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

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.

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaheng Zhang ◽  
Zekai Lin ◽  
Lin Xiao

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.


2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.


10.5772/56833 ◽  
2013 ◽  
Vol 5 ◽  
pp. 23 ◽  
Author(s):  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Ahmed Shaban ◽  
Massimo Tronci

The bullwhip effect is defined as the distortion of demand information as one moves upstream in the supply chain, causing severe inefficiencies in the whole supply chain. Although extensive research has been conducted to study the causes of the bullwhip effect and seek mitigation solutions with respect to several demand processes, less attention has been devoted to the impact of seasonal demand in multi-echelon supply chains. This paper considers a simulation approach to study the effect of demand seasonality on the bullwhip effect and inventory stability in a four-echelon supply chain that adopts a base stock ordering policy with a moving average method. The results show that high seasonality levels reduce the bullwhip effect ratio, inventory variance ratio, and average fill rate to a great extent; especially when the demand noise is low. In contrast, all the performance measures become less sensitive to the seasonality level when the noise is high. This performance indicates that using the ratios to measure seasonal supply chain dynamics is misleading, and that it is better to directly use the variance (without dividing by the demand variance) as the estimates for the bullwhip effect and inventory performance. The results also show that the supply chain performances are highly sensitive to forecasting and safety stock parameters, regardless of the seasonality level. Furthermore, the impact of information sharing quantification shows that all the performance measures are improved regardless of demand seasonality. With information sharing, the bullwhip effect and inventory variance ratios are consistent with average fill rate results.


SIMULATION ◽  
2020 ◽  
Vol 96 (9) ◽  
pp. 767-778 ◽  
Author(s):  
Ahmed Shaban ◽  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Massimo Tronci

Numerous studies have confirmed the negative impact of the lack of coordination on supply chain performance. In particular, the lack of coordination leads to the bullwhip effect, which has severe impacts on supply chain stability. This paper evaluates a proposed coordination mechanism that allows a decentralized information sharing in multi-echelon supply chains. The proposed mechanism “Info-Smooth” utilizes the ordering rule of the generalized (R, S) policy in which a replenishment order can be transferred to upstream echelons including two pieces of information (demand forecast and inventory balance). As the generalized (R, S) can allow order smoothing, Info-Smooth combines the power of both information sharing and order smoothing. A simulation modeling methodology is employed to investigate the effectiveness of Info-Smooth in a multi-echelon supply chain. The factorial design results have shown that Info-Smooth is successful in mitigating the bullwhip effect whilst keeping acceptable inventory stability, compared to the traditional supply chain model.


Author(s):  
Brent B. Moritz ◽  
Arunachalam Narayanan ◽  
Chris Parker

Problem definition: We study the bullwhip effect and analyze the impact of human behavior. We separate rational ordering in response to increasing incoming orders from irrational ordering. Academic/practical relevance: Prior research has shown that the bullwhip effect occurs in about two-thirds of firms and impacts profitability by 10%–30%. Most bullwhip mitigation efforts emphasize processes such as information sharing, collaboration, and coordination. Previous work has not been able to separate the impact of behavioral ordering from rational increases in order quantities. Methodology: Using data from a laboratory experiment, we estimate behavioral parameters from three ordering models. We use a simulation to evaluate the cost impact of bullwhip behavior on the supply chain and by echelon. Results: We find that cost increases are not equally shared. Human biases (behavioral ordering) at the retailer results in higher relative costs elsewhere in the supply chain, even as similar ordering by a wholesaler, distributor, or factory results in increased costs within that echelon. These results are consistent regardless of the behavioral models that we consider. The cognitive profile of the decision maker impacts both echelon and supply chain costs. We show that the cost impact is higher as more decision makers enter a supply chain. Managerial implications: The cost of behavioral ordering is not consistent across the supply chain. Managers can use the estimation/simulation framework to analyze the impact of human behavior in their supply chains and evaluate improvement efforts such as coordination or information sharing. Our results show that behavioral ordering by a retailer has an out-sized impact on supply chain costs, which suggests that upstream echelons are better placed to make forecasting and replenishment decisions.


Author(s):  
Zhensen Huang ◽  
Aryya Gangopadhyay

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.


Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2683-2712 ◽  
Author(s):  
Junfei Ding ◽  
Wenbin Wang

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.


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