optimal dynamic pricing of inventories with stochastic demand over finite horizons in many industries managers face the problem of selling a given stock of items by a deadline we investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm s objective is to maximize expected revenues examples that fit this framework include retailers selling fashion and seasonal goods and the travel and leisure industry which markets space such as seats on airline flights cabins on vacation cruises and rooms in hotels that become worthless if not sold by a specific time we formulate this problem using intensity control and obtain structural monotonicity results for the optimal intensity resp price as a function of the stock level and the length of the horizon for a particular exponential family of demand functions we find the optimal pricing policy in closed form for general demand functions we find an upper bound on the expected revenue based on analyzing the deterministic version of the problem and use this bound to prove that simple fixed price policies are asymptotically optimal as the volume of expected sales tends to infinity finally we extend our results to the case where demand is compound poisson only a finite number of prices is allowed the demand rate is time varying holding costs are incurred and cash flows are discounted the initial stock is a decision variable and reordering overbooking and random cancellations are allowed

on the structure of lost sales inventory models we provide a new approach to the structural analysis of the standard lost sales inventory system this approach is we think easier to work with than the original one we also derive new bounds on the optimal policy then we show that more variable demand leads to higher cost finally we extend the analysis to several important variations of the basic model

sales and operations planning a research synthesis abstract despite the growing body of literature on sales and operation planning s op efforts to synthesise the overall state of the art of research in this area are limited within this context this paper provides a systematic review of the literature on s op the purpose of this systematic review is twofold i to integrate the highly dispersed work on s op in order to identify and analyse s op as a business process and ii to assemble quantitative evidence of its impact on the performance of the firm a literature search framework is proposed with 271 papers reviewed and classified the framework embraces s op context information inputs and goals structure and processes outcomes and results the major expected outcome in most papers was a cross functional integration of plans although few studies report on the integration of finance plans into s op despite the existence of common process descriptors and definitions of s op there is a lack of unifying frameworks for maturity models measurement of s op and constructs related to the firm s performance the need for additional scientifically sound survey or case study research on s op is emphasised this paper contributes to a better understanding of s op s role as a determinant of firm s performance in the supply chain

joint management of capacity and inventory in make to stock production systems with multi class demand we evaluate the benefits of coordinating capacity and inventory decisions in a make to stock production environment we consider a firm that faces multi class demand and has additional capacity options that are temporary and randomly available we formulate the model as a markov decision process mdp and prove that a solution to the optimal joint control problem exists for several special cases we characterize the structure of the optimal policy for the general case however we show that the optimal policy is state dependent and in many instances non monotone and difficult to implement therefore we consider three pragmatic heuristic policies and assess their performance we show that the majority of the savings originate from the ability to dynamically adjust capacity and that a simple heuristic that can adjust production capacity based on workload fluctuation but uses a static production rationing policy can result in significant savings

production planning and pricing policy in a make to stock system with uncertain demand subject to machine breakdowns abstract we consider a make to stock system served by an unreliable machine that produces one type of product which is sold to customers at one of two possible prices depending on the inventory level at the time when a customer arrives i e the decision point the system manager must determine the production level and selling price at each decision point we first show that the optimal production and pricing policy is a threshold control which is characterized by three threshold parameters under both the long run discounted profit and long run average profit criteria we then establish the structural relationships among the three threshold parameters that production is off when inventory is above the threshold and that the optimal selling price should be low when inventory is above the threshold under the scenario where the machine is down or up finally we provide some numerical examples to illustrate the analytical results and gain additional insights

assessing nominal income rules for monetary policy with model and data uncertainty nominal income rules for monetary policy have long been debated but two issues are of particular recent interest first there are questions about the performance of such rules over a range of plausible empirical models especially models with and without explicit rational inflation expectations second there are questions about the performance of these rules in real time using the type of data that is actually available contemporaneously to policy makers rather than final revised data this paper determines optimal monetary policy rules in the presence of such model uncertainty and real time data uncertainty and finds only a limited role for nominal output growth

optimal dynamic scheduling policy for a make to stock production system this paper considers the dynamic scheduling problem of a single server make to stock queue with two products for the case of poisson demands and exponential production times we show that it is optimal to produce the product with the larger b index when it is backordered if the production times are identically distributed the optimal policy can further be characterized by monotone switching curves we also prove that a base stock policy coupled with a switching curve is optimal for some initial inventory levels a simple linear switching rule for determining production priority is proposed and compared with other heuristic policies in a computational experiment

dynamic capacity management with substitution we examine a multiperiod capacity allocation model with upgrading there are multiple product types corresponding to multiple classes of demand and the firm purchases capacity of each product before the first period within each period after demand arrives products are allocated to customers customers who arrive to find that their product has been depleted can be upgraded by at most one level we show that the optimal allocation policy is a simple two step algorithm first use any available capacity to satisfy same class demand and then upgrade customers until capacity reaches a protection limit so that in the second step the higher level capacity is rationed we show that these results hold both when all capacity is salvaged at the end of the last demand period as well as when capacity can be replenished in the latter case an order up to policy is optimal for replenishment although finding the optimal protection limits is computationally intensive we describe bounds for the optimal protection limits that take little effort to compute and can be used to effectively solve large problems using these heuristics we examine numerically the relative value of strictly optimal capacity and dynamic rationing the value of perfect demand information and the impact of demand and economic parameters on the value of optimal substitution

investability the key to competitive regions and cities this article proposes and develops a concept investability that can be used for analysing the competitive position of cities or regions and formulating policy responses it can be defined as conditions that are conducive to a higher level of investment and refers principally to the business environment in which economic agents operate the paper discusses various influences on investment decisions and how they will impinge on different classes of potential investors policy implications are developed and the ways in which the concept might be used in policy making are examined

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

analysis of an industrial component commonality problem we discuss a case study of an industrial production marketing coordination problem involving component commonality for the product line considered the strategic goal of the company is to move from the current low volume market to a high volume market the marketing department believes that this can be achieved by substantially lowering the end products prices however this requires a product redesign to lower production costs in order to maintain profit margins the redesign decision involves grouping end products into families all products within one family use the same version of some components this paper fits in the stream of recent literature on component commonality where the focus has shifted from inventory cost savings to production and development cost savings further we consider both costs and revenues leading to a profit maximization approach the price elasticity of demand determines the relationship between the price level and number of units sold consequently we integrate information from different functional areas such as production marketing and accounting we formulate the problem as a net present value investment decision we propose a mixed integer nonlinear optimization model to find the optimal commonality decision the recommendation based on our analysis has been implemented in the company in addition the application allows us to experimentally validate some claims made in the literature and obtain managerial insights into the trade offs

on the effect of demand randomness on inventories and costs we explore analytically cardinal effects of the extent of demand randomness on optimal inventory levels and the associated expected costs to model changes in demand randomness we make extensive use of a mean preserving transformation commonly used in probabilistic microeconomics as well as the notion of risk pooling aggregating independent demands for the single period news vendor model the order quantity and associated costs are shown to depend on the randomness parameter in a simple and highly interpretable manner we show by a simple example that in some situations risk pooling might neither reduce inventories nor move them closer to the mean or median demand the managerial relevance of such analyses is discussed

the effects of tax increment financing on economic development abstract local governments attempt to influence business location decisions and economic development through use of the property tax tax increment financing tif earmarks property tax revenues that result from growth in assessed valuation the tif revenues are to be used for economic development projects but may also be diverted for other purposes using data for the chicago metropolitan area that includes information on property value growth before and after tif adoption we find evidence that cities that adopt tif grow more slowly than those that do not we test for and reject sample selection bias as an explanation of this finding

interpreting the macroeconomic time series facts the effects of monetary policy existing theory and evidence on the effects of monetary policy are reviewed substantial room for disagreement among economists remains new evidence based on multivariate time series studies of several countries is presented while certain patterns in the data consistent with effective monetary policy are strikingly similar across countries others particularly the tendency of interest rate increases to predict high inflation are harder to reconcile with effective monetary policy

testing for indeterminacy an application to u s monetary policy reply this paper considers a prototypical new keynesian model in which the equilibrium is undetermined if monetary policy is passive the likelihood based estimation of dynamic equilibrium models is extended to allow for indeterminacies and sunspot fluctuations we construct posterior weights for the determinacy and indeterminacy region of the parameter space and estimates for the propagation of fundamental and sunspot shocks according to the estimated model u s monetary policy post 1982 is consistent with determinacy whereas the pre volcker policy is not we find that before 1979 indeterminacy substantially altered the propagation of shocks

equilibrium credit the reference point for macroprudential supervisors equilibrium credit is an important concept because it helps identify excessive credit provision this paper proposes a two stage approach to determine equilibrium credit it uses two stages to study changes in the demand for credit due to varying levels of economic financial and institutional development of a country using a panel of high and middle income countries over the period 1980 2010 this paper provides empirical evidence that the credit to gdp ratio is inappropriate to measure equilibrium credit the reason for this is that such an approach ignores heterogeneity in the parameters that determine equilibrium credit across countries due to different stages of economic development the main drivers of this heterogeneity are financial depth access to financial services use of capital markets efficiency and funding of domestic banks central bank independence the degree of supervisory integration and experience of a financial crisis countries in europe and central asia show a slower adjustment of credit to its long run equilibrium compared with other regions of the world

new keynesian macroeconomics and the term structure this article complements the structural new keynesian macro framework with a no arbitrage affine term structure model whereas our methodology is general we focus on an extended macro model with an unobservable time varying inflation target and the natural rate of output which are filtered from macro and term structure data we obtain large and significant estimates of the phillips curve and real interest rate response parameters our model also delivers strong contemporaneous responses of the entire term structure to various macroeconomic shocks the inflation target dominates the variation in the level factor whereas the monetary policy shocks dominate the variation in the slope and curvature factors

a dynamic rationing policy for continuous review inventory systems stock rationing is an inventory policy that allows differential treatment of customer classes without using separate inventories in this paper we propose a dynamic rationing policy for continuous review inventory systems which utilizes the information on the status of the outstanding replenishment orders for both backordering and lost sales environments we conduct simulation studies to compare the performance of the dynamic policy with the static critical level and the common stock policies and quantify the gain obtained we propose two new bounds on the optimum dynamic rationing policy that enables us to tell how much of the potential gain the proposed dynamic policy realizes we discuss the conditions under which stock rationing both dynamic and static is beneficial and assess the value of the dynamic policy

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

habit formation in consumption and its implications for monetary policy models this paper explores a monetary policy model with habit formation for consumers in which consumers utility depends in part on current consumption relative to past consumption the empirical tests developed in the paper show that one can reject the hypothesis of no habit formation with tremendous condence largely because the habit formation model captures the gradual hump shaped response of real spending to various shocks the paper then embeds the habit consumption specication in a monetary policy model and nds that the responses of both spending and inflation to monetary policy actions are signicantly improved by this modication jel d12 e52 e43

centralized admission and production control in a two stage supply chain with single component and customized products abstract this paper considers a two stage supply chain that a make to stock facility produces a single component in anticipation of future demand and a make to order facility produces customized products using components with the option of to accept or reject each customer order we address the problem of centralizing the admission and production control that maximizes the supply chain s profit subject to the system costs using a markov decision process model we characterize the structure of the optimal admission control and production policy and establish the monotonic impact of system parameters on the optimal policy two heuristics are presented and their performance is numerically compared to the optimal policy under different operating conditions of the system

sustainability and the anchoring of capital negotiations surrounding two major urban projects in switzerland theurillat t and crevoisier o sustainability and the anchoring of capital negotiations surrounding two major urban projects in switzerland regional studies this article deals with the anchoring of mobile financial capital in the city and urban sustainability illustrated by a case study in the swiss context it develops the theory that new forms of negotiation are appearing around urban projects development construction firms are playing a central role they are capable of evaluating and translating the multiple dimensions of a project and certain sustainability challenges into financial terms in a way that permits the anchoring of capital in the city in parallel the issue of sustainability depends greatly on the capacity of the local actors to negotiate with the promoters of urban projects

managing an assemble to order system with after sales market for components abstract in this paper we consider an assemble to order manufacturing system producing a single end product assembled from n components and serving an after sales market for individual components components are produced in a make to stock fashion one unit at a time on independent production facilities production times are exponentially distributed with finite production rates the components are stocked ahead of demand and therefore incur a holding cost rate per unit demand for the end product as well as for the individual components occurs continuously over time according to independent poisson streams in order to characterize the optimal production and inventory rationing policies we formulate such a problem using a markov decision process framework in particular we show that the optimal component production policy is a state dependent base stock policy we also show that the optimal component inventory rationing policy is a rationing policy with state dependent rationing levels recognizing that such a policy is generally not only difficult to obtain numerically but also is difficult to implement in practice we propose three heuristic policies that are easier to implement in practice we show that two of these heuristics are highly efficient compared to the optimal policy in particular we show that one of the two heuristics strikes a balance between high efficiency and computational effort and thus can be used as an effective substitute of the optimal policy

dynamic pricing through discounts for optimizing multiple class demand fulfillment in a multiple customer class model of demand fulfillment for a single item we consider the use of dynamic price discounts to encourage backlogging of demand for customer classes denied immediate service customers are assumed to arrive over several stages in a period and customer classes are distinguished by their contractual price and sensitivity to discounts through dynamic programming we determine the optimal discounts to offer assuming a linear model for the sensitivity of customers to such inducements we show that customers are served in class order and allocation of inventory to demand is determined by considering the current number of customers backlogged as well as the current inventory position through comparison to a naive supplier allocating inventory first come first served with no discounting we show that profits are primarily influenced by the allocation of capacity and the use of price discounts primarily benefits the second class customers overall fill rate heuristics for implementation of the solution in real time settings are given

urban regeneration and the development industry healey p 1991 urban regeneration and the development industry reg studies 25 97 108 this paper examines a key assumption of urban policy in britain in the 1980s this assumption is that urba

a stock rationing policy in a s s controlled stochastic production system with 2 phase coxian processing times and lost sales abstract this paper analyzes a s s controlled stochastic production system with multi class demands and lost sales demands in each class are assumed to arrive according to a poisson process and the time required to process an item is assumed to follow a 2 phase coxian distribution for each class a stock rationing level is set when customers arrive if the inventory level is lower than the predetermined rationing level the demands are lost for future demands with higher priorities a behavior of the production system is modeled as a continuous time markov chain and an efficient algorithm to calculate the steady state probability distribution of the system is proposed the average operating cost under the stock rationing policy is compared with the one without stock rationing numerical experiment shows that the proposed stock rationing policy reduces the average operating cost significantly depending on the system parameters

does chicago s tax increment financing tif programme pass the but for test job creation and economic development impacts using time series data chicago uses tax increment financing tif to promote economic development to a greater extent than any other large american city this paper conducts a comprehensive assessment of the effectiveness of chicago s tif programme in creating economic opportunities and catalysing real estate investments at the neighbourhood scale this paper uses a unique panel dataset at the block group level to analyse the impact of tif designation and investments on employment change business creation and building permit activity after controlling for potential selection bias in tif assignment this paper shows that tif ultimately fails the but for test and shows no evidence of increasing tangible economic development benefits for local residents implications for policy are considered

admission and inventory control of a single component make to order production system with replenishment setup cost and lead time abstract we consider the admission control and inventory management problems of a single component make to order production system components are purchased from suppliers in batches of fixed size subject to stochastic lead times and setup costs a control policy specifies when a batch of components is purchased and whether the demand for each mto production is accepted upon arrival we formulate the problem as a markov decision process mdp model and characterize the structure of optimal admission control and inventory replenishment policies we show that a state dependent base stock policy is optimal for the inventory replenishment although the mdp value function is not necessarily convex we also show that the optimal admission control can be identified as a lattice dependent policy a sensitivity analysis is conducted to show how the optimal policy changes as a function of the system parameters to effectively coordinate admission and inventory control decisions we propose simple implementable and yet effective heuristic policies our extensive numerical results suggest that the proposed heuristics can greatly help firms to effectively coordinate their admission and inventory control activities

integrated production and allocation policies with one direct shipping option we consider a single period inventory problem in which a supplier faces stochastic demands and customer specific waiting costs from multiple customers the objective is to develop integrated production allocation and distribution policies so that the total production and customer waiting costs are minimized we present an optimal policy for the two customer problem and derive a heuristic for a general problem based on the structural results of the two customer case we show numerically that the heuristic performs very well with error bounds of less than 2 on average while typical approximations may lead to significant sub optimality

providing cheap land for social housing breaching the state aid regulations of the single european market tasan kok t groetelaers d a haffner m e a van der heijden h m h and korthals altes w k providing cheap land for social housing breaching the state aid regulations of the single european market regional studies european union member states are not permitted to provide aid that will distort competition by favouring certain undertakings or the production of certain goods which may then undermine trading in the european market this prohibition also affects government authorities that are willing to provide cheap land for social and affordable housing this paper reviews the ways in which land is provided for social housing in the netherlands and explores possibilities for reshaping current practices to make them compatible with the regime of the single european market tasan kok t groetelaers d a haffner m e a van der heijden h m h and korthals altes w k

revenue management approach to stochastic capacity allocation problem abstract to formulate stochastic capacity allocation problems in a manufacturing system the concept and techniques of revenue management is applied in this research it is assumed the production capacity is stochastic and hence its exact size cannot be forecasted in advance at the time of planning there are two classes of frequent and occasional customers demanding this capacity the price rate as well as the penalty for order cancellation caused by overbooking is different for each class the model is developed mathematically and we propose an analytical solution method the properties of the optimal solution as well as the behavior of objective function are also analyzed the objective function is not concave in general however we prove it is a unimodal function and by taking advantage of this property the optimal solution is determined

reduce shortage with self reservation policy for a manufacturer paying both fixed and variable stockout expenditure this study considers a single item make to stock system with continuous time production and inventory controls to meet bulk demand with an exponential inter arrival time a key issue in this system is the non convex shortage cost consisting of fixed and variable expenditures when the demand is not fully satisfied we propose a self reservation policy by building a markov decision process to minimize the overall cost we find that the optimal production control is still a base stock policy but the structure of the optimal self reservation policy is very complicated however if the effective outstanding variable shortage cost is sufficiently large the optimal self reservation policy has an easy form of reserve all or nothing our numerical examples indicate the optimal policy may reduce the total average cost by 47 on average

capacity rationing decision procedures with order profit as a continuous random variable abstract when expected demand is more than available capacity a make to order manufacturer should take the more profitable orders and reject the less profitable orders in order to better allocate its limited capacity and maximize its profit however various orders will arrive at different times in the future so the manufacturer cannot look at all the order inquiries at the same time and choose the most profitable ones when an order inquiry arrives the manufacturer must promptly determine without knowing exactly what the future orders might be whether to accept the order or to reject the order thus reserving the capacity for future more profitable orders this study focuses on such an order selection decision problem under the following assumptions 1 the arrival of future customer orders is a poisson process 2 the capacity requirement of a future customer order is a continuous random variable and 3 the profit per unit capacity used by an order is also a continuous random variable under the stochastic problem assumptions this study investigates two decision procedures that determine whether to accept or to reject an order inquiry based on the available information including 1 current available manufacturing capacity 2 capacity requirement by the order and 3 the profit per unit capacity of the order one procedure is called static probability capacity rationing decision procedure spcr the other one is called dynamic stochastic capacity rationing decision procedure dscr simulation experiments are conducted to validate the proposed procedures an optimal solution method that uses 0 1 knapsack problem formulation to obtain the decisions with perfect information is used to measure the effectiveness of the proposed procedures the results show that the approach utilizing dscr outperforms other approaches by providing the highest profit and is also very robust under various problem conditions

multi class dynamic inventory rationing with stochastic demands and backordering dynamic inventory rationing is considered for systems with multiple demand classes stationary stochastic demands and backordering in the literature dynamic programming has been often applied to address this type of problems however due to the curse of dimensionality computation is a critical challenge for dynamic programming in this paper an innovative two step approach is proposed based on an idea similar to the certainty equivalence principle first the deterministic inventory rationing problem is studied where the future demands are set to be the expectation of the stochastic demand processes the important properties obtained from solving the problem with the kkt conditions are then used to develop effective dynamic rationing policies for stochastic demands which gives closed form expressions for dynamic rationing thresholds these expressions are easy to calculate and are applicable to any number of demand classes numerical results show that the expressions are close to and provide a lower bound for the optimal dynamic thresholds they also shed light on important managerial insights for example the relation between different parameters and the rationing thresholds

design and evaluation of a dynamic capacity apportionment procedure abstract deploying a decision theory based approach we develop a heuristic for short term constrained capacity allocation to multiple product classes in make to order manufacturing attempting to maximize profit by discriminating between product classes efficacy of the heuristic is evaluated by comparing its performance to a base case and an upper bound under a wide variety of operational conditions such as variations in profit attractiveness capacity tightness customer order size structure customer order rate structure and demand coefficient of variation considering three different scenarios of time variant order rate of products the results indicate that the heuristic is effective in obtaining increased profit when capacity is very tight and products are well differentiated on average it yields an increase of 9 38 in total profit with a concomitant decrease of 0 85 in capacity utilization the results of this study serve to highlight the value of proactively seeking to differentiate products particularly when demand exceeds capacity

technical note optimal control of an assembly system with multiple stages and multiple demand classes we consider an assembly system with multiple stages multiple items and multiple customer classes the system consists of m production facilities each producing a different item items are produced in variable batch sizes one batch at a time with exponentially distributed batch production times demand from each class takes place continuously over time according to a compound poisson process at each decision epoch we must determine whether or not to produce an item and should demand from a particular class arise whether or not to satisfy it from existing inventory if any is available we formulate the problem as a markov decision process and use it to characterize the structure of the optimal policy in contrast to systems with exogenous and deterministic production lead times we show that the optimal production policy for each item is a state dependent base stock policy with the base stock level nonincreasing in the inventory level of items that are downstream and nondecreasing in the inventory level of all other items for inventory allocation we show that the optimal policy is a multilevel state dependent rationing policy with the rationing level for each demand class nonincreasing in the inventory level of all nonend items we also show how the optimal control problem can be reformulated in terms of echelon inventory and how the essential features of the optimal policy can be reinterpreted in terms of echelon inventory

managing an available to promise assembly system with dynamic short term pseudo order forecast we study an order promising problem in a multiclass available to promise atp assembly system in the presence of pseudo orders a pseudo order refers to a tentative customer order whose attributes such as the likelihood of an actual order order quantity and confirmation timing can change dynamically over time a unit demand from any class is assembled from one manufactured unit and one inventory unit where the manufactured unit takes one unit of capacity and needs a single period to produce an accepted order must be filled before a positive delivery lead time the underlying order acceptance decisions involve trade offs between committing resources production capacity and component inventory to low reward firm orders and reserving resources for high reward orders we develop a markov chain model that captures the key characteristics of pseudo orders including demand lumpiness nonstationarity and volatility we then formulate a stochastic dynamic program for the atp assembly system that embeds the markov chain model as a short term forecast for pseudo orders we show that the optimal order acceptance policy is characterized by class prioritization resource imbalance based rationing and capacity inventory demand matching in particular the rationing level for each class is determined by a critical value that depends on the resource imbalance level defined as the net difference between the production capacity and component inventory levels extensive numerical tests underscore the importance of the key properties of the optimal policy and provide operational and managerial insights on the value of the short term demand forecast and the robustness of the optimal policy this paper was accepted by martin lariviere operations management

frequentist evaluation of small dsge models this article proposes a new evaluation approach for the class of small scale hybrid new keynesian dynamic stochastic general equilibrium nk dsge models typically used in monetary policy and business cycle analysis the empirical assessment of the nk dsge model is based on a conditional sequence of likelihood based tests conducted in a vector autoregressive var system in which both the low and high frequency implications of the model are addressed in a coherent framework if the low frequency behavior of the original time series of the model can be approximated by nonstationary processes stationarity must be imposed by removing the stochastic trends this gives rise to a set of recoverable unit roots cointegration restrictions in addition to the short run cross equation restrictions the procedure is based on the sequence lr1 lr2 lr3 where lr1 is the cointegration rank test lr2 is the cointegration matrix test and lr3 is the cross equation restrictions test lr2 is computed conditional on lr

changes in the federal reserve s inflation target causes and consequences this paper estimates a new keynesian model to draw inferences about the behavior of the federal reserve s unobserved inflation target the results indicate that the target rose from 1 1 4 percent in 1959 to over 8 percent in the mid to late 1970s before falling back below 2 1 2 percent in 2004 the results also provide some support for the hypothesis that over the entire postwar period federal reserve policy has systematically translated short run price pressures set off by supply side shocks into more persistent movements in inflation itself although considerable uncertainty remains about the true source of shifts in the inflation target jel e31 e32 e52

application of the scenario aggregation approach to a two stage stochastic common component inventory problem with a budget constraint abstract the purpose of this paper is to study from a new perspective the problem of allocating a given budget among product components that are required for manufacturing the end items in an assemble to order environment since some of the components are common to a number of different end items this constitutes a commonality inventory problem that in fact can be described as a two stage stochastic programming problem we explore the new possibilities made available by the scenario aggregation technique recently proposed by rockafeller and wets in work at the international institute of applied systems analysis iiasa their method was subsequently extended to deal with discrete problems this extension is utilized in the current study

stock rationing in an m ek 1 make to stock queue this paper considers the stock rationing problem of a single item make to stock production system with several demand classes and lost sales when demand is poisson and processing time has an erlang distribution we show that a single state variable called work storage level can be employed to completely capture the information regarding inventory level and the status of current production the optimal rationing policy can be characterized by a sequence of monotone critical work storage levels for each demand class there exists a work storage level at or below which it is optimal to start rejecting the demand of this class in anticipation of future arrival of higher priority demands the optimal production policy can also be characterized by a critical work storage level our numerical examples indicate that a critical stock level policy which ignores information on the status of current production performs very well

optimal production and rationing policy of two stage tandem production system abstract the rationing literature has been so far oblivious to the fact that sellable items may not only be finished products but also intermediate products to manufacture subsequent sellable products we address this gap by considering an inventory rationing problem in a two product tandem make to stock production inventory system bulk demand arrives to a partial batch production system with exponentially distributed production time for each batch the management has to decide whether to run or stop production and whether the various classes of demand for both products intermediate product ip and finished product or end product ep have to be satisfied from available inventory or not in which case demand is lost in order to maximize the firm s expected profit we present the corresponding dynamic programming formulation and characterize the optimal policy the resulting policy depends on dynamic switching curves which define a thresholds to continue or discontinue production and b thresholds to satisfy or turn down incoming orders we identify the key value drivers and compare various heuristic policies through extensive numerical analyses

optimal policies for inventory systems with priority demand classes we consider a periodic review inventory system with two priority demand classes one deterministic and the other stochastic the deterministic demand must be met immediately in each period however the units of stochastic demand that are not satisfied during the period when demand occurs are treated as lost sales at each decision epoch one has to decide not only whether an order should be placed and how much to order but also how much demand to fill from the stochastic source the firm has the option to ration inventory to the stochastic source i e not satisfy all customer demand even though there is inventory in the system we first characterize the structure of the optimal policy we show that in general the optimal order quantity and rationing policy are state dependent and do not have a simple structure we then propose a simple policy called s k s policy wheres ands ordering policy determine when and how much to order whilek rationing policy specifies how much of the stochastic demand to satisfy we report the results of a numerical study which shows that this simple policy works extremely well and is very easy to compute

a threshold inventory rationing policy for service differentiated demand classes motivated by a study of the logistics systems used to manage consumable service parts for the u s military we consider a static threshold based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage stockout and delay costs the scheme operates as a q r policy with the following feature demands from both classes are filled on a first come first serve basis as long as on hand inventory lies above a threshold levelk once on hand inventory falls below this level low priority i e low shortage cost demand is backordered while high priority demand continues to be filled we analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters i e q r andk numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy we next highlight conditions where our policy offers significant savings over traditional round up and separate stock policies encountered in the military and elsewhere finally we develop a lower bound on the cost of the optimal rationing policy numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high technology industries

the role of inventory in delivery time competition the paper operationalizes the notion of shortage cost by considering the behavior of customers and competing firms and examines the role of inventory in response time competition we start with a single firm production control model in which customers are characterized by their preferences of price quality and delivery time the optimal production inventory policy and the optimal choice between make to order and make to stock operations are determined in simple newsboy like formulas the basic model is then extended to an n firm market game in which firms compete for orders from the aspect of early delivery one could think of this setting as an oligopoly racing market the analysis shows that competition can breed a demand for produce to stock just as other economic phenomena such as economies of scale uncertainty or seasonality can induce make to stock and that delivery time competition increases the buyer s welfare while decreasing the producer s welfare

the effect of commonality on safety stock in a simple inventory model we examine the effects of component commonality on optimal safety stock levels in a two product two level inventory model the criterion is to minimize system safety stock subject to a service level constraint although our model is specialized its analysis provides insights not available in other multilevel inventory models

component rationing for available to promise scheduling in configure to order systems abstract we address the problem of rationing common components among multiple products in a configure to order system with order configuration uncertainty the objective of this problem is to maximize expected revenue by implementing a threshold rationing policy under this policy a product is available to promise if fulfilling the order for the product will not cause the inventory of any one of its required components to fall below the component s threshold level for that product the problem is modeled as a two stage stochastic integer program and solved using the sample average approximation approach a heuristic is developed to generate good feasible solutions and lower bound estimates using industry data we examine the benefit of component rationing as compared to a first come first served policy and show that this benefit is correlated to the average revenue per product and the variability in the revenue across products whose components are constrained

inventory rationing in a make to stock production system with several demand classes and lost sales this paper considers the stock rationing problem of a single item make to stock production system with several demand classes and lost sales for the case of poisson demands and exponential production times we show that the optimal policy can be characterized by a sequence of monotone stock rationing levels for each demand class there exists a stock rationing level at or below which it is optimal to start rejecting the demand of this class in anticipation of future arrival of higher priority demands a simple queueing model is analyzed to compute the operating cost of a rationing policy in a numerical study we compare the optimal rationing policy with a first come first served policy to investigate the benefit of stock rationing under different operating conditions of the system

a single product inventory model for multiple demand classes we consider a single product inventory system that serves multiple demand classes which differ in their shortage costs or service level requirements we assume a critical level control policy and a backorder clearing mechanism in which we treat a backorder for a lower priority class equivalent to a reserve stock shortfall for the higher priority class we show the equivalence between this inventory system and a serial inventory system based on this equivalence we develop a model for cost evaluation and optimization under the assumptions of poisson demand deterministic replenishment lead time and a continuous review q r policy with rationing we propose a computationally efficient heuristic and develop a bound on its performance we provide a numerical experiment to show the effectiveness of the heuristic and the value from a rationing policy finally we describe how to extend the model to permit service times and how to extend the model to a multi echelon setting

just in time component replenishment decisions for assemble to order manufacturing under capital constraint and stochastic demand abstract while just in time ideas have been enthusiastically embraced by manufacturing practitioners the small replenishment batch sizes advocated are difficult to reconcile with the standard management science cost trade off approach in a previous paper by the authors which analysed a multi product manufacturing scenario under deterministic demand this difficulty was diagnosed as being due to the standard assumption that capital for inventory is borrowed and hence boundless when inventory is financed by investors and is thus finite the investment level must be treated as an additional variable in the decision to adopt inventory reduction policies for lean investments which might be chosen to maximise return on investment roi rather than absolute profit or for reasons of flexibility jit replenishment becomes more attractive for certain components than the standard analysis would suggest because the capital formerly invested in these components can be reinvested in the inventory of the remaining batch components to improve efficiencies this paper treats the stochastic version of the same problem develops a tractable solution method for the decision problem and in addition to reinforcing the findings of the previous study reveals several other ways in which jit replenishment and component substitution can improve performance by limiting the cost of dealing with uncertainty the analysis is illustrated using an actual case study of a small manufacturing enterprise seeking to reduce inventory and increase roi

yield and allocation management in a continuous make to stock system with demand upgrade substitution abstract yield management is crucial for high tech industries to reduce over production however it is very challenging for a manufacturer to make a yield decision under the circumstance of uncertain demand and stochastic product quality for example in semiconductor manufacturing industry products are produced in batches within certain production cycle time even if the same raw material is put into the production system the product qualities measured by performance usually are not identical due to random yield in the manufacturing process since products have overlapped performance specifications products of the same batch are classified into different classes according to their qualities at the allocation stage products with higher performance can substitute for demand for products with lower performance this type of production and allocation system can be specified as a make to stock system with single material multi products multi periods upward demand substitution under random yield and uncertain demands in order to maximize profit the manufacturer needs to decide on the optimal input material quantity and the optimal allocation policy the problem is formulated as a stochastic dynamic programming model because manufacturer s profit is affected by the allocation policies atp r allocation policy is proposed to help manufacturer make real time allocation decisions a numerical experiment shows that atp r allocation policy performs better than the traditional myopic allocation policy to reduce the computation burden involved in atp r allocation policy we further propose a simplified algorithm and our experimental studies provide proof of the effectiveness of the proposed simple algorithm

dynamic inventory rationing for systems with multiple demand classes and general demand processes we consider the dynamic rationing problem for inventory systems with multiple demand classes and general demand processes we assume that backorders are allowed our aim is to find the threshold values for this dynamic rationing policy for single period systems dynamic critical level policy is developed and the detailed cost approximation subject to this policy is derived for multiperiod systems a dynamic rationing policy with periodic review is proposed the numerical study shows that our dynamic critical level policies are close to being optimal for various parameter settings

inventory policies for systems with stochastic and deterministic demand we consider a periodic review inventory system with demand arriving simultaneously from a deterministic source and a random source the deterministic demand has to be satisfied immediately and the stochastic demand can be backordered assuming that the stochastic demand is never backlogged if there is stock in the system we prove that a modified s s policy is optimal under general conditions if there is a setup cost if there is a smoothing cost instead of the setup cost we observe that the problem corresponds to a standard model with one source of demand

financing property s contribution to regeneration attracting investment and finance into inner city and other renewal areas poses particular difficulties and is frequently reliant on strong public sector commitment through special incentives or other mechanisms to provide the conditions to lever private sector activity this paper initially links the concept of market failure and the rationale for regeneration and examines policy responses from uk european and us perspectives followed by a consideration of public and private sector financing approaches international perspectives draw particularly upon the use of tax based mechanisms in regeneration notably those used in the us in the european context the paper highlights implications for regeneration stemming from the interpretation of state aid rules and competition policy conclusions reflect upon the complexity of regeneration and the importance of the different stakeholders within the regeneration process

production and inventory control of a single product assemble to order system with multiple customer classes we consider the optimal production and inventory control of an assemble to order system with m components one end product and n customer classes a control policy specifies when to produce each component and whenever an order is placed whether or not to satisfy it from on hand inventory we formulate the problem as a markov decision process and characterize the structure of an optimal policy we show that a base stock production policy is optimal but the base stock level for each component is dynamic and depends on the inventory level of all other components more specifically it is nondecreasing we show that the optimal inventory allocation for each component is a rationing policy with different rationing levels for different demand classes the rationing levels for each component are dynamic and also nondecreasing in the inventory level of all other components we compare the performance of the optimal policy to heuristic policies including the commonly used base stock policy with fixed base stock levels and find them to perform surprisingly well especially for systems with lost sales

reservation and allocation policies for influenza vaccines abstract this research investigates the impact of alternative allocation mechanisms that can be employed in the context of vaccine inventory rationing available vaccine inventory can be allocated to arrivals from high priority target groups such as healthcare professionals and low priority non target groups demand classes using partitioned allocation pa standard nesting sn and theft nesting tn in any one of the mechanisms a part of the available inventory is reserved for the exclusive use of the high priority demand class they differ however in how the unreserved portion of the inventory is utilized under pa demand from the high low priority class consumes only the reserved unreserved quantity under sn demand from the high priority class first consumes the reserved quantity once and if this quantity is exhausted high priority demand competes with low priority demand for the remaining inventory under tn the sequence of allocation is reversed both demand classes first compete for the unreserved inventory once this portion of inventory is exhausted high priority demand is fulfilled from the reserved inventory and low priority demand is rejected we develop service level probability of fulfilling the entire demand and fill rate fraction of demand fulfilled expressions for all three allocation mechanisms based on these expressions numerical analyses are conducted to illustrate which allocation mechanism a health planner should choose depending on the availability of vaccines and how the health planner should set the reserved quantity for the high priority class we observe that 1 there exist certain conditions under which one of the allocation mechanisms outperforms the others and 2 this effect is determined by the decision maker s choice of the performance measure

the impact of demand aggregation through delayed component allocation in an assemble to order system we consider an assemble to order system in which multiple products are assembled from a common component and a set of product dedicated components component capacities are chosen prior to a finite horizon selling season and the common component is allocated to the products based on observed demands we propose a collection of allocation mechanisms involving varying degrees of demand aggregation ranging from a scheme under which all demands are observed prior to making the allocation decision to allocations made for each arriving demand in this context we explore the impact of the allocation scheme on sales profits and capacity decisions including the degree of capacity imbalance we find that the benefit from increased demand aggregation is closely linked to the degree of capacity imbalance profit gains from delayed allocation tend to be higher in systems in which the optimal capacity portfolio is highly unbalanced when the allocation decision is made after observing all demands we develop insights into what detailed system parameters lead to the largest gains from demand aggregation and also explore the trade offs associated with the choice of an allocation scheme when customers exhibit impatience if the allocation scheme forces them to wait to be served this paper was accepted by ananth iyer operations and supply chain management

a small sample study of the new keynesian macro model this paper presents a small sample study of the three equation three variable new keynesian macro model while the point estimates imply that the fed has been stabilizing inflation fluctuations since 1980 our econometric analysis suggests considerable uncertainty regarding the stance of the fed against inflation the canonical new keynesian macro model is strongly rejected by the likelihood ratio test but we propose the direction in which it needs to be modified in order to fit the data

capturing the risk pooling effect through demand reshape the risk pooling effect has been documented to benefit inventory systems by reducing the need for safety stock and consequently lowering costs such as inventory holding and shortage penalty in this paper we propose a new approach called demand reshape to take advantage of the risk pooling effect it is demonstrated that a company can improve its profit by encouraging some of its customers who intended to purchase one product to switch to another the effectiveness of this approach is evaluated in various scenarios and found to be very promising

the value of flexibility in make to order systems the effect of demand correlation we consider a manufacturer of mass customized modular products who orders components under demand uncertainty and sets prices produces to order and trades excess components in a secondary market after this uncertainty is resolved the sequence of events reflects in a parsimonious fashion the considerable reduction in demand uncertainty between the procurement stage and the selling season typical of industries with long supply lead times and short product life cycles we prove that in contrast to conventional wisdom the value of production flexibility and expected profit increase with demand correlation if and only if commonality between the corresponding products does not exceed a threshold we also prove that the value of flexibility and expected profit may each increase or decrease with demand variability depending on demand correlations and component commonalities across the entire product line finally we prove that when demand shocks are independent the optimal product prices are positively correlated if and only if the degree of commonality between the corresponding products exceeds a threshold

component commonality with service level requirements this paper extends recent results of baker et al baker k r m j magazine h l w nuttle 1986 the effect of commonality on safety stocks in a simple inventory model management sci 32 982 988 in understanding the impact of component commonality on stocking levels under service level constraints a model is formulated for an arbitrary number of products with general joint demand distribution the results obtained are not all intuitive while utilizing commonality is beneficial nothing general can be said about the resulting change in the components stock levels when the cost structure is of a particular simple form though some interesting general patterns do emerge we also discuss the case of using a service level measure where rationing of common components might be required and characterize the implied rationing rule

incentives and commonality in a decentralized multiproduct assembly system in this paper we explore the impact of decentralized decision making on the behavior of multiproduct assembly systems specifically we consider a system where three components two product specific and one common are used to produce two end products to satisfy stochastic customer demands we study the system under both centralized and decentralized decision making in the decentralized system we prove that for any set of wholesale prices there exists a unique pareto optimal equilibrium in the suppliers capacity game we show that the assembler s optimal wholesale prices lie in one of two regions one leads to capacity imbalance and one does not we use these results to derive insights regarding the inefficiencies that decentralization can cause in such systems in particular several of our findings indicate that outsourcing the management of component supplies may inhibit the use of operational hedging approaches for managing uncertainty

inventory sharing and rationing in decentralized dealer networks an increasing number of manufacturers have started to pursue a strategy that promotes inventory sharing among the dealers in their distribution network in this paper we analyze a decentralized dealer network in which each independent dealer is given the flexibility to share his inventory we model inventory sharing as a multiple demand classes problem in which each dealer faces his own customer demand with high priority and inventory sharing requests from other dealers with low priority assuming that each dealer uses a base stock and threshold rationing policy for his inventory stocking and inventory sharing decisions we explicitly model the interactions between the dealers through inventory sharing and obtain aclosed form cost function for each dealer based on the steady state distribution of the inventory levels at the two dealers we then provide a detailed supermodularity analysis of the inventory sharing and inventory rationing game in which each dealer has a two dimensional strategy set stocking level and rationing level we show that the full sharing game in which dealers precommit to sharing all of their on hand inventory and the fixed sharing level game in which dealers precommit to sharing a portion of their on hand inventory are supermodular and thus a pure strategy nash equilibrium is guaranteed to exist for the rationing game in which dealers precommit to their stocking levels we show that there exists a dominant strategy equilibrium on the dealers sharing rationing levels finally a comprehensive computational study is conducted to highlight the impact of the manufacturer s incentives subsidies and or transshipment fees on the dealers sharing behavior

using imperfect advance demand information in ordering and rationing decisions in this paper we consider an inventory problem with two demand classes having different priorities the appropriate policy of rationing the available stock i e reserving some stock for meeting prospective future demand of preferred customers at the expense of deliberately losing some of the currently materialized demand of lower demand class es relies on the estimation of the future demand utilizing current signals on future demand which we refer to as imperfect advance demand information adi decreases uncertainty on future demand and may help to make better decisions on when to start rejecting lower class demand we develop a model that incorporates imperfect adi with inventory ordering replenishment decision and rationing available stock in a two period setting we show some structural properties solve the rationing problem and propose solution methods based on monte carlo simulation for the ordering problem we conduct numerical tests to measure the impact of system parameters on the expected value of imperfect adi and provide useful managerial insights

dynamic inventory rationing with mixed backorders and lost sales abstract customers may react differently when stockouts occur in this paper we investigate the rationing policy for an inventory system with a mixture of demand classes of backorder type and lost sales type since the penalty cost of backorders varies with time the priorities of demand classes also alter with time this totally changes the problem structure compared with the classic rationing models a dynamic rationing policy is studied in this paper by considering the dynamics of demand priorities a markov decision model is developed to obtain the optimal dynamic rationing levels for multiple demand classes the results indicate that between the priority switching points rationing levels often exhibit different patterns for lost sales demand classes the rationing levels always decrease as the remaining time approaches to zero for backorder demand classes the rationing levels increase in some parts due to declining of the priorities the rationing levels of all demand classes finally decline to zero to reduce the inventory holding cost the application of dynamic rationing is further extended from a single period model to a multi period s t model where unit cost has to be included the optimal ordering policy is proved to be a myopic base stock policy and the dynamic rationing policy in the single period model can still be applied with modified time independent penalty costs for lost sales classes to overcome the computational complexity a heuristic dynamic rationing policy is introduced due to its good outcome implementing such a heuristic dynamic rationing policy can be a practical solution for inventory system with mixed backorders and lost sales in order to enhance the system performance

dynamic inventory rationing strategies for inventory systems with two demand classes poisson demand and backordering we study inventory systems with two demand classes critical and non critical poisson demand and backordering we analyze dynamic rationing strategies where the number of items reserved for critical demand depends on the remaining time until the next order arrives different from results in the literature we do not discretize demand but derive a set of formulae that determine the optimal rationing level for any possible value of the remaining time moreover we show that the cost parameters can be captured in a single relevant dimension which allows us to present the optimal rationing levels in charts and lookup tables that are easy to implement numerical examples illustrate that the optimal dynamic rationing strategy outperforms all static strategies with fixed rationing levels

the stochastic knapsack revisited switch over policies and dynamic pricing the stochastic knapsack has been used as a model in wide ranging applications from dynamic resource allocation to admission control in telecommunication in recent years a variation of the model has become a basic tool in studying problems that arise in revenue management and dynamic flexible pricing and it is in this context that our study is undertaken based on a dynamic programming formulation and associated properties of the value function we study in this paper a class of control that we call switch over policies start by accepting only orders of the highest price and switch to including lower prices as time goes by with the switch over times optimally decided via convex programming we establish the asymptotic optimality of the switch over policy and develop pricing models based on this policy to optimize the price reductions over the decision horizon

influence of dependency between demands and returns in a reverse logistics system we consider two reverse logistics systems where returned products are as good as new for the first system the product return flow is independent of the demand flow we prove that the optimal policy is of base stock type and we establish monotonicity results for the optimal base stock levels with respect to the system parameters arrival rate production rate return rate production cost lost sale cost return cost and holding cost we also provide an efficient algorithm to compute the optimal base stock level for the second system demands and returns are strongly correlated a satisfied demand induces a product return after a stochastic return lead time with a certain probability when the return lead time is null we extend the results obtained for the first system when the return lead time is positive the optimal control problem is more complex and we do not prove that the optimal policy is of base stock type however we provide a framework to analyse base stock policies finally we carry out a numerical study on many scenarios to investigate the impact of ignoring dependency between demands and returns we observe that ignoring this dependency yields to non negligible cost increase