Risk Minimizing Price-Rebate-Return Contracts in Supply Chains With Ordering and Pricing Decisions: A Multimethodological Analysis

供应链 利润(经济学) 乘法函数 微观经济学 计算机科学 供求关系 业务 经济 营销 精算学 数学 数学分析
作者
Chun‐Hung Chiu,Hau‐Ling Chan,Tsan‐Ming Choi
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:67 (2): 466-482 被引量:40
标识
DOI:10.1109/tem.2018.2882843
摘要

In recent years, we have witnessed the wide implementation of many sophisticated supply contracts in the industry, such as the price, rebate, and return (P2R) contract. The P2R contract is offered by the manufacturer to the retailer. In this paper, a practice-based approach is adopted in which we first report the use of P2R contracts in the real world from industrial interviews. Based on the meanings of risk as revealed from the interviews, we proceed to construct analytical models and derive the minimum risk coordinating P2R (PMR*) contract, which yields the minimum level of risk for the manufacturer and coordinates the supply chain. We analytically show that the manufacturer's expected profit is increasing with the return price and the rebate value under the PMR* contract. We reveal that different risk measurements may lead to different PMR* contracts. In particular, when the price-dependent demand distribution takes the additive form, we interestingly find that the manufacturer can become riskfree in coordinating the supply chain with the PMR * contract; however, it is not the case for the multiplicative case. Furthermore, we observe that the demand distribution's shape affects the setting of the PMR * contract. Managerial implications are also discussed.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
秋山伊夫完成签到,获得积分10
1秒前
入门的橙橙完成签到 ,获得积分10
1秒前
BONBON发布了新的文献求助10
2秒前
4秒前
TOM完成签到,获得积分10
4秒前
隐形曼青应助欣喜访旋采纳,获得10
5秒前
852应助Millie采纳,获得10
5秒前
龍Ryu完成签到,获得积分10
6秒前
内向凌兰发布了新的文献求助10
7秒前
伍秋望完成签到,获得积分10
7秒前
8秒前
9秒前
跳跃发布了新的文献求助10
10秒前
持卿应助宗磬采纳,获得20
10秒前
10秒前
花生油炒花生米完成签到 ,获得积分10
10秒前
Riki完成签到,获得积分10
12秒前
虚幻白玉发布了新的文献求助10
12秒前
德行天下完成签到,获得积分10
12秒前
Jenny应助lan采纳,获得10
13秒前
fztnh完成签到,获得积分10
13秒前
上官若男应助lyz666采纳,获得10
13秒前
顾念完成签到 ,获得积分10
13秒前
277发布了新的文献求助10
14秒前
小二郎应助GCD采纳,获得10
15秒前
hhhhhh完成签到 ,获得积分10
15秒前
甜味拾荒者完成签到,获得积分10
17秒前
小二郎应助BONBON采纳,获得10
17秒前
18秒前
charllie完成签到 ,获得积分10
18秒前
空禅yew完成签到,获得积分10
19秒前
坚强亦丝应助跳跃采纳,获得10
21秒前
英俊的铭应助cc采纳,获得10
21秒前
huangsan完成签到,获得积分10
21秒前
匹诺曹完成签到,获得积分10
21秒前
22秒前
华仔应助进取拼搏采纳,获得10
22秒前
23秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808