Optimal newsvendor policies for dual-sourcing supply chains: A disruption risk management framework

Xanthopoulos, Anastasios; Vlachos, Dimitrios; Iakovou, Eleftherios

doi:10.1016/j.cor.2011.04.010

Cited by 118 publications

(53 citation statements)

References 29 publications

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“…However, there is a trade-off between the risk reduction strategy of dual (or multiple) sourcing, and the simplicity and cost reduction accruing from single sourcing (Xanthopoulos, Vlachos, & Iakovou, 2012). Moreover, an over-reliance on a single supplier can leave the firm exposed in the event of a quality failure (Wagner & Bode, 2006, p. 301); this means that the debate around single and multiple sourcing was never closed, especially in terms of basic components that do not require much proprietary knowledge.…”

Section: Changes In the Global Automotive Industrymentioning

confidence: 99%

Vanishing value chains, industrial districts and HRM in the Brazilian automotive industry

Dibben

Meira

Linhares

et al. 2016

The International Journal of Human Resource Management

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Section: Changes In the Global Automotive Industrymentioning

confidence: 99%

Vanishing value chains, industrial districts and HRM in the Brazilian automotive industry

Dibben

Meira

Linhares

et al. 2016

The International Journal of Human Resource Management

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“…Jean et al [23] studied the relationship-based product innovation in global supply chains where this research offered a context-based explanation for the contradictory and conflicting empirical indication with respect to relational capital innovation links. In another study, a single period inventory model has been proposed to encapsulate the trade-off between inventory policies and disruption risks considering the scenario of dual-sourcing supply chain [24]. Tang et al [25] examined multiple-attribute decision making using Pythagorean 2-tuple linguistic numbers, and proposed two operators, namely, Pythagorean 2-tuple linguistic weighted Bonferroni mean (WBM) and Pythagorean 2-tuple linguistic weighted geometric Bonferroni mean (WGBM).…”

Section: Literature Reviewmentioning

confidence: 99%

Dual Market Facility Network Design under Bounded Rationality

et al. 2018

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A number of markets, geographically separated, with different demand characteristics for different products that share a common component, are analyzed. This common component can either be manufactured locally in each of the markets or transported between the markets to fulfill the demand. However, final assemblies are localized to the respective markets. The decision making challenge is whether to manufacture the common component centrally or locally. To formulate the underlying setting, a newsvendor modeling based approach is considered. The developed model is solved using Frank-Wolfe linearization technique along with Benders' decomposition method. Further, the propensity of decision makers in each market to make suboptimal decisions leading to bounded rationality is considered. The results obtained for both the cases are compared.

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“…But as is known, in the realization of each scenario, the resulting profit of the SC can be different from this expected amount. Some of the researches that have been done in the field of risk management in SC network design problems ignore these deviations and only optimize the expected value of objective functions (Mirhassani Al-e-Hashem et al, 2011;Tsiakis et al, 2001;Santoso et al, 2005;Qiet al, 2009;Xanthopoulos et al, 2012;Georgiadis et al, 2011;CardonaValdés et al, 2010;Schütz et al, 2009;Goh et al, 2007). They used stochastic programming techniques for modeling their problems.…”

Section: Robust Solutionmentioning

confidence: 99%

“…Their model determines the location and capacity of plants and the production plan through the SC, so as to minimize the average per unit product cost. Xanthopoulos et al (2012) consider a two echelon SC composed of a wholesaler and two unreliable suppliers. They investigate the trade-off between inventory policies and suppliers' disruption risk.…”

Section: This Papermentioning

confidence: 99%

Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs

Mohammaddust

Rezapour

Farahani

et al. 2017

International Journal of Production Economics

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This paper investigates how organization should design their supply chains (SCs) and use risk mitigation strategies to meet different performance objectives. To do this, we develop two mixed integer nonlinear (MINL) lean and responsive models for a four-tier SC to understand these four strategies: i) holding back-up emergency stocks at the DCs, ii) holding back-up emergency stock for transshipment to all DCs at a strategic DC (for risk pooling in the SC), iii) reserving excess capacity in the facilities, and iv) using other facilities in the SC's network to back-up the primary facilities. A new method for designing the network is developed which works based on the definition of path to cover all possible disturbances. To solve the two proposed MINL models, a linear regression approximation is suggested to linearize the models; this technique works 2 based on a piecewise linear transformation. The efficiency of the solution technique is tested for two prevalent distribution functions. We then explore how these models operate using empirical data from an automotive SC. This enables us to develop a more comprehensive risk mitigation framework than previous studies and show how it can be used to determine the optimal SC design and risk mitigation strategies given the uncertainties faced by practitioners and the performance objectives they wish to meet.

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Optimal newsvendor policies for dual-sourcing supply chains: A disruption risk management framework

Cited by 118 publications

References 29 publications

Vanishing value chains, industrial districts and HRM in the Brazilian automotive industry

Vanishing value chains, industrial districts and HRM in the Brazilian automotive industry

Dual Market Facility Network Design under Bounded Rationality

Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs

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