The Impact of the Exchange of Market and Stock Information on the Bullwhip Effect in Supply Chains

2004 ◽  
pp. 55-62 ◽  
Author(s):  
Bernd Faißt ◽  
Dieter Arnold ◽  
Kai Furmans
Keyword(s):  
Supply Chains ◽  
Bullwhip Effect ◽  
Stock Information ◽  
The Impact

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.

scholarly journals Social networks and the situation of blood donation in Poland: a logistics perspective / Sieci społeczne a sytuacja krwiodawstwa w Polsce w perspektywie logistycznej

Management ◽  
2013 ◽  
Vol 17 (1) ◽  
pp. 153-169
Author(s):  
Jacek Szołtysek ◽  
Sebastian Twaróg ◽  
Martyna Wronka
Keyword(s):  
Social Networks ◽  
Supply Chains ◽  
Blood Supply ◽  
Blood Donors ◽  
Blood Donation ◽  
Bullwhip Effect ◽  
Secondary Role ◽  
The Impact ◽  
The Relationship ◽  
Size And Structure

Summary This article aims to present the impact of social networks on the formation on the flow of blood and its components in the civilian blood donation system in Poland. The civilian blood donation system in Poland consists of 21 independently-functioning supply chains of blood and its components (Szołtysek, Twaróg 2009, p. 15). Today, logistics plays a secondary role in the management of blood supply chains, and the integration of flow is performed randomly and intuitively. The rapidly growing recognition of social logistics (T. Takahasi 1988, pp. 245 - 251; Tenhunen 2008, pp. 515-534; Szołtysek 2010, pp. 2-6; Szołtysek 2011, pp.13-18) provides tools to improve the efficiency of the blood donation system in terms of both the existing blood supply chains, and the potential offered by network structures. An unexpected change in demand for blood and its components probably induces a bullwhip effect, and the organizations that form the chains have to deal with supplies unreasonable in terms of their size and structure. A major role in this process is played by social networks, as a source of general mobilization among potential blood donors. Finding a way to change the relationship between social networks and the system of blood donation may minimize the disruptions occurring in the flow of blood and its components in Poland.

scholarly journals Analysis of the Impact of Different Forecasting Techniques on the Inventory Bullwhip Effect in Two Parallel Supply Chains with a Competition Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-28
Author(s):  
Xigang Yuan ◽  
Xiaoqing Zhang ◽  
Dalin Zhang
Keyword(s):  
Supply Chains ◽  
Market Share ◽  
Bullwhip Effect ◽  
Sensitivity Coefficient ◽  
The Self ◽  
Price Sensitivity ◽  
Market Demand ◽  
Competition Effect ◽  
The Impact ◽  
Forecasting Techniques

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.

Prevalence of Bullwhip Effect in Hospitals

2008 ◽  
pp. 1077-1084
Author(s):  
Kannan Sethuraman ◽  
Devanath Tirupati
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Customer Service ◽  
Bullwhip Effect ◽  
The Other ◽  
Inventory Investment ◽  
Growing Body ◽  
Underlying Causes ◽  
The Impact ◽  
Detrimental Impact

Lee, et al. (1997b) state the impact of increased volatility as, “Distorted information from one end of the supply chain to the other can lead to excessive inventory investment, poor customer service, lost revenues, ineffective transportation, and missed production schedules.” Although there is a growing body of research on managing the bullwhip effect in manufacturingbased supply chains (Baganha & Cohen, 1998; Chen, Drezner, Ryan & Simchi-Levi, 2000; Chen, Ryan & Simchi-Levi, 1997; Metter, 1997), little research exists on its presence in service chains, and we are unaware of any reported research on this subject. In this chapter, we present several examples of distorted information in hospitals resulting in variability amplification and causing inefficiencies similar to the bullwhip effect. We highlight the underlying causes for this phenomenon and propose actions that can mitigate the detrimental impact of this distortion.

scholarly journals Measuring and eliminating the bullwhip in closed loop supply chains using control theory and Internet of Things

2021 ◽  
Author(s):  
Christos I. Papanagnou
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Supply Chains ◽  
Closed Loop ◽  
Bullwhip Effect ◽  
The Internet ◽  
Chain Model ◽  
Closed Loop Supply Chains ◽  
The Impact ◽  
The Internet Of Things

AbstractClosed-loop supply chains are complex systems as they involve the seamless backward and forward flow of products and information. With the advent of e-commerce and online shopping, there has been a growing interest in product returns and the associated impact on inventory variance and the bullwhip effect. In this paper, a novel four-echelon closed-loop supply chain model is presented, where base-stock replenishment policies are modelled by means of a proportional controller. A stochastic state-space model is implemented, initially to capture the supply chain dynamics while the model is analysed under stationarity conditions with the aid of a covariance matrix. This allows the bullwhip effect to be expressed as a function of replenishment policies and product return rates. Next, an optimisation method is introduced to study the impact of the Internet of Things on inventory variance and the bullwhip effect. The results show that the Internet of Things can reduce costs associated with inventory fluctuations and eliminate the bullwhip effect in closed-loop supply chains.

scholarly journals Effective Demand Forecasting in Health Supply Chains: Emerging Trend, Enablers, and Blockers

Logistics ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 12
Author(s):  
Lakshmy Subramanian
Keyword(s):  
Supply Chains ◽  
Demand Forecasting ◽  
Weak Links ◽  
Key Factors ◽  
Scarce Resources ◽  
Weakest Link ◽  
Emerging Trends ◽  
A Chain ◽  
Health Commodities ◽  
The Impact

Health supply chains aim to improve access to healthcare, and this can be attained only when health commodities appropriate to the health needs of the global population are developed, manufactured, and made available when and where needed. The weak links in the health supply chains are hindering the access of essential healthcare resulting in inefficient use of scarce resources and loss of lives. A chain is only as strong as its weakest link, and demand forecasting is one of the weakest links of health supply chains. Also, many of the existing bottlenecks in supply chains and health systems impede the accurate forecasting of demand, and without the ability to forecast demand with certainty, the stakeholders cannot plan and make commitments for the future. Forecasts are an important feeder for budgeting and logistics planning. Under this backdrop, the study examines how improved forecasting can lead to better short-term and long-term access to health commodities and outlines market-related risks. It explores further how incentives are misaligned creating an uneven distribution of risks, leading to the inability to match demand and supply. For this purpose, a systematic literature review was performed, analyzing 71 articles from a descriptive and content approach. Findings indicate the emerging trends in global health and the consequences of inaccurate demand forecasting for health supply chains. The content analysis identifies key factors that can pose a varying degree of risks for the health supply chain stakeholders. The study highlights how the key factors emerge as enablers and blockers, depending on the impact on the overall health supply chains. The study also provides recommendations for actions for reducing these risks. Consequently, limitations of this work are presented, and opportunities are identified for future lines of research. Finally, the conclusion confirms that by adopting a combination of approaches, stakeholders can ensure better information sharing, identify avenues of diversifying risks, and understand the implications.

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