Supply Chain Network Structure and Firm Returns

2014 ◽  
Author(s):  
Jing Wu ◽  
John R. Birge
Keyword(s):  
Supply Chain ◽  
Network Structure ◽  
Supply Chain Network

Impact of Auto-regressive (AR) Process in Bullwhip Analysis in a Multi-location Supply Chain Network

2019 ◽  
Vol 6 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Prabhat Mittal
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Network Structure ◽  
Bullwhip Effect ◽  
Supply Chain Network ◽  
Risk Pooling ◽  
On Demand ◽  
Forecasting Methods ◽  
Auto Regressive ◽  
Ar Process

The present study is an attempt to quantify the Bullwhip Effect (BWE) -the phenomenon in which information on demand is distorted in moving up a supply chain. Assuming that the retailer employs an order-up-to level policy with auto-regressive process (AR), the paper investigates the influence of forecasting methods on bullwhip effect. Determining the order-up-to levels and the orders for the retailers’ demands in an isolated manner neglects the correlation of the demands and the relevant risk pooling effects associated with the network structure of the supply chains are disregarded. It is illustrated that the bullwhip effects are significantly reduced with consideration of potential correlation between the retailers’ demand.

scholarly journals Research on Evaluation on Agility of Agile Supply Chain Network Based on Complex Network Theory

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Nai-Ru Xu ◽  
Jia-Bao Liu
Keyword(s):  
Supply Chain ◽  
Network Structure ◽  
Network Theory ◽  
Network Centrality ◽  
Supply Chain Network ◽  
Complex Network Theory ◽  
Research On Evaluation ◽  
Agile Supply Chain ◽  
Structure Factors ◽  
Evaluation Matrix

The paper tries to add the network structure factors of agile supply chain network into agility evaluation. The paper firstly presents three concepts including node strength centrality, betweenness centrality, and network centrality. They are used to calculate the weight of node enterprises in the agile supply chain network. And then, a series of agility indicators are designed to evaluate agility of agile supply chain network. AHP is used to calculate the weight of the indicators. Next, these indicators are used to get initial agility evaluation matrix by means of Delphi method, Data Mining, and so forth. Then FCE is used to calculate the membership degree on agility of node enterprises by combining the evaluation matrix with the weight of indicators. Last, the evaluation result of comprehensive agility of agile supply chain network is calculated on the basis of considering the weight of node enterprises. This method can reflect the effect which the network structure of supply chain network makes on the agility of the supply chain network. It is a complement to the current evaluation methods of agility.

scholarly journals Exploring the Impact of Network Structure and Demand Collaboration on the Dynamics of a Supply Chain Network Using a Robust Control Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yongchang Wei ◽  
Hongwei Wang ◽  
Fangyu Chen
Keyword(s):  
Supply Chain ◽  
Robust Control ◽  
Network Structure ◽  
Complex Dynamics ◽  
State Space Model ◽  
Bullwhip Effect ◽  
Supply Chain Network ◽  
Control Approach ◽  
Demand Fluctuations ◽  
The Impact

A supply chain network might exhibit complex dynamics in the face of increasingly volatile and uncertain environment. The impact of network structure and collaboration on the dynamics and robustness of supply chain network, however, remains to be explored. In this paper, a unified state space model for a two-layer supply chain network composed of multiple distributors and multiple retailers is developed. A robust control algorithm is advocated to reduce both order and demand fluctuations for unknown demand. Numerical simulations demonstrate that the robust control approach has the advantage to reduce both inventory and order fluctuations. In the simulation experiment, it is interesting to notice that complex network structure and collaborations might contribute to the reduction of inventory and order oscillations. This paper yields new insights into the overestimated bullwhip effect problem and helps us understand the complexities of supply chain networks.

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