Abstract: Supply chain information collaboration refers to a relationship in which supply chain partners organically integrate, coordinate, and develop resources, business processes, and organizations in order to achieve common goals. The goal is to create and coordinate efforts in all aspects of the supply chain. The overall value of the supply chain is greater than the simple sum of the value of each link, thereby improving the competitiveness of the entire supply chain. However, information sharing in supply chain information collaboration has always had problems such as information distortion, information loss, and information delay. The effective coordination of information has become a difficult point in supply chain management. This paper mainly uses the Internet of Things and big data technology to build a simulation model of the supply chain bullwhip effect based on the mathematical model of the bullwhip effect and uses the simulation method to simulate and study the key factors in the model. The image of the simulation results objectively clarifies the value of information collaboration in the supply chain.

Abstract: This paper constructs a multi-channel supply chain that includes a manufacturer, a dual-channel retailer and an online retailer. The dual-channel retailer has a traditional channel and an online ch...

Abstract: The purpose of this paper is to conduct a large-sample empirical investigation of how relational capital impacts bullwhip at the supplier.,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.,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.,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.

Abstract: In this study, the impact of information sharing on bullwhip effect (BWE) is investigated using a four-echelon supply chain simulation model where each echelon shares some of the customer demand forecast information with a retailer, the lowest echelon. The level of the demand forecast shared at each echelon is represented as information sharing rate (ISR). Four different levels of ISR are considered to evaluate its impact on BWE. A full factorial design with 64 cases is used, followed by statistical analysis. The results show that (1) overall, higher ISR more significantly reduce BWE than lower ISR at all echelons; (2) further, the impact of ISR is not same between echelons. The ISR at an echelon where BWE is measured has the highest impact. However, its impact decreases at downstream echelons; (3) BWE is affected by not only the magnitude but also the balance of ISR’s across echelons, while the former has three times more impact than the latter; (4) lastly, we demonstrate that a highly unbalanced ISR may cause reverse bullwhip effect (RBWE), particularly when the level of unblance at downstream echelons is high and the uppermost echelon where BWE is measured has the highest ISR. Based on this demonstration, we derive a functional relationship between ISR’s and RBWE using regression analysis. We believe that results from this study provide useful implications and insights for better coordination and collaboration in a supply chain.

Abstract: Information communication technologies (ICTs) have been extensively applied in smart destinations in recent years so as to improve the information transfer and information sharing amongst individual actors involving in the destination network ecosystem. This paper attempts to explore the influence of information sharing on the bullwhip effect throughout the tourism supply chain (SC) network, which has been considered as a major problem faces the destination management and all individual actors. Specifically, two mathematic models have been built to analyse the following different situations respectively; first, ICTs have not been well applied in destinations and there is no information sharing amongst individual actors, second, ICTs have been well applied in destinations and there exists information sharing amongst individual actors. Further, this paper makes a comparison of the bullwhip effects under these two situations. What's more, the data collected from JIUZHAI valley has been used to verify the correction of the mathematic analysis. Overall, this paper proves that the application of ICTs will contribute to the reduction of bullwhip effect throughout the tourism SC network by promoting the information sharing amongst individual actors, and some parameters (e.g., autocorrelation coefficient, the number of demand forecasting, and the lead time) will play a crucial role on the acting process. The results have both theoretical significance to the development of tourism SC management theory and managerial implication to tourism practices of individual actors and management departments.

Abstract: Lee et al. (1997) theorized that stores game the means by which inventory is rationed, jockeying for stock in times of scarcity. Furthermore, they theorized that this ration gaming exacerbates the ...

Abstract: 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.

Abstract: Information 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.,A 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.,The 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.,Information 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.,Colored 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.

Abstract: SCM is the integration process of dealing business partners, which starts from supplier of raw material to final customer/consumer, including all transportation activities, intermediate processes, storage activities and, finally, sale to the end customer/consumer.

Abstract: 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.

Abstract: Bullwhip effect (BWE) in a supply chain is a phenomenon wherein variance in orders placed increases as one moves upstream in the supply chain. This paper analyses the bullwhip effect from human beh...

Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing "bullwhip effect" is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.

Abstract: The objective of this study was to compare the Bullwhip Effect (BWE) in the supply chain through two methods and to determine the inventory policy for the uncertainty demand. It would be useful to determine the best forecasting method to predict the certain condition. The two methods are Artificial Neural Network (ANN) and Support Vector Regression (SVR), which would be applied in this study. The data was obtained from the instant noodle dataset where it was in random normal distribution. The forecasting demands signal have Mean Squared Error (MSE) where it is used to measure the bullwhip effect in the supply chain member. The magnification of order among the member of the supply chain would influence the inventory. It is quite important to understand forecasting techniques and the bullwhip effect for the warehouse manager to manage the inventory in the warehouse, especially in probabilistic demand of the customer. This process determines the appropriate inventory policy for the retailer. The result from this study shows that ANN and SVR have the variance of 0.00491 and 0.07703, the MSE was 1.55e-6 and 1.53e-2, and the total BWE was 95.61 and 1237.19 respectively. It concluded that the ANN has a smaller variance than SVR, therefore, the ANN has a better performance than SVR, and the ANN has smaller BWE than SVR. At last, the inventory policy was determined with the continuous review policy for the uncertainty demand in the supply chain member.

Abstract: We study the supply chain implications of dynamic pricing. Specifically, we estimate how reducing menu costs---the operational burden of adjusting prices---would affect supply chain volatility. Fitting a structural econometric model to data from a large Chinese supermarket chain, we estimate that removing menu costs would: (i) reduce the mean shipment coefficient of variation by 7.2 percentage points (pp), (ii) reduce the mean sales coefficient of variation by 4.pp, and (iii) reduce the mean bullwhip effect by 2.9 pp. These stabilizing changes are almost entirely attributable to an increase in the mean sales rate.

Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing ``bullwhip effect'' is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.

Abstract: Supply chain management and inventory control provide most exciting examples of control systems with delays. Here, Smith predictors, model-free control and new time series forecasting techniques are mixed in order to derive an efficient control synthesis. Perishable inventories are also taken into account. The most intriguing “bullwhip effect” is explained and attenuated, at least in some important situations. Numerous convincing computer simulations are presented and discussed.

Abstract: The distribution of goods from suppliers to customers plays an important role in the supply chain. In this paper, the approach of Demand Driven Distribution Resource Planning (DDDRP) is proposed in order to optimize the distribution flow in the supply chain. The purpose is to manage all sources of variability in "operational, management, supply and demand", while improving the traditional methods of Distribution Resource Planning (DRP). First, a review of the literature on the impact of variability upon distribution flow and the solutions proposed in this context is presented. Then, a general study of distribution industries is investigated in order to apply the DDDRP method; we show the buffers positioning in the distribution network, and the profile and levels of the buffers. After the dynamic adjustment, the Demand Driven Planning and the execution based on the net flow equation are presented. The results discuss the approach and the steps of implementing it in the distribution industry.

Abstract: This paper deals with the to the supply chain strategic management of organic products. The objective of this study is to propose a model that integrates the concepts of supply chain management (SCM), transaction costs theory (TTC) and bullwhip effect in supply chain of organic products generating propositions that will direct future empirical research. Therefore, this paper proposes that the SCM and TTC can contribute in reducing the distortion of perception of demand along the supply chain of organic products. A conceptual model relating the three variables studied was elaborated and three theoretical future empirical investigations to propositions in order to solve the problem of the bullwhip effect, namely the distortion of perception of demand along the supply chain of organic products.

Abstract: The Company's inability to overcome inventory problems leads to unprepared marketing distributor in anticipating a surge in consumer demand and unavailability of inventory in the warehouse. Long agricultural supply chain problems cause frequent information gaps, inaccurate and integrated inventory predictions from downstream to upstream supply chains, and uncontrolled inventory, these are the phenomenon of the bullwhip effect in the supply chain. To overcome these problems, the marketing distributor needs to predict the demand in the integrated supply chain downstream so that inventory in each chain can be controlled. Based on the data, the existing demand pattern is linear and the right method to use is SVR (Support Vector Regression), which produces the highest level of accuracy and the smallest error. Based on the results of SVR demand forecasting in the supply chain downstream, each chain is then integrated to control inventory, so that the occurrence of the bullwhip effect can be minimized. Then the company can use the aggregate mode to determine the safe upper and lower limit of inventory so that the stability of the demand for refined sugar from the supply chain downstream can always be fulfilled the company.

Abstract: Demand-Driven Material Requirements Planning (DDMRP) methodology was developed to increase ma-terial and information flow and enhance the competitive advantage of manufacturing and distribution companies. Some researchers have developed models to simulate the performance of DDMRP, neverthe-less, there were no studies found in the literature that analyzed the implementation of this methodology in a company. The present work, therefore analyzes the evolution of a company after converting from MRP to DDMRP and the impact of this process on material management. The results clearly show that using DDMRP the company increased visibility in the supply chain by re-ducing considerably the bullwhip effect and rush orders. Importantly, in the months following the imple-mentation the inventory level was reduced by more than 24% while material consumption was increased by almost 14%. Throughout the entire process, the company maintained the high service level that it had had before. Keywords : DDMRP; Inventory, Visibility, Forecast, Uncertainty.

Abstract: This paper is extensions of the Tesfay (2014) paper on the Bullwhip effects and Tesfay (2015) paper on the foundations of the Bullwhip effect and its implications on the theory of organizational coordination. The major outcome of the Tesfay (2014) paper suggests that one way or another Bullwhip effect attacks all the business collaborates in supply chain. The major outcome of the Tesfay (2015) paper suggests that the solutions from the transaction cost economics are still insufficient to produce the most efficient organizational coordination. This paper extends stochastic analysis by applying various panel data regression models and structural equations of seemingly unrelated regression (SUR) models on the experimental data from Beer game. Recursive autoregressive-SUR model estimation result confirmed that the Bullwhip effects can be cause by both intra-organizational coordination and inter-organizational coordination of the business collaborates of supply chain. In order to control the effect of intra-organizational coordination on the Bullwhip effects, the author outline a new coordination type known as the hyper-hybrid coordination. As a final point, the author has shown important applications of the hyper-hybrid coordination in the airline industry.

Abstract: EXPLORATION INTO FOOD WASTE OCCURRING IN BOVINE DAIRY, LEAFY GREEN AND APPLE SUPPLY CHAINS Mychal-Ann Hayhoe Advisor: University of Guelph, 2019 Dr. Michael von Massow Food waste is an issue of significant importance and rising concern in society. While research indicates that the majority of food waste is occurring in consumers’ homes, there is also considerable waste generated in food supply chains. Waste reduction in food supply chains represents a potentially rewarding challenge for researchers as it can reduce the environmental impact of the food system, but also because companies continually seek out money saving opportunities. In this dissertation, food waste and management literature are examined. The theory of the offering, is used to describe moving from a supply chain to a value chain. It is suggested that this will force increased valuation of food items which will help reduce waste. The concept of the bullwhip effect is also presented and the idea that it may be contributing to waste generation is introduced. Three case studies examining bovine dairy, leafy greens, and apple supply chains are used to describe where, how, and why food waste is occurring. This exploratory work of case studies produces twenty testable hypotheses to direct future research. These hypotheses are mapped onto a framework indicating where waste can be found in food supply chains suggesting what areas of the supply chain is best suited for additional research.

Abstract: This article introduces a new online simulation game called Cash Beer Game, which is an augmented version of the standard Beer Game by including cash flows. In addition to the inventory ordering and shipping activities, each player pays cash for the ordered inventory to her upstream partner and receives cash from her downstream partner. The goal of this game is to explain the interactions between material, information, and financial flows in a supply chain and help students understand the impact of financial flows on the inventory decision. The resulting bullwhip effect can be compared between teams and with that of the standard Beer Game for the same team.