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 Study of the Bullwhip Effect in a Multistage Supply Chain with Callback Structure considering Two Retailers

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Junhai Ma ◽  
Liqing Zhu ◽  
Ye Yuan ◽  
Shunqi Hou
Keyword(s):  
Supply Chain ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Lead Times ◽  
Chain Model ◽  
Supply Chain System ◽  
Forecasting Method ◽  
Supply Chain Model ◽  
The Impact ◽  
Demand Processes

With the purpose of researching the bullwhip effect when there is a callback center in the supply chain system, this paper establishes a new supply chain model with callback structure, which has a material supplier, a manufacture, and two retailers. The manufacture and retailers all employ AR(1) demand processes and use order-up-to inventory policy when they make order decisions. Moving average forecasting method is used to measure the bullwhip effect of each retailer and manufacture. We investigate the impact of lead-times of retailers and manufacture, forecasting precision, callback index, and marketing share on the bullwhip effect of both retailers and manufacture. Then we use the method of numerical simulation to indicate the different parameters in this supply chain. Furthermore, this paper puts forward some suggestions to help the enterprises to control the bullwhip effect in the supply chain with callback structure.

scholarly journals Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand

2020 ◽  
Vol 12 (16) ◽  
pp. 6470 ◽  
Author(s):  
Ahmed Shaban ◽  
Mohamed A. Shalaby ◽  
Giulio Di Gravio ◽  
Riccardo Patriarca
Keyword(s):  
Supply Chain ◽  
Performance Measures ◽  
Bullwhip Effect ◽  
Service Level ◽  
Operating Conditions ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Ordering Policy ◽  
Smoothing Parameters ◽  
The Impact

The bullwhip effect reflects the variance amplification of demand as they are moving upstream in a supply chain, and leading to the distortion of demand information that hinders supply chain performance sustainability. Extensive research has been undertaken to model, measure, and analyze the bullwhip effect while assuming stationary independent and identically distributed (i.i.d) demand, employing the classical order-up-to (OUT) policy and allowing return orders. On the contrary, correlated demand where a period’s demand is related to previous periods’ demands is evident in several real-life situations, such as demand patterns that exhibit trends or seasonality. This paper assumes correlated demand and aims to investigate the order variance ratio (OVR), net stock amplification ratio (NSA), and average fill rate/service level (AFR). Moreover, the impact of correlated demand on the supply chain performance under various operational parameters, such as lead-time, forecasting parameter, and ordering policy parameters, is analyzed. A simulation modeling approach is adopted to analyze the response of a single-echelon supply chain model that restricts return orders and faces a first order autoregressive demand process AR(1). A generalized order-up-to policy that allows order smoothing through the proper tuning of its smoothing parameters is applied. The characterization results confirm that the correlated demand affects the three performance measures and interacts with the operating conditions. The results also indicate that the generalized OUT inventory policy should be adopted with the correlated demand, as its smoothing parameters can be adapted to utilize the demand characteristics such that OVR and NSA can be reduced without affecting the service level (AFR), implying sustainable supply chain operations. Furthermore, the results of a factorial design have confirmed that the ordering policy parameters and their interactions have the largest impact on the three performance measures. Based on the above characterization, the paper provides management with means to sustain good performance of a supply chain whenever a correlated demand pattern is realized through selecting the control parameters that decrease the bullwhip effect.

scholarly journals Decoupling paradigm of push-pull theory of oscillation in the FMCG industry

2016 ◽  
Vol 47 (2) ◽  
pp. 53-66 ◽  
Author(s):  
T.P. Mbhele
Keyword(s):  
Supply Chain ◽  
Bullwhip Effect ◽  
Modern Technology ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Supply Chain Network ◽  
Innovative Strategies ◽  
Supply Chain Model ◽  
Demand Information ◽  
Order Variability

The amplification of demand order variability germinates from distorted demand information upstream while sometimes reacting to demand-driven inventory positioning influenced by the custodians of downstream information. This studyuses factor analysis to tentatively develop a supply chain model to enhance the competence of supply chain performance in terms of responsiveness, connectivity and agility. The results of the analysis indicate that the magnitude of control on the bullwhip effect and access to economic information on demand orders in the supply chain network are associated with the modelling of the push-pull theory of oscillation on three mirror dimensions of supply chain interrelationships (inventory positioning, information sharing and electronically-enabled supply chain systems). The findings provide the perspective on managing amplification in consumer demand order variability upstream in the supply chain network while enhancing the overall efficiency of supply chain performance. This article provides insight into the use of innovative strategies and modern technology to enhance supply chain visibility through integrated systems networks.

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.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

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.

RFID utilization and information sharing: the impact on supply chain performance

2010 ◽  
Vol 25 (8) ◽  
pp. 582-589 ◽  
Author(s):  
Pamela J. Zelbst ◽  
Kenneth W. Green ◽  
Victor E. Sower ◽  
Gary Baker
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Supply Chain Performance ◽  
The Impact

scholarly journals Exploring the Bullwhip Effect and Inventory Stability in a Seasonal Supply Chain

10.5772/56833 ◽  
2013 ◽  
Vol 5 ◽  
pp. 23 ◽  
Author(s):  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Ahmed Shaban ◽  
Massimo Tronci
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Performance Measures ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Fill Rate ◽  
Supply Chain Dynamics ◽  
Effect Ratio ◽  
The Impact ◽  
Demand Seasonality

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.

Coordinating of multi-echelon supply chains through the generalized (R, S) policy

SIMULATION ◽  
2020 ◽  
Vol 96 (9) ◽  
pp. 767-778 ◽  
Author(s):  
Ahmed Shaban ◽  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Massimo Tronci
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Sharing ◽  
Negative Impact ◽  
Bullwhip Effect ◽  
Coordination Mechanism ◽  
Chain Model ◽  
Demand Forecast ◽  
Modeling Methodology ◽  
Information Demand

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.

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