A supply chain contract with flexibility as a risk-sharing mechanism for demand forecasting

Kim, Whan-Seon

doi:10.1080/00207721.2011.653592

Cited by 16 publications

(9 citation statements)

References 19 publications

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“…Due to the rapid development of technology, demand information can be easily collected and updated for improving supply chain performance. However, no matter how good the employed forecasting technique is, it is almost impossible to provide accurate forecast subject to demand uncertainty [24]. Considering that the uncertain demand always results in a situation where both the supplier and retailer face the risk of over-or out-inventory, risk-sharing contract is one of the means of risk mitigation [16,25,39].…”

Section: Supply Chain Inventory Model With Risk-sharingmentioning

confidence: 99%

“…Two classes of supply chain risk-sharing models exist. In the first class, only the order risk is sharing between the supplier and the retailer, while the production risk is fully carried by the supplier (see [1,24,27,40,44,46]). For example, Li and Kouvelis [27] develop a risk-sharing sourcing contract with time, quantity, and supply flexibility.…”

Section: Supply Chain Inventory Model With Risk-sharingmentioning

confidence: 99%

“…This paper contributes to the existing literatures on risk-sharing contract and demand information updating in following three main aspects: first, to the best of our knowledge, this paper is the first to propose a bidirectional risk-sharing contract involving risks of overproduction and overstock to coordinate a two-echelon supply chain with demand information updating. Comparatively, most existing literatures only focus on single risk-sharing contracts for over-/under production risk (e.g., [20,36]) or overstock risk (e.g., [24]). Through redesigning the contract parameters, those papers explore the sufficient condition in which the supply chain achieves coordination.…”

Section: Introductionmentioning

confidence: 99%

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Coordinating a fresh-product supply chain with demand information updating: Hema Fresh O2O platform

Yang

Peng

2021

RAIRO-Oper. Res.

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Motivated by Hema Fresh's new-retail case, we study the coordination of a two-echelon fresh-product supply chain consisting of a single supplier and a single retailer. Due to a long production lead time, the supplier has to make production decision in advance based on early demand information. The market demand can be updated during the supplier's production lead time. Hence, the retailer would make order decision according to the latest demand information. Incorporating risk-sharing mechanism of overproduction and overstock, we propose a novel bi-directional risk-sharing contract to coordinate such a supply chain with demand information updating. We construct a two-stage optimization model in which the supplier first decides production quantity, and then the retailer decides final order quantity not exceeding the supplier’s initial production. In both the centralized and decentralized systems, we analytically derive the unique equilibrium of production and order decisions in a Stackelberg supplier-led game. We prove that the proposed contract can realize supply chain perfect coordination and explore how the proposed contract affects the members'decisions. The theoretical results show that, by turning the risk-sharing proportions, the supply chain profit can be arbitrarily split between the members, which is a desired property for supply chain coordination. Compared with the single risk-sharing contract, the proposed contract results in a greater supply chain profit and achieves Pareto improvement for both members. Furthermore, we also explore how the risk preference and negotiating power affect the contract selection and the additional profit allocation of the supply chain. Numerical examples are presented to verify our theoretical results.

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Section: Supply Chain Inventory Model With Risk-sharingmentioning

confidence: 99%

Section: Supply Chain Inventory Model With Risk-sharingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coordinating a fresh-product supply chain with demand information updating: Hema Fresh O2O platform

Yang

Peng

2021

RAIRO-Oper. Res.

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“…Through numerical work they found that the contract results in a win-win situation for both the supplier and the retailer in the case of price dependent demand. Kim [7] studied a bilateral contract with order quantity flexibility. To conduct comparative simulations, he developed four-echelon supply chain models, that employ the contracts and different forecasting techniques under dynamic market demands.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Order Decision of Quantity Flexibility Contract under the Competition between Multiple Suppliers and Multiple Retailers

Qian¹,

Tao²,

Qin³

2018

AJIBM

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In the supply chain system consisting of multiple suppliers and multiple retailers, in order to realize supply chain coordination, we studied the ordering decision under the quantity flexibility contract with competition between both sides. On the one hand, from the perspective of suppliers, a satisfactory production of goods for each supplier was obtained by means of a kind of interactive programmer step method. On the other hand, from the perspective of retailers, because each supplier holds a different preference attitude for different retailers, we sort retailers as preference in application of a group decision sequencing method of Markov chain. The optimal order quantity of goods for each retailer was obtained at the same time and we prove that it is Pareto optimal. Finally, we give a numerical example.

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“…They incorporated backorders, lost sales and/or outsourcing options to generate the recovery plan and developed some solution heuristics. Other studies (Baghalian et al 2013;Kim 2013;Tang et al 2012) have considered demand fluctuations when formulating a supply chain recovery model. Paul et al (2014c) have applied a real-time recovery concept on a supplier-retailer coordinated system for managing demand fluctuations under backorders and lost sales.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss

et al. 2017

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Transportation disruption, a common source of business interruptions, can cause significant economic loss to a lean supply chain. This paper studies a lean, two-stage suppliermanufacturer coordinated system where a sudden disruption interrupts the transportation network, creating delivery delays, and product quantity losses. We develop a model to generate a recovery plan after a sudden disruption occurrence, to minimize the negative impacts of the disruption. At the same time, given the computational intensity and problem complexity, three heuristics based on the delivery delay and fractional quantity loss caused by a sudden disruption are developed. We conduct a number of numerical experiments to validate our proposed solution methods, and a scenario-based analysis to test the model and analyse the impact of sudden transportation disruption under three disruption scenarios. The performance of presented heuristics against the Generalized Reduced Gradient method are compared. The results reveal that the proposed heuristics can generate a recovery plan accurately and consistently.

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A supply chain contract with flexibility as a risk-sharing mechanism for demand forecasting

Cited by 16 publications

References 19 publications

Coordinating a fresh-product supply chain with demand information updating: Hema Fresh O2O platform

Coordinating a fresh-product supply chain with demand information updating: Hema Fresh O2O platform

Research on Order Decision of Quantity Flexibility Contract under the Competition between Multiple Suppliers and Multiple Retailers

Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss

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