Bidirectional option contract for prepositioning of relief supplies under demand uncertainty

This paper focuses on the optimal option contract coordinating of ordering quantity and option prices between retailer and supplier in a VMI system under market uncertainty. The option contract is characterized by a dominant supplier with two parameters which are ordering price coand executive price cepaid by retailer. An option ordering price is paid by retailer for each additional ordering unit of product at the end of selling reason if realized demand is larger than retailer’s committed minimum ordering. An executive price plays a role of purchasing price for each unit of product if retailer set a second ordering. A successful coordination has been shown and a numerical analysis demonstrates that such an option contract brings a Pareto improvement to each party, especially to the retailer. At last, the analysis of market uncertainty effects on the profits of both sides illustrates that, as the increasing of market demand uncertainty, the retailer’s ordering quantity of options will increase but his profit will reduce, and supplier’s profit will add.

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A simulation–optimization approach for a multi-period, multi-objective supply chain with demand uncertainty and an option contract

SIMULATION ◽

10.1177/0037549718761588 ◽

2018 ◽

Vol 94 (7) ◽

pp. 649-662 ◽

Cited By ~ 2

Author(s):

M Hajian Heidary ◽

A Aghaie ◽

A Jalalimanesh

Keyword(s):

Supply Chain ◽

Supply Chains ◽

Demand Uncertainty ◽

Risk Attitude ◽

Service Level ◽

Complex Problem ◽

Optimization Approach ◽

Option Contract ◽

Risk Sensitive ◽

Objective Model

One of the main challenges in global procurement problems is the uncertainty in the demand and supply sides of supply chains. Besides, decision making in the stochastic supply chains is a complex problem. A powerful technique for decision analysis in complex stochastic problems is simulation. In this paper we propose a simulation-based optimization approach to solve a bi-objective (profit and service level) supply chain with uncertain customer demands and disruption events in the suppliers. The basic assumptions used in this paper are adopted from the multi-period newsvendor problem. In addition, based on the risk attitude of the buyers (retailers), to cope with the uncertainties, they can sign an option contract, reserving additional capacity in the secondary suppliers. Hence, a simulation approach is used to model the behavior (risk attitude) of the buyers. Indeed, because of the demand uncertainty, at the beginning of each contract period, buyers should decide on the amount of ordering from the primary suppliers. The risk attitude of the retailer (as a spectrum) is defined based on the amount of ordering from the primary supplier. Also, we use the Non-dominated Sorting Genetic Algorithm to optimize the bi-objective model. Finally, a numerical example has been solved with the proposed algorithm and the results are reported. The results showed that if the profit is more important than service level, the risk sensitive retailer prefers to show more risk averse behavior.

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Coordination mechanism of logistics outsourcing service with contract portfolio including option contract under demand uncertainty

Korean Journal of Logistics ◽

10.15735/kls.2012.20.4.008 ◽

2012 ◽

Vol 20 (4) ◽

pp. 105-122 ◽

Cited By ~ 1

Author(s):

허성오 ◽

송병준 ◽

Sang Hwa Song

Keyword(s):

Demand Uncertainty ◽

Coordination Mechanism ◽

Logistics Outsourcing ◽

Option Contract

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Pricing supply chain option contracts: a bilevel programming approach

Journal of Modelling in Management ◽

10.1108/jm2-08-2019-0195 ◽

2020 ◽

Vol 15 (4) ◽

pp. 1567-1589

Author(s):

Abir Trabelsi ◽

Hiroaki Matsukawa

Keyword(s):

Supply Chain ◽

Demand Uncertainty ◽

Stackelberg Game ◽

Wholesale Price ◽

Optimal Order ◽

Programming Approach ◽

Market Demand ◽

Content Type ◽

Option Contract ◽

Optimal Pricing Strategy

Purpose This paper considers an option contract in a two-stage supplier-retailer supply chain (SC) when market demand is stochastic. The problem is a Stackelberg game with the supplier as a leader. This research assumes demand information sharing. The purpose of this study is to determine the optimal pricing strategy of the supplier along with the optimal order strategy of the retailer in three option contract cases. Design/methodology/approach The paper model the option contract pricing problem as a bilevel problem. The problem is then solved using bilevel programing methods. After computing, the generated outcomes are compared to a benchmark (wholesale price contract) to evaluate the contract. Findings The results reveal that only one of the contract cases can arbitrarily allocate the SC profit. In both other cases, the Stackelberg supplier manages to earn the total SC profit. Further analysis of the first contract, show that from the supplier’s perspective, the first stage forecast inaccuracy is beneficial, whereas the demand uncertainty in the second stage is detrimental. This contracting strategy guarantees both players better outcomes compared to the wholesale price contract. Originality/value To the best of the authors’ knowledge, this research is the first that links the option contract literature to the bilevel programing literature. It also the first to solve the pricing problem of the commitment option contract with demand update where the retailer exercises the option before knowing the exact demand.

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Decision and Performance Analysis of a Price-Setting Manufacturer with Options under a Flexible-Cap Emission Trading Scheme (ETS)

Sustainability ◽

10.3390/su10103681 ◽

2018 ◽

Vol 10 (10) ◽

pp. 3681 ◽

Cited By ~ 3

Author(s):

Shuyi Wang ◽

Zhenhua Wu ◽

Baochen Yang

Keyword(s):

Demand Uncertainty ◽

Emission Trading ◽

Price Volatility ◽

Emission Trading Scheme ◽

Price Setting ◽

Call Option ◽

Option Contract ◽

Ordering Policy ◽

Trading Scheme ◽

And Performance

An Emission Trading Scheme (ETS) is widely considered to reduce carbon emissions and achieve sustainability. Unsatisfactory results of European Union Emission trading scheme (EU ETS) make China’s government propose a flexible-cap ETS system to overcome its weakness. This research is the first one introducing the flexible cap to limit the manufacturing carbon footprint. Current research on emission reduction primarily focuses on introducing option contracts to better develop the carbon market, with little consideration of the effectiveness of these contracts on the manufacturer’s optimality facing demand risks. This research fills this research gap by using call option contract to reduce the emission costs for a price-setting manufacturer under the flexible ETS. Newsvendor models are built to investigate the behaviours and performances of manufacturers, with a call option contract when the price-driven demand is uncertain. The joint emission ordering and product pricing problem is solved by three emission ordering policies: the non-option, only option, and mixed emission ordering policy. Analytical and numerical studies have shown that the mixed policy outperforms the others in profitability, and the only option policy provides more flexibility but poor profitability. Furthermore, the mixed ordering policy better protects against price volatility and stringent emission restrictions. Managerial insights help emission-dependent manufacturers to manage their carbon assets for better survival in an increasingly stringent emission market. This paper investigates the effectiveness of the option contract on manufacture optimality in the flexible-cap ETS system, in which the joint emission ordering and production pricing problem under demand uncertainty is solved by the newsvendor model.

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