Empirical Assessment of Bullwhip Effect in Supply Networks

Author(s):  
Dazhong Wu ◽  
Joe Teng ◽  
Sergey Ivanov ◽  
Julius Anyu

Previous empirical studies on bullwhip effects treat each industry or firm as isolated from its supply chain network. In this paper, the authors are interested in the role played by supply chain relational connection in moderating how demand variability signal is transmitted upstream. The paper conducts an empirical study based on a panel data of 55 manufacturing industries and 9 wholesale industries. The regression analysis shows that demand variability is propagated through supply chain upward and the transmission is influenced by the structural relationship between suppliers and customers, which is measured by customer-base concentration and customer interconnectedness. On the other hand, customer demand variability has a greater impact on industries with less concentrated customer base or with less interconnected customers.

2021 ◽  
Author(s):  
Nikolay Osadchiy ◽  
William Schmidt ◽  
Jing Wu

We offer a new network perspective on one of the central topics in operations management—the bullwhip effect (BWE). The topic has both practical and scholarly implications. We start with an observation: the variability of orders placed to suppliers is larger than the variability of sales to customers for most firms, yet the aggregate demand variability felt by suppliers upstream does not amplify commensurably. We hypothesize that changes to the supplier’s customer base can smooth out its aggregate demand. We test the hypothesis with a data set that tracks the evolution of supply relationships over time. We show that the effect of customer base management extends beyond the statistical benefits of aggregation. In particular, both the formation and the dissolution of customer-supplier relationships are associated with the smoothing of the aggregate demand experienced by suppliers. This provides fresh insight into how firms may leverage their customer-supplier relationships to mitigate the impact of the BWE. This paper was accepted by Jay Swaminathan, operations management.


2016 ◽  
Vol 14 (2) ◽  
pp. 292
Author(s):  
Fenny Rubbayanti Dewi ◽  
Annisa Kesy Garside

Information distortion caused PT Multi Sarana Indotani got higher demand than the distributor. Demand variability in each echelon of the supply chain (bullwhip effect) may occur due to lack of demand stability that the producer had difficulty in determining the amount of production. One of the collaboration methods that can be applied to overcome the information distortion as causes of the bullwhip effect is vendor managed inventory, where the needs of distributor and retailers monitored and controlled by the producer. In this case, vendor managed inventory applied to two echelons, producer, and distributor. 


2030 ◽  
2010 ◽  
Author(s):  
Rutger van Santen ◽  
Djan Khoe ◽  
Bram Vermeer

Our lives seem to revolve around schedules. If we don’t honor them with second-to-second precision, we miss our trains and our workplace rosters fall apart. We’re reliant on one another, and we constantly have to coordinate our schedules with those of others. Planning is crucial to our industry, too. If you unexpectedly run out of nuts and bolts, you can’t make any more cars, and the entire production process grinds to a halt. No manufacturer can afford that, so industrial companies employ large teams of specialists whose job is to ensure there are never any shortages of key parts. A worldwide logistic network has become our industry’s lifeblood. The central issue facing logistics is that of reliability. How do you keep your supply network intact? And how do you limit the consequences if it fails? These are questions that go far beyond the supply of nuts and bolts for new cars. Reliable logistics touches equally on the web of interactions that determine food production and the optimization of the Internet. It also extends to power supply, telecommunications, and workforce. Reliable networks make our society tick. But they face uncertainties of various kinds. That lends a broader significance to insights gained from industrial logistics, which offer us tools we can use to optimize networks and account for uncertainties in other areas as well. The reliability of a supply network is intimately bound up with the inventories you need to maintain. Businesses hold millions of dollars’ worth of supplies in their warehouses to make absolutely certain they never cease production due to a failure in the supply chain. So the key question is how large a stock do you need to hold of each component? Smart planning to hold down inventory levels in your warehouse generates immediate savings. On the other hand, you need enough stock to ensure continuity should anything go wrong. Optimizing storage is a common problem in supply networks. There is always a trade-off between the reliability of the network and the need for it to be profitable in an economic sense.


2019 ◽  
Vol 6 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Prabhat Mittal

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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Heidari ◽  
Din Mohammad Imani ◽  
Mohammad Khalilzadeh

Purpose This paper aims to study the hub transportation system in supply chain networks which would contribute to reducing costs and environmental pollution, as well as to economic development and social responsibility. As not all customers tend to buy green products, several customer groups should be considered in terms of need type. Design/methodology/approach In this paper, a multi-objective hub location problem is developed for designing a sustainable supply chain network based on customer segmentation. It deals with the aspects of economic (cost reduction), environment (minimizing greenhouse gas emissions by the transport sector) and social responsibility (creating employment and community development). The epsilon-constraint method and augmented epsilon-constraint (AEC) method are used to solve the small-sized instances of this multi-objective problem. Due to the non-deterministic polynomial-time hardness of this problem, two non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective grey wolf optimizer (MOGWO) metaheuristic algorithms are also applied to tackle the large-sized instances of this problem. Findings As expected, the AEC method is able to provide better Pareto solutions according to the goals of the decision-makers. The Taguchi method was used for setting the parameters of the two metaheuristic algorithms. Considering the meaningful difference, the MOGWO algorithm outperforms the NSGA-II algorithm according to the rate of achievement to two objectives simultaneously and the spread of non-dominance solutions indexes. Regarding the other indexes, there was no meaningful difference between the performance of the two algorithms. Practical implications The model of this research provides a comprehensive solution for supply chain companies that want to achieve a rational balance between the three aspects of sustainability. Originality/value The importance of considering customer diversity on the one hand and saving on hub transportation costs, on the other hand, triggered us to propose a hub location model for designing a sustainable supply chain network based on customer segmentation.


2018 ◽  
Vol 52 (4-5) ◽  
pp. 1377-1396 ◽  
Author(s):  
Ali Sabbaghnia ◽  
Jafar Razmi ◽  
Reza Babazadeh ◽  
Behzad Moshiri

Controlling the bullwhip effect and reducing the propagated inventory levels throughout the supply chain layers has an important role in reducing the total inventory costs of a supply chain. In this study, an optimal controller that considers demand as control variable is designed to dampen propagated inventory fluctuations for each node throughout the supply chain network. The model proves to be very useful in revealing the dynamic characteristics of the chain and provides a proper interface to study decisions taken into account at each node of the supply chain in different periods by decision makers (DMs). In the proposed approach, two feedback loops and online updated values of net stock quantities are used for calculation of the orders. To investigate the efficiency of the proposed approach, a real case of bicycle industry is conducted. The acquired results justify the efficiency of the proposed approach in controlling and dampening the bullwhip effect and reducing inventory levels, net stock quantities and inventory attributed costs throughout the supply chain network layers.


2018 ◽  
Vol 28 (5) ◽  
pp. 1-10
Author(s):  
Ho Young Choi ◽  
Baek Seo Seong ◽  
Joung Ho Lee

2016 ◽  
Vol 47 (2) ◽  
pp. 53-66 ◽  
Author(s):  
T.P. Mbhele

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yongchang Wei ◽  
Hongwei Wang ◽  
Fangyu Chen

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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