calculating order up to levels for products with intermittent demand abstract the croston 1972 forecasting and stock control for intermittent demands operational research quarterly 23 289 303 method is the standard method for forecasting intermittent demand it has been shown to perform well in various studies and is available in most commercial forecasting packages however little attention has been paid to linking the method with inventory control i e using the generated forecasts to calculate the inventory control parameters in this study we consider the most commonly applied order up to policy and show how the forecasts can be used to calculate order up to levels in a numerical study we show that the calculated order up to levels lead to service levels that are close to their targets

a political economy model of congressional careers our main goal is to quantify the returns to a career in the united states congress we specify a dynamic model of career decisions of a member of congress and estimate this model using a newly collected dataset given estimates of the structural model we assess reelection probabilities estimate the effect of congressional experience on private and public sector wages and quantify the value of congressional seat moreover we assess how an increase in the congressional wage or the imposition of term limits would affect the career decisions of politicians and the returns from a career in congress

a deterministic inventory model for deteriorating items with stock dependent demand rate abstract a deterministic inventory model is developed by assuming that the demand rate is stock dependent and the items deteriorate at a constant rate the expression for the average net profit over one production run is derived and its optimization with respect to the decision variables q initial stock and t duration of a production cycle is carried out this leads to two highly nonlinear equations which are solved by using a subroutine neqnf in imsl math library in cyber 180 480a computer system the optimal solution so derived is compared with that for the no deterioration 0 case sensitivity of the optimal solution to changes in parameter values is examined several aspects of the functional form for the demand rate are considered in a separate section finally the salient features of the problem and its solution are discussed in brief

analytical evaluation of lead time demand in polytree supply chains with uncertain demand lead time and inter demand time abstract in a stochastic supply chain network knowing the exact distribution of lead time demand ltd for each node allows determining inventory policy parameters service levels and optimal costs to determine the ltd distributions a stochastic analytical model has been developed for a multi echelon supply chain organised into an arbitrary polytree network where the variables demand quantity lead time and inter demand time are uncertain and can follow any probability distribution the model is based on a conventional nq batch policy for each node with discrete time and continuous demand any network can be broken down into four basic elements which represent root and leaf node topologies the model derives key convolutions for the four basic elements and then follows the same technique for evaluating resulting ltd distributions for each node in the network the paper presents the formulation in seven steps that can be used to obtain exact ltd distributions either in the two dimensional form or as a compound one dimensional ltd distribution per variable lead time for each node in any polytree supply chain the ltd distributions can be calculated either analytically for smaller networks or using numerical integration for larger networks the validation of the developed framework has been conducted by comparing the obtained formalism based ltd distribution for two test networks against simulation the pairs of simulated and formalism based distributions have been plotted against each other as well as subjected to various goodness of fit tests and error analysis the results suggest that the formalism based and simulated probability distributions are consistent

note periodic review s s policies for joint replenishment inventory systems this note deals with the joint replenishment problem with stochastic demands a new class of policies called ps s policy is proposed for this problem the proposed policy uses independent periodic review s s policies for each item results on test problems show that the proposed policy is superior to other classes of policies for the problem

how much demand should be fulfilled we study the inventory replenishment of a product whose demand can be manipulated by restricting the supply this research is motivated by a novel marketing tactic employed by manufacturers of fashion and luxury items such a tactic combines innovative marketing with deliberate understocking in an attempt to create shortages i e waitlists that add to the allure and sense of exclusivity of a product and stimulate its demand we model the problem as a finite horizon periodic review system where demand in each period is a decreasing function of the net ending inventory in the previous period although the optimal structure can be complex in general under certain conditions we are able to characterize the optimal policy as a state dependent monotone base stock policy we compare this policy with the optimal policy for the case in which demand is independent of the net inventory we also show that understocking is optimal in various scenarios we then propose a novel strategy called the inventory withholding strategy to further explore the wait list effect by making customers wait even when there is inventory on hand to satisfy them our numerical experiments study the impact of various model parameters in combination with the wait list effect on the optimal policy and the corresponding expected profits

estimating the lead time demand distribution when the daily demand is non normal and autocorrelated hon shiang lau abstract this paper develops convenient formulas for estimating the probability distribution of lead time demand when the inventory item s daily demand follows a probability distribution of any arbitrary shape and when simple univariate models can be found for the autocorrelated daily demand series numerical examples are presented to illustrate the use of these formulas the numerical results also indicate that significant error may be incurred when inventory decisions are made without proper consideration of the autocorrelations or the arbitrary distribution shapes of daily demands

power approximation for computing s s policies using service level the paper presents an analytic approximation for computing s s policies for single items under periodic review with fixed ordering costs linear holding costs and a service level requirement the replenishment lead time is fixed and unfilled demand is backlogged the approximation is similar to ehrhardt s power approximation however we do not assume the knowledge of shortage costs which are difficult to estimate in practice we define a service level which measures the average backlog relative to the average demand this quantity is easy to understand and frequently used in practice the resulting power approximation policies are easy to compute and require only knowledge of the mean and variance of demand computational results show that the approximation gives a service level which is within one percentage point of the required service level in most cases furthermore the expected total costs of the approximation taking into consideration a penalty cost for stockouts are well within one percent of optimal

empirically driven hierarchical classification of stock keeping units this paper proposes a hierarchical multi criteria classification method developed for inventory management purposes and applied in a case study of the spare parts business of a household appliance manufacturer the classification method is built on the basis of six dimensions resulting in 12 different classes of spare parts for which differentiated forecasting and inventory policies are proposed and tested the results of our simulation study demonstrate the reduction of the total logistics costs by about 20 whilst still achieving the specified target service level for each class even more importantly the proposed approach is simple enough to be understood and applied by company managers thus increasing the probability of its adoption in the same or similar fashion in other real world settings

secession with natural resources we look at the formation of new indian states in 2001 to uncover the effects of political secession on the comparative economic performance of natural resource rich and natural resource poor areas resource rich constituencies fared comparatively worse within new states that inherited a relatively larger proportion of natural resources we argue that these patterns reflect how political reorganisation affected the quality of state governance of natural resources we describe a model of collusion between state politicians and resource rent recipients that can account for the relationships we see in the data between natural resource abundance and post breakup local outcomes

evaluation of forecasting error measurements and techniques for intermittent demand abstract this paper is a part and contribution to develop flexible and robust supply chain forecasting systems under changing market demands it suggests new tools and models to evaluate forecasting error measurements the paper especially studies slow moving or intermittent demand when for items the forecasting time periods often have zero demand for the difficult to forecast intermittent demand the croston forecasting technique is mostly regarded as a better choice than single exponential smoothing these two methods croston and single exponential smoothing together with two modifications of the croston method are discussed and evaluated with real intermittent data the apprehended performance of a forecasting technique is dependent of the chosen measurement of forecast errors the main purpose is to examine and evaluate different forecasting error measurements traditional measurements of forecast errors are studied mean absolute deviation mad mean square error mse etc together with new suggested error and bias measurements periods in stock pis and number of shortages nos pis considers the time aspect of the forecast error nos considers the development of cumulated forecast error cfe a complementary measure for descriptive statistics of time series is also suggested mean average change the conclusion through principal components analysis pca is that a single measure of forecast errors does not present the total different dimensions of the errors complementary error measures must be used

on the stock control performance of intermittent demand estimators the purpose of this paper is to assess the empirical stock control performance of intermittent demand estimation procedures the forecasting methods considered are the simple moving average single exponential smoothing croston s method and a new method recently developed by the authors of this paper we first discuss the nature of the empirical demand data set 3000 stock keeping units and we specify the stock control model to be used for experimentation purposes performance measures are then selected to report customer service level and stock volume differences the out of sample empirical comparison results demonstrate the superior stock control performance of the new intermittent demand forecasting method and enable insights to be gained into the empirical utility of the other estimators

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

on the interaction between forecasting and stock control the case of non stationary demand the effect of using estimated forecast demand parameters on the performance of an inventory control system is an intriguing and important subject recent research has been undertaken on this phenomenon assuming stationary demand data in this paper we extend the research to non stationary demands by means of simulation the case of a periodic order up to level inventory system is considered and the experimental structure allows us to evaluate in a progressive manner the accumulated effect of using the optimal forecasting method optimal forecast parameters and correct variance expression procedures the results allow insights to be gained into operational issues and demonstrate the scope for improving stock control systems

the value of real time yield information in multi stage inventory systems exact and heuristic approaches abstract we consider a random yield inventory system where a company has access to real time information about the actual yield realizations to contribute to a better understanding of the value of this information we develop a mathematical model of the inventory system and derive structural properties we build on these properties to develop an optimal solution approach that can be used to solve small to medium sized problems to solve large problems we develop two heuristics we conduct numerical experiments to test the performances of our approaches and to identify conditions under which real time yield information is particularly beneficial our research provides the approaches that are necessary to implement inventory control policies that utilize real time yield information the results can also be used to estimate the cost savings that can be achieved by using real time yield information the cost savings can then be compared against the required investments to decide if such an investment is profitable

coordinated replenishments in inventory systems with correlated demands abstract demand correlation among different inventory items is common in real life multi item inventory systems however this phenomenon has not received sufficient attention in the existing inventory literature in this paper we construct a markovian model for a two item inventory system with correlated demands and coordinated replenishments we obtain an expression for the long run total cost per unit of time under the can order replenishment policy for the scenario with independent replenishments the explicit formula for the long run total cost per time unit can be derived which leads to analytical solutions for the optimal policies we then present numerical examples of the optimal can order policies and discuss some managerial insights regarding demand correlation and replenishment coordination our numerical results also suggest a possible heuristic method for obtaining can order replenishment policies for multi item systems

a robustness study of a multi echelon inventory model via simulation abstract this paper examines the robustness of a standard model of multi echelon inventory systems specifically the models discussed in axsater oper res 48 5 2000 686 a simulation model was developed to explore the model s ability to predict system performance for a two echelon one warehouse multiple retailer system using r q inventory policies under conditions that violate the model s fundamental modeling assumptions in particular the impact of non stationary demand on this stationary demand inventory model was examined the model performs well at the low demand and large retailer order batch size situations but our testing of the model indicated that care must be taken when applying this model to situations that violate its fundamental assumption these results should help practitioners to better understand the assumptions of these models and to determine when or when not to apply these models in practice

deterministic eoq with partial backordering and correlated demand caused by cross selling abstract there has been much work regarding the deterministic eoq with partial backordering the majority of these studies assume no correlation in sales so independent demands across items is applied in the models however it is generally recognized that cross selling effects between items often appear in real contexts thus incorporating such effects in the inventory model in the form of correlated demands makes it of more practical relevance in this paper the authors address a two item inventory system where the demand of a minor item is correlated to that of a major item because of cross selling we firstly present a two item eoq model with identical order cycles where the unmet demand of the major item can be partially backordered with lost sales whereas the demand of the minor item must be met without stockouts this model is further extended to fit a more practical case where the order cycle of the major item is an integer multiple of that of the minor item the optimal solutions of the two models as well as the inventory decision procedures are also developed comparative analysis on these two eoq models has been drawn in the computational study which presents some insights into the parameter effect on the optimal inventory policy

german inventory to sales ratios 1971 2005 an empirical analysis of business practice abstract the purpose of this study is to test empirically for the first time the general hypothesis that inventory to sales ratios have decreased over time in the german economy although inventory reduction has been a prevalent topic in the production and operations management literature there is a lack of empirically confirmed answers to questions they are as follows have inventories in german firms decreased overall during the past decades what sectors of german industry are leading lagging behind inventory reduction has inventory reduction developed differently for raw materials work in process or finished goods in which periods was marginal inventory reduction greatest to the best of our knowledge this empirical study is the first to broadly investigate inventory development from the 1970s until the present for a major european economy germany and will provide the first answers to the research questions stated above using aggregate industry level data provided by the deutsche bundesbank we show that inventory levels decreased overall in many sectors of german industry this reduction was mainly marked for raw materials and finished goods particularly for the second half of the time frame investigated

setting stock levels for wholesaling performance measures and conflict of objectives between supplier and stockist abstract the situation considered is that where a sales outlet holds a stock of goods for sale which are topped up by regular weekly deliveries demand is highly variable and ranges from high to very low over the many items held in stock an appropriate stock system to use in these circumstances is an order up to policy but the problem is to set the right order up to levels for each item items which experience low demand require particular care the mathematical model used for setting stock levels for these items has to allow for the possibility of stockouts occuring before the review time and not only in the period from review to delivery the paper consideres various measures which are used for assessing the performance of sales outlets and the implications of these measures for setting stock levels some measures are shown to be very sensitive to the level of sales and also need to be used with care when making interbranch comparisons a consideration of performance measures also brings out the potential for conflict of interest between supplier and stockist

cost function for a periodic reorder point system with time dependent replenishment costs abstract a single item inventory model with probabilistic demand is considered in this paper the replenishment of items is cyclical and occurs every n periods the order for replenishment can be placed at the end of any period during the cycle replenishment costs setup and unit costs are stated as a function of time the units ordered are set equal to an order quantity q the general expression of this inventory system is formulated by developing the stationary distribution of the inventory position units ordered and the probability of placing an order during any period the expression is stated in terms of the reorder point s and the order quantity q and can be used to locate the optimal solution

a periodic review model with serially correlated inventory level dependent demand abstract it has been established that the demand rates of many consumer products are serially correlated and are dependent on the amount of inventory displayed to the customer a periodic review model is developed that considers both of these effects an adaptive base stock policy based on the critical fractile is presented and a solution methodology is developed the effect of this demand pattern on the safety stock requirement is investigated

enriching demand forecasts with managerial information to improve inventory replenishment decisions exploiting judgment and fostering learning this paper is concerned with analyzing and modelling the effects of judgmental adjustments to replenishment order quantities judgmentally adjusting replenishment quantities suggested by specialized statistical software packages is the norm in industry yet to date no studies have attempted to either analytically model this situation or practically characterize its implications in terms of learning we consider a newsvendor setting where information available to managers is reflected in the form of a signal that may or may not be correct and which may or may not be trusted we show the analytical equivalence of adjusting an order quantity and deriving an entirely new one in light of a necessary update of the estimated demand distribution further we assess the system s behavior through a simulation experiment on theoretically generated data and we study how to foster learning to efficiently utilize managerial information judgmental adjustments are found to be beneficial even when the probability of a correct signal is not known more generally some interesting insights emerge into the practice of judgmentally adjusting order quantities

the private returns to public office we study the wealth accumulation of indian state politicians using public disclosures required of all candidates the annual asset growth of winners is 3 5 percent higher than that of runners up a difference that holds also in a set of close elections the relative asset growth of winners is greater in more corrupt states and for those holding ministerial positions these results are consistent with a rent seeking explanation for the relatively high rate of growth in winners assets

do nominal devaluations lead to real devaluations in ldcs abstract devaluation or depreciation of nominal exchange rate is a policy to boost exports however since any favorable effects of devaluation could be offset by its inflationary effects one must consider real devaluation this note investigates whether nominal devaluation leads to real devaluation by employing a relatively new method of cointegration and error correction modeling

intermittent demand forecasts with neural networks intermittent demand appears when demand events occur only sporadically typically such time series have few observations making intermittent demand forecasting challenging forecast errors can be costly in terms of unmet demand or obsolescent stock intermittent demand forecasting has been addressed using established forecasting methods including simple moving averages exponential smoothing and croston s method with its variants this study proposes a neural network nn methodology to forecast intermittent time series these nns are used to provide dynamic demand rate forecasts which do not assume constant demand rate in the future and can capture interactions between the non zero demand and the inter arrival rate of demand events overcoming the limitations of croston s method in order to mitigate the issue of limited fitting sample which is common in intermittent demand the proposed models use regularised training and median ensembles over multiple training initialisations to produce robust forecasts the nns are evaluated against established benchmarks using both forecasting accuracy and inventory metrics the findings of forecasting and inventory metrics are conflicting while nns achieved poor forecasting accuracy and bias all nn variants achieved higher service levels than the best performing croston s method variant without requiring analogous increases in stock holding volume therefore nns are found to be effective for intermittent demand applications this study provides further arguments and evidence against the use of conventional forecasting accuracy metrics to evaluate forecasting methods for intermittent demand concluding that attention to inventory metrics is desirable

forecasting and stock control a study in a wholesaling context wholesalers add value to the products they deal with by essentially bringing them closer to the end consumers in that respect the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels in this paper we address issues pertinent to forecasting and inventory management in a wholesaling environment and discuss the recommendations proposed in such a context in a case study organization our findings demonstrate the considerable scope that exists for improving current practices and offers insights into possible managerial issues

on the returns to holding political office is it worth it abstract the paper estimates causal effects of being elected in a local election on monetary returns the claim for causality is made in a research design where the income of some candidate who just barely won a seat is compared to that of some other candidate who was close to winning a seat for the same party but ultimately did not this research design is made possible thanks to a comprehensive detailed data set covering all swedish politicians who have run for office in the period 1991 2006 the analysis establishes that monetary returns from local politics are absent both in the short and long run by relating this null result to effects on the future political career the paper provides suggestive evidence that local politicians are not primarily motivated by money

analysis of order up to level inventory systems with compound poisson demand abstract we analyse a single echelon single item inventory system where the demand and the lead time are stochastic demand is modelled as a compound poisson process and the stock is controlled according to a continuous time order up to out level policy we propose a method for determining the optimal out level for cost oriented inventory systems where unfilled demands are backordered we first establish an analytical characterization of the optimal out level the actual calculation is based on a numerical procedure the accuracy of which can be set as highly as desired by means of a numerical investigation we show that the method is very efficient in calculating the optimal out level we compare our results with those obtained using an approximation proposed in the literature and we show that there is a significant difference in accuracy for slow moving items our work allows insights to be gained on stock control related issues for both fast and slow moving stock keeping units skus

the optimal review period in a dynamic inventory model consider a single item periodic review infinite horizon undiscounted inventory model with stochastic demands proportional holding and shortage costs and full backlogging orders can arrive in every period and the cost of receiving them is negligible as in a jit setting every t periods one observes the current stock level and orders deliveries for the next t periods thus incurring a fixed setup cost the goal is to find a review period t and an ordering policy that minimize the long run expected average cost per period flynn and garstka flynn j s garstka 1990 a dynamic inventory model with periodic auditing opns res 38 1089 1103 characterize an optimal ordering policy when t is fixed and study a myopic policy whose cost is often close to the optimal cost this paper covers the problem of selecting t we prove an optimal review period t exists characterize its properties and present methods for its computation we also study an approximation to t based on the myopic policy of ou

paying politicians theory and evidence this paper looks at the theory behind the idea that paying politicians better will improve their performance the paper lays out a political agency model with adverse selection and moral hazard where politicians are subject to two period term limits this model provides a number of predictions about how the pay of politicians affects agency problems we also consider what happens when the pool of politicians is endogenous the main ideas in the model are confronted with data on u s governors jel d72 j33

analysis of a forecasting production inventory system with stationary demand we consider a production stage that produces a single item in a make to stock manner demand for finished goods is stationary in each time period an updated vector of demand forecasts over the forecast horizon becomes available for use in production decisions we model the sequence of forecast update vectors using the martingale model of forecast evolution developed by graves et al 1986 1998 and heath and jackson 1994 the production stage is modeled as a single server discrete time continuous state queue we focus on a modified base stock policy incorporating forecast information and use an approximate analysis rooted in heavy traffic theory and random walk theory to obtain a closed form expression for the forecast corrected base stock level that minimizes the expected steady state inventory holding and backorder costs this expression which is shown to be accurate under certain conditions in a simulation study sheds some light on the interrelationships among safety stock stochastic correlated demand inaccurate forecasts and random and capacitated production in forecasting production inventory systems

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

investigating the added value of integrating human judgement into statistical demand forecasting systems abstract whilst the research literature points towards the benefits of a statistical approach business practice continues in many cases to rely on judgmental approaches for demand forecasting in today s dynamic environment it is especially relevant to consider a combination of both approaches however the question remains as to how this combination should occur this study compares two different ways of combining statistical and judgmental forecasting employing real life data from an international publishing company that produces weekly forecasts on regular and exceptional products two forecasting methodologies that are able to include human judgment are compared in a restrictive judgement model expert predictions are incorporated as restrictions on the forecasting model in an integrative judgment model this information is taken into account as a predictive variable in the demand forecasting process the proposed models are compared on error metrics and analysed with regard to the properties of the adjustments direction size and of the forecast itself volatility periodicity the integrative approach has a positive effect on accuracy in all scenarios however in those cases where the restrictive approach proved to be beneficial the integrative approach limited these beneficial effects the study links with demand planning by using the forecasts as input for an optimization model to determine the ideal number of skus per point of sale pos making a distinction between sku forecasts and sku per pos forecasts importantly this enables performance to be expressed as a measure of profitability which proves to be higher for the integrative approach than for the restrictive approach

incumbent performance and electoral control in the pure theory of electoral competition citizens compare the platforms of the candidates and vote for the one whose platform is preferred candidate strategies are identified with promises about future performance in office models of this sort have been developed in both static mckelvey 1975 and dynamic kramer 1977 i settings and all appear to have the property that if the set of alternatives is large enough in some sense equilibrium platforms rarely exist but these models have another feature that is quite as disturbing as their instability in the static setting discussed by mckelvey little attention is paid to the possibility that once in office the politician s preferences may diverge from those of his constituents and that he may therefore choose policies at variance from his platform instead it is simply assumed that promises will be kept whether or not such behavior is congruent with the interest of the officeholder it is sometimes argued that an enforcement mechanism may exist to discipline politicians for failing to keep promises but without a specification of the mechanism it is not obvious that it would be in the interests of the

periodic versus can order policies for coordinated multi item inventory systems the coordinated multi item inventory problem refers to the problem of managing inventories where there is a joint fixed cost for replenishing plus an item by item fixed cost for each item included in the replenishment order given that the optimal solution is likely to be too complex attention has focused on fixed heuristics and in particular can order or s c s policies this paper makes two contributions first a new lower bound on the cost of the optimal policy is proposed in order that the performance of heuristics may be measured second motivated by the lower bound a simple periodic policy is proposed and shown to be an improvement over can order policies for many data sets

the concomitants of exchange rate depreciation less developed countries 1971 1973 this study shows what happens when less developed countries ldcs revalue their currencies with these findings we aim to provide evidence toward improving their currency valuation policies a background presumption and justification for the inquiry is that disequilibrium exchange rates can be an important cause of serious injury to economic performance against which the costs of shifting toward equilibrium rates can be measured but whether or not this presumption is valid exchange rate variation is a phenomenon with potential major effects which should be known more accurately so that policy can be better guided exchange rate revaluation is taken to mean a substantial alteration in the average rate at which transactions are effected between domestic and foreign currencies this concept implies three problems the exchange rate shift must be a certain size for it to be counted one country has current and capital transactions with a number of other countries and transactions may be carried out at both official and free black market rates section i below addresses these problems

intermittent demand linking forecasting to inventory obsolescence the standard method to forecast intermittent demand is that by croston this method is available in erp type solutions such as sap and specialised forecasting software packages e g forecast pro and often applied in practice it uses exponential smoothing to separately update the estimated demand size and demand interval whenever a positive demand occurs and their ratio provides the forecast of demand per period the croston method has two important disadvantages first and foremost not updating after many periods with zero demand renders the method unsuitable for dealing with obsolescence issues second the method is positively biased and this is true for all points in time i e considering the forecasts made at an arbitrary time period and issue points only i e considering the forecasts following a positive demand occurrence only the second issue has been addressed in the literature by the proposal of an estimator syntetos boylan approximation sba that is approximately unbiased in this paper we propose a new method that overcomes both these shortcomings while not adding complexity different from the croston method the new method is unbiased for all points in time and it updates the demand probability instead of the demand interval doing so in every period the comparative merits of the new estimator are assessed by means of an extensive simulation experiment the results indicate its superior performance and enable insights to be gained into the linkage between demand forecasting and obsolescence

busting the princelings the campaign against corruption in china s primary land market using data on over a million land transactions during 2004 2016 where local governments are the sole seller we find that firms linked to members of china s supreme political elites the politburo obtained a price discount ranging from 55 4 to 59 9 compared with those without the same connections these firms also purchased slightly more land in return the provincial party secretaries who provided the discount to these princeling firms are 23 4 more likely to be promoted to positions of national leadership to curb corruption president xi jinping stepped up investigations and strengthened personnel control at the province level using a spatially matched sample e g within a 500 meter radius we find a reduction in corruption of between 42 6 and 31 5 in the provinces either targeted by the central inspection teams or whose party secretary was replaced by one appointed by xi accordingly this crackdown on corruption has also significantly reduced the promotional prospects of those local officials who rely on supplying a discount to get ahead

adapting wright s modification of holt s method to forecasting intermittent demand abstract the challenge of accurately forecasting demand for spare parts is due to the intermittent nature of their demand this study compares a recent modification of croston s method and a method based on holt s double exponential smoothing taking the firm s competitive priorities into consideration wright s modification of holt s method is presented as a viable alternative when forecasting demand for spares especially when trend is present results indicate that firms focusing on minimizing inventory levels as a priority should consider forecasting using the modified croston s method if their priority is high customer service then the modified holt s method is superior

coordinated replenishments in a multi item inventory system with compound poisson demands in many practical applications or multi item inventory systems significant economies of scale can be exploited when coordinating replenishment orders for groups of items this paper considers a continuous review multi item inventory system with compound poisson demand processes excess demands are backlogged and each replenishment requires a lead time there is a major setup cost associated with any replenishment of the family of items and a minor item dependent setup cost when including a particular item in this replenishment moreover there are holding and penalty costs we present an algorithm which searches for a simple coordinated control rule minimizing the long run average cost per unit time subject to a service level constraint per item on the fraction of demand satisfied directly from on hand inventory this algorithm is based on a heuristic decomposition procedure and a specialized policy iteration method to solve the single item subproblems generated by the decomposition procedure the model applies to multi location inventory systems with similar cost structures for coordinated deliveries

on the bias of intermittent demand estimates forecasting and inventory control for intermittent demand items has been a major problem in the manufacturing and supply environment croston operational research quarterly 23 1972 289 proposed a method according to which intermittent demand estimates can be built from constituent events croston s method has been reported to be a robust method but has shown more modest benefits in forecasting accuracy than expected in this research one of the causes of this unexpected performance has been identified as a first step towards improving croston s method certain limitations are identified in croston s approach and a correction in his derivation of the expected estimate of demand per time period is presented in addition a modification to his method that gives approximately unbiased demand per period estimates is introduced all the conclusions are confirmed by means of an extended simulation experiment where croston s and revised croston s methods are compared the forecasting accuracy comparison corresponds to a situation of an inventory control system employing a re order interval or product group review

an improved method for forecasting spare parts demand using extreme value theory inventory control for spare parts is essential for many organizations due to the trade off between preventing high holding cost and stockouts the lead time demand distribution plays a central role in inventory control the estimation of this distribution is problematic as the spare part demand is often intermittent and as a consequence often only a limited number of non zero data points are available in practice the well known empirical method uses historical demand data to construct the lead time demand distribution although it performs reasonably well when service requirements are relatively low it has difficulties in achieving high target service levels in this paper we improve the empirical method by applying extreme value theory to model the tail of the lead time demand distribution to make the most out of a limited number of demand observations we establish that extreme value theory can be applied to lead time demand periods computed over overlapping intervals we consider two service levels the expected waiting time and cycle service level our experiments show that our method improves the inventory performance compared to the empirical method and is competitive with the wss method croston s method and sba for a range of demand distributions

political careers or career politicians two main career paths are prevalent among politicians in modern democracies there are career politicians i e politicians who work in the political sector until retirement and political careers i e there are politicians who leave politics before retirement and work in the private sector in this paper we propose a dynamic equilibrium model of the careers of politicians in a political economy with a private sector and a political sector where individuals are heterogeneous with respect to their market ability as well as their political skills we characterize the conditions under which the two career paths emerge in equilibrium and establish a number of comparative statics results with respect to the quality of politicians and their careers

demand forecasting for multiple slow moving items with short requests history and unequal demand variance modeling the lead time demand for the multiple slow moving inventory items in the case when the available requests history is very short is a challenge for inventory management the classical forecasting technique which is based on the aggregation of the stock keeping units to overcome the mentioned historical data peculiarity is known to lead to very poor performance in many cases important for industrial applications an alternative approach to the demand forecasting for the considered problem is based on the bayesian paradigm when the initially developed population averaged demand probability distribution is modified for each item using its specific requests history this paper follows this approach and presents a new model which relies on the beta distribution as a prior for the request probability and allows to account for disparity in variance of demand between different stock keeping units to estimate the model parameters a special computationally effective technique based on the generalized method of moments is developed simulation results indicate the superiority of the proposed model over the known ones while the computational burden does not increase

operations research in inventory management a review and critique the objectives of inventory management including the relevant related costs are examined in this paper a brief review of standard problems that have been effectively solved is presented however we point out that a serious gap exists between theory and practice in many organizations suggestions are made for bridging this gap finally a list is provided of a number of research problems whose implementable solution would have a major beneficial impact on the practice of inventory management

safety stock determination with correlated demands and arbitrary lead times abstract in this new paper a new method is proposed for determining the safety stock when daily demands are autocorrelated and lead times follow an arbitrary distribution the method is then used as a basis for examining effects on the safety stock when the usual assumptions namely independence and normality of daily demand and normality of lead times are violated the new method is derived by using inequalities on the basis of probability arguments it is simple to use and provides an upper bound of the safety stock further numerical investigation based on the new method shows that the effect of autocorrelation is more pronounced than departure from normality in determining the safety stock substantial error may be incurred if such autocorrelation is ignored in the test cases

the accuracy of a modified croston procedure a modified croston procedure to forecast intermittent demand is reviewed the modified procedure published in this journal in 2004 consists of a new method for estimating the mean demand and a smoothing method for estimating the variance of the forecasted demand rate it is found that the smoothed variance estimate is based on an invalid measure of forecast accuracy moreover it is shown that the method of forecasting mean demand produces biased forecasts the accuracy of this method is assessed using simulated data and the mean square error measure and compared with croston s method and single exponential smoothing it is found that croston s method is generally more accurate than its modification particularly for strongly intermittent series

an association clustering algorithm for can order policies in the joint replenishment problem abstract many studies have shown that the total cost of employing joint replenishment for correlated items is less than the total cost of using single item replenishment savings increase dramatically when the demand between items is closely related although the benefits of joint replenishment are significant it is difficult to define the demand correlation among items especially when the number of items increases a large number of items reduces the efficiency and advantage of the multi item inventory control to overcome this difficulty an association clustering algorithm this paper proposes to evaluate the correlated demands among items the proposed algorithm utilizes the support concept in association rule analysis to measure the similarity among items based on these measurements a clustering method is developed to group items with close demand in a hierarchal way the can order policy is then applied to the optimal clustering result as decided by the proposed performance index to illustrate the benefits of the proposed association clustering algorithm for replenishment systems a set of simulations and a sensitivity analysis is conducted the results of the experiments show that the proposed method outperforms several replenishment models

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

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

dynastic political rents economic benefits to relatives of top politicians we exploit close elections in swedish municipalities to test whether relatives of politicians who become mayors obtain economic benefits we find no benefits for the siblings of new mayors but the

the economies of massed reserves the economy of massed reserves first mentioned by e a g robinson 1958 pp 26 27 is now firmly established in the industrial organization literature as an example of a potential plant level scale economy the massing of reserves results in a savings in the proportion of required reserves to expected output as the scale of a facility increases examples of such reserves are bank tellers specialized tools and equipment repairmen inventories spare parts and checkout lines the potential economies from massing reserves are dependent on the underlying stochastic processes governing the supply and or demand of the service provided theoretical justification for the economies of massed reserves has usually been based on an appeal to the law of large numbers for example donald hay and derek morris wrote the law of large numbers makes the number of breakdowns more predictable in a plant using a large number of machines so that the number of stand by maintenance staff need not be increased in proportion to size 1979 p 44 this paper demonstrates that the law of large numbers does not provide a theoretical explanation of massed reserves scale economies instead it is shown that the expected economies of massed reserves can be calculated from the steady state properties of well known queuing models queuing models apply to any case where a servicing input is held in reserve to cope with the stochastic nature of the market or production process in addition a method for quantifying the expected economies of queuing processes is developed the magnitude of these expected economies is shown to be significant and calculable for example the expected economies inherent in a widely applied queuing model are shown to exceed 23 percent in some cases section i establishes the irrelevance of the law of large numbers as a theory of scale economies section ii provides a formal method for determining the scale economies inherent in the most often mentioned massed reserves example machine repair section iii shows that the same method can be used to calculate scale economies for the remaining massed reserves examples specialized repair tools and equipment checkout counter clerks bank tellers and other service personnel capacity and inventories and spare parts in addition it is demonstrated that the same method can be used to calculate scale economies for some multiproduct operations

pay for politicians and candidate selection an empirical analysis abstract a growing theoretical literature on the effect of politicians salaries on the average level of skills of political candidates yields ambiguous predictions in this paper we estimate the effect of pay for politicians on the level of education of parliamentary candidates we take advantage of an exceptional reform where the salaries of finnish mps were increased by 35 in the year 2000 intended to make the pay for parliamentarians more competitive a difference in differences analysis using candidates in municipal elections as a control group suggests that the higher salary increased the fraction of candidates with higher education among female candidates while we find no significant effect for male candidates

the intergenerational effects of political influence evidence from china this paper considers the effects of fathers political influence on their offspring s labour market outcomes in china political influence refers to the ability to convert political power into econ

politicians payments in a proportional party system abstract are there monetary returns to politics this question is approached in this paper as one of few to quantify the monetary returns to holding political office in a country with proportional representation system i apply a difference in difference setting with a carefully chosen control group to rich data on candidates to the swedish national parliament both short and long run effects of being elected on different types of income are estimated results show that yes mostly thanks to relatively high remuneration while still in office politics can yield positive monetary returns in the long run however the effect is instead compositional in the sense that ex politicians receive more pension income and work less

exploiting elapsed time for managing intermittent demand for spare parts we present an intermittent demand forecasting method that conditions on the elapsed time since the last demand occurrence to anticipate incoming demand and show using empirical data that this can substantially reduce both stock investment and lost revenue for spare parts management we extensively benchmark our method against existing forecasting and bootstrapping methods on forecast accuracy and inventory performance and demonstrate that its performance is robust under general conditions our method is the first to incorporate that activities at the demand side such as aggregation of demand preventive and corrective maintenance can lead to a positive relation between demand size and inter arrival time of demand occurrences by anticipating incoming demand our method offers substantial financial gains

businesspeople in elected office identifying private benefits from firm level returns do businesspeople who win elected office use their positions to help their firms business leaders become politicians around the world yet we know little about whether their commitment to public service trumps their own private interests using an original dataset of 2 703 firms in russia i employ a regression discontinuity design to identify the causal effect of firm directors winning seats in subnational legislatures from 2004 to 2013 first having a connection to a winning politician increases a firm s revenue by 60 and profitability by 15 over a term in office i then test between different mechanisms finding that connected firms improve their performance by gaining access to bureaucrats and not by signaling legitimacy to financiers the value of winning a seat increases in more politically competitive regions but falls markedly when more businesspeople win office in a convocation politically connected firms extract fewer benefits when faced with greater competition from other rent seekers

a taxonomy and research overview of perishable asset revenue management yield management overbooking and pricing this paper proposes the term perishable asset revenue management to denote the field that combines the areas of yield management overbooking and pricing for perishable assets after summarizing the characteristics common to problems in this field the paper discusses the objectives and constraints faced by decision makers then it offers a comprehensive taxonomy with 14 different elements and reviews the research that has been done related to each element finally it suggests some important areas of future research that can help bridge the gap between theory and application

continuous review s s policies with lost sales a method is developed to calculate an s s policy that minimizes the average stationary cost in an inventory system with constant lead time fixed order cost linear holding cost per unit time linear penalty cost per unit short discrete compound poisson demand and lost sales it is assumed that at most one order is outstanding or equivalently that s s s the procedure is compared to several easier to compute approximate solutions including one that assumes backordering examples are given that reveal that although the backorder solution is different than the lost sales one the cost penalty of using it in the lost sales situation is small

forecasting sales of slow and fast moving inventories abstract traditional computerised inventory control systems usually rely on exponential smoothing to forecast the demand for fast moving inventories practices in relation to slow moving inventories are more varied but the croston method is often used it is an adaptation of exponential smoothing that 1 incorporates a bernoulli process to capture the sporadic nature of demand and 2 allows the average variability to change over time the croston approach is critically appraised in this paper corrections are made to underlying theory and modifications are proposed to overcome certain implementation difficulties a parametric bootstrap approach is outlined that integrates demand forecasting with inventory control the approach is illustrated on real demand data for car parts

democracy and demography societal effects of fertility limits on local leaders we investigate whether restricting elected leadership positions to candidates with desirable characteristics leads to society wide adoption of those characteristics in a low income democracy with high political participation exploiting quasi experimental variation in fertility limits imposed on village council members in india to curb population growth we find that rural couples significantly decreased fertility in response socially disadvantaged families exhibit the greatest reduction in marginal fertility immediately following the passage of these limits but the decline in the long run stock of children is more evenly spread across socioeconomic groups the limits however also increased the already male biased sex ratio at birth in castes with strong son preference therefore while restricting access to elected office may aid in achieving social objectives it can also worsen inequality

the effects of integrating management judgement into intermittent demand forecasts empirical research suggests that quantitatively derived forecasts are very frequently judgementally adjusted nevertheless little work has been conducted to evaluate the performance of these judgemental adjustments in a practical demand sales context in addition the relevant analysis does not distinguish between slow and fast moving items currently there are neither conceptual developments nor empirical evidence on the issue of integrating judgements and statistical forecasts for slow intermittent demand items moreover no results have ever been reported on the stock control implications of these human judgements our work analyses monthly intermittent demand forecasts for the uk branch of a major international pharmaceutical company the company relies upon a commercially available statistical forecasting system to produce forecasts that are subsequently judgementally adjusted based on marketing intelligence gathered by the company forecasters the benefits of the intervention are evaluated by comparing the actual sales to system and final forecasts using both forecast accuracy and inventory control accuracy implication metrics our study allows insights to be gained on potential improvements to intermittent demand forecasting processes and subsequently the design effectiveness of forecasting support systems

optimal centralized ordering policies in multi echelon inventory systems with correlated demands this paper treats a depot warehouse system in which demand occurs at the warehouse or retail level this work differs from a number of other studies in that we allow item demands to be correlated both across warehouses and also correlated in time our motivation for this generalization arises from our experience with an actual system of this type used by a major national producer and distributor of consumer products we observed both high correlations between successive monthly demands around 0 7 and correlations between demands for an item at different locations also about 0 7 in a given time period we derive an explicit expression for the optimal safety stock as a function of the level of correlation through time the analysis requires two assumptions 1 the allocation assumption and 2 the equal coefficient of variation assumption similar assumptions have been used by other researchers finally numerical evaluations are included to illustrate the impact of the various magnitudes of correlation

the effects of integrating management judgement into out levels in or out of context physical inventories constitute a significant proportion of companies investments in today s competitive environment the trade off between customer service levels and inventory reserves is addressed in practice by statistical inventory software solutions given the tremendous number of stock keeping units skus that contemporary organizations deal with such solutions are fully automated however empirical evidence suggests that managers habitually judgementally adjust the output of such solutions such as replenishment orders or re order levels this research is concerned with the value being added or not when statistically derived inventory related decisions order up to out levels in particular are judgementally adjusted we aim at developing our current understanding on the effects of incorporating human judgement into inventory decisions to our knowledge such effects do not appear to have been studied empirically before and this is the first endeavour to do so a number of research questions are examined and a simulation experiment is performed using an extended database of approximately 1 800 skus from the electronics industry in order to evaluate human judgement effects the linkage between adjustments and their justification is also evaluated given the apparent lack of comprehensive empirical evidence in this area including the field of demand forecasting this is a contribution in its own right insights are offered to academics to facilitate further research in this area practitioners to enable more constructive intervention into statistical inventory solutions and software developers to consider the interface with human decision makers

managing inventory with multiple products lags in delivery resource constraints and lost sales a mathematical programming approach this paper develops an order up tos inventory model that is designed to handle multiple items resource constraints lags in delivery and lost sales without sacrificing computational simplicity mild conditions are shown to ensure that the expected average holding cost and the expected average shortage cost are separable convex functions of the order up to levels we develop nonparametric estimates of these costs and use them in conjunction with linear programming to produce what is termed the lp policy the lp policy has two major advantages over traditional methods first it can be computed in complex environments such as the one described above and second it does not require an explicit functional form of demand something that is difficult to specify accurately in practice in two numerical experiments designed so that optimal policies could be computed the lp policy fared well differing from the optimal profit by an average of 2 20 and 1 84 respectively these results compare quite favorably with the errors incurred in traditional methods when a correctly specified distribution uses estimated parameters our findings support the effectiveness of this mathematical programming technique for approximating complex real world inventory control problems

analysis of a q r t inventory policy with deterministic and random yields when future supply is uncertain abstract this paper considers a stochastic inventory model where the quantity ordered sometimes may not be available due to strikes etc we represent the supplier s availability process as a two state continuous time markov chain where one state corresponds to availability and the other state corresponds to unavailability of the supplier the problem is to determine the reorder point the order quantity when the system is found in on state and how long to wait before the next order if system is in off state it is assumed that the state of the system is identified at a cost using the renewal reward theorem we construct the objective function as the long run average cost numerical sensitivity analysis results are provided we also analyze the problem when the yield i e amount received if available is random and discuss an example with beta distributed yield

effects of correlation on intermittent demand forecasting and stock control abstract this study investigates the effects of three different types of correlation on forecasting and stock control of intermittent demand items applying appropriate forecasting and stock control methods to theoretically generated compound poisson demand data we show that correlation in intermittent demand does play a role in forecast quality and stock control performance negative autocorrelation levels lead to higher service levels than positive values while cost does not significantly change our results also show that high intermittency levels intensify these changes in service level we also show that cross correlation produces results in the opposite direction of autocorrelation in size or intervals that is positive negative cross correlation leads to higher lower service levels

lumpy demand forecasting using neural networks abstract the current study applies neural network nn modeling in forecasting lumpy demand it is to the best of our knowledge the first such study our study compares the performance of nn forecasts to those using three traditional time series methods single exponential smoothing croston s method and the syntetos boylan approximation we find nn models to generally perform better than the traditional methods using three different performance measures we also independently validate earlier findings that the syntetos boylan approximation performs better than the croston s and single exponential smoothing methods in lumpy demand forecasting

forecasting method for noisy demand abstract exponential smoothing methods are very commonly used for forecasting demand regarding the process of forecasting demand the main approach towards the selection and optimisation of alternative methods relates to the minimisation of forecast error measures such as the mean square error mse with regard to pegels classification of usage of proper forecasting methods hw methods additive and multiplicative are appropriate for demand with trend and seasonality which corresponds to b 2 and b 3 but hw methods are not accurate enough for demand with large noise that is often a property of real data in this paper we present improved an hw method for demand with noise and we demonstrate that a reduction in forecast error mse can be reached from the results we prove that the proposed method is more accurate than the existing ones and that it is the proper choice for forecasting noisy demand furthermore we show that essential reduction of supply chain costs can be achieved if we use improved the hw method for joined optimisation

electoral accountability and corruption evidence from the audits of local governments we show that political institutions affect corruption levels we use audit reports in brazil to construct new measures of political cor ruption in local governments and test whether electoral account ability affects the corruption practices of incumbent politicians we find significantly less corruption in municipalities where mayors can get reelected mayors with reelection incentives misappropriate 27 percent fewer resources than mayors without reelection incentives these effects are more pronounced among municipalities with less access to information and where the likelihood of judicial punish ment is lower overall our findings suggest that electoral rules that enhance political accountability play a crucial role in constraining politician s corrupt behavior jel d72 k42 017

schooling and labor market consequences of school construction in indonesia evidence from an unusual policy experiment between 1973 and 1978 the indonesian government engaged in one of the largest school construction programs on record combining differences across regions in the number of schools constructed with differences across cohorts induced by the timing of the program suggests that each primary school constructed per 1 000 children led to an average increase of 0 12 to 0 19 years of education as well as a 1 5 to 2 7 percent increase in wages this implies estimates of economic returns to education ranging from 6 8 to 10 6 percent

dynamic version of the economic lot size model this article originally appeared in management science october 1958 volume 5 number 1 pp 89 96 published by the institute of management sciences a forward algorithm for a solution to the following dynamic version of the economic lot size model is given allowing the possibility of demands for a single item inventory holding charges and setup costs to vary over n periods we desire a minimum total cost inventory management scheme which satisfies known demand in every period disjoint planning horizons are shown to be possible which eliminate the necessity of having data for the full n periods

on the empirical performance of t s s heuristics the periodic t s s policies have received considerable attention from the academic literature determination of the optimal parameters is computationally prohibitive and a number of heuristic procedures have been put forward however these heuristics have never been compared in an extensive empirical study such an investigation on 3055 skus is carried out in this paper our study provides insights into the performance of t s s heuristics also in relation to demand forecasting the results show that naddor s heuristic is best able to minimize the total cost however the normal and power approximations achieve more efficient solutions in that backorder volumes are smaller at the same inventory levels indicating the potentially superior performance of these methods if the balancing of holding and backorder costs can be improved the results also show that for all heuristics the sba variant of the croston forecasting method significantly outperforms croston as well as single exponential smoothing ses

adjustment policies and the real exchange rate in kenya since 1975 abstract we show using several proxies that the real exchange rate in kenya has moved in accordance with the dependent economy model since 1975 the adjustment policy supported by the international monetary fund imf in the first half of the 1980s led to a rise in the kenyan real exchange rate and an improvement of its external position macroeconomic policy since 1986 however has resulted in a deterioration of the external position and is likely to result in a reduction in the real exchange rate in the near future

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