scholarly journals The Impact of Bullwhip Effect on the Cash Flow in Two-Parallel Supply Chain Systems with the Competition Effect

2022 ◽  
Vol 2022 ◽  
pp. 1-21
Author(s):  
Xingji Chen ◽  
Jing Zeng ◽  
Xigang Yuan

While considering the competition effect and market share, this study discusses how the cash flow bullwhip effect (CFBE) is impacted in two-product and two-parallel supply chain systems by comparing the situation that it has one kind of product in two-level supply chain (SC). Specifically, the study aimed to examine two-product and two-parallel SC systems that include two suppliers and two retailers. Assuming that the demand function is a linear relationship of price self-sensitivity coefficient and price cross-sensitivity coefficient, which is an AR(1) process, two retailers share the demand. After that, the quantitative equation of the CFBE was deduced from two-product and two-parallel SC systems. Finally, we get the condition that the competition effect and the market share increase or decrease the CFBE, which was in contrast to the situation without the competition effect and the market share. The paper suggested that the manager can cooperate with their partner if two products are substitutable. On the other hand, the firm should improve the forecasting accuracy of the customer’s demand and improve the service quality so that it can increase the market share and reduce the CFBE in two-parallel SC systems.

2020 ◽  
Vol 2020 ◽  
pp. 1-28
Author(s):  
Xigang Yuan ◽  
Xiaoqing Zhang ◽  
Dalin Zhang

This paper studies the impact of different forecasting techniques on the inventory bullwhip effect in two parallel supply chains with the competition effect, which is in contrast to the situation of a single product in a serial supply chain. In particular, this paper constructs two parallel supply chains, each of which includes one manufacturer and one retailer. Moreover, the market demand is impacted by the self-price sensitivity coefficient, the cross-price sensitivity coefficient, the market share, and the demand shock. We then assumed that the retailer can forecast market demand by using different forecasting techniques (i.e., the moving average technique (MA), the exponential smoothing technique (ES), and the minimum mean square error technique (MMSE)). We constructed the quantity model of the bullwhip effect and the inventory bullwhip effect. Finally, we analyzed the impact of different forecasting techniques and market share on the inventory bullwhip effect. We analyzed the conditions under which the retailers should choose different types of forecasting techniques on the basis of the inventory bullwhip effect. The results show that the MMSE forecasting technique can reduce the lead-time demand forecast error to the largest extent, and the inventory bullwhip effect can obtain the lowest level using the MMSE method: retailer-1 can reduce the inventory bullwhip effect by using the MA technique, when the self-price sensitivity coefficient, the price autoregressive coefficient, and the probabilities associated with customers choosing retailer-1’s product are very low.


2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Junhai Ma ◽  
Binshuo Bao ◽  
Xiaogang Ma

An important phenomenon in supply chain management which is known as the bullwhip effect suggests that demand variability increases as one moves up a supply chain. This paper contrasts the bullwhip effect for a two-stage supply chain consisting of one supplier and two retailers under three forecasting methods based on the market share. We can quantify the correlation coefficient between the two retailers clearly, in consideration of market share. The two retailers both employ the order-up-to inventory policy for replenishments. The bullwhip effect is measured, respectively, under the minimum mean squared error (MMSE), moving average (MA), and exponential smoothing (ES) forecasting methods. The effect of autoregressive coefficient, lead time, and the market share on a bullwhip effect measure is investigated by using algebraic analysis and numerical simulation. And the comparison of the bullwhip effect under three forecasting methods is conducted. The conclusion suggests that different forecasting methods and various parameters lead to different bullwhip effects. Hence, the corresponding forecasting method should be chosen by the managers under different parameters in practice.


Logistics ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Hicham Lamzaouek ◽  
Hicham Drissi ◽  
Naima El Haoud

The bullwhip effect is a pervasive phenomenon in all supply chains causing excessive inventory, delivery delays, deterioration of customer service, and high costs. Some researchers have studied this phenomenon from a financial perspective by shedding light on the phenomenon of cash flow bullwhip (CFB). The objective of this article is to provide the state of the art in relation to research work on CFB. Our ambition is not to make an exhaustive list, but to synthesize the main contributions, to enable us to identify other interesting research perspectives. In this regard, certain lines of research remain insufficiently explored, such as the role that supply chain digitization could play in controlling CFB, the impact of CFB on the profitability of companies, or the impacts of the omnichannel commerce on CFB.


2018 ◽  
Vol 10 (2) ◽  
pp. 23-29
Author(s):  
Zahid Hussain ◽  
Ahmad Bin Jusoh ◽  
Muhammad Sarfraz ◽  
Khalil Ur Rehman Wahla

The purpose of this research paper was to find the impact of the supply chain on firm performance in Textile firm of Pakistan. Data was collected through questioners in the month of March 2018, Approximately 30 questioners were distributed among the managers of the ten textile organizations in Faisalabad which are expected to have the best knowledge about the supply chain operations and its impact on the performance of the organization, all of them responded positively. It is found that dimensions associated with SCM methods as well as explain the connection amongst SCM methods, aggressive benefit, as well as firm performance. The actual study focuses on the causal associations in between SCM exercise, aggressive benefit as well as firm performance as well as ignores the actual feasible recursive associations.  


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.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jie Jian ◽  
Huipeng Li ◽  
Nian Zhang ◽  
Jiafu Su

The increasing homogeneous product market has made more competition among companies to focus on improving customers’ experience. In order to get more competitive advantages, companies often launch discount products to attract consumers. However, stimulated by discount products, the perception of anticipated regret is becoming stronger, which is an inevitable issue in front of companies with price discount strategy. Considering the impact of anticipated regret for discount products, this paper quantitatively describes the utility functions and deduces the demand functions of original price products and discount products. The theoretical analysis and numerical simulation are used to analyze centralized and decentralized models of supply chain for discount products. On its basis, the revenue-sharing contract is designed to optimize the profits of supply chain. This paper finds that the price of products increases first and then decreases with the increase of regret sensitivity coefficient and consumer heterogeneity. When the regret sensitivity coefficient and consumer heterogeneity are lower, companies in the supply chain can adopt the “skimming pricing” strategy in order to obtain more profits. When the regret sensitivity coefficient and consumer heterogeneity increase, companies in the supply chain can adopt “penetrating pricing” strategies to stimulate market demand. For high regret consumers, manufacturers can adopt a “commitment advertising” strategy to promise price and quality, and retailers can adopt a “prestige pricing” strategy to reduce consumer perception of regret. In response to products with higher differences in consumer acceptance, manufacturers can adopt a “differentiated customization” strategy to meet different types of consumer demand and retailers can adopt a “differential pricing” strategy for precise marketing.


2013 ◽  
Vol 340 ◽  
pp. 312-319
Author(s):  
Fu Xin Yang ◽  
Bai Lan Zhang ◽  
Zhi Yuan Su

To study the bullwhip effect (BWE) in supply chain (SC), this paper built two system dynamics (SD) models strictly referring to the AR(1) (autoregressive process) model constructed by Frank Chen. Using Vensim simulation software, it analyzed the impact of the correlation coefficient of demand, lead time, smoothing time of demand and information to BWE, and then put forward some proposals on how to reduce BWE. By contrasting the simulation results of SD models with the AR(1) models', it verifies the validity of the AR(1) model of Frank Chen from a simulation perspective. It also shows SD model combined with AR(1) model can analyze BWE in SC reliably and powerfully.


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.


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