scholarly journals Simulation Research on Information-Sharing Value of Two-Level Supply Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaheng Zhang ◽  
Zekai Lin ◽  
Lin Xiao
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Information Sharing ◽  
Chain Model ◽  
Simulation Research ◽  
Incentive Effect ◽  
Actual Evaluation ◽  
Demand Information ◽  
And Performance ◽  
The Impact

In the two-stage supply chain model, the incentive effect to the supplier’s sharing of demand information and performance evaluation and the effect of various parameters on the incentive effect of the supply chain are studied through a multiagent simulation model constructed for the purpose. It is found that the incentive coefficient of demand information-sharing degree, the number of selected suppliers, the order allocation coefficient, and the order proportion are positively related to the incentive effect of demand information sharing. So, the greater the demand information sharing is, the greater the impact of these parameters on the incentive effect is. Based on the demand information sharing, the supplier performance evaluation rules are shared, and when the actual evaluation rules are inconsistent with the supplier’s expectations, the incentive effect is further enhanced. Other parameters do not affect the incentive effect of demand information sharing and performance evaluation rule sharing.

A Study on Leagile Supply Chain Model and Performance Evaluation System Based on Lean Agile Theory

2014 ◽  
Vol 635-637 ◽  
pp. 1771-1775 ◽  
Author(s):  
Hui Min Jia ◽  
Kai Chao Yu ◽  
Jin Chang Zhang
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Evaluation System ◽  
Operating Mode ◽  
Agile Manufacturing ◽  
Chain Model ◽  
Performance Evaluation System ◽  
Supply Chain Model ◽  
And Performance ◽  
Lean Supply Chain

Leagile supply chain integrates lean supply chain and agile supply chain. In this paper, the theory of lean production and agile manufacturing are compared and analyzed, and then the leagile supply chain model and the performance evaluation system based on DEA are established. Based on the above, this paper provides an example of the evaluation system to verify the operability and effectiveness, which can provide the reference for enterprises to improve operating mode of the supply chain or develop a new leagile supply chain.

An Empirical Comparison of Anticipatory and Response‐Based Supply Chain Strategies

1998 ◽  
Vol 9 (2) ◽  
pp. 21-34 ◽  
Author(s):  
David J. Closs ◽  
Anthony S. Roath ◽  
Thomas J. Goldsby ◽  
James A. Eckert ◽  
Stephen M. Swartz
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Information Exchange ◽  
Demand Uncertainty ◽  
Chain Model ◽  
Performance Impact ◽  
Simulation Research ◽  
Supply Chain Model ◽  
Demand Variation ◽  
And Performance

This paper reports simulation research that empirically investigates and compares supply chain performance under varying conditions of information exchange and demand uncertainty. Specifically, the research objective is to quantitatively document the characteristics and performance impact of information exchange among supply chain entities. The findings suggest that the response‐based supply chain model consistently outperforms the anticipatory model in terms of customer service delivered under conditions of both low and high demand variation. Comparisons of inventory holdings across supply chain models demonstrate that the retailers' inventory burden is significantly lower in the response‐based scenario. The inventory savings enjoyed by retailers in the response‐based model are substantial enough to lower system‐wide inventories. In sum, the study supports the feasibility of achieving both improved service and lower inventories as a result of information sharing.

Information Sharing in Supply Chain Management with Demand Uncertainty

2011 ◽  
pp. 44-62 ◽  
Author(s):  
Zhensen Huang ◽  
Aryya Gangopadhyay
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Demand Uncertainty ◽  
Bullwhip Effect ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Simulation Approach ◽  
Supply Chain Model ◽  
Trading Partners ◽  
The Impact

Information sharing is a major strategy to counteract the amplification of demand fluctuation going up the supply chain, known as the bullwhip effect. However, sharing information through interorganizational channels can raise concerns for business management from both technical and commercial perspectives. The existing literature focuses on examining the value of information sharing in specific problem environments with somewhat simplified supply chain models. The present study takes a simulation approach in investigating the impact of information sharing among trading partners on supply chain performance in a comprehensive supply chain model that consists of multiple stages of trading partners and multiple players at each stage.

scholarly journals Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Salvatore Cannella ◽  
Roberto Dominguez ◽  
Jose M. Framinan ◽  
Manfredi Bruccoleri
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Negative Impact ◽  
Positive Impact ◽  
Bullwhip Effect ◽  
Sources Of Information ◽  
Short Delay ◽  
Demand Information ◽  
Demand Variability ◽  
The Impact

We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand error has a negative impact on SC performance, which is exacerbated by the magnitude of the error and by low demand variability scenarios. In contrast, demand delay produces a nonlinear behavior in the supply chain response (i.e., a short delay may have a negative impact and a long delay may have a positive impact), being influenced by the supply chain configuration.

Information sharing in a green supply chain with promotional effort

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2683-2712 ◽  
Author(s):  
Junfei Ding ◽  
Wenbin Wang
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Consumer Surplus ◽  
Green Supply Chain ◽  
Future Research ◽  
Content Type ◽  
Promotional Effort ◽  
Demand Information ◽  
The Impact ◽  
Share Information

Purpose The purpose of this paper is to investigate the retailer’s strategy of information sharing in a green supply chain with promotional effort, and the impact of information sharing on the decisions and profits of the manufacturer and the retailer. Design/methodology/approach The developed models aim to maximize the profits of the manufacturer, the retailer and the green supply chain system. The game theory is used to obtain the equilibrium solutions of both the manufacturer and the retailer. A two-part compensation (TPC) contract is designed to motivate the retailer to share information with the retailer. Numerical examples are used to show the impact of parameters on decisions by Matlab 2014. Findings The results show that the green degree increases while the promotional effort level decreases when the manufacturer receives the larger demand information from the retailer; information sharing leads to a profit increase to the manufacturer and a profit loss to the retailer, but can increase the profit of supply chain under a certain condition; information sharing reduces the expected consumer surplus. The TPC contract designed in this paper can not only motivate the retailer to share information but also increases the consumer surplus. Research limitations/implications The study has been done in a monopoly environment where only a retailer can forecast demand information. It is an interesting direction of future research when considering there are more retailers who can forecast such information in a supply chain. Originality/value There exist two main aspects that are different from the existing literature. The stochastic demand function related to the retail price, the green degree and the promotional effort have never appeared in previous literature. This paper considers a green product supply chain with a manufacturer who produces green products and a retailer who has an information advantage because of her promotional effort; this paper investigates the impact of information sharing on the consumer surplus and designs a contract to coordinate the green supply chain.

scholarly journals Information Acquisition and Its Incentives in an E-Commerce Supply Chain under the Offline Showroom Model

2021 ◽  
Vol 16 (5) ◽  
pp. 1791-1804
Author(s):  
Mengli Li ◽  
Xumei Zhang
Keyword(s):  
Supply Chain ◽  
Information Acquisition ◽  
Incentive Contracts ◽  
Demand Forecast ◽  
Competition Intensity ◽  
Demand Information ◽  
Optimal Information ◽  
Acquisition Strategy ◽  
The One ◽  
The Impact

Recently, the showroom model has developed fast for allowing consumers to evaluate a product offline and then buy it online. This paper aims at exploring the optimal information acquisition strategy and its incentive contracts in an e-commerce supply chain with two competing e-tailers and an offline showroom. Based on signaling game theory, we build a mathematical model by considering the impact of experience service and competition intensity on consumers’ demand. We find that, on the one hand, information acquisition promotes supply chain members to obtain demand information directly or indirectly, which leads to forecast revenue. On the other hand, information acquisition promotes supply chain members to distort optimal decisions, which results in signal cost. The optimal information acquisition strategy depends on the joint impact of forecast revenue, signal cost and demand forecast cost. Notably, in some conditions, the offline showroom will not acquire demand information even when its cost is equal to zero. We also design two different information acquisition incentive contracts to obtain Pareto improvement for all supply chain members.

The impact of information sharing on ordering policies to improve supply chain performances

2015 ◽  
Vol 82 ◽  
pp. 127-142 ◽  
Author(s):  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Ahmed Shaban ◽  
Massimo Tronci
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Ordering Policies ◽  
The Impact ◽  
Improve Supply Chain

scholarly journals Mathematical model of the feedback between global supply chain disruption and COVID-19 dynamics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xingyu Li ◽  
Amin Ghadami ◽  
John M. Drake ◽  
Pejman Rohani ◽  
Bogdan I. Epureanu
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Care Delivery ◽  
Global Supply Chain ◽  
Economic Losses ◽  
Chain Model ◽  
Supply Chain Disruption ◽  
Disease Networks ◽  
Resource Allocation Strategy ◽  
The Impact

AbstractThe pandemic of COVID-19 has become one of the greatest threats to human health, causing severe disruptions in the global supply chain, and compromising health care delivery worldwide. Although government authorities sought to contain the spread of SARS-CoV-2, by restricting travel and in-person activities, failure to deploy time-sensitive strategies in ramping-up of critical resource production exacerbated the outbreak. Here, we developed a mathematical model to analyze the effects of the interaction between supply chain disruption and infectious disease dynamics using coupled production and disease networks built on global data. Analysis of the supply chain model suggests that time-sensitive containment strategies could be created to balance objectives in pandemic control and economic losses, leading to a spatiotemporal separation of infection peaks that alleviates the societal impact of the disease. A lean resource allocation strategy can reduce the impact of supply chain shortages from 11.91 to 1.11% in North America. Our model highlights the importance of cross-sectoral coordination and region-wise collaboration to optimally contain a pandemic and provides a framework that could advance the containment and model-based decision making for future pandemics.

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