using real option analysis for highly uncertain technology investments the case of wind energy technology this study examines the feasibility of using a theoretical model and empirical analysis methods to value renewable energy re investment from perspective of real option analysis roa based on use of a roa approach the re value is evaluated with respect to its ability to conform to the main sensitivity analysis of re investment as well as an empirical method devised to value re investment by using actual data the economic intuitiveness underlying the decision making process for re investment is elucidated while empirical analysis is performed to demonstrate the effectiveness of the options value embedded in current development planning in taiwan for wind energy in addition to revealing the advantages of re development when considering real option analytical results indicate that roa is a highly effective means of quantifying how investment planning uncertainty including managerial flexibility influences re development besides evaluating the value of current re investment this study demonstrates that results of the theoretical model empirical analysis and sensitivity analysis correlate well with each other restated the value of developing re increases when increasing the underlying price time to maturity risk free rate and volatility conversely the value of developing re decreases when increasing the exercise price

the impact of setup costs commonality and capacity on schedule stability an exploratory study abstract this paper examines the effect of setup costs component commonality and capacity on schedule stability in supply chains in particular this work focuses on the situation where schedule changes over a rolling horizon convey information that is important to successful coordination in the supply chain a lot sizing model is deployed within the structure of a designed experiment to evaluate the effects of these design factors on schedule stability findings suggest that designing component commonality into products avoiding the tendency to batch multiple customer orders into fewer production orders and providing surplus capacity have a stabilizing effect on rolling schedules

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

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

inventory management for stochastic lead times with order crossovers we study the impact of stochastic lead times with order crossover on inventory costs and safety stocks in the order up to out policy to motivate our research we present global logistics data which violates the traditional assumption that lead time demand is normally distributed we also observe that order crossover is a common and important phenomenon in real supply chains we present a new method for determining the distribution of the number of open orders using this method we identify the distribution of inventory levels when orders and the work in process are correlated this correlation is present when demand is auto correlated demand forecasts are generated with non optimal methods or when certain ordering policies are present our method allows us to obtain exact safety stock requirements for the so called proportional order up to pout policy a popular implementable linear generalization of the out policy we highlight that the out replenishment policy is not cost optimal in global supply chains as we are able to demonstrate the pout policy always outperforms it under order cross over we show that unlike the constant lead time case minimum safety stocks and minimal inventory variance do not always lead to minimum costs under stochastic lead times with order crossover we also highlight an interesting side effect of minimizing inventory costs under stochastic lead times with order crossover with the pout policy an often significant reduction in the order variance

taming the bullwhip effect whilst watching customer service in a single supply chain echelon we study a generalised order up to policy that has highly desirable properties in terms of order and inventory variance and customer service levels it generates we quantify exactly the variance amplification in replenishment orders i e the bullwhip effect and the variance of inventory levels over time for i i d and the weakly stationary auto regressive ar moving average ma and auto regressive moving average arma demand processes we demonstrate that high customer service as measured by fill rate and smooth replenishments need not increase inventory cost substantially we observe that in some instances of the arma demand pattern this comes at the expense of a relatively small increase in safety stock whilst in other instances inventory levels can actually be reduced

learning from private and public observations of othersʼ actions we study how a continuum of agents learn about disseminated information by observing others actions every period each agent observes a public and private noisy signal centered around the aggregate action taken by the population the public signal represents an endogenous aggregate variable such as a price or a quantity the private signal represents the information gathered through private communication and local interactions we identify conditions such that the average learning curve is s shaped learning is slow initially intensifies rapidly and finally converges slowly to the truth we show that increasing public information always slows down learning in the long run and under some conditions reduces welfare lastly optimal diffusion of information requires that agents strive to be different agents need to be rewarded for choosing actions away from the population average

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

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

considering the investment decisions with real options games approach abstract the mix of games theory with the real options has been a dynamic range of exploration in the most recent decade the engaging quality of the specialists for displaying aggressive speculation choices by blending ideas from both hypotheses is on account of a venture choice in a focused business sector can be seen in its substance as a game between firms in this paper we expand a model to consider finite horizon real option games under incomplete information with various parameters in incomplete information games firms actions express significant information about profitability to contestants the encapsulation of this information proposed original blocks in models with strategic interactions this is because of circularity where best exercise decisions are based on previous decisions taken which at a given time are quiet to be mentioned because about the dynamic programming principle we expand an extended version of the least squares monte carlo algorithm to confront these results the model can aid in understanding the relation between strategic optionality and information besides how this influences the best decision policy and its value results we find the informational feature is of great significance for firms best decision policy and optimization of project values

information revelation through option exercise in many real world situations agents must formulate option exercise strategies with imperfect information in such a setting agents may infer the private signals of other agents through their observed exercise strategies the building of an office building the drilling of an exploratory oil well and the commitment of a pharmaceutical company toward the research of a new drug all convey private information to other market participants this article develops an equilibrium framework for option exercise games with asymmetric private information many interesting aspects of the patterns of equilibrium exercise are analyzed in particular informational cascades where agents ignore their private information and jump on the exercise bandwagon may arise endogenously article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

a dynamic duopoly investment game without commitment under uncertain market expansion abstract we model capacity building investments in a homogeneous product duopoly facing uncertain demand growth capacity building is achieved through the addition of production units that are durable and lumpy and whose cost is irreversible while building their capacity over time firms compete a la cournot in the product market given their installed capacity there is no exogenous order of moves no commitment regarding future decisions and no finite horizon we investigate markov perfect equilibrium mpe paths of the investment game which may include episodes during which firms invest at different times a preemption pattern and episodes in which firms invest simultaneously a tacit collusion pattern these episodes may alternate and are typically several when firms have yet to invest in capacity the sole pattern that is mpe compatible is a preemption episode firms invest at different times but have equal value the first such investment may occur earlier and therefore be riskier than socially optimal when both firms hold capacity tacit collusion episodes may be mpe compatible firms invest simultaneously at a postponed time hence holding back production in the meantime thereby generating an investment wave in the industry such investment episodes are more likely with higher demand volatility faster market growth and lower cost of capital discount rate

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

the effect of uncertainty on investment evidence from texas oil drilling this paper estimates the response of investment to changes in uncertainty using data on oil drilling in texas and the expected volatility of the future price of oil using a dynamic model of firms investment problem i find that i the response of drilling activity to changes in price volatility has a magnitude consistent with the optimal response prescribed by theory ii the cost of failing to respond to volatility shocks is economically significant and iii implied volatility data derived from futures options prices yields a better fit to firms investment behavior than backward looking volatility measures such as garch jel c58 d92 g13 g31 l71 q31 the real options literature beginning with marschak 1949 and arrow 1968 and developed in bernanke 1983 pindyck 1991 and dixit and pindyck 1994 explains how firms should make decisions about investments that involve sunk costs real options theory views such investments as options in that at any point in time a firm may choose to either invest immediately or delay and observe the evolution of the investment s payoff a key insight is that the option to delay has value when future states of the world with positive returns to investing and states with negative returns are both possible even holding the expected future return constant at its present level thus in the presence of irreversibility and uncertainty a naive investment timing rule proceed with an investment if its expected benefit even slightly exceeds its cost is suboptimal because it does not account for the value of continuing to hold the option instead firms should delay irreversible investments until a significant gap develops between the investments expected benefits and costs moreover as uncertainty increases real options theory tells us that the incentive to delay should grow stronger and the gap between the expected benefit and cost necessary to trigger investment should widen while real options theory therefore prescribes how firms should carry out irreversible investments in uncertain environments it is not empirically well known

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

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

small sample uncertainty aspects in relation to bullwhip effect measurement abstract the bullwhip effect as a concept has been known for almost half a century starting with the forrester effect the bullwhip effect is allegedly observed in many supply chains and it is generally accepted as a potential malice despite this the bullwhip effect still seems to be first and foremost a conceptual phenomenon some even simply denies that the phenomenon exists at all in practice this of course makes it important to perform measurements because only what gets measured gets done as the saying goes in analytics few measurements are reported in the literature however typically based on standard statistical assumptions in the case of a standard measurement of the bullwhip effect independence amongst the participating variables are required amongst others but this is definitely known not to be perfectly true if any systematic control at all have taken place in the supply chain this paper analyses the bullwhip measurement implications in case the standard test assumptions are violated and illustrates how to improve on the testing setup this is further done with a special emphasis on the unavoidable small sample aspects relating to such measurement in practice which typically renders all statistical asymptotic or robust arguments quite unusable it is shown how h 0 95 confidence test intervals still easily can be obtained numerically in such cases

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

a bayesian approach to real options the case of distinguishing between temporary and permanent shocks traditional real options models demonstrate the importance of the option to wait due to uncertainty over future shocks to project cash flows however there is often another important source of uncertainty uncertainty over the permanence of past shocks adding bayesian uncertainty over the permanence of past shocks augments the traditional option to wait with an additional option to learn the implied investment behavior differs significantly from that in standard models for example investment may occur at a time of stable or decreasing cash flows respond sluggishly to cash flow shocks and depend on the timing of project cash flows during the past two decades the real options approach to valuation of irreversible investment opportunities has become part of the mainstream literature in financial economics the central idea is that the opportunity to invest is equivalent to an american call option on the underlying investment project as a consequence the problem of optimal investment timing is analogous to the optimal exercise decision for an american option applications of the real options approach are now numerous 1 one feature that is common to virtually all real options models is that the underlying uncertainty pertains only to future shocks since future cash flows are uncertain there is an important opportunity cost of investing today the value of the asset might go up so that tomorrow will be an even better time to invest this opportunity cost is often referred to in the literature as the option

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

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

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

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

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

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

strategic entry in a triopoly market of firms with asymmetric cost structures abstract this paper examines the strategic investment timing decision in a triopoly market comprising firms with asymmetric cost structures we present three novel results first in the case where there are relatively small cost asymmetries between firms and a relatively small first mover advantage the firm with the lowest cost structure is not always the first investor in other cases the firm with the lowest cost structure is the first investor second an increase in volatility increases the possibility that a firm without the lowest cost structure is the first investor finally even in the three asymmetric firm model we show that the first investor threshold is larger in a triopoly than in a duopoly although it is smaller in a duopoly than in a monopoly

option exercise games an application to the equilibrium investment strategies of firms under the standard real options approach to investment under uncertainty agents formulate optimal exercise strategies in isolation and ignore competitive interactions however in many real world asset markets exercise strategies cannot be determined separately but must be formed as part of a strategic equilibrium this article provides a tractable approach for deriving equilibrium investment strategies in a continuous time cournot nash framework the impact of competition on exercise strategies is dramatic for example while standard real options models emphasize that a valuable option to wait leads firms to invest only at large positive net present values the impact of competition drastically erodes the value of the option to wait and leads to investment at very near the zero net present value threshold copyright 2002 oxford university press

transfer function analysis of forecasting induced bullwhip in supply chains the present paper analyses the bullwhip problem generated by exponential smoothing algorithms in both stand alone passing on orders mode and within inventory controlled feedback systems results are predicted from transfer function analysis and then confirmed by simulation via the bullwhip explorer supply chain software a novel feature of the paper is the introduction of the matched filter concept into the exponential smoothing algorithm this adjusts the value of the smoothing constant depending on whether the constant linear or quadratic forecasting model is used it is shown that matching the filter via noise bandwidth equalises the output variance when the demand is a random signal hence some of the unwanted effects of using the linear and quadratic forecasting models are attenuated however there is little benefit obtained by using sophisticated forecasting methods within inventory controlled feedback systems as their tracking ability is reduced

on bullwhip in a family of order up to policies with arma 2 2 demand and arbitrary lead times a number of papers have recently appeared that investigate the bullwhip effect the variance amplification of ordering decisions in the supply chain produced by the order up to replenishment policy an adapted policy with a proportional inventory position feedback controller has shown improved bullwhip behaviour the dynamic behaviour of this so called proportional order up to policy has been investigated for arbitrary lead times and several demand models such as i i d demand and autoregressive moving average ar 1 and arma 1 1 models it has been shown that for a correct choice of the feedback parameter the bullwhip effect can always be avoided however less attractive properties of this policy have also become clear herein we investigate the behaviour of the proportional order up to policy for arma 2 2 demand with arbitrary lead times in order to compensate for possible weaknesses of the proportional out policy we propose another replenishment rule that accounts for the characteristics of the demand in a superior manner the characteristics of both policies are compared for several parameter settings of the arma 2 2 model finally the consequences of our full state feedback order up to policy are discussed

real options and preemption under incomplete information abstract this paper introduces incomplete information and preemption into an equilibrium model of firms facing real investment decisions the optimal investment strategy may lie anywhere between the zero npv trigger level and the optimal strategy of a monopolist depending on the distribution of competitors costs and the implied fear of preemption our model implies that the equity returns of firms which hold real options and are subject to preemption will contain jumps and positive skewness

investment timing and learning externalities abstract we study a duopoly model of investment in which each player learns about the quality of a common value project by observing some public background information and possibly the experience of his rival investment costs are private information and the background signal takes the form of a poisson process conditional on the quality of the project being low the resulting attrition game has a unique symmetric equilibrium which depends on initial public beliefs we determine the impact of changes in the cost and signal distributions on investment timing and how equilibrium is affected when a first mover advantage is introduced

demand evolution in stochastic inventory systems riskiness increase abstract this paper characterizes demand evolution in the steady state under common inventory policies in a single location stochastic inventory system our results show that downstream demand nonstrictly second degree stochastically dominates upstream orders and the bullwhip effect occurs we provide the link between demand evolution and utility theory for stochastic inventory systems our model is general in that ultimate customer demand follows an arbitrary stationary distribution and the facility may arbitrarily select policy parameters

trade policy in mexico this evaluation examines mexican trade policies applied over three well defined periods during the last quarter century and makes recommendations for the future each discussion begins with a description of the macroeconomic background and then analyzes trade policy developments of the period with further attention given to industrial policy measures changes in mexican exports and imports and their contribution to industrial growth are discussed mexico s current economic difficulties stem from 1956 when increases in public consumption contributed to inflation and to the appreciation of the peso in real terms under fixed exchange rates the overvaluation of the exchange rate led to the application of protectionist measures which discriminated against exports the situation was aggravated by excessively expansionary policies which necessitated substantial foreign borrowing and exacerbated protectionist pressures this paper makes recommendations for remedying macroeconomic disequilibria reducing price distortions and reforming trade policy with a view to moving towards an outward oriented development strategy future growth will depend however on increased investments particularly in export activities that may be encouraged by appropriate incentives

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

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

delay and information aggregation in stopping games with private information abstract we consider equilibrium timing decisions in a model with a large number of players and informational externalities the players have private information about a common payoff parameter that determines the optimal time to invest they learn from each other in real time by observing past investment decisions we develop new methods of analysis for such large games and we give a full characterization of symmetric equilibria we show that the equilibrium statistical inferences are based on an exponential learning model although the beliefs converge to truth learning takes place too late ex ante welfare is strictly between that without observational learning and that with full information

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

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

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

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

optimization of a vendor managed inventory supply chain with guaranteed stability and robustness abstract in this work we address the steady state optimization of a supply chain model that belongs to the class of vendor managed inventory automatic pipeline inventory and order based production control systems vmi apiobpcs the supply chain is optimized with the so called normal vector method which has specifically been developed for the economic optimization of uncertain dynamical systems with constraints on dynamics we demonstrate that the normal vector method provides robust optimal points of operation for a number of scenarios since the method strictly distinguishes economic optimality which is treated as the optimization objective from dynamical requirements which are incorporate by appropriate constraints it provides a measure for the cost of stability and robustness as a desired side effect

rogue seasonality detection in supply chains rogue seasonality or unintended cyclic variability in order and other supply chain variables is an endogenous disturbance generated by a company s internal processes such as inventory and production control systems the ability to automatically detect diagnose and discriminate rogue seasonality from exogenous disturbances is of prime importance to decision makers this paper compares the effectiveness of alternative time series techniques based on fourier and discrete wavelet transforms autocorrelation and cross correlation functions and autoregressive model in detecting rogue seasonality rogue seasonalities of various intensities were generated using different simulation designs and demand patterns to evaluate each of these techniques an index for rogue seasonality based on the clustering profile of the supply chain variables was defined and used in the evaluation the fourier transform technique was found to be the most effective for rogue seasonality detection which was also subsequently validated using data from a steel supply network

mature or emerging markets competitive duopoly investment decisions abstract we develop a competitive investment model wherein two competing firms consider investing into two projects targeting separately a mature and an emerging market the returns firms obtain from investments into these markets are assumed to follow an s shaped curve and depend on both firms actions considering symmetric environments in terms of investment opportunities we find that different forms of interactions may arise e g prisoner s dilemma and game of chicken and outline corresponding strategies that offer higher returns by exploiting first mover advantages cooperation opportunities and aggressive choices we also discuss the market conditions that can lead to these outcomes finally considering non symmetric environments we show that a firm may be better off when its competitor s budget increases

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

strategic delegation in a legislative bargaining model with pork and public goods abstract this paper examines the incentives of voters to appoint legislators with different preferences from their own the paper adopts an underlying legislative bargaining model proposed by volden and wiseman 2007 in which legislators with heterogeneous preferences divide a fixed budget between a public good and pork projects local public goods we show that voters have an incentive to strategically delegate to affect how the budget is divided at the legislative level when voters preferences for pork are not too strong the incentives for strategic delegation exist to appoint representatives who will direct more money to the public good and not to pork projects this generally results in at least as many representatives as districts that favor the public good the comparative statics predict that when strategic delegation occurs increasing the size of the legislature increases the fraction of the budget spent on the public good

exact solutions to the supply chain equations for arbitrary time dependent demands abstract we study the impact on inventory of an unexpected non linear time dependent demand and present the exact solutions over time to the supply chain equations without requiring any approximations we begin by imposing a boundary condition of stability at infinity from which we derive expressions for the estimated demand and the target work in progress when the demand is time dependent the resulting inventory equation is solved in terms of the lambert modes with all of the demand non linearities confined to the pre shape function the series solution is exact and all terms are reasonably easy to calculate so users can determine the inventory behavior to any desired precision to illustrate we solve the equations for a non linear quadratic time dependence in the demand for practical use only a few terms in the series are required a proposition illustrated by the for all practical purposes fapp solution while the paper provides a theoretical foundation the result is decidedly practical an accurate and reasonably easy to implement model that companies can use to analyze the impact of non linear time dependent demands

investment under uncertainty does competition matter abstract empirical applications of real options models in competitive environments implicitly exploit the optimality of myopic planning in a seminal paper leahy j v 1993 investment in competitive equilibrium the optimality of myopic behavior quarterly journal of economics 108 1105 1133 shows that the optimal investment strategy of a myopic planner who ignores market entries and exits of competitors as well as the resulting price effects constitutes a market equilibrium under rather general conditions as a result the calculation of optimal investment strategies is simplified considerably because competition does not have to be taken into account in this paper however we demonstrate by using simulation experiments that myopic planning may lead to non optimal investment strategies this is due to the fact that it is difficult or even impossible to specify the correct or equivalent price process for the myopic investor using real world data we quantify the degree of suboptimality and propose measures to reduce the error

order and inventory variance amplification the equivalence of discrete and continuous time analyses the well known bullwhip effect concerns the increasing variance of orders as they proceed through the supply chain in the continuous time representation we solve the delay differential equation for the inventory balance which is coupled to the ordering policy the time domain evolution of the system emerges we calculate the bullwhip effect and compare it to known results for the discrete time representation the discrete and continuous bullwhip effect expressions have similar structures we show that the two domains are managerially equivalent so that in practice either domain can be used to study a supply chain

trade in manufactured goods patterns of change this paper looks at the changing pattern of trade in manufactured goods between the developed industrial countries and the developing countries it first reviews recent changes in this trade and the policies applied it then analyzes the comparative advantages of the industrial and the developing countries and indicates the commodity composition of this trade the implications of the results are drawn with reference to the benefits of trade in manufactured goods for the participants

strategic investment in technological innovations abstract the aim of this paper is to determine the optimal timing of technology investment of a single firm in a duopoly framework as time passes different technologies are invented which after sometime become available for the firm to adopt the question here is not only when a firm should invest but also which technology should be adopted for different scenarios the optimal technology investment decision is determined outcomes range from pre emption equilibria to equilibria with second mover advantages

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

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

comparative advantage trade and growth export led growth revisited abstract this paper argues that the evidence in support of export promotion and export led growth is not as strong as is sometimes suggested and that the effectiveness of such policies depends on both the level of development and the structure of exports employing cross section analysis for a wide range of less developed countries we found a strong correlation between economic growth and the proportion of manufactures and stage three processed primary products moreover the proportions of both manufactures and stage three items were also strongly correlated to the level of per capita income although not conclusive these findings lend support to our contention

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

real options in strategic investment games between two asymmetric firms abstract this paper examines strategic investment games between two firms that compete for optimal entry in a project that generates uncertain revenue flows under asymmetry on both the sunk cost of investment and revenue flows of the two competing firms we investigate the value of real investment options and strategic interaction of investment decisions compared to earlier models that only allow for asymmetry on sunk cost our model demonstrates a richer set of strategic interactions of entry decisions we provide a complete characterization of pre emptive dominant and simultaneous equilibriums by analyzing the relative value of leader s and follower s optimal investment thresholds in a duopoly market with negative externalities a firm may reduce loss of real options value by selecting appropriate pre emptive entry when one firm has a dominant advantage over its competitor both the dominant firm and dominated firm enter at their respective leader s and follower s optimal thresholds when the pre emptive thresholds of both firms happen to coincide the two firms enter simultaneously under positive externalities firms do not compete to lead

measuring and avoiding the bullwhip effect a control theoretic approach an important contributory factor to the bullwhip effect i e the variance amplification of order quantities observed in supply chains is the replenishment rule used by supply chain members first the bullwhip effect induced by the use of different forecasting methods in order up to replenishment policies is analysed variance amplification is quantified and we prove that the bullwhip effect is guaranteed in the order up to model irrespective of the forecasting method used thus when production is inflexible and significant costs are incurred by frequently switching production quantities up and down order up to policies may no longer be desirable or even achievable in the second part of the paper a general decision rule is introduced that avoids variance amplification and succeeds in generating smooth ordering patterns even when demand has to be forecasted the methodology is based on control systems engineering and allows important insights to be gained about the dynamic behaviour of replenishment rules

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