optimal promotion planning depth and frequency for a two stage supply chain under markov switching demand abstract in considering the retailer supplier supply chain this paper analyzes how a retailer reasonably decides both the depth and frequency of the price discount promotion including or excluding a supplier s inventory decision assuming that the promotion frequency used by the retailer is probabilistic we model a promotion inventory decision under an ar 1 demand with a markov switching promotion regime after obtaining the optimal promotion plan our analysis also considers the behavior of the optimal promotion decision the retailer s price format selection either an every day low price policy edlp or a promotion policy hilo and the impact of information sharing of promotion status on the system s performance our results suggest that a retailer tends to overpromote if inventory cost is excluded in its promotion decision that increasing the market share is a preferable action for both the retailer and the supplier that total margin and price elasticity play an important role in selecting the price format and that the profitability for a supplier of sharing promotion information depends on the transition probabilities of the markov switching regime

the brazilian economy in 1994 1999 from the real plan to inflation targets this paper investigates the three main events that shook the brazilian economy in 1994 1999 a period that represented a turning point in the country s economic history these events were the implementation of the real plan in 1994 the devaluation crisis in 1999 and the subsequent adoption of inflation targets the principal contributions of this period were the drastic reduction of high inflation rates the biggest problem in brazil since the 1970s and the reorientation towards economic growth which were also supported by a privatisation programme the openness of the economy to foreign capital a trade liberalisation process and the ongoing fiscal adjustments nevertheless the period also left its scars such as high budget and current account deficits accompanied by a policy of elevated interest rates and until 1999 a highly appreciated exchange rate the paper concludes with a cautiously optimistic evaluation of the country s economic future based on the accomplishments of the 1990s and the possibility of a long term commitment to low inflation targets

impact of information sharing and lead time on bullwhip effect and on hand inventory abstract this work analyzes a two echelon warehouse retailer serial supply chain to study the impact of information sharing is and lead time on bullwhip effect and on hand inventory the customer demand at the retailer is assumed to be an autoregressive ar 1 process both the echelons use a minimum mean squared error mmse model for forecasting lead time demand ltd and follow an adaptive base stock inventory policy to determine their respective order quantities for the cases of without is and inter as well as intra echelon is expressions for the bullwhip effect and on hand inventory for the warehouse are obtained considering deterministic lead time the results are compared with the previous research work and an easy analysis of the various bullwhip effect expressions under different scenarios is done to understand the impact of is on the bullwhip effect phenomenon it is shown that some part of bullwhip effect will always remain even after sharing both inter as well as intra echelon information further with the help of a numerical example it is shown that the lead time reduction is more beneficial in comparison to the sharing of information in terms of reduction in the bullwhip effect phenomenon

measuring the bullwhip effect for supply chains with seasonal demand components abstract a bullwhip measure for a two stage supply chain with an order up to inventory policy is derived for a general stationary sarma p q p q s demand process explicit expressions for several sarma models are obtained to illustrate the key relationship between lead time and seasonal lag it is found that the bullwhip effect can be reduced considerably by shortening the lead time in relation to the seasonal lag value

production chains and aggregate output volatility abstract a production chain s aggregate output volatility depends upon a number of factors including the number of firms in a chain the management strategy of the firms the point at which products are differentiated lead times and the persistence of demand shocks the influence of these factors is quantified here with an n firm model of the production chain under pure production to stock pts the firms in the chain respond simultaneously to a demand shock producing a positive covariance across firms that raises aggregate volatility under production to order pto the chain s response to a demand shock is staggered but when demand shocks are persistent there is a catch up effect that raises the volatility of each firm s production above that of a firm that under pts nevertheless pto chains typically exhibit less volatility than pts chains thanks to the covariance effect further simulations demonstrate that the production chain stabilizes as the number of production cycles in an observation period increases

analysis of compound bullwhip effect causes abstract this research investigates compound causes of the bullwhip effect bwe by considering an inventory system with multiple price sensitive demand streams joint price and demand dynamics are captured by a vector time series process that incorporates the stochastic co movements in price and demand we study two bwe measures one for each demand stream individually and one for the aggregated demand we show that demand parameters including demand autocorrelation cross correlation and price sensitivity serve as root causes of the bwe we prove that the impact of these parameters on the bwe can be additively decomposed conditions are established under which a pair of simultaneous compound causes may attenuate or dampen the bwe when demand streams are aggregated we derive a pooling factor that quantifies the impact of demand aggregation on order stability when positive the pooling factor corresponds to a synergy effect that captures the gain in the stability of the pooled orders conditions for the existence of the synergy effect are obtained for several special cases involving a zero leadtime we also discuss how our analytical findings can be managerially applied to bullwhip mitigation strategies

providing a measure for bullwhip effect in a two product supply chain with exponential smoothing forecasts abstract in this paper a two product and two echelon supply chain is considered in order to quantify the bullwhip effect demands of the products are correlated and are represented by a first order vector autoregressive model retailer uses order up to ordering policy for replenishment of stocks and utilizes exponential smoothing forecast method to predict demand in lead time period according to the mentioned assumptions an equation is derived for bullwhip effect measurement and then a numerical example is presented for a better perception of the bullwhip effect behavior when the parameters change a comparison of the bullwhip effect measure has been done when two main forecasting methods i e exponential smoothing and moving average are used and empirical results are provided at last a cost analysis is conducted based on shortage and holding cost under different bullwhip effect measures

inventories stock outs and production smoothing if stock outs are ignored and if demand shocks are additive then optimal behaviour requires that the marginal cost of production mc be equated with the expected marginal revenue of increasing expected sales by one unit emr however with more general demand shocks and still ignoring stock outs the excess of mc over emr has the same sign as the covariance of the slope of the demand curve and the marginal valuation of inventory the equality of emr and mc is also broken by taking account of stock outs even if demand shocks are additive if there is a production lag then taking account of stock outs implies that optimal behaviour will be characterized by production smoothing even if the cost of production is linear two alternative definitions of production smoothing are presented and optimal behaviour in the presence of stock outs displays each type of smoothing it is a well known proposition that a firm producing a storable good under conditions of increasing marginal cost will tend to smooth the time profile of its production relative to the time profile of its sales the incentive to smooth production arises from the fact that the cost function is a convex function of the level of production for a given average level of production average costs can be reduced by reducing the variation in production of course if the cost function is linear in the level of production then this incentive to smooth production disappears however we will demonstrate in this paper that if the possibility of stock outs is explicitly incorporated into the firm s dynamic optimization problem i e if we impose a non negativity constraint on inventories and if there is a lag in production then optimal behaviour can be characterized by production smoothing even if the cost function is linear

the impact of forecasting methods on the bullwhip effect abstract this paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first order autoregressive process describes the customer demand and an order up to inventory policy characterizes the replenishment decision a bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean squared forecasting error for the specified demand process similar measures are obtained for the moving average and exponential smoothing methods the findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process moreover a simple rule is established to help managers select a forecasting method that yields the lowest inventory cost

inventory control under temporal demand heteroscedasticity abstract this paper studies an inventory control problem when the variance of demand is time varying and exhibits temporal heteroscedasticity we use a first order autoregressive process to characterize the dynamic changes in the level of demand over time and a garch 1 1 structure to describe the changes in the variance of demand under these demand settings we quantify the effect of a temporal heterogeneous variance on inventory performance for a system controlled via an order up to level policy we show that the effect of temporal heteroscedasticity on the forecasting accuracy can be additively decomposed from the total forecasting error variance the decomposition is used to derive the absolute and relative cost deviations when the temporal heteroscedasticity is ignored the relationship of these cost deviations to demand autocorrelation and replenishment leadtime is investigated computational results show that ignoring temporal heteroscedasticity can increase firm s inventory costs by as much as 30 when demand autocorrelation is highly positive

a time series framework for supply chain inventory management we consider a supply chain in which the underlying demand process can be described in a linear state space form inventory is managed at various points of the chain members based on local information that each member observes and continuously updates the key feature of our model is that it takes into account the ability of the members to observe subsets of the underlying state vector and adopt their forecasting and replenishment policies accordingly this enables us to model situations in which the members are privy to certain explanatory variables of the demand with the latter possibly evolving according to a vector autoregressive time series for each member we identify an associated demand evolution model for which we propose an adaptive inventory replenishment policy that utilizes the kalman filter technique we then provide a simple methodology for assessing the benefits of various types of information sharing agreements between members of the supply chain we also discuss inventory positioning and cost performance assessment in the supply chain our performance metrics and inventory target levels are usually presented in matrix forms allowing them to accommodate a relatively large spectrum of linear demand models and making them simple to implement several illustrations for possible applications of our models are provided

medical interventions among pregnant women in fee for service and managed care insurance a propensity score analysis this paper extends earlier research on the effect of managed care on the receipt of four medical interventions for pregnant women ultrasound induction stimulation of birth electronic fetal monitor and caesarean delivery propensity score methods are used to account for sample selection issues regarding insurance choice managed care enrollees are more likely to receive an ultrasound which may be indicative of receiving better prenatal care managed care plans reduce the rate of caesarean deliveries but such limitations may be beneficial given the substantial medical evidence that caesarean deliveries are over utilized the results indicate that insurance coverage does influence treatment intensity but that utilization controls and provider financial incentives do not adversely affect care for pregnant women

evaluation of cycle count policies for supply chains with inventory inaccuracy and implications on rfid investments inventory record inaccuracy leads to ineffective replenishment decisions and deteriorates supply chain performance conducting cycle counts i e periodic inventory auditing is a common approach to correcting inventory records it is not clear however how inaccuracy at different locations affects supply chain performance and how an effective cycle count program for a multi stage supply chain should be designed this paper aims to answer these questions by considering a serial supply chain that has inventory record inaccuracy and operates under local base stock policies a random error representing a stock loss such as shrinkage or spoilage reduces the physical inventory at each location in each period the errors are cumulative and are not observed until a location performs a cycle count we provide a simple recursion to evaluate the system cost and propose a heuristic to obtain effective base stock levels for a two stage system with identical error distributions and counting costs we prove that it is more effective to conduct more frequent cycle counts at the downstream stage in a numerical study for more general systems we find that location proximity to the customer error rates and counting costs are primary factors that determine which stages should get a higher priority when allocating cycle counts however it is in general not effective to allocate all cycle counts to the priority stages only one should balance cycle counts between priority stages and non priority stages by considering secondary factors such as lead times holding costs and the supply chain length in particular more cycle counts should be allocated to a stage when the ratio of its lead time to the total system lead time is small and the ratio of its holding cost to the total system holding cost is large in addition more cycle counts should be allocated to downstream stages when the number of stages in the supply chain is large the analysis and insights generated from our study can be used to design guidelines or scorecard systems that help managers design better cycle count policies finally we discuss implications of our study on rfid investments in a supply chain

a unified theory of the dynamics of closed loop supply chains we investigate the dynamics of a closed loop supply chain with first order auto regressive ar 1 demand and return processes we assume these two processes are cross correlated the remanufacturing process is subject to a random triage yield remanufactured products are considered as goodas new and used to partially satisfy market demand newly manufactured products make up the remainder we derive the optimal linear policy in our closed loop supply chain setting to minimise the manufacturer s inventory costs we show that the lead time paradox can emerge in many cases in particular the auto and cross correlation parameters and variances of the error terms in the demand and the returns as well as the remanufacturing lead time all influence the existence of the lead time paradox finally we propose managerial recommendations for manufacturers

the stabilizing effect of inventory in supply chains this paper presents a hierarchical model framework for the analysis of the stabilizing effect of inventories in multiechelon manufacturing distribution supply chains this framework is used to compare the variance of demand to the variance of replenishment orders at different echelons of the system e g retailer wholesaler empirical data and experience with management games suggest that in most industries inventory management policies can have a destabilizing effect by increasing the volatility of demand as it passes up through the chain the bullwhip effect our model helps to explain these observations and indicates mechanisms that can promote stabilization the analysis results also define sufficient conditions for the existence of stabilization and relate these conditions to the optimality of myopic control policies

the effect of inventory record inaccuracy in information exchange supply chains abstract the goal of this paper is to quantify the impact of inventory record inaccuracy on the dynamics of collaborative supply chains both in terms of operational performance i e order and inventory stability and customer service level to do so we model an information exchange supply chain under shrinkage errors in the inventory item recording activity of their nodes present the mathematical formulation of such supply chain model and conduct a numerical simulation assuming different levels of errors results clearly show that inventory record inaccuracy strongly compromises supply chain stability particularly when moving upwards in the supply chain important managerial insights can be extracted from this analysis such as the role of benefit sharing strategies in order to guarantee the advantage of investments in connectivity technologies

analysis of the bullwhip effect in a multiproduct setting with interdependent demands the bullwhip effect has been extensively studied primarily based on the analysis of various single product models with a few exceptions we extend the single product analysis to the multiproduct setting of interdependent demand streams with auto correlation and cross product correlation as well as contemporaneous correlation across forecasting errors we find that interdependency between demand streams plays a critical role in determining the existence and magnitude of the bullwhip effect specifically we consider two operating environments a the firm orders product specific materials so that the ordering decision is based on the product level and b the firm orders generic materials so that the order decision is based on the category level we show that even with demand pooling a firm operating at the category level can experience a larger bullwhip effect and a larger order variance under certain conditions that depend on the number of products in the category and the demand dependencies

style of practice and assortative mating a recursive probit analysis of cesarean section scheduling in italy we study practice variation in scheduling of caesarean section cs delivery across public and private hospitals in italy adopting a novel perspective we look at the role played by patients preferences for the treatment the recursive probit model is revisited as a useful tool to assess the presence of assortative mating of patients and provider driven by style of practice according to our evidence the propensity to schedule a cs is codetermined with patient self sorting into hospital types we measure a significantly higher inclination to practice cs scheduling in private hospitals and conclude that assortative mating is of minor relevance in our case even if we cannot exclude it to be present

bayes solution to dynamic inventory models under unknown demand distribution this paper considers the periodic review inventory problem for which one or more parameters of the demand distribution are unknown with a known prior distribution chosen from the natural conjugate

the production and inventory behavior of the american automobile industry understanding inventory movements is central to an understanding of business cycles this paper presents an empirical study of the behavior of inventories in the automobile industry it finds that inventory behavior is well explained by the assumption of intertemporal optimization with rational expectations the underlying cost structure appears to have substantial costs of changing production as well as substantial costs of being away from target inventory thelatter being a function of current sales given this cost structure whether inventory behavior is stabilizing or destabilizing depends on the characteristics of the demand process in the automobile industry inventory behavior is destabilizing the variance of production is larger than the variance of sales

measure of bullwhip effect in supply chains the case of high order autoregressive demand process abstract bullwhip effect the phenomenon in which variance of demand is amplified when moving upstream has attracted the attention of many researchers for the last few decades although the main sources that cause bullwhip effect have been identified quantifying the bullwhip effect still remains a challenge in the past measuring the bullwhip effect for supply chains with autoregressive demand process has been conducted by some researchers however most past researches focused mainly on the simple ar 1 model in many practical situations autoregressive models with higher order should be employed because they might better represent the demand process up to now very little effort has been spent on this matter therefore this research is conducted to fill this gap by first dealing with ar 2 demand process and investigating the behavior of the developed measure with respect to autoregressive coefficients and order lead time extension to the general ar p demand process is then considered

revisiting the value of information sharing in two stage supply chains abstract there is a substantive amount of literature showing that demand information sharing can lead to considerable reduction of the bullwhip effect inventory costs the core argument analysis underlying these results is that the downstream supply chain member the retailer quickly adapts its inventory position to an updated end customer demand forecast however in many real life situations retailers adapt slowly rather than quickly to changes in customer demand as they cannot be sure that any change is structural in this paper we show that the adaption speed and underlying unknown demand process crucially affect the value of information sharing for the situation with a single upstream supply chain member manufacturer and a single retailer we consider two demand processes stationary or random walk these represent two extremes where a change in customer demand is never or always structural respectively the retailer and manufacturer both forecast demand using a moving average where the manufacturer bases its forecast on retailer demand without information sharing but on end customer demand with information sharing in line with existing results the value of information turns out to be positive under stationary demand one contribution though is showing that some of the existing papers have overestimated this value by making an unfair comparison our most striking and insightful finding is that the value of information is negative when demand follows a random walk and the retailer is slow to react slow adaptation is the norm in real life situations and deserves more attention in future research exploring when information sharing indeed pays off

a measure of bullwhip effect in supply chains with a mixed autoregressive moving average demand process abstract in this paper we quantify the impact of the bullwhip effect the phenomenon in which information on demand is distorted as moving up a supply chain for a simple two stage supply chain with one supplier and one retailer assuming that the retailer employs a base stock inventory policy and that the demand forecast is performed via a mixed autoregressive moving average model arma 1 1 we investigate the effects of the autoregressive coefficient the moving average parameter and the lead time on the bullwhip effect

adjustment strategies for a fixed delivery contract we consider a long term contractual agreement between buyer and seller in whichq units are delivered to the buyer at regular time intervals it must be true that the delivery quantity q is less than the mean demand per period in order to manage the inventory the buyer has the option of adjusting the delivery quantity upwards just prior to a delivery but must pay a premium to do so demand is assumed random and we model the system in a continuous review setting we show that the equations one must solve to find optimal adjustment strategies are intractable a diffusion approximation is developed which when coupled with the solution to an even simpler deterministic version of the problem yields very simple but effective approximations extensive computations are included to compare the performance of the optimal and approximate policies we also empirically derive a formula for computingq whose accuracy is established computationally we prove that the fixed delivery contract results in lower variance of orders to the seller we also include a computational study to find the unit cost discount that equalizes the expected costs for the fixed delivery contract and the base stock contract for a large parameter set

value of information in capacitated supply chains we incorporate information flow between a supplier and a retailer in a two echelon model that captures the capacitated setting of a typical supply chain we consider three situations 1 a traditional model where there is no information to the supplier prior to a demand to him except for past data 2 the supplier knows the s s policy used by the retailer as well as the end item demand distribution and 3 the supplier has full information about the state of the retailer order up to policies continue to be optimal for models with information flow for the finite horizon the infinite horizon discounted and the infinite horizon average cost cases study of these three models enables us to understand the relationships between capacity inventory and information at the supplier level as well as how they are affected by the retailer s s s values and end item demand distribution we estimate the savings at the supplier due to information flow and study when information is most beneficial

supply contract with bidirectional options the buyer s perspective abstract this paper develops a single period two stage supply contract with bidirectional options by which the buyer can adjust the initial order both upward and downward at the beginning of the planning horizon the buyer places an initial order and purchases options after updating the demand forecast the buyer exercises options to adjust the initial order we analyze the contract from the buyer s perspective and formulate the buyer s optimal policies in particular we obtain closed form formulae to describe the buyer s optimal behavior when the demand is uniformly distributed we also analyze how the parameters affect the buyer s behavior and prove numerically that using bidirectional options can improve the buyer s profit

information distortion in a supply chain the bullwhip effect this article originally appeared in management science april 1997 volume 43 number 4 pp 546 558 published by the institute of management sciences consider a series of companies in a supply chain each of whom orders from its immediate upstream member in this setting inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions this paper claims that the information transferred in the form of orders tends to be distorted and can misguide upstream members in their inventory and production decisions in particular the variance of orders may be larger than that of sales and distortion tends to increase as one moves upstream a phenomenon termed bullwhip effect this paper analyzes four sources of the bullwhip effect demand signal processing rationing game order batching and price variations actions that can be taken to mitigate the detrimental impact of this distortion are also discussed

multi product lot sizing with a transportation capacity reservation contract abstract although transportation costs can form more than 50 of the total logistics costs of a product they are often neglected in lot sizing research and modelling nonetheless the body of research that does take transportation costs into account is gradually growing the bulk of this type of research however assumes that freight rates decrease as shipping weights and or volumes increase inspired by the situation with a large european manufacturing company we study a multi product lot sizing model where in any period any portion of a reserved transportation capacity can be used in exchange for a guaranteed price if the capacity is insufficient then the shipper needs to contract additional transportation capacity on the spot market where the prevailing price is higher accordingly the freight rates are piece wise linearly increasing in our model we prove that the problem of determining transportation lot sizes so as to meet warehouse demand with no backlogging allowed and to minimize total costs that is the sum of inventory carrying ordering and transportation costs is np hard in the strong sense furthermore we present a lagrangean relaxation algorithm to compute lower and upper bounds of which comprehensive computational experiments show the compelling performance in terms of quality and speed

the variability of aggregate demand with s s inventory policies this paper develops a general theory of the aggregate implications of s s inventory policies it is shown that s s policies add to the variability of demand with the variance of orders exceeding the variance of sales overall the s s theory contradicts the widely held notion that retail inventories act as a buffer protecting manufacturers from fluctuating sales in 1951 arrow harris and marschak 3 introduced the s s form of inventory policy the policies are designed for retailers of finished goods who face economies of scale when placing orders with their suppliers to pursue an s s inventory policy the retailer establishes a lower stock point s and an upper stock point s no order is placed until inventories fall to s or below whereupon they are restored to the maximum of s a general proof of the optimality of these s s inventory policies was provided by scarf 13 at the microeconomic level the model has been extensively investigated formulae are available to compute optimal policies e g ehrhardt 6 and these policies are xidely used in industry e g schwartz ed 14 in addition the model has been extended to increasingly complex demand environments e g karlin and fabens 11 in contrast little is known about the macroeconomic implications of s s policies several recent papers have begun to correct this deficiency akerlof has suggested that pursuit of constant threshold money holding policies of the s s variety might be responsible for the observed low short run income elasticity of the demand for money akerlof 1 and akerlof and milbourne 2 in the operations research literature ehrhardt schultz and wagner 7 analyzed the demand environment of a wholesaler supplying several retailers they required that the distinct retailers have independent sales ruling out the analysis of common factors in sales finally simulation results of blinder 4 suggested a role for the s s model in understanding retail sector inventories however the theoretical difficulties with the model remained unresolved blinder commented if firms have a technology that makes the s s rule optimal aggregation across firms is inherently difficult indeed it is precisely this difficulty which has prevented the s s model from being used in empirical work to date blinder 4 p 459 in this paper we present a general theory of the aggregate implications of s s policies our central finding is that s s policies add to the variability of demand with the variance of orders exceeding the variance of sales this result holds even in the presence of common factors in retail sales in addition a close connection

the bullwhip effect progress trends and directions the bullwhip effect refers to the phenomenon where order variability increases as the orders move upstream in the supply chain this paper provides a review of the bullwhip literature which adopts empirical experimental and analytical methodologies early econometric evidence of bullwhip is highlighted findings from empirical and experimental research are compared with analytical and simulation results assumptions and approximations for modelling the bullwhip effect in terms of demand forecast delay replenishment policy and coordination strategy are considered we identify recent research trends and future research directions concerned with supply chain structure product type price competition and sustainability

reduction of the value of information sharing as demand becomes strongly auto correlated information sharing has been identified in the academic literature as one of the most important levers to mitigate the bullwhip effect in supply chains a highly cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain when the downstream demand is autoregressive of order one is an increasing function of the autoregressive parameter of the demand in this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero we also show that this maximum value of the autoregressive parameter can be as high as 0 7 which represents a common value that may be encountered in many practical contexts this means that large benefits of information sharing cannot be assumed for those stock keeping units skus with highly positively auto correlated demand instead equally careful analysis is needed for these items as for those skus with less strongly auto correlated demand

scarf s state reduction method flexibility and a dependent demand inventory model we consider a finite horizon inventory model with linear holding shortage and ordering costs the demand random variables are dependent and average demand is described by an exponential smoothing formula this model can be formulated as a two state variable inventory level weighted past demands dynamic program using a procedure first developed by scarf for a bayesian inventory model we are able to reformulate the model as a one state variable dynamic program resulting in a considerable computational saving over the two state variable formulation we also show that this dependent demand model orders less than or equal the amount ordered by a comparable independent demand model we establish this result under the assumption that demand represents failures that are repaired by the beginning of the next period

an arima supply chain model this paper presents a multistage supply chain model that is based on autoregressive integrated moving average arima time series models given an arima model of consumer demand and the lead times at each stage it is shown that the orders and inventories at each stage are also arima and closed form expressions for these models are given the paper also discusses the causes of the bullwhip effect a phenomenon in which variation in demand produces larger variations in upstream orders and inventory this discussion reveals how different modeling can lead to different insights because they make different assumptions about the cause of the bullwhip effect these observations are used to develop managerial insights about reducing the bullwhip effect

the role of forecasting on bullwhip effect for e scm applications abstract the bullwhip effect represents the information distortion in customer demand between orders to supplier and sales to the buyer demand forecasting is one of the main causes of the bullwhip effect the purpose of this study is to analyze the impact of exponential smoothing forecasts on the bullwhip effect for electronic supply chain management e scm applications a simulation model is developed to experiment the different scenarios of selecting right parameters for the exponential smoothing forecasting technique it is found that longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in e scm in contrast increased seasonality helps to reduce the bullwhip effect the most significant managerial implication of this study lies in the need to reduce lead times along the e supply chain to mitigate the bullwhip effect while high seasonality would reduce the forecast accuracy it has a positive influence on the reduction of bullwhip effect e scm managers are therefore strongly suggested to utilize exponential smoothing by selecting lower values for and and a mid value for to keep the bullwhip ratio low while at the same time to increase forecast accuracy

order variability in perishable product supply chains abstract empirical research has shown that the degree of order variability in supply chains is significantly influenced by product and industry specific factors this paper analyzes the impact of perishability on order variability and the bullwhip effect in supply chains we decompose the ordering process of a retailer into a sales and an outdating process and quantify their short and long term variability and correlation we find differences to non perishable product supply chains driven by the impact of the inventory depletion policy stock out management and retailers service level requirement these three factors significantly affect the retailer s order variability and thus the decision making process and the profitability of the upstream supply stage for the majority of instances the perishable nature of a product results in the ordering process having a lower variability than the demand process only when inventory depletion is dominated by last in first out in high service level environments variability amplification can be observed we propose a dynamic ordering policy for the upstream supply stage taking into account negative correlation of retailer orders between periods this dynamic policy may lead to substantial performance improvements in a sensitivity analysis we investigate the impact of shelf life lead time and demand correlation

canaries and vultures a quantitative history of monetary mismanagement in brazil during the last two decades of the twentieth century brazil went through a sequence of failed stabilization plans that tried to cope with an enduring hyperinflation this paper uses a money demand model to evaluate monetary policies during those episodes consistency between money supply and expected conditional money demand growth rates is considered for each plan it is shown that unsuccessful programs were marked by excessive liquidity the results not only suggest that monetary mismanagement led to the failure of the plans but also that the excessive liquidity could have been predicted

inventories and sticky prices note in a recent contribution to this review alan blinder provides an interesting analysis of the relationship between optimal inventory decisions and the process of price adjustment arguing that inventory permits separation of production and sale decisions and allows the firm greater flexibility in responding to anticipated demand disturbances blinder shows that the responsiveness of relative prices depends critically upon the cost of storage and the temporal structure of the demand shocks few economists would fault the intuitive substance of blinder s basic proposition and the proposition is justified with characteristic precision the analysis however is considerably less general than blinder maintains the formal argument of his paper relies upon a simple model of a monopolist capable of backlogging orders and storing unsold goods as the model is constructed order backlogs assume a role of fundamental importance in any stationary equilibrium this feature of the model vitiates blinder s extension of his result to situations in which order backlogs are prohibited the basic monopoly model developed in sections i and ii of blinder s paper places no restriction upon the sign of inventory negative inventory is interpreted as net unfilled orders while no distinction is drawn between reductions in gross inventory and additions to the order backlog as a result the cost of holding inventory is symmetric around an arbitrary minimum point the only role of inventory is to permit the time paths of production and sales to differ gross inventory allows production to antedate sales while order backlogs generate revenue before production costs are borne under these circumstances if future costs and revenues are discounted it is natural to expect any stationary equilibrium level of net inventory to be negative this can be shown to be true of blinder s model it is useful to distinguish in general between the nonstochastic stationary level of inventory n and the stochastic stationary level n the former is realized when the current expected demand disturbance eo is zero and production equals sales the latter which differs from customary usage represents the level of inventory expected to prevail when adjustment to the current nonzero expected demand disturbance is complete if the demand disturbance is not a random walk so that p 1 in blinder s 5 the two equilibria coincide relatively little attention is devoted to either stationary solution because blinder s main interest is in the optimal current solution level n1 the stochastic stationary level is crucially important however since it represents the goal toward which the current choice must provide an optimal first step to verify that both nand n are negative whenever production is strictly positive note that blinder s necessary condition 7 with the coefficient cl set equal to zero together with the definition of xa as the deviation of the shadow value of inventory q from its nonstochastic stationary value q implies

research on bullwhip effect in energy efficient air conditioning supply chain abstract this paper investigates the energy efficient air conditioning supply chain which is composed of one supplier midea and two retailers i e suning and gome with a view of market share we measure the impact of retail prices variability in the two echelon supply chain on the bullwhip effect suning and gome are assumed to possess the autonomy of choosing prices and separately acquire various market shares according to which the relationship between the two prices is simply quantified the order up to inventory policy and the moving average forecasting method are respectively employed by the two retailers furthermore we cast light on how factors like price market share lead time and autoregressive coefficient affect bullwhip effect the results indicate that it s inadvisable to conduct large fluctuation on price besides demand dates that are more historical may actually reduce the bullwhip effect we also find that the bullwhip effect will be bigger when the competition becomes fiercer and there s a necessity for retailers to take measures to reduce the influence of competitors prices

inventories and the volatility of production a stylized fact associated with inventory behavior is that the variance of production exceeds the variance of sales this paper presents a model of production decisions with demand uncertainty that incorporates no nnegativity constraints on inventories even with no productivity shocks optimal behavior by the firm is consistent with this stylized fact either if demand exhibits positive serial correlation or if the firm can backlog excess demand the reason is that a demand shock affects both the actual inventory level given unchanged production and the desired level production must replenish the stock and adjust to the new desired level copyright 1987 by american economic association

conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing abstract a reverse bullwhip effect in pricing rbp occurs when an amplification of price variability takes place moving from the upstream suppliers to the downstream customers in a supply chain in this study we investigate rbp conditions for supply chains where joint replenishment and pricing decisions are made commencing with a single stage supply chain in which a retailer faces a random and price sensitive demand we extend the results to a multi stage supply chain using a leader follower game theoretical framework we discuss rbp conditions for supply chains where newsvendor and continuous review inventory policies are employed and present numerical examples for commonly used demand functions

goodwill inventory penalty and adaptive supply chain management abstract information visibility is generally useful for decision makers distributed across supply chains availability of information on inventory levels price lead times demand etc can help reduce uncertainties as well as alleviate problems associated with bullwhip effect a majority of extant literature in this area assume a static supply chain network configuration while this was sufficient a few decades ago advances in e commerce and the ease with which order processing can be performed over the internet necessitates appropriate dynamic re configuration of supply chains over time each node in the supply chain is modeled as an actor who makes independent decisions based on information gathered from the next level upstream a knowledge based framework is used for dynamic supply chain configuration and to consider the effects of inventory constraints and goodwill as well as their effects on the performance dynamics of supply chains preliminary results indicate that neither static nor dynamic configurations are consistently dominant scenarios where static configurations perform better than the modeled system are identified

hospital insurer bargaining an empirical investigation of appendectomy pricing employers increased sensitivity to health care costs has forced insurers to seek ways to lower costs through effective bargaining with providers what factors determine the prices negotiated between hospitals and insurers the hospital insurer interaction is captured in the context of a bargaining model in which the gains from bargaining are explicitly defined appendectomy was chosen because it is a well defined procedure with little clinical variation our results show that certain hospital institutional arrangements e g hospital affiliations hmo penetration and greater hospital concentration improve hospitals bargaining position furthermore hospitals bargaining effectiveness has diminished over time and varies across states

the multivariate bullwhip effect abstract a multivariate bullwhip expression for m products with an order up to inventory policy is developed the demand models under consideration are differenced stationary vector time series with a wold representation for which general forecasting formulas are available resulting in a large class of possible models including nonstationary ones examples are provided for common demand models and implemented on sales data it is found that the multivariate approach gives rise to mechanisms for understanding and reducing the bullwhip effect through horizontal information sharing particularly for the nonstationary demand case in the stationary setting a more nuanced approach to bullwhip reduction can be achieved by managing the relationship between cross correlations and lead times a method of determining whether a multivariate or univariate approach generates a lower bullwhip effect is proposed

an empirically simulated investigation of the impact of demand forecasting on the bullwhip effect evidence from u s auto industry this study empirically examines the impacts of three major aspects of demand forecasting on the magnitude of the bullwhip effect three research questions are addressed to investigate the association between 1 forecast accuracy 2 aggregate forecasting and 3 responsive forecasting and the bullwhip effect using forecasted demand generated from popular time series forecasting models and real life demand data the study investigates the relationship between the forecasted results and the consequential bullwhip effect the findings show that the forecasting methods used lead to the variation of the bullwhip effect moreover the lead time reduction and the stable demand forecast are beneficial to reduce the bullwhip effect however our empirical results differ from previous findings in two ways i improving forecast accuracy does not necessarily reduce the bullwhip effect and ii aggregate forecasting does not always reduce the bullwhip effect

bargaining power fear of disagreement and wage settlements theory and evidence from u s industry the paper develops and estimates a theoretical model of wage determination and union nonunion wage differentials in order to overcome the institutional ctiticisms of the formal bargaining literature the paper generalizes the nash zeuthen harsanyi model by linking the solution to the institutional concepts of bargaining power and fear or cost of disagreement and by making the outcome depend not only on endogenous but also on exogenous factors an operational specification of bargaining power and fear of disagreement allows the model to be estimated with data covering twelve companies and trade unions during the period from mid 1950 s to the late 1970 s while giving limited support to the nashzeuthen harsanyi solution the empirical analysis indicates that the bargaining outcome usually deviates from the nash zeuthen harsanyi point and in accordance with the institutionalist claim that it varies significantly with exogenous factors contrary to the traditional labor economics view the results do not support the general conclusion that the bargaining solution lies on the marginal revenue product curve of labor instead the relevant coefficients suggest that for many firms and unions the outcome might be better characterized by the efficient contract vertical contract curve

impacts of forecast inventory policy and lead time on supply chain inventory a numerical study abstract this paper first proposes the use of metaheuristic to combine with exponential smoothing methods in forecasting future demands and in determining the optimal inventory policy values for each node in a supply chain network based on historical demand or order streams without the need of any prior knowledge about the demand distribution or distribution fitting the effects of five demand forecasting methods two inventory policies and three lead times on the total inventory cost of a 3 echelon serial supply chain system are then investigated the effect of sharing the demand information for planning the inventories is also compared with that of no sharing for testing 15 quarterly and 15 monthly time series were taken from the m3 competition and are considered as the multi item demand streams to be fulfilled in the supply chain the results indicate that 1 the damped pegel forecasting method is the best in terms of prediction errors because it outperforms others in three of five measures followed by the simple exponential smoothing that wins one of the remaining two and ties the damped pegel in one 2 the supply chain inventory cost increases with increasing lead time and echelon level of the supply chain when the s s policy is used but not the r q policy 3 the r q inventory policy generally incurs lower supply chain inventory cost than the s s policy 4 sharing demand information reduces inventory cost and the reduction is higher for s s than for r q 5 the best demand forecasting method for minimizing inventory cost varies with the inventory policy used and lead time and 6 the correlation between forecasting errors and inventory costs is either negligible or minimal

demand fluctuation and chaotic behaviour by interaction between customers and suppliers this paper presents an investigation on simulation of interaction between customers and suppliers in a three tier supply chain system in the simulation customers respond to the price discount offer made by the supplier and the supplier makes adjusts the price according to stock held the simulation shows that the behaviour of such interaction exhibits deterministic chaos it is found that the attractors of the model move with the environment and the initial states thus the bifurcating points in such a system are unable to provide a guideline in system design to avoid chaos

coordinating lead times and safety stocks under autocorrelated demand we consider a supply chain in which orders and lead times are linked endogenously as opposed to assuming lead times are exogenous this assumption is relevant when a retailer s orders are produced by a supplier with finite capacity and replenished when the order is completed the retailer faces demands that are correlated over time either positively or negatively which may for example be induced by a pricing or promotion policy the auto correlation in demand affects the order stream placed by the retailer onto the supplier and this in turn influences the resulting lead times seen by the retailer since these lead times also determine the retailer s orders and its safety stocks which the retailer must set to cover lead time demand there is a mutual dependency between orders and lead times the inclusion of endogenous lead times and autocorrelated demand represents a better fit with real life situations however it poses some additional methodological issues compared to assuming exogenous lead times or stationary demand processes that are independent over time by means of a markov chain analysis and matrix analytic methods we develop a procedure to determine the distribution of lead times and inventories that takes into account the correlation between orders and lead times our analysis shows that negative autocorrelation in demand although more erratic improves both lead time and inventory performance relative to iid demand positive correlation makes matters worse than iid demand due to the endogeneity of lead times these effects are much more pronounced and substantial error may be incurred if this endogeneity is ignored

a novel time varying bullwhip effect metric an application to promotional sales abstract bullwhip effect is a problem of paramount importance that reduces competitiveness of supply chains around the world a significant effort is being devoted by both practitioners and academics to understand its causes and to reduce its pernicious consequences nevertheless limited research has been carried out to analyse potential metrics to measure it that typically are summarized in the coefficient of variation ratio of different echelons demand this work proposes a new metric based on a time varying extension of the aforementioned bullwhip effect metric by employing recursive estimation algorithms expressed in the state space framework to provide at each single time period a real time bullwhip effect estimate in order to illustrate the results a case study based on a serially linked supply chain of two echelons from the chemical industry is analysed particularly this metric is employed to analyse the effect of promotional campaigns on the bullwhip effect on a real time fashion the results show that effectively the bullwhip effect is not constant along time but interestingly it is reduced during the promotional periods and it is bigger before and after the promotion takes place

impact of market demand mis specification on a two level supply chain this paper investigates the impact of mis specifying the market demand process on a serially linked two level supply chain box jenkins models are used to represent both the true and a mis specified market demand processes it is shown that the impact of mis specification on cost is minor if the supply chain tries to minimise the market demand forecast errors furthermore our analysis suggests that mis specification does not always result in additional costs a managerial insight is revealed poor forecast accuracy is not always bad for the total supply chain costs in other words employing more accurate forecasting methods may actually result in higher total supply chain costs

the bullwhip effect in capacitated supply chains with consideration for product life cycle aspects abstract this paper presents an analysis of the bullwhip effect and net stock amplification in a three echelon supply chain considering step changes in the production rates during a product s life cycle demand the analysis is focused around highly complex and engineered products e g automobiles that have relatively long production life cycles and require significant capital investment in manufacturing using a simulation approach we analyze three stages of the product life cycle including low volumes during product introduction peak demand and eventual decline toward the end of the life cycle parts of the simulation model have been adopted by a major north american automotive oem as part of a scenario analysis tool for strategic supply network design and analysis the simulation results show that performance of a system as a whole deteriorates when there is a step change in the life cycle demand while restriction in production capacity does not significantly impact the bullwhip effect it increases the net stock amplification significantly for the supply chain setting under consideration furthermore a number of important managerial insights are presented based on sensitivity analysis of interaction effect of capacity constraints with other supply chain parameters

rational expectations and tax policy experimental market evidence abstract experimental markets are used to test whether 1 1 subjects forecasts of future and unknown policy conform to the rational expectations hypothesis and 2 2 subjects purchases of commodities are made in anticipation of such policy forecast results confirm previous studies that support adaptive expectations on the other hand subjects exhibited a type of as if rationality by learning to alter their commodity purchases intertemporally in anticipation of fiscal changes this ability was only slightly diminished when policy was stochastic or when the micro economies were in disequilibrium and in chaos

joint optimisation of demand forecasting and stock control parameters abstract exponential smoothing methods are very commonly used for forecasting demand in a supply chain context when estimating the parameters used in these methods a common practice is to optimise only the smoothing constants and not the initial parameter values in this paper we show that if we treat initial values as well as smoothing constants as decision variables a considerable reduction in forecast error can be achieved additionally the optimisation of the forecasting method should not be treated separately from the production or inventory model in which forecasts are used the case of a centralised supply chain with an order up to inventory policy shows that calculated forecasts of demand determined by minimising mean absolute error mae or mean squared error mse are not optimal finally a method for simultaneous optimisation of demand forecasting and a stock control policy is described initial and smoothing parameters in the forecasting methods can be determined to minimise the total costs

bullwhip effect measurement and its implications the bullwhip effect or demand information distortion has been a subject of both theoretical and empirical studies in the operations management literature in this paper we develop a simple set of formulas that describe the traditional bullwhip measure as a combined outcome of several important drivers such as finite capacity batch ordering and seasonality our modeling framework is descriptive in nature as it features certain plausible approximations that are commonly employed in practical inventory systems the results are nonetheless compelling and can be used to explain various conflicting observations in previous empirical studies building on the theoretical framework we discuss the managerial implications of the bullwhip measurement we show that the measurement can be completely noninformative about the underlying supply chain cost performance if it is not linked to the operational details such as decision intervals and leadtimes specifically we show that an aggregated measurement over relatively long time periods can mask the operational level bullwhip in addition we show that masking also exists under product or location aggregation in some illustrative cases

the effect of replenishment policies on the bullwhip effect a transfer function approach an important phenomenon in supply chain management known as the bullwhip effect suggests that demand variability increases as one moves up a supply chain this paper examines the influence of different replenishment policies on the occurrence of the bullwhip effect the paper demonstrates that certain replenishment policies can in themselves be inducers of the bullwhip effect while others inherently lower demand variability the main causes of increase in variability are projections of future demand expectations which result in over exaggerated responses to changes in demand we suggest that through appropriate selection and use of certain replenishment rules the bullwhip effect can be avoided subsequently allowing supply chain management costs to be lowered

nash bargaining model of hmo premiums this paper estimates a model of commercial hmo premiums based on nash s axiomatic approach to bargaining between hmos and employers the bargaining models incorporate variables that measure the power of the parties to affect the division of potential gains from a contract it is found that an increase in the number of competing hmos increases the employer s bargaining power and leads to lower premiums especially for for profit hmos it is also found that employers bargaining power over non profit hmos is positively related to the ratio of the hmo s administrative expenses total expenses

inventories and sticky prices more on the microfoundations of macroeconomics the role of inventories in making prices sticky is studied by analyzing a dynamic linear quadratic model of a monopoly firm facing stochastic demand but able to store its finished goods in inventory it is shown that in contrast to the usual presumption firms that exhibit the smallest output responses to demand fluctuations may also exhibit the smallest price fluctuations specifically firms which have very flexible inventory storage facilities or are subjected to very transitory demand shocks will rely on inventories as buffers and will change neither production nor price very much on the other hand firms which have very inflexible storage facilities or whose demand shocks are quite permanent will display large swings in both price and output the standard assumption about inventory carrying costs that has been used in the literature that they are linear is shown to imply that production is impervious to fluctuations in demand it is also established that prices may respond more strongly to positive demand shocks than to negative ones if it is impossible to hold negative inventories i e to have unfilled orders the model offers an explanation for stickiness in relative prices however under certain circumstances it may help explain the persistence of inflation this abstract was borrowed from another version of this item

can the production smoothing model of inventory behavior be saved the production smoothing model of inventory behavior has a long and venerable history and theoretical foundations that seem very strong yet certain overwhelming facts seem not only to defy explanation within the production smoothing framework but actually to argue that the basic idea of production smoothing is all wrong most prominent among these is the fact that the variance of detrended production exceeds the variance of detrended sales this paper first documents the stylized facts then it derives the production smoothing model rigorously and explains how the model can be amended to make it consistent with the facts finally it reviews the theoretical and empirical evidence and tries to draw some tentative conclusions

a pragmatic approach to the design of bullwhip controllers it is well known that forecasting mechanisms can greatly increase bullwhip demand variance amplification of orders as processed by both human and algorithmic decision makers this paper is concerned with the application of the well established apiobpcs decision support system a variant of the order up to rule in such circumstances it has two feedback controls based on the inventory and the orders in pipeline respectively with gains set equal according to the deziel eilon rule there is one feed forward control based on exponential forecasting although this is not a restriction on the application of this system we consider the pragmatic role of apiobpcs in the situation where the echelon decision maker may be handling a wide range of sku s in a non altruistic environment where upmarket information may either be withheld or simply unavailable under such circumstances it has been established via site based studies that the decision makers output the orders reflect a wide range of strategies or maybe ignorance three strategies may be regarded as appropriate i e pass orders along demand smoothing and level scheduling depending on context apiobpcs can be adapted to each of these modus operandi in the first case with the added capability of smoothing the sharp edges with a modicum of inventory variation and in the last case with the advantage of built in trend detection players in non altruistic supply chains must be able to cope with added uncertainties due to lead time variations we show that apiobpcs may be well matched to such situations and is hence copable as well as capable the paper includes recommended parameter settings according to desired decision making policies

forecasting and inventory performance in a two stage supply chain with arima 0 1 1 demand theory and empirical analysis the arima 0 1 1 demand model has been analysed extensively by researchers and used widely by forecasting practitioners due to its attractive theoretical properties and empirical evidence in its support however no empirical investigations have been conducted in the academic literature to analyse demand forecasting and inventory performance under such a demand model in this paper we consider a supply chain formed by a manufacturer and a retailer facing an arima 0 1 1 demand process the relationship between the forecasting accuracy and inventory performance is analysed along with an investigation on the potential benefits of forecast information sharing between the retailer and the manufacturer results are obtained analytically but also empirically by means of experimentation with the sales data related to 329 stock keeping units skus from a major european superstore our analysis contributes towards the development of the current state of knowledge in the areas of inventory forecasting and forecast information sharing and offers insights that should be valuable from the practitioner perspective