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

decomposition analysis of co2 emission intensity between oil producing and non oil producing sub saharan african countries abstract the need to decompose co2 emission intensity is predicated upon the need for effective climate change mitigation and adaptation policies such analysis enables key variables that instigate co2 emission intensity to be identified while at the same time providing opportunities to verify the mitigation and adaptation capacities of countries however most co2 decomposition analysis has been conducted for the developed economies and little attention has been paid to sub saharan africa the need for such an analysis for ssa is overwhelming for several reasons firstly the region is amongst the most vulnerable to climate change secondly there are disparities in the amount and composition of energy consumption and the levels of economic growth and development in the region thus a decomposition analysis of co2 emission intensity for ssa affords the opportunity to identify key influencing variables and to see how they compare among countries in the region also attempts have been made to distinguish between oil and non oil producing ssa countries to this effect a comparative static analysis of co2 emission intensity for oil producing and non oil producing ssa countries for the periods 1971 1998 has been undertaken using the refined laspeyres decomposition model our analysis confirms the findings for other regions that co2 emission intensity is attributable to energy consumption intensity co2 emission coefficient of energy types and economic structure particularly co2 emission coefficient of energy use was found to exercise the most influence on co2 emission intensity for both oil and non oil producing sub saharan african countries in the first sub interval period of our investigation from 1971 1981 in the second subinterval of 1981 1991 energy intensity and structural effect were the two major influencing factors on emission intensity for the two groups of countries however energy intensity effect had the most pronounced impact on co2 emission intensity in non oil producing sub saharan african countries while the structural effect explained most of the increase in co2 emission intensity among the oil producing countries finally for the period 1991 1998 structural effect accounted for much of the decrease in intensity among non oil producers while co2 emission coefficient of energy use was the major force driving the decrease among oil producing countries the dynamic changes in the co2 emission intensity and energy intensity effects for the two groups of countries suggest that fuel switching had been predominantly towards more carbon intensive production in oil producing countries and less carbon intensive production in non oil producing ssa countries in addition to the decomposition analysis the article discusses policy implications of the results we hope that the information and analyses provided here would help inform national energy and climate policy makers in ssa of the relative weaknesses and possible areas of strategic emphasis in their planning processes for mitigating the effects of climate change

two dimensional efficiency decomposition to measure the demand effect in productivity analysis this paper proposes a two dimensional efficiency decomposition 2ded of profitability for a production system to account for the demand effect observed in productivity analysis the first dimension identifies four components of efficiency capacity design demand generation operations and demand consumption using network data envelopment analysis network dea the second dimension decomposes the efficiency measures and integrates them into a profitability efficiency framework thus each component s profitability change can be analyzed based on technical efficiency change scale efficiency change and allocative efficiency change an empirical study based on data from 2006 to 2008 for the us airline industry finds that the regress of productivity is mainly caused by a demand fluctuation in 2007 2008 rather than technical regression in production capabilities

energy metrics for driving competitiveness of countries energy weakness magnitude gdp per barrel and barrels per capita abstract energy metrics is the development of a whole new theoretical framework for the conception and measurement of energy and economic system performances energy efficiency and productivity improvements with important political economy implications consistent with the best use of all natural and economic resources the purpose of this research is to present some vital energy indicators based on magnitude and scale of energy weakness gdp per barrel of oil that is an indicator of energy productivity and barrels of oil per capita that is an indicator of energy efficiency energy metrics can support the monitoring of energy and economic system performances in order to design effective energy strategy and political economy interventions focused on the competitive advantage increase of countries in modern economies

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

productivity change in canadian mining 1957 1979 this paper calculates multifactor productivity trends in seven canadian mining industries and relates changes in productivity to various factors including changes in output and factor prices and the decline in the quality of the ore being mined it is found that productivity decline in mining has been pronounced and tended to predate that of manufacturing by several years there are indications that the most important factors in the decline have been the fall in mineral grade contraction of output increases in interest rates and an apparent decline in the rate of technical innovation

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

capital and the theory of productivity measurement the purpose of this paper is twofold to provide a brief survey of recent approaches to the measurement of total factor productivity and to comment on some of the special problems which are associated with capital thus in sections i iv below four approaches to the measurement of total factor productivity are outlined while section v compares and contrasts the approaches in section vi i consider how the various approaches have to be modified when welldefined rental markets for components of the capital stock do not exist the usual case

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 r q inventory policies with poisson demands and lost sales discounted and undiscounted cases abstract we consider a continuous review r q inventory system with poisson demands and at most one order outstanding the replenishment lead time is either constant or exponentially distributed demands not covered immediately from inventory are lost costs include a linear order cost with a fixed cost per order and a fixed cost per unit lost sale as regards inventory holding costs the cost of capital often constitutes a major part this paper focuses on these interest related holding costs in the undiscounted case holding costs are linear and inventory performance is measured by the long run average total cost incurred per unit time in the discounted case the performance measure is the expected present value of the ordering and lost sales costs the cost associated with capital tied up in inventory is accounted for by an appropriate discount rate we formulate an exact model and design a policy iteration algorithm for the discounted case results on the form of an optimal replenishment policy are derived and the model is compared to a previously derived model for the undiscounted case numerical experiments are used to evaluate the difference between the optimal solutions with and without discounting the effect of a stochastic lead time on this difference is also considered by comparing solutions with constant and exponential lead times in general the differences seem to be fairly small but exceptional cases exist when the service level is low

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

a utility based analysis of the wage subsidy program abstract because the poverty line is usually defined in terms of income two families may be classified as having poverty level incomes even though their hours of work and therefore their utilities may be very different this paper compares a government income support program that defines the poverty line in terms of utility with several other support programs that define the poverty line in terms of income through the use of the wage solution of the indirect utility function we find the amount of wage subsidy required to raise a subpoverty line family to the poverty line as defined by the utility function this subsidy is compared with wage subsidies based on directly observable quantities such as income

inventory policies for all or nothing demand processes abstract when there is insufficient stock to meet a specific customer order a common assumption is that the remaining stock will be used to satisfy the order partially while the balance of the order is backordered or lost this is the partial backorder or partial lost sales assumption in this paper we consider what happens when the nature of the demand process is such that orders must be met in full or not at all this is the all or nothing demand assumption we concentrate for the purpose of illustration on the context of a continuous review model with a poisson customer arrival rate with a fixed lead time and for which not more than one replenishment order may be outstanding at any time

tractable q r heuristic models for constrained service levels the fill rate the proportion of demand that is satisfied from stock is a viable alternative in inventory models to the hard to quantify penalty cost however a number of difficulties have impeded its implementation among them that the existing cycle based approximate solutions do not reflect the possibility of multiple outstanding orders and that the optimal policy cannot be found directly but must be iteratively calculated we show that for a large family of leadtime demand distributions the optimal policy depends on only two parameters the fill rate and the economic order quantity eoq scaled by the standard deviation of demand over the constant leadtime if we then assume that the leadtime demand is normally distributed we can use the asymptotic results as the eoq goes to zero and to positive infinity to fit atheoretic curves for the order quantity q and the reorder point r these fitted curves yield a good q r policy without iteration we also find that among the set of simple heuristics the limit form as eoq goes to positive infinity provides a better alternative to simply setting q equal to the eoq

optimal dynamic reinsurance policies under a generalized denneberg s absolute deviation principle abstract this paper studies the optimal dynamic reinsurance policy for an insurance company whose surplus is modeled by the diffusion approximation of the classical cramer lundberg model we assume the reinsurance premium is calculated according to a proposed mean cvar premium principle which generalizes denneberg s absolute deviation principle and expected value principle moreover we require that both ceded loss and retention functions are non decreasing to rule out moral hazard under the objective of minimizing the ruin probability we obtain the optimal reinsurance policy explicitly and we denote the resulting treaty as the dual excess of loss reinsurance this form of the optimal treaty is new to the literature and lends support to the fact that reinsurance contracts in practice often involve layers it also demonstrates that reinsurance treaties such as the proportional and the standard excess of loss which are typically found to be optimal in the dynamic reinsurance model need not be optimal when we consider a more general optimization model we also consider other generalizations including i allowing the insurer to manage its business through both reinsurance and investment and ii n piecewise mean cvar premium principle in the former case we not only show that the dual excess of loss reinsurance policy remains optimal but also demonstrate that investing in stock can further enhance insurer s financial stability with lower ruin probability for the latter case we establish that the optimal reinsurance treaty can have at most n layers which is also more consistent with practice

a nonparametric method to estimate a technical change effect on marginal abatement costs of u s coal power plants the literature usually assumes that technical change reduces marginal abatement cost however recent results suggest that precisely the opposite occurs this paper proposes a nonparametric method to determine the effect of technical change on marginal abatement cost the method decomposes nox marginal abatement cost changes in 2000 2004 and in 2004 2008 for 325 boilers operating in 134 u s bituminous coal power plant into technical and non technical change effects we find that technical change reduces the nox marginal cost about 28 3 in 2000 2004 and 26 5 in 2004 2008 however more stringent regulations enacted the nox budget program results in lower nox emission levels as plant operators install more advanced nox abatement equipment which in turn causes an overall increase in marginal abatement cost

when married men lose jobs income replacement within the family using matched file data from the january and march 1986 current population surveys the author estimates a model of earnings reduction and family income replacement in 1985 for a group of married men displaced from full time nonagricultural jobs the displacements which occurred between 1981 and 1984 resulted in substantial earnings losses for a large fraction of the sample husbands with earnings losses had higher levels of spouse earnings and income transfers in 1985 than the control group of non displaced husbands but the fraction of lost earnings replaced was not large on average the author concludes that long term trends in both the nature of the experience of displaced workers and the structure of the family economy call for reconsideration of traditional family adjustment mechanisms

quasi fixed cyclic production schemes for multiple products with stochastic demand abstract in this paper we present an approach to generate cyclic production schemes for multiple products with stochastic demand to be produced on a single production unit this scheme specifies a fixed and periodic production sequence called a cycle where each product may occur more than once in the sequence in order to stabilize the cycle length alternative control strategies are introduced these strategies keep the cycle length close to a target length by means of adding idle time to the cycle cutting production short or overproduction on basis of the selected control strategy as well as a base stock policy target inventory levels are determined for each production run in the cycle demand can be backlogged but a certain service level is required setup times are sequence dependent and the storage is capacitated employing the developed strategies we investigate the tradeoff between stability of cycle length and total cost induced by the production schedule in a computational study based on both real world data and random test instances

unemployment and the inter regional mobility of labour the relationship between unemployment and interregional labor migration in the united kingdom is explored using data from the labour force survey for 1984 and 1977 the authors conclude that the experience of unemployment increases the likelihood of migration and that households in areas of high unemployment are more likely to move they also find that during periods of higher overall unemployment migration propensities are reduced annotation

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

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

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

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

transport and co2 productivity growth and carbon dioxide emissions in the european commercial transport industry in the last decades transport activities persistently increased in the eu27 and were strongly coupled to growth in gross domestic product like most production processes they are inevitably linked with the generation of environmentally hazardous by products such as co2 emissions this leads to the question of how to promote a sustainable transport sector that meets both environmental protection targets and economic requirements in this context the objective of this paper is to compare the co2 sensitve productivity development of the european commercial transport industry for the period between 1995 and 2006 we calculate a malmquist luenberger productivity index to investigate the effects of country specific regulations on productivity and to identify innovative countries our results show a high variation in the co2 sensitive productivity development and a slight productivity decrease on average efficiency losses indicate that the majority of the countries were not able to follow the technological improvements induced by some innovative countries

wage curve evidence from panel data abstract we examine the us wage curve using longitudinal micro data results support the wage curve but are sensitive to inclusion of regional and or personal fixed effects we find that hourly wages are less responsive to local unemployment than annual earnings

technological change in illinois agriculture 1982 1984 abstract this paper has two main purposes 1 to develop a method for measuring the extent and bias of technical change which involves the use of non parametric production frontiers and does not require information on prices or factor shares 2 to apply this method to individual farm data drawn from a sample of illinois grain farms for the years 1982 and 1984 the results indicate that technical innovation is land using in nature and that the rate of technical change is related to the size of farm

robustness of order up to policies in lost sales inventory systems we study an inventory system under periodic review when excess demand is lost it is known huh et al 2009 that the best base stock policy is asymptotically optimal as the lost sales penalty cost parameter grows we now show that this result is robust in the following sense consider the base stock level which is optimal in a backordering system with a per unit per period backordering cost in which the backorder cost parameter is a function of the lost sales parameter in the original system then there is a large family of functions mapping the lost sales cost parameter to the backorder cost parameter such that the resulting base stock policy is asymptotically optimal we also demonstrate the robustness phenomenon through a second result we consider the base stock level which is optimal in a backordering system in which a unit of backorder is charged a penalty cost only once such a system has been studied by rosling we show that this base stock policy is also asymptotically optimal furthermore we show that a modification suggested by archibald of this base stock level also results in an asymptotically optimal policy finally we numerically test the performance of this heuristic policy for a wide spectrum of values for the lost sales penalty cost parameter and illustrate the superior performance of archibald s method

another look at estimators for intermittent demand abstract in this paper we focus on forecasting for intermittent demand data we propose a new aggregation framework for intermittent demand forecasting that performs aggregation over the demand volumes in contrast to the standard framework that employs temporal over time aggregation to achieve this we construct a transformed time series the inverse intermittent demand series the new algorithm is expected to work best on erratic and lumpy demand as a result of the variance reduction of the non zero demands the improvement in forecasting performance is empirically demonstrated through an extensive evaluation in more than 8000 time series of two well researched spare parts data sets from the automotive and defence sectors furthermore a simulation is performed so as to provide a stock control evaluation the proposed framework could find popularity among practitioners given its suitability when dealing with clump sizes as such it could be used in conjunction with existing popular forecasting methods for intermittent demand as an exception handling mechanism when certain types of demand are observed

regional and sectoral attribution to percentage changes in the european divisia carbonization index abstract concerns on rising concentrations of co2 in the atmosphere and global warming have increased in recent years numerous environmental studies analyze the trends in co2 emissions and their main drivers in this paper we focus on the dynamics of the carbonization effect as a driving force for co2 emissions in the european union eu by implementing the sato vartia logarithmic mean divisia index method the trend of european emissions in the 2000 2010 period is factorized by both sector and country the analysis stresses the relevance of the carbonization and intensity effects in order to reduce emissions then based on so called attribution analysis we present a new theoretical framework that enables the attribution of both economic sector and individual eu member state to percentage changes in the carbonization index results show strong concentration of this reducing influence in some big economies in fact germany the united kingdom france and italy have contributed by more than 50 industry emerges as the most influential sector contributing to offset any improvement in the carbonization index our findings suggest strategies aiming at encouraging innovation technical change research on higher quality energies fuel substitution and installation of abatement technologies particularly in the industrial sector of large economies

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

the multi sourcing location inventory problem with stochastic demand abstract this paper deals with a multi period location inventory optimization problem in a multi echelon supply chain network characterized by an uncertain demand and a multi sourcing feature the aim of the paper is to propose a generic modeling approach to integrate key features of the inventory planning decisions made under a reorder point order up to level s s policy with the location allocation design decisions to cope with demand uncertainty given the hierarchical structure of the problem a two stage stochastic mathematical model that maximizes the total expected supply chain network profit is proposed this optimization model is intractable due to its non linearity therefore a linear approximation is proposed and a sample average approximation approach is used to produce near optimal solutions numerical experiments are conducted to validate the proposed modeling and solution approaches the results show the efficiency of the linear approximation of the s s policy at the strategic level to produce robust design solutions under uncertainty they underline the sensitivity of the design solution to the demand type and the impact of the inventory holding costs and backorder costs especially under non stationary processes

intermittent demand forecasting an empirical study on accuracy and the risk of obsolescence intermittent demand items account collectively for considerable proportions of the total stock value of any organization forecasting the relevant inventory requirements constitutes a very difficult task and most work in this area is based on croston s estimator that relies upon exponentially smoothed demand sizes and inter demand intervals this method has been shown to be biased and a number of variants have been introduced in the literature including the recently proposed tsb method that updates the demand probability instead of the demand interval and in doing so reacts faster to decreasing demand the tsb has been shown theoretically to be unbiased for all points in time but its empirical performance has not been investigated yet and this constitutes one of the objectives of our work more generally we explore the empirical performance of forecasting methods used in an intermittent demand context paying particular attention to the effects and implications of the smoothing constant values employed for updating purposes we do so by means of experimentation on large empirical datasets from the military sector and automotive industry the results enable insights to be gained into the sensitivity of the various methods forecasting and stock control performance to the smoothing constant values used the paper concludes with an agenda for further research

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

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

spare parts management linking distributional assumptions to demand classification spare parts are known to be associated with intermittent demand patterns and such patterns cause considerable problems with regards to forecasting and stock control due to their compound nature that renders the normality assumption invalid compound distributions have been used to model intermittent demand patterns there is however a lack of theoretical analysis and little relevant empirical evidence in support of these distributions in this paper we conduct a detailed empirical investigation on the goodness of fit of various compound poisson distributions and we develop a distribution based demand classification scheme the validity of which is also assessed in empirical terms our empirical investigation provides evidence in support of certain demand distributions and the work described in this paper should facilitate the task of selecting such distributions in a real world spare parts inventory context an extensive discussion on parameter estimation related difficulties in this area is also provided

how different are the british in their willingness to move evidence from international social survey data drinkwater s and ingram p how different are the british in their willingness to move evidence from international social survey data regional studies this paper analyses people s willingness to move using data from the 1995 british social attitudes survey and international social survey programme the personal characteristics and sub regional indicators that are important in explaining the willingness to move within britain are identified it is also found that the willingness to move is only higher in a few other countries including the usa the equivalent desire to move is found to be much lower in eastern european countries and in several other european union member states compositional effects such as age and education are generally important in explaining differences in attitudes towards migration in comparison with other western economies however structural effects such as institutions history and culture tend to play a more dominant role in explaining differences compared with countries

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

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

operating characteristics of the s 1 s inventory system with partial backorders and constant resupply times in this paper we consider an s 1 s inventory system with poisson demand and constant resupply times an arriving customer facing stockout will either backorder or withdraw its order expressions describing steady state operating characteristics of the system and the expected total cost rate are developed furthermore the behavior of the expected total cost rate as the function of the relevant parameters is explored

technical note linear inflation rules for the random yield problem analysis and computations in this paper we propose a simple heuristic approach for the inventory control problem with stochastic demand and multiplicative random yield our heuristic tries to find the best candidate within a class of policies that are referred to in the literature as the linear inflation rule lir policies our approach is computationally fast easy to implement and intuitive to understand moreover we find that in a significant number of instances our heuristic performs better than several other well known heuristics that are available in the literature

human capital and convergence a production frontier approach using nonparametric production frontier methods we decompose labor productivity growth into components attributable to technological change shifts in the world production frontier technological catch up movements toward or away from the frontier and physical and human capital accumulation movements along the frontier we find that 1 technological change is decidedly nonneutral 2 productivity growth is driven primarily by physical and human capital accumulation 3 the increased international dispersion of productivity is explained primarily by physical capital accumulation and 4 international polarization the shift from a unimodal to a bimodal distribution is brought about primarily by efficiency changes technological catch up

aggregation of price risk over commodities an economic index number approach this article extends the economic theory of index numbers to the aggregation of price risk over commodities in production superlative indexes of aggregate price risk are related to tornqvist and fisher type output quantity indexes an application to major crops in manitoba illustrates the empirical importance of the analysis

how flexible are wages in response to local unemployment in south africa it is commonly claimed that the south african labor market is unusually inflexible owing to the strength of the country s unions and the system of centralized collective bargaining one sign of labor market inflexibility is low responsiveness of wages to local unemployment analyzing data from the south african living standards survey the authors find that the elasticity of wages with respect to local unemployment rates in south africa in 1993 was about 0 1 the similarity of this elasticity to that found in other countries including the united states and the united kingdom is surprising given south africa s national unemployment rate of over 30 the wage curve elasticity persists over a much wider range of unemployment rates in south africa than in oecd countries implying that unemployment in south africa can have a large impact on wages

inventory models with minimal service level constraints abstract this paper investigates inventory models in which the stockout cost is replaced by a minimal service level constraint slc that requires a certain level of service to be met in every period the minimal service level approach has the virtue of simplifying the computation of an optimal ordering policy because the optimal reorder level is solely determined by the minimal slc and demand distributions it is found that above a certain critical service level the optimal s s policy collapses to a simple base stock or order up to level policy which is independent on the cost parameters this shows the minimal slc models to be qualitatively different from their shortage cost counterparts we also demonstrate that the imputed shortage cost transforming a minimal slc model to a shortage cost model does not generally exist the minimal slc approach is extended to models with negligible set up costs the optimality of myopic base stock policies is established under mild conditions

demand forecasting with four parameter exponential smoothing abstract exponential smoothing methods are powerful tools for denoising time series predicting future demand and decreasing inventory costs in this paper we develop a smoothing and forecasting method that is intuitive easy to implement computationally stable and can satisfactorily handle both additive and multiplicative seasonality even when time series contain several zero entries and large noise component we start with the classical additive holt winters method and introduce an additional smoothing parameter in the level recurrence equation all parameters are required to lie within 0 1 and estimated by minimizing the one step ahead forecasting errors in the sample doing so the errors decrease substantially especially for the time series with strong trends the newly developed method produces more accurate short term out of sample forecasts than the classical holt winters methods and the holt winters methods with damped trend the performance of the method is evaluated using a battery of real quarterly and monthly time series from the m3 competition a simulation study is conducted for further in depth analysis of the method under different demand patterns we developed and justified the use of a symmetric relative efficiency measure that allows researchers ad practitioners to evaluate the performance of different smoothing and forecasting methods

british unemployment letter from america this paper asks whether there are any lessons to be learned about unemployment in britain from the united states experience the fundamental issues to be addressed are embodied in data showing that the relative unemployment performance of britain and the united states reversed itself between the i9g6os and the i98os in the early i960s the unemployment rate in britain averaged i 9 about one third that in the united states in the late i 980s the unemployment rate in britain at 9 5 was more than one and a half times higher than that in the united states the paper examines reasons for this the immediate candidates as explanations for these facts are the changing priorities of government macroeconomic policies governments in the past fifteen years have placed greater weight on minimising price inflation and considerably less weight on reducing unemployment than they did four decades ago this is because governments have been persuaded that their unemployment goals entailed not a constant but an accelerating rate of price inflation hence they have pursued policies that have been aimed first at reducing the rate of price inflation and then at maintaining a constant low rate of inflation however government macroeconomic policies appear more relevant as an explanation for movements in unemployment over the business cycle than as an explanation for the upward trend in unemployment over four decades and the distinctive feature of britain s unemployment is that it increased continually over each five year interval from the first half of the i 950s to the first half of the i98os what is needed are explanations directed not toward cyclical factors but toward the trend

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

the determinants of individual unemployment durations in an era of high unemployment this paper presents the results of an econometric analysis of the conditional probability of leaving unemployment for two male inflow cohorts entering unemployment at very different points in time 1978 and 1987 the effect of income while unemployed is found to be much weaker for the i987 cohort an elasticity of o i compared with 0 4 and is only found to be significant for teenagers and in the first three months of a spell demand constraints measured by the local unemployment rate are found to have a stronger negative effect on the exit probability for the i987 cohort than in 1978 the i 980s witnessed continual high levels of unemployment in britain and the movement of unemployment up the economic and political agenda unemployment results in major output and income losses and is the cause of much misery to those involved the nation is poorer because of it for both reasons it is therefore important to understand the process that generates a given level of unemployment this process can be considered in terms of two key probabilities the probability of an individual entering unemployment and the probability of an unemployed individual leaving unemployment to take up a job or for other reasons these probabilities will vary with the characteristics of the individual concerned and over time changes in the aggregate unemployment rate can under certain assumptions be decomposed into changes in the inflow rate into unemployment and changes in the steady

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

productivity and technical change the case of taiwan this paper analyses productivity growth in 16 of taiwan s manufacturing industries during the period 1978 1992 the non parametric data envelopment analysis approach is used to compute malmquist productivity indexes these are decomposed into efficiency change and technical change the latter is further decomposed into an output bias an input bias and a magnitude component in addition the direction of input bias is identified empirical results indicate that the sector s tfp increased at a rate of 2 89 per annum which could be ascribed to a technical progress 2 56 and an efficiency improvement 0 33

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

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

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

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

inventory control with generalized expediting we consider a single item periodic review inventory control problem in which discrete stochastic demand must be satisfied when shortages occur the unmet demand must be filled by some form of expediting we allow a very general form for the cost structure of expediting we explicitly consider the case where expedited production is allowed to produce up to a positive inventory level we also consider the case where expedited production beyond the deficit is not permitted an alternate application for this model is an inventory system with general lost sales costs for the infinite horizon discounted problem we characterize the structure of the optimal stationary expediting policy and show that an s s policy is optimal for regular production for the special cases where the expediting cost function is concave or consists of a fixed and linear per unit cost we show that the optimal stationary expediting policy is generalized s s or order up to respectively a numerical study allows us to gain insight into when expediting above and beyond the deficit is cost effective

approximations for the relative outdating of perishable products by combining stochastic modeling simulation and regression modeling abstract in this paper we derive approximations for the expected amount of outdating waste in an inventory system with perishable products periodic review positive lead time fixed case pack sizes and a first in first out withdrawal policy demand is discrete and stochastic demand which is not met from inventory on hand will be lost the approximations can be used to evaluate how the amount of outdating can be reduced by changing the safety stock and or the product and demand characteristics we first derive approximations in an analytical way and then use regression to improve these approximations the final approximation is very fast and performs very well the mean and standard deviation of the approximation error are equal to 0 01 and 0 78 moreover the approximation is applicable in situations with parameter settings which are frequently encountered in practice and for which no other approximations have been derived in the literature before

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

comment on b holmlund unemployment insurance in theory and practice holmlund s exposition on the development of the economic analysis of unemployment insurance is well balanced it covers theoretical contributions micro and macro as well as analyses of the welfare and political economy aspects of unemployment insurance empirical evidence is also reported as mentioned by holmlund this evidence is rather mixed and does not give any unambiguous support to the conclusions derived in theory say between unemployment insurance and unemployment duration my comments go a little further than holmlund s exposition in emphasizing the mixed character of the empirical evidence

growth and convergence of the oecd countries a multi sector production frontier approach abstract kumar and russell 2002 henderson and russell 2005 and badunenko henderson and russell 2013 have proposed a production frontier methodology to analyze the economic growth and the convergence of growth rates across countries they see two main advantages to this methodology 1 it reconstructs the world production frontier without relying on any particular typically unverifiable assumptions on any aspects of the growth process and 2 it allows to decompose labor productivity growth into several parts in this paper i extend the previous approach by considering a multi sector setting this setting allows to propose a more realistic and complete country level analysis while keeping the same advantages as with the previous methodology i also tackle the criticism of less reliable data at the sector level than at the country level by showing how the multi sector approach can easily be adapted i apply it to the oecd countries from 1995 to 2008 the results confirm the non neutrality of technological change i also find that capital accumulation plays the biggest role in the increase of output labor productivity while technological change and human capital accumulation also play an important role but it is twice as small as capital accumulation interestingly these results suggest the emergence of two groups eastern and central european countries and the eu15 and korea the two groups seem to diverge over time

employment status and the decision to migrate the purpose of this paper is to examine the demographic and socioeconomic determinants of migration for both the employed and unemployed hypotheses concerning the effects of age education and public services are developed and tested using data on interstate migration of the u s labor force from 1965 to 1970 for individuals at risk to either primary or repeat migration the age and education selectivity of migration were in general confirmed however for unemployed potential primary migrants education selectivity was not observed it was also found that the provision of welfare services have little or no impact on the migration decision of the unemployed however unemployment was shown to significantly affect the role played by educational quality and training accessibility within the migration decision excerpt