scholarly journals Multiperiod Production and Ordering Policies for a Retailer-Led Supply Chain through Option Contracts

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Nana Wan ◽  
Xu Chen
Keyword(s):  
Supply Chain ◽  
Call Option ◽  
Order Quantity ◽  
Dominant Position ◽  
Service Levels ◽  
Option Contracts ◽  
Exercise Price ◽  
Stock Type ◽  
Production Quantity ◽  
Dominant Retailer

This paper formulates two groups of multiperiod production and ordering models with call and bidirectional option contracts for a two-party supply chain consisting of one followed supplier and one dominant retailer, respectively. Based on dynamic programming theory, we characterize the optimal policy structures for two partners in each period. We also provide an approximation for the corresponding policy parameters evaluation in two cases. Then, we investigate the impacts of different option contracts and the demand risk on the decisions and performances of two members. Our results suggest that, whether concerning call or bidirectional option contracts, the optimal policies for two members always follow a base stock type. When the price parameters are the same for different option contracts, the service levels of both the system and the retailer are higher with call option contracts than with bidirectional ones, whereas the retailer’s inventory risk is lower with bidirectional option contracts than with call ones. Under the same conditions stated above, call option contracts can always benefit the supplier, but not the retailer. Owing to the retailer’s dominant position, call option contracts are better choice for the supply chain if the option (exercise) price is low (high), while bidirectional option contracts are more suitable choice for the supply chain if the option (exercise) price is high (low). In addition, an increase in the demand risk would prompt the supplier to increase his production quantity and the retailer to reduce the initial firm order quantity, either with call or bidirectional option contracts.

scholarly journals Optimal Decisions and Financing Strategies Selection of Supply Chain with Capital Constraint

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Bo Wang ◽  
De-Chun Huang ◽  
Hai-yan Li ◽  
Ji-Yong Ding
Keyword(s):  
Supply Chain ◽  
Decision Model ◽  
Numerical Study ◽  
Order Quantity ◽  
Optimal Production ◽  
Optimal Decisions ◽  
Financing Mode ◽  
Procurement Contract ◽  
Production Quantity ◽  
Selection Of

Two financing modes can be considered for manufacturer’s production capital constrained: RPFM (retailer’s prepayment financing mode) and PCFM (procurement contract financing mode). Under the RPFM, the retailer places order in advance for a discount price and makes prepayment; manufacturer is able to finance from a bank as production quantity cannot satisfy the second-order quantity of retailer. By contrast, manufacturers make financing from commercial banks based on the procurement contract with upstream supplier under the PCFM. Taking into account the relation between production volumes with the manufacturer’s own capital and retailer’s order quantity, the optimal production and financing decision model for manufacturer under these two financing modes are built. Moreover, the profits of the manufacturer, the retailer, and the supply chain are compared and discussed. Results show that both of the two modes can create new value and profit for the supply chain with capital constraint and achieve optimal production under “newsvendor” mode; the supply chain has the better performance under the RPFM than that achieved under the PCFM. Also, under the RPFM, the manufacturer’s production and the profit of the whole supply chain would be increased when the manufacturer makes the second financing. Similar conclusion is reached under the PCFM. Finally, numerical study was given to demonstrate the conclusions.

scholarly journals Modelling Wholesale Company’s Supply Chain Using System Dynamics

2020 ◽  
Vol 21 (2) ◽  
pp. 149-158
Author(s):  
Ain Kiisler ◽  
Olli-Pekka Hilmola
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Pulse Train ◽  
Real Life ◽  
Small Scale ◽  
Order Quantity ◽  
Service Levels ◽  
Reorder Point ◽  
Distribution Operations ◽  
Research Findings

AbstractResearch is based on wholesale and distribution operations of real-life case company, and in this setting, the most critical part of company’s supply chain is the inventory replenishment to warehouse (Distribution Center) as well as fulfilling and delivering customers’ orders. Different Economic Order Quantity (EOQ)-based models have been considered (Reorder Point, Reorder Point with pipeline on order inventory, and “pulse train”). Simulation system evaluates annual total logistics costs. Results show that in an environment, where local warehouse inventory levels are rather high and replenishment order quantity is rather small, it is important have frequent shipments divided in suitable intervals. In simulation model, this could be done e.g. with the use of “pulse train” function or incorporating pipeline on order inventory in order decision. The research findings are valid for a small-scale supply chain servicing small and geographically limited markets with clients assuming high customer service levels (e.g. 24-hours lead time). For bigger markets, the cross-docking based supply chain models are worth considering in simulations.

scholarly journals Coordination of a Random Yield Supply Chain with a Loss-Averse Supplier

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jiarong Luo ◽  
Xu Chen
Keyword(s):  
Supply Chain ◽  
Loss Aversion ◽  
Optimal Order ◽  
Random Yield ◽  
Order Quantity ◽  
Optimal Production ◽  
Numerical Examples ◽  
Risk Neutral ◽  
Production Quantity ◽  
Optimal Order Quantity

This paper investigates the coordination of a supply chain consisting of a loss-averse supplier and a risk-neutral buyer who orders products from the supplier who suffers from random yield to meet a deterministic demand. We derive the risk-neutral buyer’s optimal order policy and the loss-averse supplier’s optimal production policy under shortage-penalty-surplus-subsidy (SPSS) contracts. We also analyze the impacts of loss aversion on the loss-averse supplier’s production decision making and find that the loss-averse supplier may produce less than, equal to, or more than the risk-neutral supplier. Then, we provide explicit conditions on which the random yield supply chain with a loss-averse supplier can be coordinated under SPSS contracts. Finally, adopting numerical examples, we find that when the shortage penalty is low, the buyer’s optimal order quantity will increase, while the supplier’s optimal production quantity will first decrease and then increase as the loss aversion level increases. When the shortage penalty is high, the buyer’s optimal order quantity will decrease but the supplier’s optimal production quantity will always increase as the loss aversion level increases. Furthermore, the numerical examples provide strong evidence for the view that SPSS contracts can effectively improve the performance of the whole supply chain.

scholarly journals Price negotiation and coordination in outsourcing supply chain under yield and demand uncertainties

2021 ◽  
Author(s):  
Zhiming Chen ◽  
Chongping Chen
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Lot Sizing ◽  
Selling Price ◽  
Order Quantity ◽  
Bayesian Game ◽  
Production Quantity ◽  
Production Strategy ◽  
The Common ◽  
Coordination Contract

This paper considers the issues of pricing, lot-sizing decisions and coordination in a supply chain consisting of one original equipment manufacturer (OEM) and one contract manufacturer (CM). A Bayesian game accounting for asymmetric information is established to optimize the CM’s outsourcing price and the OEM’s selling price. A Stackelberg game incorporating yield and demand uncertainties is subsequently modeled to optimize the CM’s production quantity and the OEM’s order quantity. Finally, a shortage penalty with surplus purchase contract is proposed to coordinate the supply chain. It is found that the optimal outsourcing price is either the lower limit or the stationary point of the common price domain, while the optimal selling price is the upper limit. Whether the CM adopts a conservative or an aggressive production strategy depends on the threshold of the outsourcing price. Moreover, the coordination contract offers great flexibility in parameter selection. By setting the order quantity, penalty price and surplus purchase price properly, the supply chain can realize a win-win situation.

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