, while the potential losses from failing to consider rampant collusion can be significant.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Production and Operations Management
Production and Operations Management 管理科学-工程:制造
CiteScore
7.50
自引率
16.00%
发文量
278
审稿时长
24 months
期刊介绍: The mission of Production and Operations Management is to serve as the flagship research journal in operations management in manufacturing and services. The journal publishes scientific research into the problems, interest, and concerns of managers who manage product and process design, operations, and supply chains. It covers all topics in product and process design, operations, and supply chain management and welcomes papers using any research paradigm.
期刊最新文献
Complementarity analysis of a multi‐item inventory model with leading product pricing The impact of COVID‐19 on supply chain credit risk Physician Practice Migration and Changes in Practice Style: An Empirical Analysis of Inappropriate Diagnostic Imaging in Primary Care Extraction of visual information to predict crowdfunding success Supply chain short‐term financing for responsible production at small and medium‐sized enterprises
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1