Sourcing and Pricing Strategy Research of Supply Chain Network under Supply Disruption Risk

2013 ◽  
Vol 5 (9) ◽  
pp. 723-732
Author(s):  
Ling HOU ◽  
Dongyan CHEN ◽  
Chunxian TENG
Keyword(s):  
Supply Chain ◽  
Pricing Strategy ◽  
Supply Chain Network ◽  
Strategy Research ◽  
Supply Disruption ◽  
Disruption Risk

Analyzing the Supply Chain Network Reconfiguration under Disruption Risk Environment

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Usha Mohan ◽  
S. Prasanna Venkatesan ◽  
Varthini Rajagopal ◽  
Rishabh Gaur ◽  
Shubham Jha
Keyword(s):  
Supply Chain ◽  
Network Reconfiguration ◽  
Supply Chain Network ◽  
Risk Environment ◽  
Disruption Risk

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ehsan Mohebban-Azad ◽  
Amir-Reza Abtahi ◽  
Reza Yousefi-Zenouz
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Problem Definition ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Inventory Routing ◽  
Content Type ◽  
Proposed Model ◽  
Disruption Risk ◽  
Disruption Risks

Purpose This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system. Design/methodology/approach A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it. Findings The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods. Originality/value In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.

scholarly journals Contract Coordination in Dual Sourcing Supply Chain under Supply Disruption Risk

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Tong Shu ◽  
Fang Yang ◽  
Shou Chen ◽  
Shouyang Wang ◽  
Kin Keung Lai ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
Wholesale Price ◽  
Order Quantity ◽  
Product Price ◽  
Strike Price ◽  
Supply Disruption ◽  
Dual Sourcing ◽  
Coordination Model ◽  
Disruption Risk

This paper explores a coordination model for a three-echelon supply chain including two different manufacturers, one distributer and one retailer via the combined option and back contracts. And one manufacturer provides the high wholesale price with low supply disruption risk and the other is completely the opposite. This differs from the previous supply chain coordination model. Firstly, supply disruption is added to the three-echelon supply chain. Secondly, considering the coordination of the supply chain, we deploy the combined option and back contracts which are seldom used in the previous study. Furthermore, it is interesting that supply disruption risk and buyback factor do not affect the distributor’s order quantity from the manufacturer who has low product price and unreliable operating ability, while the order quantity increases with the rise of option premium and option strike price. The distributor’s order quantity from the manufacturer, which has high product price and reliable operating ability, increases with the rise of supply disruption risk but decreases when the buyback factor, option premium, and option strike price decrease.

Managers' risk perception of supply chain uncertainties

2020 ◽  
Vol 120 (9) ◽  
pp. 1617-1634 ◽  
Author(s):  
Yuji Sato ◽  
Ying Kei Tse ◽  
Kim Hua Tan
Keyword(s):  
Supply Chain ◽  
Risk Perception ◽  
Comparative Studies ◽  
Risk Perceptions ◽  
Structural Model ◽  
Comparative Case Study ◽  
Sustainable Supply Chain ◽  
Supply Disruption ◽  
Content Type ◽  
Disruption Risk

PurposeThis paper provides a practical framework for managers to develop a sustainable supply chain. Given that rapid globalization has increased supply disruption risk, managers have been forced to establish efficient and responsive supply chain strategies. Nevertheless, diverse uncertainty factors, such as risk perception of strategies, have made practical management difficult. Quantifying managers' risk perceptions and applying them to supply chain strategies allows the authors to propose a structural and practical model for managing supply disruption.Design/methodology/approachThe existing structural model is refined by taking subjective factors into account using the analytic hierarchy process. The applicability of the refined model is demonstrated through a comparative case study.FindingsManagers' risk perceptions vary not only among companies but also between managing divisions within a company, which necessitates possible changes in strategy due to environmental turbulence. The principal component analysis (PCA) characterizes managers' risk perceptions that illustrate companies' emphases on disruption risk.Practical implicationsThe proposed approach quantifies risk perception, which enables practitioners to deal with subjective information in quantitative form. Comparative studies clarify differences in perception given different business backgrounds. The results provide managers with in-depth insights for establishing supply chain strategies reflecting their risk perception.Originality/valueQuantification of managers' subjective risk perception clarifies both the trend and the individual features for uncertainties. The results allow the authors to conduct the PCA, which characterizes companies. Comparative studies generalize the results of extant work, shedding light on cross-sectional differences given different business backgrounds. The effectiveness of the approach is confirmed through retrospective interviews with practitioners.

scholarly journals An integrated location-inventory model for a spare part’s supply chain considering facility disruption risk and CO2 emission

2021 ◽  
Vol 14 (2) ◽  
pp. 87
Author(s):  
Rubayet Karim ◽  
Koichi Nakade
Keyword(s):  
Supply Chain ◽  
Co2 Emission ◽  
Spare Part ◽  
Spare Parts ◽  
Inventory Model ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Supply Chain Network ◽  
Emission Level ◽  
Disruption Risk

Purpose: Managing the inventory of spare parts is very difficult because of the stochastic nature of part’s demand. Also, only controlling the inventory of the spare part is not enough; instead, the supply chain of the spare part needs to be managed efficiently. Moreover, every organization now aims to have a resilient and sustainable supply chain to overcome the risk of facility disruption and to ensure environmental sustainability. This paper thus aims to establish a model of inventory-location relating to the resilient supply chain network of spare parts.Design/methodology/approach: First, applying queuing theory, a location-inventory model for a spare parts supply chain facing a facility disruption risk and has a restriction for CO2 emission, is developed. The model is later formulated as a non-linear mixed-integer programming problem and is solved using MATLAB.Findings: The model gives optimal decisions about the location of the warehouse facility and the policy of inventory management of each location selected. The sensitivity analysis shows that the very low probability of facility disruption does not influence controlling the average emission level. However, the average emission level certainly decreases with the increment of the disruption probability when the facility disruption probability is significant.Practical implications: Using this model, based on the cost and emission parameters and the likelihood of facility disruption, the spare part’s manufacturer can optimize the total average cost of the spare part’s supply chain through making a trade-off between productions, warehouse selection, inventory warehousing and demand allocation.Originality/value: Previous research focuses only on developing a framework for designing an efficient spare parts planning and control system. The inventory-location model for spare parts is not addressed in the sense of risk of facilities disturbance and emission. This research first time jointly considered the probabilistic facility disruption risk and carbon emission for modeling the spare part’s supply chain network.

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