Impact of risk aversion and backup supplier on sourcing decisions of a firm

Merzifonluoğlu, Yasemin

doi:10.1080/00207543.2014.999956

Cited by 24 publications

(16 citation statements)

References 55 publications

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“…Note that optimality properties of pure contract sourcing case (Model 1.1 (Normal)) confirm the results presented by Merzifonluoglu (2015).…”

Section: Model 11 (Normal) Model 12 (Normal) and Model 13 (Normal)supporting

confidence: 84%

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Risk averse supply portfolio selection with supply, demand and spot market volatility

Merzifonluoğlu

2015

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“…Note that optimality properties of pure contract sourcing case (Model 1.1 (Normal)) confirm the results presented by Merzifonluoglu (2015).…”

Section: Model 11 (Normal) Model 12 (Normal) and Model 13 (Normal)supporting

confidence: 84%

“…Merzifonluoglu (2015) studied the impact of backup supplier and risk aversion on supplier portfolio. However, they have not included spot market in their analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk averse supply portfolio selection with supply, demand and spot market volatility

Merzifonluoğlu

2015

Omega

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“…Sawik 26 studied the problem of supplier selection considering some protection decisions against disruptions and the reallocation of excess inventories in the protected suppliers. Merzifonluoglu 27 developed a newsvendor model with backup suppliers and analyzed the effect of risk aversion on the supplier selection process. The main related literature was introduced in the above three sections.…”

Section: The Newsvendor Problem With Hedging Contractsmentioning

confidence: 99%

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

2018

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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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“…; as a result, the backup production of the backup supplier is more responsive and more reliable than regular production. Most of existing related studies even suppose that backup production is perfectly reliable (e.g., [7], [9]- [11]). There is also a disadvantage for sequential ordering; that is, backup sourcing leads to high procurement cost because the responsive and reliable production of backup supplier is expensive.…”

Section: Introductionmentioning

confidence: 99%

“…The firm (newsvendor) first determines order quantities from unreliable capacitated primary suppliers. After the realization of customer demand and reliabilities of the primary suppliers, the firm purchases from the backup supplier [11]. Guo et al (2016) consider a firm that procures a product from a regular supplier whose production is subject to both supply disruption and random yield and a backup supplier whose production capacity requires reservation in advance [18].…”

Section: Introductionmentioning

confidence: 99%

Dual Sourcing Strategy for High-Tech Manufacturer Under Supply Risk and Capacity Constraint

Zeng

2019

IEEE Access

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High-tech manufacturers frequently suffer from supply risk and capacity constraint. This paper considers a manufacturer who procures a type of high-tech component from two suppliers with asymmetric costs, capacities, and reliabilities, where the low-cost supplier has low reliability. One supplier is selected as a primary supplier and another as a backup supplier. The manufacturer places regular order to the primary supplier and determines backup order quantity from the backup supplier after random yield realization of the primary supplier. By developing a dynamic game-theoretical model, we obtain the optimal wholesale prices for the primary supplier and backup supplier, the optimal order quantity and supplier arrangement decisions for the manufacturer. We show that the manufacturer selects the low-cost supplier as a primary supplier and the high-cost supplier as a backup supplier (namely, LH policy) when the reliabilities of the two suppliers are close. When these reliabilities are not so close, the manufacturer chooses the high-cost supplier as a primary supplier and the low-cost supplier as a backup supplier (namely, HL policy). In addition, the manufacturer in the industry with scale diseconomies is more likely to select HL policy than that in the industry with scale economies. Compared with centralized decision making scheme, decentralized scheme induces the manufacturer more likely to select HL policy in the industry without scale economies, whereas in the industry with scale economies, decentralized scheme induces the manufacturer more likely to choose either HL policy when the capacity advantage of the low-cost supplier is weak, or LH policy when this advantage is significant. INDEX TERMS Supply chain management, supply and demand, production management, operations research, capacity constraint.

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Impact of risk aversion and backup supplier on sourcing decisions of a firm

Cited by 24 publications

References 55 publications

Risk averse supply portfolio selection with supply, demand and spot market volatility

Risk averse supply portfolio selection with supply, demand and spot market volatility

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

Dual Sourcing Strategy for High-Tech Manufacturer Under Supply Risk and Capacity Constraint

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