Optimal Salesforce Compensation with General Demand and Operational Considerations

Haotian Song, Guoming Lai, Wenqiang Xiao
{"title":"Optimal Salesforce Compensation with General Demand and Operational Considerations","authors":"Haotian Song, Guoming Lai, Wenqiang Xiao","doi":"10.1287/msom.2022.0400","DOIUrl":null,"url":null,"abstract":"Problem definition: We investigate the optimal salesforce compensation scheme in the context of private information and unobservable actions, considering common operational factors encountered in practice, including inventory costs, contractible versus censored demand information, and controlled versus delegated ordering. Methodology/results: Based on an agency model with general demand and cost functions, we derive optimality conditions for implementable contracts that can achieve the second-best outcome in all scenarios. The contracts are in the forms of a menu with linear compensation for demand or sales, incorporating inventory costs. Moreover, the contracts feature adjustments in compensation corresponding to the ordering level if it is delegated. Managerial implications: Our study reveals that, under reasonably mild conditions, optimal salesforce contracts can still maintain relatively simple forms, even when confronted with common operational factors and generalized demand and cost functions. However, the contracts must be tailored to suit the operational settings. Intriguingly, neither the loss of demand information nor the delegation of inventory decisions would compromise system efficiency at optimum.Funding: H. Song is partially supported by the Key International Cooperation and Exchange Projects of the NSFC [Grant W2411062] and the Foundation for Innovative Research Groups of the NSFC [Grant 71821002].Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0400 .","PeriodicalId":501267,"journal":{"name":"Manufacturing & Service Operations Management","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Manufacturing & Service Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/msom.2022.0400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Problem definition: We investigate the optimal salesforce compensation scheme in the context of private information and unobservable actions, considering common operational factors encountered in practice, including inventory costs, contractible versus censored demand information, and controlled versus delegated ordering. Methodology/results: Based on an agency model with general demand and cost functions, we derive optimality conditions for implementable contracts that can achieve the second-best outcome in all scenarios. The contracts are in the forms of a menu with linear compensation for demand or sales, incorporating inventory costs. Moreover, the contracts feature adjustments in compensation corresponding to the ordering level if it is delegated. Managerial implications: Our study reveals that, under reasonably mild conditions, optimal salesforce contracts can still maintain relatively simple forms, even when confronted with common operational factors and generalized demand and cost functions. However, the contracts must be tailored to suit the operational settings. Intriguingly, neither the loss of demand information nor the delegation of inventory decisions would compromise system efficiency at optimum.Funding: H. Song is partially supported by the Key International Cooperation and Exchange Projects of the NSFC [Grant W2411062] and the Foundation for Innovative Research Groups of the NSFC [Grant 71821002].Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0400 .
考虑到一般需求和运营因素的最佳 Salesforce 补偿方案
问题定义:考虑到实践中常见的运营因素,包括库存成本、可收缩需求信息与可删减需求信息,以及受控订货与委托订货,我们研究了在私人信息和不可观察行动背景下的最优销售人员补偿方案。方法/结果:基于具有一般需求和成本函数的代理模型,我们推导出了可执行合同的最优条件,这些合同在所有情况下都能实现次优结果。这些合同采用菜单形式,对需求或销售进行线性补偿,并包含库存成本。此外,如果委托订货,合同的特点是根据订货水平调整补偿。管理意义:我们的研究表明,在相当温和的条件下,即使面对共同的运营因素和广义的需求与成本函数,最优的销售队伍合同仍能保持相对简单的形式。然而,合同必须量身定制,以适应运营环境。耐人寻味的是,无论是需求信息的损失还是库存决策的委托,都不会影响系统的最佳效率:H. Song 的研究得到了国家自然科学基金委重点国际合作与交流项目[批准号:W2411062]和国家自然科学基金委创新研究群体基金[批准号:71821002]的部分资助:在线附录见 https://doi.org/10.1287/msom.2022.0400 。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信