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

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

stock rationing under service level constraints in a vertically integrated distribution system this paper addresses a rationing problem in a two level vertically integrated distribution system composed of one manufacturer and several retail points the motivating case developed in the vending machine sector and modeled as a newsvendor like problem is representative of many real settings where short term changes in demand can be substantial while capacity modification is not a viable option the paper provides an analytical discussion of the problem from two different standpoints a pure profit maximization perspective and a minimum service level perspective both subject to a product availability constraint that affects the service level the company can provide and the related expected profit by analyzing the lagrangean formulation of the problem we devise efficient computational procedures based on dichotomy search to find the optimal allotments to retailers maximizing the expected profit and ensuring a minimum service level then we extend the analysis to the evaluation of the highest service level that can be provided under a product availability constraint we identify conditions such that the proposed search procedures succeed in finding the optimal solutions as well as bounds for the search domains the proposed approach is legitimated under several demand distribution functions subject to a few commonly adopted restrictions that encompass many of the usually adopted continuous distributions finally the paper presents a three step decision making framework using the proposed procedures summarizing the decision paths the manufacturer might follow in order to optimize the allocation decision

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

a make to stock system with multiple customer classes and batch ordering this paper examines the impact of customer order sizes on a make to stock system with multiple demand classes we first characterize the manufacturer s optimal production and rationing policies when the demand is nonunitary and lost if unsatisfied we also investigate the optimal policies of a backorder system with two demand classes and fixed order sizes through a numerical study we show the effects of batch orders on the manufacturer s inventory cost as well as on the benefit of optimal stock rationing it is shown that batch ordering may reduce the manufacturer s overall cost if carefully introduced in a first come first served fcfs system with the same effective demand rates the customers order sizes also have a strong impact on the benefit of optimal stock rationing

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

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

an exact analytical solution to the production inventory control problem abstract the full set of continuous differential delay equations describing the inventory and orders for a typical industrial production control system are solved exactly for a step function surge in demand the replenishment delay is explicitly included the order rate is tuned with three parameters which modulate the demand smoothing the recovery of the inventory deficit and the desired level of work in process the analytical solutions are validated by comparison with numerical integration and confirm the instabilities and inventory deficits found elsewhere useful management strategies can be deduced and the approach should be widely applicable in supply chains

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

cooperation between multiple news vendors with transshipments we study a situation with n retailers each of them facing a news vendor problem i e selling to customers over a finite period of time product with a short life cycle such as fashion groups of retailers might improve their expected joint profit by coordinating their orders followed by transshipments after demand realization is known we analyze these situations by defining a cooperative game called a general news vendor game for such a situation with n retailers we concentrate on whether it makes sense to cooperate by studying properties of general news vendor games our main result states that general news vendor games have non empty cores

the extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015 in 1994 through classic control theory john naim and towill developed the automatic pipeline inventory and order based production control system apiobpcs which extended the original iobpcs archetype developed by towill in 1982 well recognised as a base framework for a production planning and control system due to the prevalence of the two original models in the last three decades in the academic and industrial communities this paper aims to systematically review how the iobpcs archetypes have been adopted exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains using various databases such as scopus web of science google scholar 111 papers we found that the iobpcs archetypes have been studied regarding the a modification of four inherent policies related to forecasting inventory lead time and pipeline to create a family of models b adoption of the iobpcs family to reduce supply chain dynamics and in particular bullwhip c extension of the iobpcs family to represent different supply chain scenarios such as order book based production control and closed loop processes simulation is the most popular method adopted by researchers and the number of works based on discrete time based methods is greater than those utilising continuous time approaches most studies are conceptual with limited practical applications described future research needs to focus on cost flexibility and sustainability in the context of supply chain dynamics and although there are a few existing studies more analytical approaches are required to gain robust insights into the influence of nonlinear elements on supply chain behaviour also empirical exploitation of the existing models is recommended

capacity allocation using past sales when to turn and earn consider a supplier selling to multiple retailers demand varies across periods but the supplier s capacity and wholesale price are fixed if demand is high the retailers needs exceed capacity and the supplier must implement an allocation mechanism to dole out production we examine how the choice of mechanism impacts retailer actions and supply chain performance in particular we analyze turn and earn allocation a method commonly used in the automobile industry this scheme bases current allocations on past sales and thus enables retailers to influence their future allocations they compete for scarce capacity even if they do not compete for customers we show that turn and earn induces the retailers to increase their sales when demand is low and the supplier s capacity is otherwise underutilized supplier profits thus increase the impact on the supply chain depends on how restrictive capacity is with mildly tight capacity the retailers higher sales rate does not significantly lower their profits but does reduce the cost of idle capacity supply chain performance improves with extremely tight capacity the retailers intense competition dissipates more profits than the supplier gains and supply chain performance suffers consequently turn and earn does not generally coordinate the system it is best characterized as a means for the supplier to increase her profits at the expense of the retailers and potentially even the supply chain furthermore these results hold even if the retailers can hold inventory in anticipation of scarce capacity

turn and earn incentives with a product line when manufacturers do not have sufficient capacity to meet demand and cannot increase prices they have to determine other methods to allocate goods among retailers a common allocation mechanism is based on a retailer s sales history a retailer that has ordered larger quantities in the past should get a greater allocation than a retailer that has historically ordered smaller quantities this mechanism known as a turn and earn allocation rule is commonly used in many industries such as automobiles microprocessors video game consoles etc the existing literature has considered the effect of turn and earn allocation rules when a manufacturer sells a single product however when we consider a product line it is not clear whether the manufacturer is better off basing its allocation on the sales history of the entire product line or solely on the sales history of the product in short supply in particular a shortage of one product can lead retailers and consumers to move toward other products in the line this in turn can have an effect on the manufacturer s optimal allocation mechanism we examine this issue by developing a model of a supplier selling two substitutable goods through two retailers within this setup we introduce a general turn and earn allocation rule that allows the entire sales history to influence allocation levels counter to previous work we show that certain turn and earn rules not only help the manufacturer but can also help the retailer and increase total supply chain profits this paper was accepted by martin lariviere operations management

supply network dynamics as a source of new business abstract supply networks where operational control extends well over organizational boundaries have emerged in industries producing relatively complex and customized products with tight profit margins products like ships automobiles and telecommunication systems incorporate complex design and engineering skills that are produced through a tier structured multi level supply networks efficiency in these networks has stemmed from specialization and cost efficiency in individual value adding operations this paper demonstrates how supplier networks have evolved and how the inherent dynamics of these networks generate constantly new business opportunities for fast moving companies with a clear focus on operational efficiency we use action research methodology on cases from the shipbuilding and constructions industry to document some of the dynamic features of supply networks this insight is then applied to the electronics manufacturing services business to explain the fundamentals of successful operations in this highly competitive business with ever narrowing margins in this dynamic market of contract manufacturing companies with constant focus on the reduction of production lead times by incorporating value added operations either physically or logically to maintain and recreate profitable business to succeed in doing this issues related to industrial parks local tacit knowledge and reverse repair logistics must be managed in cross organizational manner we conclude that there is an ever changing limit to the expansion of supplier networks through specialization and cost efficiency and that at one point contracting and integrating parts of the supply network will create operationally outperforming business models that further boost the inherent dynamics of supply networks

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

managing the order pipeline to reduce supply chain volatility the bullwhip effect in particular and supply chain volatility in general has been the subject of much analytical and empirical investigation by researchers one goal of this work has been to determine supply chain designs and policies that minimize volatility using a system dynamics approach we use three distinct supply chain volatility metrics to compare the ability of two alternative pipeline inventory management policies to respond to a demand shock the results indicate that no one policy dominates on all three metrics of supply chain volatility a simplistic static pipeline policy minimizes the bullwhip effect and lessens the likelihood of on hand inventory oscillations while a more sophisticated dynamic pipeline policy may converge more rapidly to the new equilibrium in addition simulation results suggest that the dynamic policy provides better customer service through fewer stockouts and backorders

the impact of sharing customer returns information in a supply chain with and without a buyback policy in this paper we examine a single period problem in a supply chain in which a stackelberg manufacturer supplies a product to a retailer who faces customer returns and demand uncertainty we show that the manufacturer incurs a significant profit loss with and without a buyback policy if it fails to account for customer returns in the wholesale price decision under the assumption that the retailer is better informed than the manufacturer on customer returns information we show that without a buyback policy the retailer prefers not to share if the manufacturer overestimates while it prefers to share customer returns information if the manufacturer underestimates this information if the manufacturer offers a buyback policy we have the opposite results we also discuss incentives to share the customer returns information and some of the issues that are raised in sharing this information

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

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

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

optimizing reorder intervals for two echelon distribution systems with stochastic demand we consider a periodic review inventory system in which n non identical retailers replenish from a warehouse which further replenishes from an outside vendor with ample supply each facility faces poisson demand and replenishes according to a base stock policy in a fixed time interval fixed costs are incurred for placing an order the warehouse fills the retailers orders in the same sequence as the occurrence of the demand at the retailers the objective is to minimize the average system cost per period this paper develops an evaluation scheme and provides a method to obtain the optimal base stock levels and reorder intervals specifically with fixed reorder intervals we show that the optimal base stock levels can be obtained by generalizing the result in the literature to find the optimal reorder intervals we first allocate the total system cost to each facility and then construct a lower bound to the allocated facility cost these lower bound functions which are separable functions of reorder i

the bullwhip effect in closed loop supply chains a systematic literature review abstract the bullwhip effect or how uncertainty associated with the end customers demand propagates through the entire supply chain has been widely discussed in supply chain management literature although there is a well established research stream on the causes and mitigating factors for the bullwhip effect in forward supply chains few studies have investigated how this phenomenon manifests itself in closed loop supply chains we argue that this phenomenon can affect the supply chain s environmental performance by increasing emissions waste and consumption of natural resources aiming at filling this theoretical gap this article compares the causes and mitigating factors of the bullwhip effect in forward supply chains and closed loop supply chains to this end we employ a systematic literature review that combines bibliometric and content analyses the studies examined in our review indicate that the causes of the bullwhip effect in closed loop supply chains are similar to those in forward supply chains however most of the studies have not considered that the quality of returned products are different from the quality of their new counterparts products adding another variable into the complexity of a given supply chain which in turn could lead to higher variability thereby causing the bullwhip effect regarding mitigation we found that the primary mitigating factor is related to increasing the product return rate moreover we suggest that closing a supply chain can reduce the bullwhip effect which could lead to positive impacts in the environmental performance of supply chains

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

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

capacity allocation and scheduling in supply chains we consider a multiple product supply chain where a manufacturer receives orders from several distributors if the orders cannot all be met from available production capacity then the manufacturer allocates that capacity and a set of resubmittable orders among the distributors the distributors may share their allocated capacity among themselves before submitting revised orders finally the manufacturer schedules the revised orders to minimize its cost we consider three practical coordination issues first we estimate the benefit to the manufacturer from considering scheduling costs and constraints in making capacity and order allocation decisions second we estimate the additional profit that the distributors achieve when they share their allocated capacity third we estimate the value of coordination between the manufacturer and the distributors our work is among the first to consider all three issues simultaneously we model scheduling costs and constraints within the manufacturer s capacity allocation problem we model the distributors capacity sharing problem as a cooperative game that has properties that are unique within cooperative game theory finally we develop optimal algorithms for all the models defined by the three coordination issues our exact evaluation of decisions about the appropriate coordination level improves managers ability to make those decisions

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 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 in supply chain networks this paper analyzes the propagation and amplification of order fluctuations i e the bullwhip effect in supply chain networks operated with linear and time invariant inventory management policies the supply chain network is allowed to include multiple customers e g markets any network structure with or without sharing information the paper characterizes the stream of orders placed by any supplier for any stationary customer demand processes and gives exact formulas for the variance of the orders placed and the amplification of order fluctuations the paper also derives robust analytical conditions based only on inventory management policies to predict the presence of the bullwhip effect for any network structure any inventory replenishment policies and arbitrary customer demand processes numerical examples show that the analytical results accurately quantify the bullwhip effect managerial insights are drawn from the analysis the methodology presented in this paper generalizes those in previous studies for serial supply chains

robust optimization of the 0 1 knapsack problem balancing risk and return in assortment optimization abstract retailers face the important but challenging task of optimizing their product assortments the challenge is to find for every category in every store the assortment that maximizes expected category profit adding to the complexity of this 0 1 knapsack problem retailers should also consider the risk associated with every assortment while every product in the assortment offers an expected return there is also uncertainty around its expected demand and profit contribution therefore retailers face the difficult task of designing a portfolio of products that balances risk and return in this paper we develop a robust approach to optimize retail assortments that offers this balance since the dimensionality of this robust 0 1 knapsack problem in practice often precludes full enumeration we propose a novel efficient and real time heuristic that solves this problem the heuristic constructs an approximation of the risk return efficient frontier of assortments we find that the robust solutions offer the retailer a considerable reduction in risk variance yet only imply a small reduction in expected return the constructed approximations contain assortments that are optimal solutions to the robust assortment optimization problem moreover they represent insightful visualizations of the solution space allowing for interactivity what risk premium should the retailer pay in real time matter of seconds

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

experimental tests of the endowment effect abstract the endowment effect which predicts undertrading and a willingness to accept greater than willingness to pay is studied using responses that remove all reference to buying or selling and focuses only on choice tasks the results significantly lower the willingness to pay willingness to accept discrepancy but the latter is still significant a high efficiency open display uniform price auction is used to exchange mugs for money since mugs are randomly assigned to half of 2n subjects n 2 mugs are predicted to trade less than n 2 mugs trade on average but more than previously reported the phenomenon exists but is less prominent than reported previously

state space investigation of the bullwhip problem with arma 1 1 demand processes using state space techniques we study a myopic order up to policy the policy is myopic because it is optimal at minimising local inventory holding and shortage costs in particular we study the bullwhip effect produced by the replenishment policy reacting to a stochastic arma 1 1 demand processes we reveal that bullwhip is fundamentally caused by the co variance between the inventory level and the demand forecast we go on to highlight the impact of a simple control engineering inspired bullwhip reduction technique a proportional controller in the inventory feedback loop although it can be shown this approach is always able to remove bullwhip we expose that it is not possible to arbitrarily tune the proportional controller without knowing in advance the likely structure of the demand process we conclude with an investigation of trade offs and optimisations in the order and inventory variance and their sum produced by our policy

on the stability of supply chains this paper examines the stability of decentralized multistage supply chains under arbitrary demand conditions it looks for intrinsic properties of the inventory replenishment policies that hold for all customer demand processes and for policies with desirable properties it is found that the overall conditions experienced by suppliers several stages removed from the final customer e g the variances of the orders they receive and the inventories they keep depend on the policy much more than on the demand process a policy specific but demand independent upper bound for the order variance amplification factor of any decentralized policy is shown to exist and its formula is presented the bound is always tight for the suppliers at the end of a long chain so that a policy exhibits the bullwhip effect if and only if its bound is greater than 1 a simple necessary condition for bullwhip avoidance is also identified in terms of a policy s gain gain is the marginal change in average inventory induced by a policy when there is a small but sustained change in the demand rate it is shown thatall policies with positive gain produce the bullwhip effect if they do not use future order commitments because manufacturers can reduce costs by operating with positive gain this explains the prevalence of the bullwhip effect a family of commitment based policies that can dynamically maintain any desired inventory level for any demand rate e g achieve positive gain without the bullwhip effect is also presented the family includes just in time strategies as a special case simulation results are used as an illustration

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

supply chain coordination perspectives empirical studies and research directions supply chains sc are generally complex and are characterized by numerous activities spread over multiple functions and organizations which pose interesting challenges for effective sc coordination to meet these challenges sc members must work towards a unified system and coordinate with each other a systematic literature review is presented in this paper to throw light on the importance of sc coordination the objectives of this paper are to report and review various perspectives on sc coordination issues understand and appreciate various mechanisms available for coordination and identify the gaps existing in the literature a framework is suggested indicating scope for further research

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

characterization of the bullwhip effect in linear time invariant supply chains some formulae and tests the authors analyze the bullwhip effect in multistage decentralized supply chains operated with linear and time invariant inventory management policies the focus is on robustness the supply chain is modeled as a single input single output control system driven by arbitrary customer demands the authors derive robust analytical conditions to predict the presence of the bullwhip effect and bound its magnitude based only on the way inventories are managed these results hold independently of the customer demand the authors also characterize the stream of orders placed at any stage of the chain when the customer demand process is known and ergodic and give an exact formula for the variance of the orders placed this formula generalizes existing results by broadening the class of inventory replenishment policies and customer demand processes to which it applies the authors also show that the bullwhip effect can be mitigated by introducing commitments for future orders into the ordering policies

trust trustworthiness and information sharing in supply chains bridging china and the united states whether and how trust and trustworthiness differ between a collectivist society e g china and an individualistic one e g the united states generates much ongoing scientific debate and bears significant practical values for managing cross country transactions we experimentally investigate how supply chain members countries of origin china versus the united states affect trust trustworthiness and strategic information sharing behavior in a cross country supply chain we consider a two tier supply chain in which the upstream supplier solicits demand forecast information from the retailer to plan production but the retailer has an incentive to manipulate her forecast to ensure abundant supply the levels of trust and trustworthiness in the supply chain and supplier s capability to determine the optimal production quantity affect the efficacy of forecast sharing and the resulting profits we develop an experimental design to disentangle these three aspects and to allow for real time interactions b

the strategic peril of information sharing in a vertical nash supply chain a note abstract conventional wisdom suggests that information sharing benefits at least one of the participants however we find that information sharing can be strategically detrimental to both members in a vertical nash supply chain comparative statics show that each supply chain member s beneficial areas are smaller when its information source becomes more variable and larger as its signal is less accurate furthermore the pareto inferior areas in which both supply chain members get worse are non monotonic in exogenous parameters

optimal policies and approximations for a serial multiechelon inventory system with time correlated demand since clark and scarf s pioneering work most advances in multiechelon inventory systems have been based on demand processes that are time independent this paper revisits the serial multiechelon inventory system of clark and scarf and develops three key results first we provide a simple lower bound approximation to the optimal echelon inventory levels and an upper bound to the total system cost for the basic model of clark and scarf second we show that the structure of the optimal stocking policy of clark and scarf holds under time correlated demand processes using a martingale model of forecast evolution third we extend the approximation to the time correlated demand process and study in particular for an autoregressive demand model the impact of lead times and autocorrelation on the performance of the serial inventory system

the effects of information transparency on suppliers manufacturers and consumers in online markets this paper looks into the effects of information transparency on market participants in an online trading environment we study these effects in business to business electronic markets with firms competing in both upstream and downstream industries the prior literature generally assumes that either the downstream firm buyer or the upstream firm seller is a monopoly it is not clear whether information transparency would still create value if both buyers and sellers face oligopolistic competition where the benefits of information transparency could be competed away to answer this question we first develop a simple two echelon e market model and then extend the model to more general settings we find that information transparency can create value for the overall e market yet it affects buyers and sellers very differently one side will be hurt depending on the competition mode cournot or bertrand in the downstream this suggests that a manufacturer owned a supplier owned and a neutral e market will have different preferences for information transparency finally we find that information transparency can hurt consumers when the downstream industry engages in bertrand competition this is a surprising result given the expectation that online markets create substantial value for consumers

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 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

quantifying the bullwhip effect in closed loop supply chains the interplay of information transparencies return rates and lead times abstract the bullwhip effect manifests itself in the form of an increased order and inventory variability in the uppermost nodes of the supply chain this dynamic phenomenon is not yet well understood in closed loop supply chain settings despite their growing importance in modern societies pursuing circular economy opportunities indeed the problem specific literature has provided somewhat conflicting findings to better understand the bullwhip effect in closed loop systems we obtain expressions for the order and inventory variance amplification in four archetypes that differ in the structure of information transparency interestingly we observe that the impact of return rates and lead times on the system performance strongly depend on the degree of supply chain visibility this perspective allows us to revisit discrepancies in prior works we later move the study from the operational to the economic prism here we prove the existence of an optimal return rate and we derive its expression in the four closed loop supply chain archetypes we show that the optimal rate is dependent on the node s cost structure the lead times and the variability of demand properties of the different closed loop systems and relevant managerial implications are also discussed in our work

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

measuring endogenous supply chain volatility beyond the bullwhip effect most recent research on supply chain volatility has focused on one particular dimension of that volatility namely the amplification of upstream order variability while not ignoring this aspect of supply chain volatility we focus on a different but equally critical aspect of volatility the cyclical oscillation of on hand and on order inventories about their target values we prove that such cyclicality does not require oscillatory or random retailer demand as a prerequisite the resulting volatility is therefore endogenous rather than simply an amplification of exogenous demand inputs we also measure the amount of amplification resulting from a step increase in demand the order amplification is the product of two factors each of which is clearly linked to either on hand or on order inventory our results attest that supply chain volatility can arise in the absence of exogenous oscillatory or random demand and suggest strategies for avoiding or minimizing such volatility

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 empirical investigation on causes and effects of the bullwhip effect evidence from the personal care sector abstract this paper analyses the empirical demand data for fast moving consumer goods to measure the bullwhip effect the data consist of the sell in from a large manufacturer to the retailers and the sell out from a retailer to the consumers our findings show that the bullwhip effect can be substantial indeed in more than 50 of the cases the demand upstream sell in is twice as variable as the demand downstream sell out however in other cases it can be negligible and in one case the demand upstream is slightly less variable than the demand downstream so while the bullwhip effect can be very large it need not be so finally we attempted to delve into the dynamics that generate a significant bullwhip effect and discovered that among the various causes that create the bullwhip effect discussed by lee et al 1997a price fluctuations and forward buys driven by sales targets play a decisive role we show that the flatter the final consumer demand sell out the more room there is for the retailers to forward buy in order to take advantage of the deals offered by the manufacturer s sales force toward the end of the sales period on the contrary the more variable the final consumer demand the less willing the retailer is to make a risky inventory investment and thus the more the retailer s orders closely follow consumer demand this result at the product family level is very consistent with the results that cachon et al 2007 obtained at the company industry level

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

vertical contracts in a supply chain and the bullwhip effect this paper shows that decentralized supply chains in which upstream firms use linear wholesale prices may experience lower upstream production and downstream sales volatility than vertically inte

on the variance of intermittent demand estimates intermittent demand occurs at random with many time periods showing no demand at all forecasting such demand patterns constitutes a challenging exercise because of the associated dual source of variation demand intervals and demand sizes research in this area has developed rapidly in recent years with new results implemented into supply chain software solutions because of its practical implications in an inventory context both the accuracy of the forecasts and their variability sampling error of the mean have equal importance in terms of service level achievement and or inventory cost minimisation although the former issue has been studied extensively mainly building upon croston s model 1972 the latter has been largely ignored the purpose of this paper is to analyse the most well cited intermittent demand estimation procedures in terms of the variance of their estimates detailed derivations are offered along with a discussion of the underlying assumptions as such we hope that our contribution may constitute a point of reference for further analytical work in this area as well as facilitate a better understanding of issues related to modelling intermittent demands

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

in search of intra industry bullwhips abstract previous research e g cachon et al 2007 has examined the prevalence and magnitude of the bullwhip effect across industries measuring the bullwhip as the ratio of the variance in the stream of orders placed relative to the variance in orders received in some cases surrogates are used for the order measures our contribution is to use the decomposition framework of jin et al 2016a to look intra industry examining whether the bullwhip is created in shipping manufacturing or ordering and exploring whether this varies across industries our analysis is based on monthly industry level u s census bureau data we find and begin to explain significant differences across industries regarding the source of the bullwhip be it in shipping manufacturing and or ordering we also examine how the bullwhip is impacted by the duration and end point of the time aggregation interval our results suggest that some managers may want to shift their reporting period

measure of bullwhip effect in supply chains with autoregressive demand process abstract in supply chain management one of the most critical problems which require a lot of effort to deal with is how to quantify and alleviate the impact of bullwhip effect the phenomenon in which information on demand is distorted while moving upstream although it is well established that demand forecast lead time order batching shortage gaming and price fluctuation are the main sources that lead to the bullwhip effect the problem of quantifying bullwhip effect still remain unsolved in many situations due to the complex nature of the problem in this research a measure of bullwhip effect will be developed for a simple two stage supply chain that includes only one retailer and one supplier in the environment where the retailer employs base stock policy for their inventory and demand forecast is performed through the first order autoregressive model ar 1 the effect of autoregressive coefficient and lead time on this measure will then be investigated

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

bullwhip and batching an exploration the rounding of orders to achieve a batch size is recognised as a source of the bullwhip problem within supply chains while it is often advocated that batch sizes should be reduced as much as possible there has been limited investigation into the impact of batching on bullwhip here we consider scenarios where orders are placed only in multiples of a fixed batch size for both deterministic and stochastic demand rates we derive a closed form expression for bullwhip when demand is deterministic this is validated through a simple model of a production control system an expression for bullwhip in a pass on orders scenario with stochastic demand is also derived and validated using simulation we show the impact of changing batch size on bullwhip in a production control system our results show that a manager may achieve economies through batching while minimising the impact on bullwhip through the careful selection of the batch size

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

strategic commitments for an optimal capacity decision under asymmetric forecast information we study the important problem of how to assure credible forecast information sharing between a supplier and a manufacturer the supplier is responsible for acquiring the necessary capacity before receiving an order from the manufacturer who possesses private forecast information for her end product we address how different contracts affect the supplier s capacity decision and hence the profitability of the supplier and the manufacturer we fully develop two contracts and provide explicit formulae to enable credible forecast information sharing the first is a nonlinear capacity reservation contract under which the manufacturer agrees to pay a fee to reserve capacity the second is an advance purchase contract under which the manufacturer is induced to place a firm order before the supplier secures the component capacity used to build the end product these contracts serve a strategic role in information sharing the capacity reservation contract enables the supplier to detect the manufacturer s private forecast information while the advance purchase contract enables the manufacturer to signal her forecast information we show that channel coordination is possible even under asymmetric forecast information by combining the advance purchase contract with an appropriate payback agreement through our structural and numerical results we also show that the degree of forecast information asymmetry and the risk adjusted profit margin are two important drivers that determine supply chain efficiency and which contract to adopt

optimal fiscal federalism in the presence of tax competition abstract this paper models the optimal division of public goods provision between central and regional governments in an economy with interregional tax competition regional provision is inefficient because governments compete for scarce capital by lowering their capital taxes and public good levels to inefficiently low levels on the other hand central provision is inefficient because it is determined by the minimum winning coalition within a legislature the optimal degree to which public good provision should be decentralized depends on a tradeoff between these inefficiencies in our main model complete centralization is never optimal regional governments should supply some public goods

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

an infinite horizon inventory model with periodic order commitment abstract this paper studies an infinite horizon inventory model of a buyer with a periodic order commitment the commitment requires the buyer to purchase at least a certain fixed amount on a periodic basis there is no extra adjustment cost should the buyer decide to order more than the basic amount we consider general discrete demand distributions we formulate a markov chain to represent the behavior of the inventory system stimulated by the solution approach to the classical gi m 1 queue we derive the steady state results and obtain the exact closed form cost function numerical examples are provided

analyzing the effect of the inventory policy on order and inventory variability with linear control theory in this paper we apply linear control theory to study the effect of various inventory policies on order and inventory variability which are key drivers of supply chain performance in particular we study a two echelon supply chain with a stationary demand pattern under the influence of three inventory policies an inventory on hand policy that bases orders on the visible inventory at an installation an installation stock policy that bases orders on the inventory position on hand plus on order inventory at an installation and an echelon stock policy that bases orders on the inventory position at that installation and all downstream installations we prove analytically that the inventory on hand policy is unstable in practical settings confirming analytically what has been observed in experimental settings and in practice we also prove that the installation stock and echelon stock policies are stable and analyze their effect on order and inventory fluctuation specifically we show the general superiority of the echelon stock in our setting and demonstrate analytically the effect of forecasting parameters on order and inventory fluctuations confirming the results in other research

modeling and analysis of cash flow bullwhip in supply chain abstract the bullwhip effect that occurs in supply chain inventory can distort demand forecasts and lead to inefficiencies such as excessive inventory stock outs and backorders in this paper we theorize that inventory bullwhip also leads to cash flow bullwhip cfb specifically this paper focuses on studying cfb by developing mathematical and simulation models to analyze the relationship between inventory and cash flow bullwhip by using cash conversion cycle ccc as a metric the mathematical models for inventory bullwhip are developed for two stage and generic multi stage supply chains and then by extending these inventory models the cfb models are developed for two stage cfb predicted by the proposed mathematical models approximately differ 14 from detailed simulation models we find that increasing variability increases inventory and cash flow bullwhip along with lead time whereas increasing the demand observation period has the opposite effect the average marginal impact of the bullwhip effect on the cfb is approximately 20 additionally the cfb is also an increasing function of an expected value of inventory and a decreasing function of an expected value of demand

capacity restrictions and supply chain performance modelling and analysing load dependent lead times abstract several studies have reported that capacitated supply chains may benefit from an improved dynamic performance as compared to unconstrained ones this occurs as a consequence of the capacity limit acting as a production smoothing filter in this research the relationship between capacity restrictions and the operational performance of supply chains is investigated from a novel perspective i e we assume that the influence of capacity constraints on lead times depends on the supply chain s responsiveness under these circumstances the experiments show that there is a negative effect of capacity constraints on supply chain performance both in terms of process efficiency internal and customer satisfaction external nonetheless the magnitude of this impact greatly depends on the responsiveness of the firm market conditions and adopted policies for inventory management more specifically the combination of tight capacity restrictions and low responsiveness significantly contributes to decrease supply chain performance which may be very damaging for the dynamic behavior of the system in this sense efficient capacity planning proves to be essential to prevent the supply chain from entering into a vicious circle

coordinating supply chains with competition capacity allocation in semiconductor manufacturing abstract this paper motivated by the experiences of a major us based semiconductor manufacturer presents an integrated model of incentive problems arising in forecasting and capacity allocation our model involves multiple product managers and multiple manufacturing managers who forecast the means of their respective demand and capacity distributions a central coordinator is responsible for allocating capacities to product lines when these distributions are unknown to the central coordinator and capacity is scarce the managers misrepresent their forecasts a product manager inflates his forecast to gain a greater allocation of the capacity a manufacturing manager deflates his forecast to cover for the uncertainties in production we propose a game theoretic model and design a mechanism a bonus scheme for all managers and an allocation rule to allocate realized capacity to the product managers that elicits truthful reporting by all managers the results herein show that the structure of the truth eliciting bonus schemes is rather simple with easily calculable parameters we also show that large classes of allocation rules including the current allocation practice of the firm are manipulable a bonus is often required for elicitation of truthful information we synthesize the implications of our results for the practitioners

optimal inventory decisions in a multiperiod newsvendor problem with partially observed markovian supply capacities abstract this paper considers a multi period news vendor problem with partially observed supply capacity information which evolves as a markovian process the supply capacity is fully observed by the buyer when the capacity is smaller than the buyer s ordering quantity otherwise the buyer knows that the current period supply capacity is greater than its ordering quantity based on these two observations the buyer updates the future supply capacity forecasting accordingly with a dynamic programming formulation we prove the existence of an optimal ordering policy we also prove that the optimal order quantity is greater than the myopic order quantity

pricing games and impact of private demand information in decentralized assembly systems this paper analyzes decentralized assembly systems under asymmetric demand information and sequential contracting we reveal new insights on the value of contract type price only versus complex demand information complete versus asymmetric and contract sequence first mover versus second mover to different players our results for the basic model show the following 1 complex contracts increase the suppliers aggregate profit however individual suppliers do not necessarily benefit from a complex contracting equilibrium we identify the conditions under which each supplier benefits from such an equilibrium 2 eliminating information asymmetry is not always beneficial for the suppliers because obtaining information might bring only marginal value and hence might not be realistically justified furthermore a downstream supplier might prefer information asymmetry to complete information especially when demand variability is moderate 3 unless there is a high demand risk the first mover advantage is prevalent when the assembler is a price taker we extend our basic model to analyze two additional scenarios first we study cases where the suppliers may offer contracts of different complexity beyond enriching our understanding of contract choice in decentralized assembly systems such variations enhance the analysis beyond the standard methodology of principal agent models and utilize solution techniques from optimal control second we analyze the situation where the suppliers may possess different levels of information on demand under complex contracts we show that an upstream supplier always benefits from a downstream supplier s superior information however the additional information might decrease the downstream supplier s profit especially when the forecast variability is low compared to the total demand variability in the system our results for the basic model and its extensions confirm that studying interactions between suppliers specifically under different contract types and information structures in assembly systems presents rich opportunities for future research

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

strategic commitment versus postponement in a two tier supply chain abstract in this paper the trade off between strategic commitment and operational flexibility is examined as it arises in a supply chain when a supplier offers competing buyers opportunities to make early purchase commitments for a product with a short life cycle traditionally the use of incentives for early purchase commitments for short life cycle products has been justified on the basis of a supplier s production lead times or capacity constraints an alternative explanation has been proposed by offering early purchasing opportunities a supplier can influence the form of competition in the downstream market using a single period model it has been shown that below a threshold level of demand uncertainty the supplier can benefit from providing adequate pricing incentives to entice downstream buyers to commit to purchase quantities before demand information is revealed moreover such early purchasing opportunities can benefit the supplier as well as the buyers even in the absence of production lead times or capacity constraints

measuring imputed cost in the semiconductor equipment supply chain we consider the order fulfillment process of a supplier producing a customized capital good such as production equipment commercial aircraft medical devices or defense systems as is common in these industries prior to receiving a firm purchase order from the customer the supplier receives a series of shared forecasts which are called soft orders facing a stochastic internal manufacturing lead time the supplier must decide at what time to begin the fulfillment of the order this decision requires a trade off between starting too early leading to potential holding or cancellation costs and starting too late leading to potential delay costs we collect detailed data of shared forecasts actual purchase orders production lead times and delivery dates for a supplier buyer dyad in the semiconductor equipment supply chain under the assumption that the supplier acts rationally optimally balancing the cancellation holding and delay costs we are able to estimate the corresponding imputed cost parameters based on the observed data our estimation results reveal that the supplier perceives the cost of cancellation to be about two times higher and the holding costs to be about three times higher than the delay cost in other words the supplier is very conservative when commencing the order fulfillment which undermines the effectiveness of the overall forecast sharing mechanism

quantifying value chain analysis in the context of livestock systems in developing countries the analysis of value chains has augmented our knowledge on the complexities inter linkages distributional benefits and institutional arrangements of production and marketing channels in developing countries however the analysis remains relatively qualitative and case specific with limited ability to rank or assess the impact of alternative interventions or to analyze sufficiently the complex market dynamics and feedbacks present in livestock systems this paper offers theoretical and applied insights on ways to improve the analytical rigor of the value chain methodology that combines both qualitative and quantitative approaches

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

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

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