Journal articles on the topic 'Bullwhip Effect'
To see the other types of publications on this topic, follow the link: Bullwhip Effect.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Bullwhip Effect.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Jin, Ming, Nicole DeHoratius, and Glen Schmidt. "Want to reduce the bullwhip? Measure it. Here’s how." Supply Chain Management: An International Journal 22, no. 4 (June 12, 2017): 297–304. http://dx.doi.org/10.1108/scm-02-2017-0088.
Full textAbstract:
Purpose The popular “beer game” illustrates the bullwhip effect where a small perturbation in downstream demand can create wild swings in upstream product flows. The purpose of this paper is to present a methodical framework to measure the bullwhip effect and evaluate its impact. Design/methodology/approach This paper illustrates a framework using SKU-level data from an industry-leading manufacturer, its distributors, end-users and suppliers. Findings Firms benefit from tracking multiple intra-firm bullwhips and from tracking bullwhips pertinent to specific products, specific suppliers and specific customers. The framework presented in this paper enables managers to pinpoint bullwhip sources and mitigate bullwhip effects. Research limitations/implications This paper presents a framework for methodically measuring and tracking intra-firm and inter-firm bullwhips. Practical implications A disconnect exists between what is known and taught regarding the bullwhip effect and how it is actually tracked and managed in practice. This paper aims to reduce this gap. For the various products analyzed herein, the authors show how using this framework has the potential to reduce delivered product cost by 2 to 15 per cent. Social implications Properly managing the bullwhip leads to lower inventories and potentially lower product prices while simultaneously increasing firm profits. Originality/value This paper presents a novel approach to systematically tracking intra-firm bullwhips along with bullwhips specific to a given supplier or customer.
2
Hohmann, Susanne, and Stephan Zelewski. "Effects of Vendor-Managed Inventory on the Bullwhip Effect." International Journal of Information Systems and Supply Chain Management 4, no. 3 (July 2011): 1–17. http://dx.doi.org/10.4018/jisscm.2011070101.
Full textAbstract:
The bullwhip effect means that demand variability increases as one moves up the supply chain. In the following article the bullwhip effect is quantified for each part of the supply chain which is presupposed to consist of a producer, a wholesaler, a retailer, and a consumer. After considering the causes of the bullwhip effect, it will be shown with the help of a nonlinear optimization model to what extent the bullwhip effect can be reduced using vendor-managed inventory (VMI) as one concept of Collaborative Planning, Forecasting and Replenishment (CPFR). In contrast to other studies in this field the reduction of the bullwhip effect will be accurately quantified for each part of the supply chain.
3
Yebabe, Yohannes. "The Bullwhip Effect." International Journal of Applied Logistics 5, no. 1 (January 2014): 33–51. http://dx.doi.org/10.4018/ijal.2014010103.
Full textAbstract:
Supply chain management is a fledgling science which concerned with synchronization of both material flow and information flow by integrating companies for a common objective to meet the requirements of the end customer. Bullwhip effect is an important research topic of the supply chain management. The Bullwhip effect is precarious to both short and long run competitive advantage, the dependability sustainability advantage of the chain. This paper proposes to show the impact of the Bullwhip effect on the supply chain using experimentally simulated data from Beer distribution game. The game represents a simple supply chain which consists of factory, distributor, wholesaler and retailer. The paper used empirical models of ANOVA, spectral density estimation, ARMAX and Cochrane- Orcutt autoregression. The result of the study prevails that when we quantify the impact of the Bullwhip effect to different actors of the supply chain with respect of inventory holding cost and stock-out case it is found that different cost implications. When quantifying the impact of the Bullwhip effect to the whole supply chain it is found that at least one of the competitive advantages of the chain is lost. When generalizing it the all the actors in the supply chain will suffer from the Bullwhip effect. The overall evidence from statistical causality analysis suggest that without proper both intra-organizational and inter-organizational coordination of the companies across the supply chain it is difficult to have effective and efficient customer relationship management, customer demand management and inventory management.
4
Ma, Le, Yi Chai, Ying Ying Zhang, and Lu Zheng. "Modeling and Analysis of the Bullwhip Effect in Remanufacturing Closed-Loop Supply Chain." Applied Mechanics and Materials 541-542 (March 2014): 1556–61. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.1556.
Full textAbstract:
In this paper, the closed-loop supply chain bullwhip effect as the research object, according to the bullwhip effect value comparison shows the existence of reverse supply chain can reduce the bullwhip effect, and recovery products rate is higher, the effect of reducing the bullwhip effect is more obvious. In demand mutations conditions, recovery products rate higher the bullwhip effect in favor weakened. In the random demand conditions, with the recovery products rate increases, suppliers bullwhip effect decreased significantly.
5
Ma, Junhai, and Xiaogang Ma. "A Comparison of Bullwhip Effect under Various Forecasting Techniques in Supply Chains with Two Retailers." Abstract and Applied Analysis 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/796384.
Full textAbstract:
We examine the impact of three forecasting methods on the bullwhip effect in a two-stage supply chain with one supplier and two retailers. A first order mixed autoregressive-moving average model (ARMA(1, 1)) performs the demand forecast and an order-up-to inventory policy characterizes the inventory decision. The bullwhip effect is measured, respectively, under the minimum mean-squared error (MMSE), moving average (MA), and exponential smoothing (ES) forecasting techniques. The effect of parameters on the bullwhip effect under three forecasting methods is analyzed and the bullwhip effect under three forecasting methods is compared. Conclusions indicate that different forecasting methods lead to different bullwhip effects caused by lead time, underlying parameters of the demand process, market competition, and the consistency of demand volatility between two retailers. Moreover, some suggestions are present to help managers to select the forecasting method that yields the lowest bullwhip effect.
6
Gupta, Sachin, and Anurag Saxena. "Predicting the impact of operational and financial variables on bullwhip effect using threshold regression: Indian context." Journal of Global Operations and Strategic Sourcing 13, no. 2 (May 25, 2020): 211–27. http://dx.doi.org/10.1108/jgoss-05-2019-0040.
Full textAbstract:
Purpose The operational aspects of supply chain, when handled correctly, results in diminishing the impact of the bullwhip effect. The purpose of this study is to analyze the impact of operational and financial variables on the bullwhip effect. Various operational factors that contribute to the bullwhip effect in a supply chain are identified and their impact on variability in production is measured at manufacturer’s end in the supply chain. Design/methodology/approach Ten different sectors of the Indian economy are identified and analyzed on the basis of bullwhip effect. The ratio of change in production with respect to change in demand is taken as a metric to measure the bullwhip effect. Initially, the impact of identified variables on bullwhip effect is analyzed using the linear regression analysis and then to gain more insights, the threshold regression model is applied according to the change in bullwhip ratio. Findings The study identifies four threshold regions in which bullwhip ratio is changing its slope considerably. The operational and financial variables impacting bullwhip effect differently in these four regions provide useful insights about how the variables are impacting the bullwhip effect. Research limitations/implications Past 11 years of observations on identified operational and financial variables are studied for ten different sectors. The operational and financial variables are identified on basis of available literature but may not be exhaustive in nature. Practical implications The present study implies that the emphasis must be given to the magnitude of the bullwhip ratio. Strategies must be adopted that result in mitigation of bullwhip effect. Such mitigation strategies must not only be restricted on the basis of type of product or sector, perhaps they must be on the basis of threshold region of bullwhip ratio. Originality/value The study suggests a novel approach to study the bullwhip effect in supply chain management using the application of threshold regression considering the bullwhip ratio as a threshold variable.
7
Chao, Yu Fang. "The Bullwhip Effect in Supply Chain and Countermeasures." Advanced Materials Research 711 (June 2013): 799–804. http://dx.doi.org/10.4028/www.scientific.net/amr.711.799.
Full textAbstract:
As supply chain involves a wide spread of enterprises, it is inevitable to have a bullwhip effect. The reason, why bullwhip effect occurs, includes such factors as demand forecast, delay in delivery, bulk orders and others. Bullwhip effect results increased inventory, differences in supply and demand, posing great risks on enterprise operation. To reducing the bullwhip effect in supply chains, such strategies as establishing an information-sharing platform, establishing strategic partnerships, direct ship and transit, stabling market demand fluctuations, should be taken, which will improve the competitiveness of enterprises in supply chain.
8
Ma, Junhai, Binshuo Bao, and Xiaogang Ma. "Inherent Complexity Research on the Bullwhip Effect in Supply Chains with Two Retailers: The Impact of Three Forecasting Methods Considering Market Share." Abstract and Applied Analysis 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/306907.
Full textAbstract:
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.
9
Zhang, Ji Hai, and Quan Quan Zhang. "The System Dynamics Analyses of Bullwhip Effect in China Processed Oil Supply Chain." Applied Mechanics and Materials 295-298 (February 2013): 3310–17. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.3310.
Full textAbstract:
Bullwhip effect is a serious problem in supply chain management, it brings about production disorder, inventory imbalance, business process obstruction, waste of resources and market chaos. Our processed oil supply chain is so a large complicated system that bullwhip effect of it is more serious. To deal this problem, this paper discussed China processed oil supply chain, aim at maintaining processed oil supply, analysed the strength of bullwhip effect in the chain, proved delay is the basic reason of bullwhip effect and pointed out reducing delay is the key point to weaken bullwhip effect. We used system dynamics analysis and Anylogic simulation software to get the conclusion. Finally, we put forward some effective strategies to deal with bullwhip effect in China processed oil supply chain for improving the chain's operating efficiency.
10
Nagaraja, Chaitra H., and Tucker McElroy. "The multivariate bullwhip effect." European Journal of Operational Research 267, no. 1 (May 2018): 96–106. http://dx.doi.org/10.1016/j.ejor.2017.11.015.
Full text
11
Akkermans, Henk, and Chris Voss. "The service bullwhip effect." International Journal of Operations & Production Management 33, no. 6 (May 17, 2013): 765–88. http://dx.doi.org/10.1108/ijopm-10-2012-0402.
Full text
12
Susanto, Indra Kusumajati, and RR Rieka F. Hutami. "Analisis bullwhip effect dalam sistem rantai pasok pada produk Abon dan Dendeng Sapi Asri." Operations Excellence: Journal of Applied Industrial Engineering 13, no. 2 (August 5, 2021): 169. http://dx.doi.org/10.22441/oe.2021.v13.i2.016.
Full textAbstract:
One of the obstacles facing micro, small and medium-sized enterprises (MSMEs) in Indonesia is the bullwhip effect. The bullwhip effect is an event that occurs in the supply chain due to an increase in order fluctuations or order cancellations due to information distortions. This study aims to determine the value of the bullwhip effect and explain the main causes of its occurrence in order to explain about the approach to reducing the bullwhip effect in micro, small and medium-sized enterprises (MSMEs) in Indonesia that operational management can be maximized through operational management. This study uses quantitative methods to determine the value of the bullwhip effect. And qualitative methods are used to identify the root cause and reduction of the bullwhip effect. With primary data from interviews. In addition, secondary data comes from demand data and order data on products for distributors and retailers managed by the company. The results showed that the value of the bullwhip effect on the product at one of the micro, small and medium-sized enterprises (MSMEs) in Indonesia was almost completely above 1.00 and above the specified parameters. This provides information that there is a product bullwhip effect in one of the micro, small and medium-sized enterprises (MSMEs) in Indonesia. Meanwhile, the main cause of the bullwhip effect in one of the smallest, small and medium-sized enterprises (MSMEs) in Indonesia is a demand forecast error.
13
Dyah Lintang Trenggonowati, Maria Ulfah, Asep Ridwan, and Rasie Arthafia. "Proposed Improvement on Supply Chain System to Minimize The Bullwhip Effect Phenomenon with Monte Carlo Simulation Approach." Journal of Innovation and Technology 2, no. 2 (October 31, 2021): 40–45. http://dx.doi.org/10.31629/jit.v2i2.3854.
Full textAbstract:
PT XYZ is one of the most company which produce welded steel pipe in Indonesia such as longitudinal and spiral pipes. In order to meet consumer’s demand, this company faced with an obstacle namely the distortion of information in supply chain. Distortion of information from downstream to upstream channel causes the difference between the product demand from consumer to PT XYZ and order of raw materials from PT XYZ to the supplier which is called the bullwhip effect. The objective of this research is to calculate the value of bullwhip effect as well as designing improvements to minimize the bullwhip effect. Based on the research results, obtained the index value of bullwhip effect on longitudinal pipe products is 1.06 and the index value of bullwhip effect on spiral pipe products is 0.80. The improvement design to minimize the phenomenon of bullwhip effect is to build an integrated information system for the customer, manufacturer, and supplier. The method that is used to improve the index value of bullwhip effect is Monte Carlo simulation. Monte Carlo simulation is used to obtain the order number of raw materials in order to approach the number of consumer’s demand. After applying the Monte Carlo simulation, obtained the index value of bullwhip effect on longitudinal pipe product is 1.01 and the index value of bullwhip effect on spiral pipe products is 1.00. It can be concluded that the use of Monte Carlo simulation had been optimizing the index value of bullwhip effect amounted to 4.71% for longitudinal pipe products and 25% for spiral pipe products.
14
Jaya, Anugrah Putra, and Syamsul Bachri. "MENGUKUR BULLWHIP EFFECT PRODUK MAS (PADA JARINGAN SUPPLY CHAIN PT.SEMBILAN PILAR UTAMA DAN SWALAYAN KOYA)." Managament Insight: Jurnal Ilmiah Manajemen 12, no. 2 (June 28, 2019): 101–17. http://dx.doi.org/10.33369/insight.12.2.101-117.
Full textAbstract:
The purpose of this study is to measure the bullwhip effect in supply chain MAS 240 ml in PT. Sembilan Pilar Utama and Swalayan Koya. This research measure method is using bullwhip effect method that presented by Fransoo and Wouters (2000). The results of research, we know that the bullwhip effect happened because of the coefficient of variation orders higher than the coefficient of variation in product demand, inaccurate demand prediction, and order batching. The solution that may be effective to reduce the bullwhip effect that occurs is more concerned with the pattern of order and the product demand.Keywords: supply chain management, bullwhip effect.
15
Brito, Gabriela Dias, Pedro Dias Pinto, and Adriano David Monteiro de Barros. "Reverse bullwhip effect: duality of a dynamic model of Supply Chain." Independent Journal of Management & Production 11, no. 6 (October 1, 2020): 2043. http://dx.doi.org/10.14807/ijmp.v11i6.1043.
Full textAbstract:
This study aims to investigate control strategies for the bullwhip effect based on a dynamic model of the linear supply chain, proposed by Helbing and Lammer (2005), which describes the inventory dynamics and production rates of productive units. We simulated the model for instability and stability conditions defined by mathematical analysis. Through these results, we verified both classical and reverse bullwhip effects associated with instability and stability conditions, respectively. The model revealed a duality once the control strategy proposed by Helbing and Lamer (2005) for the classical bullwhip effect ends up causing a reverse effect, which is equally troubling. In the reverse bullwhip effect, we observed amplification of the production rates in the network chains from the supplier to the customer in a way that the upstream chain was not able to meet the needs of the downstream chain. To withhold both effects, we suggest the dynamic control of the parameters that describe the network based on Helbing and Lammer (2005) model.
16
Verma, Mona, Reena Jain, and Chandra K. Jaggi. "Impact of Price-Sensitive Demand and Premium Payment Scheme on Bullwhip Effect." International Journal of Information Systems and Supply Chain Management 15, no. 1 (January 2022): 1–24. http://dx.doi.org/10.4018/ijisscm.289225.
Full textAbstract:
Bullwhip effect reduces the efficiency, responsiveness, and value of the supply chain. There are some indirect causes like lead time, the number of echelons, and some direct causes of bullwhip effect such as rationing or price variation. Due to capacity constraints, retailers are forced to experience rationing of their demands. Fear of rationing usually gives rise to manipulable demand and hence increases the bullwhip effect. Moreover, if the retailer’s demand is price sensitive then it will cause price variation. The offerings of premium payment by retailers due to unfulfilled demand lure the supplier to extend his existing capacity and to allocate them more supply. In this paper, an attempt has been made to mitigate the impact of the bullwhip effect using a premium payment scheme. A technique has been coined that will help in reducing the bullwhip effect. The increased value of the supply chain on using a premium payment scheme is proof of the reduction of the bullwhip effect. Results are validated through numerical analysis.
17
Gupta, Sachin, and Anurag Saxena. "Classification of Operational and Financial Variables Affecting the Bullwhip Effect in Indian Sectors: A Machine Learning Approach." Recent Patents on Computer Science 12, no. 3 (May 8, 2019): 171–79. http://dx.doi.org/10.2174/2213275911666181012121059.
Full textAbstract:
Background: The increased variability in production or procurement with respect to less increase of variability in demand or sales is considered as bullwhip effect. Bullwhip effect is considered as an encumbrance in optimization of supply chain as it causes inadequacy in the supply chain. Various operations and supply chain management consultants, managers and researchers are doing a rigorous study to find the causes behind the dynamic nature of the supply chain management and have listed shorter product life cycle, change in technology, change in consumer preference and era of globalization, to name a few. Most of the literature that explored bullwhip effect is found to be based on simulations and mathematical models. Exploring bullwhip effect using machine learning is the novel approach of the present study. Methods: Present study explores the operational and financial variables affecting the bullwhip effect on the basis of secondary data. Data mining and machine learning techniques are used to explore the variables affecting bullwhip effect in Indian sectors. Rapid Miner tool has been used for data mining and 10-fold cross validation has been performed. Weka Alternating Decision Tree (w-ADT) has been built for decision makers to mitigate bullwhip effect after the classification. Results: Out of the 19 selected variables affecting bullwhip effect 7 variables have been selected which have highest accuracy level with minimum deviation. Conclusion: Classification technique using machine learning provides an effective tool and techniques to explore bullwhip effect in supply chain management.
18
Zhao, Rong, Raj Mashruwala, Shailendra Pandit, and Jaydeep Balakrishnan. "Supply chain relational capital and the bullwhip effect." International Journal of Operations & Production Management 39, no. 5 (August 15, 2019): 658–89. http://dx.doi.org/10.1108/ijopm-03-2018-0186.
Full textAbstract:
Purpose The purpose of this paper is to conduct a large-sample empirical investigation of how relational capital impacts bullwhip at the supplier. Design/methodology/approach The study uses mandatory disclosures in regulatory filings of US firms to identify a supplier’s major customers and constructs empirical proxies of supply chain relational capital, i.e., length of the relationship between suppliers and customers and partner interdependence. Multivariate regression analyses are performed to examine the effects of relational capital on bullwhip at the supplier. Findings The findings show that bullwhip at the supplier is greater when customers are more dependent on their suppliers, but is reduced when suppliers share longer relationships with their customers. The results also provide additional insights on several firm characteristics that impact supplier bullwhip, including shocks in order backlog, selling intensity and variations in profit margins. Furthermore, the authors document that the effect of supply chain relationships on bullwhip tends to vary across industries and over time. Originality/value The study employs a novel data set that is constructed using firms’ financial disclosures. This large panel data set consisting of 13,993 observations over 36 years enables thorough and robust analyses to characterize supply chain relationships and gain a deeper understanding of their impact on bullwhip.
19
Lestari, Puji, Liong Irena, and I. Gede Agus Widyadana. "PENGARUH PENENTUAN JUMLAH PEMESANAN PADA BULLWHIP EFFECT." J@ti Undip : Jurnal Teknik Industri 12, no. 1 (March 22, 2017): 49. http://dx.doi.org/10.14710/jati.12.1.49-56.
Full textAbstract:
Bullwhip effect adalah suatu kondisi dimana terjadi peningkatan variasi permintaan dalam suatu rantai pasok. Bullwhip effect ini dapat diakibatkan oleh beberapa faktor salah satunya yaitu jumlah pemesanan. Jumlah pemesanan yang dilakukan oleh masing-masing pemasok akan mempengaruhi jumlah pemesanan pada pemasok yang lain. Perbedaan jumlah pemesanan antar pemasok ini akan menimbulkan bullwhip effect. Penelitian ini akan menunjukkan pengaruh penentuan jumlah pemesanan terhadap bullwhip effect dengan menggunakan metode Silver Meal dan Lot For Lot. Hasil yang diperoleh diukur dengan melihat perbedaan biaya per unit pada keseluruhan rantai pasok. Hasil penelitian menunjukkan bahwa pihak pembeli lebih baik menggunakan metode Silver Meal karena variasi permintaan masih mewakili permintaan yang sebenarnya sedangkan pada pihak penjual lebih baik menggunakan Lot For Lot karena variasi permintaan sudah tidak dapat mewakili permintaan sebenarnya. Penggunaan metode Lot For Lot pada pihak penjual menyebabkan variasi permintaan yang sudah tidak mewakili permintaan sebenarnya tidak diperhitungkan. AbstractBullwhip effect is the increased variability of demand in supply chain. Order quantity could be a factor that cause bullwhip effect. Deciding order quantity by an actor in supply chain will affect the order quantity by the other actors. Different order quantity is known as bullwhip effect. This research will show the effect of lot sizing, Silver Meal and Lot For Lot, on bullwhip effect. The result could be seen on the cost per unit in supply chain. The result shows that Silver Meal is better used by a buyer because demand variation could present the real demand, while Lot For Lot is better used by a seller because demand variation could not present the real demand. Using Lot For Lot causes the demand variation is not included.
20
Yuan, Xigang, Xiaoqing Zhang, and Dalin Zhang. "Analysis of the Impact of Different Forecasting Techniques on the Inventory Bullwhip Effect in Two Parallel Supply Chains with a Competition Effect." Journal of Engineering 2020 (September 11, 2020): 1–28. http://dx.doi.org/10.1155/2020/2987218.
Full textAbstract:
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.
21
Woo, Shin Sc, Ya Hui Li, Xi Feng Lu, and Yu Quan Du. "Some Simulation Results on Bullwhip Effect in Supply Chain with Several Dealers." Advanced Materials Research 774-776 (September 2013): 1979–86. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.1979.
Full textAbstract:
In order to discuss the bullwhip effect in the supply chain with several dealers, a four-level supply chain model is developed based on system dynamics. Through the use of dynamic simulation, the bullwhip effect was evaluated based on several factors such as return proportion, direct utilization proportion of recycling products and sales plan of each dealer. Experimental results show that a higher return proportion and a more direct utilization of recycled products can mitigate the bullwhip effect. Moreover, different sales plan of each dealer has various degrees of influence on the bullwhip effect.
22
HU, Yize. "The Impacts of Supplier-Base Concentration on Bullwhip Effect: Evidence from Chinese Manufacturing Firms." Revista de Cercetare si Interventie Sociala 64 (March 6, 2019): 262–75. http://dx.doi.org/10.33788/rcis.64.21.
Full textAbstract:
This paper empirically tests the influence of supplier-base concentration on the size of the bullwhip effect of enterprises. The study quantifies bullwhip effect of the enterprise by the ratio of fluctuations in production and the fluctuations in demand in each of the four quarters of each year. The study found that about half of the listed manufacturers in China have a bullwhip effect, and the size of the bullwhip effect of the enterprise is very heterogeneous. Empirical analysis found that after controlling the quarterly ratio of demand, the persistence of demand shock, the number of days of inventory holding, the gross profit margin, the size of the enterprise, and the lead time, the concentration of suppliers was significantly negatively correlated with the size of the bullwhip effect. This shows that the more concentrated the supplier of the enterprise, the closer the company and the supplier are in information sharing and production cooperation, and the shorter the company will be from receiving the order to delivering the goods to the customer. The rapid response of the company to customer demand reduces the distortion of demand and therefore reduces the bullwhip effect.
23
Hsu, Chih-Hung, Xue-Hua Yang, Ting-Yi Zhang, An-Yuan Chang, and Qing-Wen Zheng. "Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 7 (December 10, 2021): 3375–405. http://dx.doi.org/10.3390/jtaer16070183.
Full textAbstract:
With the development of economic globalization, the uncertainty of supply chains is also increasing, and alleviating the bullwhip effect has become an important issue. From previous discussions on alleviating the bullwhip effect, there was no research on alleviating it by enhancing supply chain agility through improving big data. Moreover, it has not been found that quality function deployment is used to analyze the interdependence between big data and supply chain agility, as well as between supply chain agility and the bullwhip effect. In particular, the interaction of bullwhip effect factors are not considered. In this study, the multicriteria decision-making integrated framework is proposed and the largest relay manufacturer in China is taken to identify key big data enablers to enhance supply chain agility and mitigate the bullwhip effect, thus providing an effective method for electronic equipment manufacturing enterprises to develop a supply chain that can quickly respond to changes and uncertainties. These big data enablers can enhance supply chain agility and reduce the bullwhip effect. This framework provides an effective method for electronic manufacturers to formulate supply chain agility indicators and big data enablers to mitigate the bullwhip effect and also provides a reference for other manufacturing enterprises in supply chain management.
24
Febryanto, Indra. "ANALISIS BULLWHIP EFFECT PADA PERENCANAAN KEBUTUHAN MATERIAL BELT CONVEYOR." WAHANA 70, no. 1 (June 1, 2018): 47–51. http://dx.doi.org/10.36456/wahana.v70i1.1567.
Full textAbstract:
Controlling the supply of raw materials belt conveyor is a very important management function because it is a vital company investment, both in terms of value and future prospects. Well-implemented inventory control management can trigger a company's success in production. In manufacturing companies there is often a delay in the arrival of material arrival due to various things, such as the bullwhip effect between the company with suppliers, companies with distributors or companies with buyers. The focus of this research is to know how big the occurrence of bullwhip effect and how to decrease the bullwhip effect that already happened. From the calculation results obtained a decrease in the value of the bullwhip effect from the original to PU White products 2,786 to 1,524, blue PU products 3,297 to 1,455, and PVC Green 2.025 to 1.5794.
25
Maserih, Maserih. "Analisis Bullwhip Effect Dan Day Of Inventory (Doi) Serta Implikasinya Terhadap Supply Chain Management." Jurnal STEI Ekonomi 26, no. 01 (September 4, 2017): 123–35. http://dx.doi.org/10.36406/jemi.v26i01.199.
Full textAbstract:
Tesis ini bertujuan untuk mengukur Bullwhip Effectdan Day Of Inventory(DOI) di PT. XYZ Tbks, serta untuk menganalisis apakah Bullwhip Effect dan Day Of Inventory tersebut dapat memberikan dampak terhadap Supply Chain Management di PT. XYZ Tbk.Metode yang digunakan dalam penelitian ini adalah analisis deskriptif dengan metode pengumpulan data melalui studi pustaka, observasi, interview. Dari hasil penulisan dapat diketahui bahwa dengan meminimalkan Bullwhip Effect maka akan menekan angka Day Of Inventory.Bullwhip Effect sangat berdampak pada Supply Chain Management oleh karena itu perlu ditangani dengan sebaik baiknya.Day Of Inventory (DOI) sangat berdampak pada Supply Chain Management oleh sebab itu perlu ditangani dengan sebaik baiknya. Dengan meminimalkan Bullwhip Effect dan Day Of Inventory akan membantu meningkatkan kinerja Suply ChainManagement.
26
Durán Peña, Julián Andrés, Ángel Ortiz Bas, and Nydia Marcela Reyes Maldonado. "Impact of Bullwhip Effect in Quality and Waste in Perishable Supply Chain." Processes 9, no. 7 (July 16, 2021): 1232. http://dx.doi.org/10.3390/pr9071232.
Full textAbstract:
The bullwhip effect results from inefficiencies in the supply chain; in perishable products, the inefficiencies are quality in the supply chain and product waste. We carried out a literature review to determine the causes of the bullwhip effect and the supply chain’s quality factors of this phenomenon’s perishable products. Update the demand, the level of deterioration of the product, and the number of intermediaries is the causes of the bullwhip effect most investigated. On the other hand, the product’s safety and the quality of the information are the quality factors of the chain of supplies of perishable products more researched. Future research should address the causes of human behavior that affect the bullwhip effect in the perishable goods supply chain.
27
Megawati, Yulie. "IDENTIFICATION EXISTENCE OF BULLWHIP EFFECT ON SUPPLY CHAIN PT. ABC." Business and Entrepreneurial Review 9, no. 1 (March 30, 2016): 91. http://dx.doi.org/10.25105/ber.v9i1.25.
Full textAbstract:
Bullwhip effect is the main evidence of inefficiency in the supply chain of a company. Bullwhip effect describes the tendency of increasing the number of purchases of raw material supply chain<br />as a result of the inability to predict the increase in the number of requests. This study is the high level of inventory, whether as a result of the bullwhip effect or was due to an increase in demand. The purpose of this study was to determine the contribution of each factor causes of the bullwhip effect, identify the factors that provide the greatest impact on supply chain performance and find solutions to reduce the impact caused. The approach of this research is done by collecting data for inventory movement in the period 2003-2007, analyzing the interaction between members in the supply chain. Theory - the theory was used to create a research model. Data analysis is done by analyzing graphs and statistical analysis for the right to draw conclusions from this research. Results from this study that the coordination of “end to end” supply chain to reduce the impact of<br />bullwhip effect in supply chain
28
He, Suchao, Xigang Yuan, and Xiaoqing Zhang. "The Government’s Environment Policy Index Impact on Recycler Behavior in Electronic Products Closed-Loop Supply Chain." Discrete Dynamics in Nature and Society 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/7646248.
Full textAbstract:
We establish the model of multilevel closed-loop supply chain (CLSC) which included raw material supplier, manufacturer, distributor, retailer, and third-party recycler based on system dynamics (SD). Considering factors which influence recycler behavior-environmental policy index and recovery delay, we apply SD software—Vensim—to simulate CLSC model and study recycler behavior’s influence on the entire CLSC through calculating the bullwhip effect of all levels members order rate. Research shows that (1) the larger the environmental policy index, the greater the recycle proportion and the better the effect of weakening retailer’s order rate in forward supply chain, which however, increasingly, strengthen the reverse supply chain bullwhip effect, (2) the shorter the recovery delay, the better the effect of weakening the forward supply chain bullwhip effect and the longer the recovery delay, which increasingly weakens the reverse supply chain bullwhip effect, and (3) the effect of environmental policy index on the bullwhip effect of all levels members order rate is more significant than recovery delay.
29
Jin, Yao 'Henry', Brent D. Williams, Matthew A. Waller, and Adriana Rossiter Hofer. "Masking the bullwhip effect in retail: the influence of data aggregation." International Journal of Physical Distribution & Logistics Management 45, no. 8 (September 7, 2015): 814–30. http://dx.doi.org/10.1108/ijpdlm-11-2014-0264.
Full textAbstract:
Purpose – The accurate measurement of demand variability amplification across different nodes in the supply chain, or “bullwhip effect,” is critical for firms to achieve more efficient inventory, production, and ordering planning processes. Building on recent analytical research that suggests that data aggregation tends to mask the bullwhip effect in the retail industry, the purpose of this paper is to empirically investigate whether different patterns of data aggregation influence its measurement. Design/methodology/approach – Utilizing weekly, product-level order and sales data from three product categories of a consumer packaged goods manufacturer, the study uses hierarchical linear modeling to empirically test the effects of data aggregation on different measures of bullwhip. Findings – The authors findings lend strong support to the masking effect of aggregating sales and order data along product-location and temporal dimensions, as well as the dampening effect of seasonality on the measurement of the bullwhip effect. Research limitations/implications – These findings indicate that inconsistencies found in the literature may be due to measurement aggregation and statistical techniques, both of which should be applied with care by academics and practitioners in order to preserve the fidelity of their analyses. Originality/value – Using product-weekly level data that cover both seasonal and non-seasonal demand, this study is the first, to the author’s knowledge, to systematically aggregate data up to category and monthly levels to empirically examine the impact of data aggregation and seasonality on bullwhip measurement.
30
Aslan, Tunay. "SIMULATED CHAOS IN BULLWHIP EFFECT." Pressacademia 2, no. 1 (June 30, 2015): 37. http://dx.doi.org/10.17261/pressacademia.2015111603.
Full text
31
Duan, Yongrui, Yuliang Yao, and Jiazhen Huo. "Bullwhip effect under substitute products." Journal of Operations Management 36, no. 1 (March 9, 2015): 75–89. http://dx.doi.org/10.1016/j.jom.2015.03.002.
Full text
32
Chatfield, Dean C., and Alan M. Pritchard. "Returns and the bullwhip effect." Transportation Research Part E: Logistics and Transportation Review 49, no. 1 (January 2013): 159–75. http://dx.doi.org/10.1016/j.tre.2012.08.004.
Full text
33
Cannella, S., A. P. Barbosa-Póvoa, J. M. Framinan, and S. Relvas. "Metrics for bullwhip effect analysis." Journal of the Operational Research Society 64, no. 1 (January 2013): 1–16. http://dx.doi.org/10.1057/jors.2011.139.
Full text
34
Özelkan, Ertunga C., and Metin Çakanyıldırım. "Reverse bullwhip effect in pricing." European Journal of Operational Research 192, no. 1 (January 2009): 302–12. http://dx.doi.org/10.1016/j.ejor.2007.09.009.
Full text
35
Yuliana, Pram Eliyah, and Sri Rahayu. "Analisis Pengaruh Penerapan Metode DRP Terhadap Bullwhip Effect Pada Rantai Suplai." Journal of Information System,Graphics, Hospitality and Technology 1, no. 02 (October 31, 2019): 42–46. http://dx.doi.org/10.37823/insight.v1i02.46.
Full textAbstract:
Dalam sebuah rantai suplai, aliran informasi yang akurat dari setiap tahapan sangat penting untuk memenuhi kebutuhan konsumen. Distorsi informasi mengakibatkan pola permintaan yang semakin fluktuatif kearah hulu dalam rantai suplai. Meningkatnya fluktuasi atau variabilitas permintaan dari hilir ke hulu suatu rantai suplai dinamakan bullwhip effect (BE). Nilai BE didapat dari perbandingan antara kebutuhan dan pemesanan yang dilakukan untuk memenuhi permintaan. Nilai BE yang ideal adalah 1, yang berarti terdapat keseimbangan antara kebutuhan dan pemesanan yang dilakukan sehingga tidak menyebabkan penumpukan ataupun kekurangan persediaan. Ada beberapa hal yang bisa menyebabkan terjadinya bullwhip effect, diantaranya order batching, yaitu penentuan ukuran pemesanan pada setiap tahapan rantai suplai.
Pada penelitian ini akan dilakukan analisis pengaruh penerapan metode Distribution Requirement Planning (DRP) terhadap Bullwhip Effect pada level sub distributor ke distributor utama. Distribution Requirement Planning adalah suatu metode untuk menangani pengadaan persediaan dalam suatu jaringan distribusi multi eselon Dengan membuat DPR maka pemesanan dapat direncanakan dengan baik sesuai dengan permintaan dari eselon dibawahnya dalam rantai suplai. Studi kasus dilakukan pada distributor minyak goreng UD Trimei yang melayani beberapa sub distributor di wilayah Jawa Timur dan diambil contoh dua jenis produk yaitu Hemart 500 ml dan Hemart 1000 ml. Pada UD Trimei sering terjadi ketidaksesuaian stock karena tidak adanya perencanaan terhadap ketersediaan produk pada distributor ini. Masalah tersebut diselesaikan dengan metode distribution requirement planning untuk menentukan jumlah pemesanan pada perusahaan. Setelah metode ini diterapkan untuk merencanakan kebutuhan kedepan pada perusahaan ini, keadaan membaik yang ditandai dengan nilai bullwhip effect yang mendekati nilai 1. Nilai bullwhip effect sebelum penerapan metode distribution requirement planning pada produk Hemart 500ml adalah 3.18 sedang pada produk Hemart 1000 ml adalah 2.89 .Setelah penerapan metode distribution requirement planning nilai bullwhip effect Hemart 500ml menjadi 1.07 dan untuk produk Hemart 1000 ml menjadi 0,99.
Kata Kunci—Bullwhip Effect, Rantai Supplai, Order Batching, DRP.
36
Apriyani, Dwi, Rita Nurmalina, and Burhanuddin Burhanuddin. "Bullwhip Effect Study in Leaf Organic Supply Chain." AGRARIS: Journal of Agribusiness and Rural Development Research 7, no. 1 (January 15, 2021): 1–10. http://dx.doi.org/10.18196/agraris.v7i1.9842.
Full textAbstract:
The mismatch between the availability of vegetables and consumer demand is one of the causes of inefficient supply chains. This study aims to analyze the bullwhip effect on the organic leaf vegetable supply chain at PT Simply Fresh Organic (SFO). The analysis method used is a comparison between the coefficient of variation of orders created with the coefficient of variation in requests received by each supply chain institution. The data used are secondary data obtained from PT SFO. The measurement results show that the supply chain flow of organic leaf vegetables had a bullwhip effect at the PT SFO level and no bullwhip effect occurs at the retail level. The value of the BE supply chain value calculation at PT SFO shows a higher figure than at the retail level. The bullwhip effect at PT SFO occurred because of a rationing and shortage gaming policy. Therefore, each member of the supply chain must maintain transparency of data information and utilize digital technology to improve the accuracy of data forecasting requests and reservations quickly.
37
Dong, Hai, Jin Hua Liu, and Liang Yu Liu. "Optimization Control of the Bullwhip Effect in Supply Chain Inventory." Advanced Materials Research 945-949 (June 2014): 3187–90. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.3187.
Full textAbstract:
The bullwhip effect was caused by fuzzy demand among the enterprises. In order to reduce this effect, control theory was applied to solve the inventory in supply chain. Firstly, inventory control in supply chain and the bullwhip effect was researched. Secondly, a kind of proportional integral differential (PID) controller was developed for inventory control in a three-level supply chain, and the mathematical model of the PID controller for inventory control was presented. Finally, the results show that the PID controller can evidently alleviate the bullwhip effect and inventory fluctuations under the suitable combination of control gain.
38
Taylor, Maxwell M. "A Critical Evaluation Of Empirical Non-Linear Control System And System Dynamics Modeling Theories For Mitigating Risks Arising From Bullwhip Effect." International Journal of Management & Information Systems (IJMIS) 20, no. 1 (January 13, 2016): 1. http://dx.doi.org/10.19030/ijmis.v20i1.9550.
Full textAbstract:
Bullwhip effect is a threat observed in multi-echelon supply chains, which is one of the prominent indicators of inefficiencies in a supply chain. Primarily, bullwhip effect occurs as a result of disruptions in information and materials flow, lead-time delays, lack of coordination, and panic stocking amidst visibility into local risk factors. When bullwhip effect occurs, the demand variations entering the supply chain from the customer end amplifies gradually as it flows upstream towards the supplier ends. This may cause unused inventory and may later lead to wastage and obsolescence. Bullwhip effect can be curbed through many approaches. This study has focused on control theory approach that promotes small-scale control behaviors throughout the supply chain to dampen the bullwhip tidal waves. The approach investigated in this research is a combination of control system modeling and systems dynamics modeling, which is not researched adequately by bullwhip academics. Based on the investigations, a six-step approach for reducing Bullwhip effect is proposed in this research and illustrated with examples. The six-step approach comprises of first-level multi-echelon survey to derive the initial system dynamics model, second-level survey to collect primary data for all the variables and relationships formed, principal component analysis and Cronbach Alpha / split-half testing for reliability, verification, and validity testing and exploring the best optimal construct using structural equation modeling, and finally, applying controllers to the optimal systems dynamics model through interpretive analysis of the model.
39
Latuny, W., and Wisnu M. S. Picauly. "ANALISIS BULLWHIP EFFECT DENGAN MENGGUNAKAN METODE PERAMALAN PADA SUPPLY CHAIN DI DISTRIBUTOR PT. SEMEN TONASA (Studi Kasus: Distributor PT. Semen Tonasa)." ARIKA 13, no. 2 (September 25, 2019): 113–26. http://dx.doi.org/10.30598/arika.2019.13.2.113.
Full textAbstract:
Bullwhip effect merupakan fenomena pada supply chain, dimana adanya perbedaan jumlah permintaan konsumen ditiap periode baik itu semakin sedikit atau semakin banyak yang dapat berpengaruh pada semua tingkatan dalam supply chain. Hal itu juga yang dialami dari Sub Distributor PT. Padi Mas Prima yang mendistribusikan Produk Semen Tonasa pada tiap ritel di kota ambon yaitu ritel Aneka Guna,Ritel Benua dan Ritel Wayame Adapun tujuan penelitian ini Menganalisis Bullwhip Effect dengan metode peramalan dan meminimalisasi terjadinya bullwhip effect. Perhitungan bullwhip effect menggunakan pendekatan model Moving Average dan Single Exponential Smoothing yang akan dipilih berdasarkan Mean Absolute Deviation dan Tracking Signal Hasil dari penelitian model yang dipilih adalah model Single Exponential Smoothing diperoleh hasil dari peramalan selama 12 periode, dari hasil peramalan tersebut menunjukkan adanya penurunan nilai bullwhip effect pada Sub Distributor PT. Padi Mas Prima, yang sebelumnya 1.02 nilainya menjadi 0.18 dengan tingkat presentase penurunan sebesar 82.4%, Ritel Aneka Guna yang nilainya 1.07 menjadi 0.71 dengan tingkat presentase penurunan sebesar 33.6%, Ritel Benua yang nilainya 1.03 nilainya menurun menjadi 0.86 dengan tingkat presentase penurunan sebesar 16.5%, dan Ritel Wayame yang sebelumnya 1.10 nilainya menurun menjadi 0.96 dengan tingkat presentase penurunan sebesar 12.7%. Dimana nilai bullwhip effect > 1.01 dapat diartikan bahwa terjadi amplifikasi permintaan, sedangkan nilai bullwhip effect < 1.01 dapat diartikan bahawa permintaan masih stabil atau terjadi penghalusan pola permintaan usaha perbaikan dilakukan dengan melakukan pemesanan produk pada supplier dengan memperhatikan jumlah persediaan yang ada, menjaga arus informasi permintaan dan penjualan produk, serta menjaga lead time agar tetap stabil.
40
Mittal, Prabhat. "Impact of Auto-regressive (AR) Process in Bullwhip Analysis in a Multi-location Supply Chain Network." Journal of Business Management and Information Systems 6, no. 1 (June 30, 2019): 19–26. http://dx.doi.org/10.48001/jbmis.2019.0601002.
Full textAbstract:
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.
41
SABILAH, ADE IRPAN. "ANALISA BULLWHIP EFFECT PENGADAAN STOCK FRANCHISE AYAM SABANA." JURNAL REKAYASA SISTEM INDUSTRI 7, no. 1 (December 7, 2021): 1–5. http://dx.doi.org/10.33884/jrsi.v7i1.4461.
Full textAbstract:
The COVID-19 pandemic made some companies must pay attention to all their business needs appropriately and measurably.Strategic use in some companies there are maing the limited on the stock supply, it is expected to reduce the losses that will be experienced by business people. The Sabana franchise has problems in determining the optimal safety stock so that there is no bullwhip effect in the supply chain for these raw materials. The losses caused by the bullwhip effect are not only on product availability but also on storage costs in manufacturers or retailers. The purpose of this study is to determine the value, causes, and proposed solutions to reduce the occurrence of the Bullwhip Effect and can optimally forecast inventory requirements using the Single Exponential Smoothing method.
42
Costantino, Francesco, Giulio Di Gravio, Ahmed Shaban, and Massimo Tronci. "Exploring the Bullwhip Effect and Inventory Stability in a Seasonal Supply Chain." International Journal of Engineering Business Management 5 (January 1, 2013): 23. http://dx.doi.org/10.5772/56833.
Full textAbstract:
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.
43
Ma, Junhai, Jing Zhang, and Liqing Zhu. "Study of the Bullwhip Effect under Various Forecasting Methods in Electronics Supply Chain with Dual Retailers considering Market Share." Complexity 2018 (2018): 1–19. http://dx.doi.org/10.1155/2018/8539740.
Full textAbstract:
We establish in this paper a new two-stage supply chain with one manufacturer and two retailers which have a fixed market share in the mature and stable market with specific reference to consumer electronics industry. This paper offers insights into how the three forecasting methods affect the bullwhip effect considering the market share under the ARMA(1,1) demand process and the order-up-to inventory policy. We also discuss the stability of the order with the theory of entropy. In particular, we derive the expressions of bullwhip effect measure under the MMSE, MA, and ES methods and compare them by numerical simulations. Results show that the MA is always better in contrast to the ES for reducing the bullwhip effect in our supply chain model. When moving average coefficient is lower than a certain value, the MMSE method is the best for reducing the bullwhip effect; otherwise, the MA method is the best. Moreover, the larger the market share of the retailer with a long lead time is, the greater the bullwhip effect is, no matter what the forecasting method is.
44
Sousa, Ribeiro, Relvas, and Barbosa-Póvoa. "Using Machine Learning for Enhancing the Understanding of Bullwhip Effect in the Oil and Gas Industry." Machine Learning and Knowledge Extraction 1, no. 3 (September 6, 2019): 994–1012. http://dx.doi.org/10.3390/make1030057.
Full textAbstract:
Several suppliers of oil and gas (O & G) equipment and services have reported the necessity of making frequent resources planning adjustments due to the variability of demand, which originates in unbalanced production levels. The occurrence of these specific problems for the suppliers and operators is often related to the bullwhip effect. For studying such a problem, a research proposal is herein presented. Studying the bullwhip effect in the O & G industry requires collecting data from different levels of the supply chain, namely: services, upstream and midstream suppliers, and downstream clients. The first phase of the proposed research consists of gathering the available production and financial data. A second phase will be the statistical treatment of the data in order to evaluate the importance of the bullwhip effect in the oil and gas industry. The third phase of the program involves applying artificial neural networks (ANN) to forecast the demand. At this stage, ANN based on different training methods will be used. Further on, the attained mathematical model will be used to simulate the effects of demand fluctuations and assess the bullwhip effect in an oil and gas supply chain.
45
Yuan, Xi Gang, and Nan Zhu. "Bullwhip Effect Analysis in Two-Level Supply Chain Distribution Network Using Different Demand Forecasting Technology." Asia-Pacific Journal of Operational Research 33, no. 03 (June 2016): 1650016. http://dx.doi.org/10.1142/s0217595916500160.
Full textAbstract:
Following the basic work conducted by Lee et al. [(1997a), The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102; (1997b), Information distribution in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558] and using two first-order autoregressive AR(1) models, respectively, this paper provides three quantitative models of the bullwhip effect of the two-level supply chain distribution network consisting of a single manufacturer and two retailers. The paper assumes that two retailers adopt the order point method, uses three kinds of demand forecasting technology, i.e., moving average, exponential smoothing and minimum mean square error methods, respectively, provides three corresponding models for analyzing the impact of bullwhip effect of two-level supply chain distribution network. At the same time, this paper compares and analyzes the results of the three models through simulation.
46
Lampret, Tadeja, and Vojko Potočan. "Bullwhip Effect in the Information Flow of a Supply Chain: A Role of Culture." Logistics & sustainable transport 5, no. 1 (November 1, 2014): 34–45. http://dx.doi.org/10.1515/jlst-2015-0005.
Full textAbstract:
Abstract The main goal of our research is to analyze and display causes of a bullwhip effect formation within a supply chain, as well as to provide the appropriate solutions to limit the occurrence of the bullwhip effect by using the proper information flow and partners’ cooperation within the supply chain. The bullwhip effect is one of the most important issues in the supply chain management and it is present in many companies. It preserves a character of invisibility because there are lots of causes for its formation and they are usually difficult to discern. The bullwhip effect is a phenomenon of an increase in the order variability within a supply chain. The higher we are within the supply chain, the higher is the order variability. The company encountered with the whip effect can successfully reduce its impact by improving the information flow, as well as improving partners’ cooperation within the supply chain. In this way the company can limit its negative repercussions and increase the profit. The article focuses on the overview of the bullwhip effect within a distribution chain, from its causes to suggestions and measures how to ease its negative repercussions on the organisation. Part of the causes could be found in the market demand variability and in the lack of communication about the actual marked demand within the supply chain. The rest of the causes are related to obstacles that emerge among different partners within the supply chain (role of culture). A qualitative analysis is applied on the basis of the selected cognitions from the supply chain management. The quantitative analysis is based on the theoretical research of the effective flow of information among the participants and its contribution to the reduction of the bullwhip impact. The article discusses two research questions: 1) The correct information flow within the supply chain and the improvement of the communication among partners can lead to the bullwhip effect reduction, and 2) A reduction of the bullwhip influence can lead to the increase of cooperation among partners. The results of the analysis can be used for further research.
47
Zeng, Wenlong, Fei Peng, Qiaozhang Hong, and Jinsheng Liu. "Research on the Formation and Solution of the Bullwhip Effect of Electricity Material Reserve." Journal of Physics: Conference Series 2108, no. 1 (November 1, 2021): 012055. http://dx.doi.org/10.1088/1742-6596/2108/1/012055.
Full textAbstract:
Abstract With the deepening of the power system reform together with the transformation and development of power companies, the importance of supply chain management has become increasingly prominent. As an important part of the power supply chain management of power companies, the accuracy of electricity material reserves has an impact on the entire process of the company’s supply chain. This article analyzes the reasons for the bullwhip effect in the process of electricity material storage, points out the harm caused by the bullwhip effect, and proposes ways to weaken the bullwhip effect such as improving the accuracy of demand reserves, strengthening inventory management.
48
Ma, Junhai, Liqing Zhu, Ye Yuan, and Shunqi Hou. "Study of the Bullwhip Effect in a Multistage Supply Chain with Callback Structure considering Two Retailers." Complexity 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/3650148.
Full textAbstract:
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.
49
Patmond Mbhele, Thokozani. "Engineering patterns of supply chain optimization to manage oscillation effect." Problems and Perspectives in Management 15, no. 2 (June 8, 2017): 124–39. http://dx.doi.org/10.21511/ppm.15(2).2017.12.
Full textAbstract:
The cascading order variability from downstream trumping up the upstream site of the supply chain network indicates the deleterious effect to the performance of the fast moving consumer goods industry. The fundamental likelihood to optimization in this industry requires dexterous flows of quasi-real-time information, as well as reliable product availability. In this context, this study analyzes the challenges of bullwhip effect on the perspective of ingenious optimization strategies, and further contemplates to establish the engineering patterns of interrelationships on the magnitude of pooling the resources to advance supply chain capabilities. The suppression of bullwhip effect on underlying optimization strategies is sought to elevate accelerated responsiveness, improve network demand visibility and reduce volatility in frequencies to inventory replenishment. A rigorous and disciplined quantitative approach afforded the tentatively development of pattern of interrelated supply chain dimensions. The factor analysis method was used on 448 responses and insightful findings were produced from the compelling purposive sampling technique. The findings indicate that the magnitude of better ameliorating bullwhip effect, the value of competitive economic information and strength of selected optimization strategies depend on the model of unified engineering patterns. This paper provides insights to FMCG industry on using innovative strategies and modern technology to enhance supply chain visibility through integrated systems networks.
50
Di, Weiya, Junhai Ma, and Xueli Zhan. "Study of the Dynamic Characteristics of BWE Based on Products, Difference With a Two-Stage Supply Chain." International Journal of Information Systems and Supply Chain Management 12, no. 2 (April 2019): 1–21. http://dx.doi.org/10.4018/ijisscm.2019040101.
Full textAbstract:
In previous studies, many researchers have achieved significant success in reducing the negative effects brought about by the bullwhip effect. In this article, the authors have established a supply chain that consists of one supplier and two retailers and has adopted a Cournot-Bertrand mixed duopoly model that successfully combines a nonlinear complexity dynamic system with the bullwhip effect. In order to partition systems with various degrees of disorder and take appropriate methods to refrain systems from falling into a chaos state, numerical simulation methods are conducted to find the stability range, bifurcation range and the chaos range. This article focuses on three different ranges that the authors analyze about the bullwhip effect and inventory variability. In the end, some practical suggestions on behavioral science management are made.