Scalable methodology for supply chain inventory coordination with private information

2009 ◽  
Vol 195 (1) ◽  
pp. 262-279 ◽  
Author(s):  
Chi-Leung Chu ◽  
V. Jorge Leon
Keyword(s):  
Supply Chain ◽  
Private Information ◽  
Inventory Coordination

scholarly journals The Incentive Model in Supply Chain with Trade Credit and Default Risk

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Hong Cheng ◽  
Yingsheng Su ◽  
Jinjiang Yan ◽  
Xianyu Wang ◽  
Mingyang Li
Keyword(s):  
Supply Chain ◽  
Asymmetric Information ◽  
Moral Hazard ◽  
Private Information ◽  
Default Risk ◽  
Trade Credit ◽  
Uncertain Demand ◽  
Market Demand ◽  
Incentive Contract ◽  
Risk Neutral

Trade credit is widely used for its advantages. However, trade credit also brings default risk to the manufacturer due to the uncertain demand. And moral hazard may aggravate the default risk. The purpose of this paper is to investigate the role of moral hazard in trade credit and explore incentive contract under uncertain demand and asymmetric information. We consider a two-echelon supply chain consisting of a risk-neutral retailer ordering a single product from a risk-neutral manufacturer. Market demand is stochastic and is influenced by retailer’s sales effort which is his private information. Incentive theory is used to develop the principal-agent model and get the incentive contract from the manufacturer’s perspective. Results show that the retailer will reduce his effort level to get more profit and the manufacturer’s profit will be reduced, in the case of asymmetric information. Facing this result, the manufacturer will reduce the order quantity in incentive contract to lessen his losses. Numerical examples are provided to illustrate all these theoretical results and to draw managerial insights.

Supply Chain Inventory Coordination under Uncertain Demand via Combining Monte Carlo Simulation and Fitness Inheritance PSO

2015 ◽  
Vol 6 (1) ◽  
pp. 1-22
Author(s):  
Heting Cao ◽  
Xingquan Zuo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Distribution Function ◽  
Supply Chain ◽  
Simulation Model ◽  
Uncertain Demand ◽  
Computational Time ◽  
Arbitrary Distribution ◽  
Demand Distribution ◽  
Inventory Coordination

Supply chain coordination consists of multiple aspects, among which inventory coordination is the most widely used in practice. Inventory coordination is challenging due to the uncertainty of customers' demand. Existing researches typically assume that the demand is either a deterministic constant or a stochastic variable following a known distribution function. However, the former cannot reflect the practical costumers' demand, and the later make the model inaccurate when the demand distribution is ambiguous or highly variable. In this paper, the authors propose a Monte Carlo simulation model of such problem, which can mimic the inventory changing procedure of a supply chain with uncertain demand following an arbitrary distribution function. Then, a PSO is combined with the simulation model to achieve a coordination decision scheme to minimize the total inventory cost. Experiments show that their approach is able to produce a high quality solution within a short computational time and outperforms comparative approaches.

scholarly journals The Reward-Penalty Mechanism in a Closed-Loop Supply Chain with Asymmetric Information of the Third-Party Collector

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Wenbin Wang ◽  
Jia Lv ◽  
Ni An ◽  
Jie Guan ◽  
Shiyuan Quan
Keyword(s):  
Supply Chain ◽  
Asymmetric Information ◽  
Private Information ◽  
Closed Loop ◽  
Third Party ◽  
Closed Loop Supply Chain ◽  
Effort Level ◽  
The Third ◽  
The Third Party ◽  
Buy Back

This paper investigates the reward-penalty mechanism (RPM) implemented by the government in a closed-loop supply chain (CLSC) with asymmetric information. The manufacturer produces and sells products to consumers, while the collection of waste electrical and electronic equipment (WEEE) is delegated to the third-party collector, the one who has private information about the collection effort level. An information screening contract for the manufacturer is put forward to obtain the private information from the third-party collector, which is composed of buy-back price and franchise fee. By utilizing principal-agent theory, two cases are mainly examined including the CLSC without the RPM and the CLSC with the RPM. The results demonstrate that (i) the information screening contract is effective in capturing the collector’s collection effort level, (ii) raising the buy-back price to motivate the third-party collector is confirmed to perform well on enhancing the collection quantity from consumers, (iii) H-type collector collects more WEEEs and earns more profits than L-type collector, and (iv) the RPM improves the collection quantity of the enterprise and reaps more environmental benefits. The numerical results verify the validity of the contract and the feasibility of the RPM.

scholarly journals Incentive Strategies for Low-Carbon Supply Chains with Asymmetric Information of Carbon Reduction Efficiency

2018 ◽  
Vol 15 (12) ◽  
pp. 2736 ◽  
Author(s):  
Qinpeng Wang ◽  
Longfei He
Keyword(s):  
Supply Chain ◽  
Private Information ◽  
High Efficiency ◽  
Low Carbon ◽  
Carbon Reduction ◽  
Carbon Supply ◽  
Reduction Efficiency ◽  
Information Rent ◽  
Low Efficiency ◽  
The Impact

Information concerning carbon reduction efficiency is of great significance to supply chain operations. Considering the impact of information asymmetry on the performance of low-carbon supply chain, we therefore analyze a chain system with a single product designer and a single manufacturer. The manufacturer owns information on carbon reduction efficiency, whereas the product designer only knows that the carbon reduction efficiency of the manufacturer is either high or low. To induce the manufacturer to reveal his true private information of carbon-reduction efficiency to the product designer, we devise the pooling and separating equilibrium models to compare the impacts of these two models on supply chain performance, respectively. We find that the high-efficiency manufacturer gets his first-best choice at the equilibrium decision in the separating model, and obtains the information rent in the pooling model. The information rent increases in the efficiency difference between the two emission-reduction types. Additionally, we examine how the probability of the high (or low)-efficiency manufacturer being chosen impacts on both the profits of chain members and carbon-reduction levels. The research provides a reference for companies about how to cooperate with partner who possess private information of carbon emissions.

Private Information and Dynamic Bargaining in Supply Chains: An Experimental Study

2020 ◽  
Author(s):  
Andrew M. Davis ◽  
Kyle Hyndman
Keyword(s):  
Supply Chain ◽  
Private Information ◽  
Human Subjects ◽  
Problem Definition ◽  
Bargaining Solution ◽  
Additional Experiment ◽  
Cost Information ◽  
Private Cost ◽  
Managerial Implications ◽  
Verifiable Disclosure

Problem definition: We conduct a controlled human-subjects experiment in a two-tier supply chain where a supplier’s per-unit production cost may be private information while bargaining with a buyer. Academic/practical relevance: Academically, supply chain studies often assume full-information or highly structured bargaining. We consider private information with dynamic, unstructured bargaining. In practice, a buyer may not know its supplier’s cost exactly and interact with its supplier in a back-and-forth bargaining environment. Thus, understanding how a supplier’s private cost information affects both supply chain outcomes and bargaining is new to the literature and relevant to practice. Methodology: We employ insights from mechanism design to generate restrictions on the space of agreements and solve for a specific bargaining solution under private information to generate precise predictions. These predictions are then tested through a human-subjects experiment. Results: In our experiment, theory predicts that all supplier types should earn at least 50% of total profits when their cost information is private. However, we find that high-cost suppliers earn a disproportionately low share of total profits under private information, 20.16%. We show that this is because buyers, under private information, act as if they are bargaining with the lowest-cost supplier and suppliers do not appear to blame buyers for behaving this way. Based on these findings, we conduct an additional experiment where suppliers have the ability to communicate their private costs to buyers and observe that verifiable disclosure significantly increases profits for high-cost suppliers. Managerial implications: High-cost suppliers actually suffer from having their costs as private information, which runs counter to theory. However, if high-cost suppliers can credibly disclose their costs to buyers, they can significantly increase profits. Lastly, although private information does not lead to more disagreements, negotiations do take longer, which can be costly to firms.

A Survey of Privacy-Aware Supply Chain Collaboration: From Theory to Applications

2013 ◽  
Vol 28 (1) ◽  
pp. 243-268 ◽  
Author(s):  
Yuan Hong ◽  
Jaideep Vaidya ◽  
Shengbin Wang
Keyword(s):  
Supply Chain ◽  
Private Information ◽  
Operations Management ◽  
Negative Impact ◽  
Privacy Preserving ◽  
Research Trend ◽  
Future Research ◽  
Supply Chain Collaboration ◽  
Research Results ◽  
Proprietary Information

ABSTRACT In the contemporary information era, the ubiquitous collection of data from different parties frequently accommodates significant mutual benefits to the involved participants. However, data is a double-bladed sword. Inappropriate access or use of data by the recipients may pose serious privacy issues that explicitly harm the data owners. In the past decade, swiftly increasing privacy concerns arise in many business processes such as supply chain management. How to protect the private information of different participants in the supply chain has become a key multidisciplinary research problem in information systems, production and operations management, computer science, and mathematics. Specifically, in the real world, manufacturers, distributors, and retailers commonly collaborate with each other to cater to the demands of supplying and marketing. In their traditional cooperation, all the parties completely share their proprietary information so as to jointly optimize their operations (e.g., maximize their profit or minimize their cost). Now, they realize that completely sharing such information would bring considerable negative impact to themselves. For overcoming this, some recent research results begin to make the following ideal occasion possible—all the participants collaboratively solve a realistic problem without revealing any private proprietary information to each other. In this paper, we primarily review the literature on the applications of privacy-preserving techniques to supply chain collaboration among multiple parties. We first identify various private proprietary information required in the supply chain collaboration, and discuss several potential privacy-preserving techniques. Then, we review the relevant research results from theory to applications. Since intensive collaboration in modern supply chains opens even more opportunities in both academia and industry, we finally outline the future research trend and the potential challenges in this promising area.

Privacy Preserving Coordinating Model in Lot to Lot Supply Chain Based on Common Replenishment Epoch

2010 ◽  
Vol 39 ◽  
pp. 580-587
Author(s):  
Wei Jung Zhong ◽  
Cui Hua Xie ◽  
Yu Lin Zhang
Keyword(s):  
Supply Chain ◽  
Private Information ◽  
Privacy Preserving ◽  
Entire System ◽  
Purchase Price ◽  
Lot Size ◽  
Chain Management ◽  
Central Planner ◽  
Related Cost ◽  
Total Average

One of the important streams of research in supply chain management is the coordination between suppliers and retailers by varying the lot-size and the purchase price and common replenishment epoch (CRE). But most of the CRE solutions either assume existence of a central planner who has all the information about the system, or assume that each participant of the computation shares all of his information with other participants. These solutions are problematic when the data is sensitive and the participants are reluctant to share their private information. The development and deployment of privacy preserving coordinating model in lot to lot supply chain based on common replenishment epoch could allow supply chain collaborations to take place without revealing any participant's data to the others, reaping the benefits of collaboration while avoiding the drawbacks. In this paper, we develop and apply secure minimum sum of multi-dimensional protocol to the problem of coordinating a single-vendor multi-retailer inventory system with a probabilistic demand which follows normal distribution, where the objective is to find a CRE policy for each facility in the system such that the total average ordering and inventory-related cost of the entire system is minimized.

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