Abstract:In this article we analyze the interactions among the assembler and two component suppliers in their procurement decisions under a Vendor-Managed Inventory (VMI) contract. Under the VMI contract, the assembler rst o ers a unit price for each component and will pay component suppliers only for the amounts used to meet the actual demand. The two independent component suppliers then decide on the production quantities of their individual components before the actual demand is realized. We assume that one of the c… Show more
“…Gurnani and Gerchak [19] consider an assembler that procures components from two suppliers, and investigate the assembler's order decision and two suppliers' production decisions in the presence of random component yields. Pan and So [30] and Li et al [26] analyse the interactions among the assembler and suppliers in their procurement decisions in a random yield production system. He et al [20] study the impacts of decision sequences on a random yield supply chain with a service level constraint.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Fang et al [7] study a push assembly system with multiple suppliers, simultaneous supplier contracts, and a wholesale price contract. Pan and So [30] make pricing and production decisions in an assembly system with uncertain supply under a pull contract. Other factors are also considered in the literatures related to pull and push contracts, such as the presence of an outside market [14], the impact of a hybrid push-pull contract [16], a supply chain risk-averse attitude [41], and different lead times for products [42].…”
Section: Literature Reviewmentioning
confidence: 99%
“…In this paper, we focus on the uncertain supply problem in a supplier-retailer supply chain with different market dominance, which is depicted by bargaining power through the well-known pull and push contracts. Supply uncertainty is a concerned problem in both the industrial and academic worlds [18,19,30,36,40] and can be caused by a number of reasons, such as supply disruptions due to bad weather, natural disasters, suppliers going out of business, yield uncertainty due to product defects or batch processes in which only a certain percentage of the yield is usable or lead time uncertainty which results from stock-outs at the supplier or manufacturer or due to transit delays [35]. In this paper, we mainly focus on random production yields to investigate how supply uncertainty influences the supply chain members' decisions.…”
This paper investigates how a random supply can influence management decisions under pull and push contracts in a decentralized supply chain with one supplier and one retailer. We suppose that the supplier faces yield uncertainty, and we adopt game models to analyse the supply chain members’ decisions (i.e., wholesale price and order quantity) under the two commonly used contracts. Specifically, we analyse the revenue sharing mechanism and buyback mechanism with pull and push contracts, respectively, and find that the buyback contract can efficiently coordinate the supply chain with push contract, while the revenue sharing contract cannot improve the performance with a pull contract. Then we design a modified revenue sharing contract that introduces a subsidy for excess inventory and shows that for the pull case, the proposed mechanism can coordinate the supply chain effectively. Finally, the analysis results are displayed intuitively by numerical cases.
“…Gurnani and Gerchak [19] consider an assembler that procures components from two suppliers, and investigate the assembler's order decision and two suppliers' production decisions in the presence of random component yields. Pan and So [30] and Li et al [26] analyse the interactions among the assembler and suppliers in their procurement decisions in a random yield production system. He et al [20] study the impacts of decision sequences on a random yield supply chain with a service level constraint.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Fang et al [7] study a push assembly system with multiple suppliers, simultaneous supplier contracts, and a wholesale price contract. Pan and So [30] make pricing and production decisions in an assembly system with uncertain supply under a pull contract. Other factors are also considered in the literatures related to pull and push contracts, such as the presence of an outside market [14], the impact of a hybrid push-pull contract [16], a supply chain risk-averse attitude [41], and different lead times for products [42].…”
Section: Literature Reviewmentioning
confidence: 99%
“…In this paper, we focus on the uncertain supply problem in a supplier-retailer supply chain with different market dominance, which is depicted by bargaining power through the well-known pull and push contracts. Supply uncertainty is a concerned problem in both the industrial and academic worlds [18,19,30,36,40] and can be caused by a number of reasons, such as supply disruptions due to bad weather, natural disasters, suppliers going out of business, yield uncertainty due to product defects or batch processes in which only a certain percentage of the yield is usable or lead time uncertainty which results from stock-outs at the supplier or manufacturer or due to transit delays [35]. In this paper, we mainly focus on random production yields to investigate how supply uncertainty influences the supply chain members' decisions.…”
This paper investigates how a random supply can influence management decisions under pull and push contracts in a decentralized supply chain with one supplier and one retailer. We suppose that the supplier faces yield uncertainty, and we adopt game models to analyse the supply chain members’ decisions (i.e., wholesale price and order quantity) under the two commonly used contracts. Specifically, we analyse the revenue sharing mechanism and buyback mechanism with pull and push contracts, respectively, and find that the buyback contract can efficiently coordinate the supply chain with push contract, while the revenue sharing contract cannot improve the performance with a pull contract. Then we design a modified revenue sharing contract that introduces a subsidy for excess inventory and shows that for the pull case, the proposed mechanism can coordinate the supply chain effectively. Finally, the analysis results are displayed intuitively by numerical cases.
“…(), and Pan and So () explore the inventory/production/pricing decisions for a centralized assembly system subject to random supply yields. A few papers also study contracting issues in a decentralized assembly system with random yields; see, e.g., Gurnani and Gerchak (), Güler and Bilgiç (), and Pan and So ().…”
In a decentralized assembly supply chain, one assembler assembles a set of n components, each produced by a different supplier, into a final product to meet an uncertain market demand. Each supplier faces an uncertain production capacity such that only the lesser of the planned production quantity and the realized capacity can be delivered to the assembler. We assume that the suppliers' random capacities and the random demand follow an arbitrary continuous multivariate distribution. We formulate the problem as a two-stage Stackelberg game. In the base model, the assembler and the suppliers adopt a so-called vendor-managed-consigned-inventory (VMCI) contract. We analytically characterize the equilibrium of this game, based on which we obtain several managerial insights. Particularly, we show that a reduction in one supplier's production cost or capacity uncertainty, or an increase in the component salvage value, might sometimes hurt this particular supplier's profitability. Furthermore, we demonstrate that when the suppliers' capacities become more positively correlated, the assembler is always better off, but the suppliers might be better or worse off. Later, in the article, we also solve the game under a wholesale price contract. We find that the assembler always prefers the VMCI contract, and the suppliers always prefer the wholesale price contract. In addition, we illustrate that the VMCI contract is more efficient than the wholesale price contract for this decentralized assembly supply chain.
“…However, Mishra and Raghunathan [40] found that VMI intensifies the competition among manufacturers of competing brands, thus providing benefits to retailers. Pan and So [41] analyzed the interaction among the assembler and two component suppliers under a VMI contract. One supplier has uncertainty in the supply process, in which the actual number of components available for assembly is equal to a random fraction of the production quantity.…”
This paper presents some analytical results on production and order dynamics in the context of a discrete-time VMI supply chain system composed of one retailer and one manufacturer. We firstly derive the lower bound and upper bound on the range of inventory fluctuations for the retailer under unknown demand. We prove that the production fluctuations can be interestingly smoothed and stabilized independent of the delivery frequency of the manufacturer used to satisfy the retailer’s demand, even if the retailer subsystem is unstable. The sufficient and necessary stability condition for the whole supply chain system is obtained. To further explore the production fluctuation problem, the bullwhip effect under unknown demand is explored based on a transfer function model with the purpose of disclosing the influences of parameters on production fluctuations. Finally, simulation experiments are used to validate the theoretical results with respect to inventory and production fluctuations.
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