forecasting aggregate demand an analytical evaluation of top down versus bottom up forecasting in a production planning framework abstract we study the relative effectiveness of top down td and bottom up bu strategies for forecasting the aggregate demand in a production planning framework the aggregate demand series is composed of several correlated subaggregate components or items each of which is assumed to follow a stationary time series process which is correlated over time as is common in a production planning environment it is assumed that exponential smoothing is used as the forecasting technique under both strategies we analytically show that there is no difference in the relative performance of td and bu forecasting strategies when the time series for all of the subaggregate components follow a first order univariate moving average ma 1 process with identical coefficients of the serial correlation term we then perform a simulation study to examine the case when the coefficients of the serial correlation term for the subaggregate components are not identical it is found from the simulation study that the difference in the performance of the two forecasting strategies is relatively insignificant when the correlation between the subaggregate components is small or moderate

the future of natural gas consumption in beijing guangdong and shanghai an assessment utilizing markal natural gas could possibly become a si0gnificant portion of the future fuel mix in china however there is still great uncertainty surrounding the size of this potential market and therefore its impact on the global gas trade in order to identify some of the important factors that might drive natural gas consumption in key demand areas in china we focus on three regions beijing guangdong and shanghai using the economic optimization model markal we initially assume that the drivers are government mandates of emissions standards reform of the chinese financial structure the price and available supply of natural gas and the rate of penetration of advanced power generating and end use the results from the model show that the level of natural gas consumption is most sensitive to policy scenarios which strictly limit so2 emissions from power plants the model also revealed that the low cost of capital for power plants in china boosts the economic viability of capital intensive coal fired plants this suggests that reform within the financial sector could be a lever for encouraging increased natural gas use

issues involved with the seasonal adjustment of economic time series in the first part of this article we briefly review the history of seasonal adjustment and statistical time series analysis in order to understand why seasonal adjustment methods have evolved into their present form this review provides insight into some of the problems that must be addressed by seasonal adjustment procedures and points out that advances in modem time series analysis raise the question of whether seasonal adjustment should be performed at all this in turn leads to a discussion in the second part of issues involved in seasonal adjustment we state our opinions about the issues raised and review some of the work of other authors first we comment on reasons that have been given for doing seasonal adjustment and suggest a new possible justification we then emphasize the need to define precisely the seasonal and nonseasonal components and offer our definitions finally we discuss criteria for evaluating seasonal adjustments we contend that proposed criteria based on empirical compariso

impacts of crisis events on international tourism demand in thailand in thai this study assesses the impacts of nine major crisis events during 2001 2009 on the number of foreign tourists in thailand the sarima with intervention models and x 12 arima are applied the results show that each crisis had a different effect on the number of tourists depending on the duration of situation type of crisis and country of origin the disease outbreaks had a greater impact than the other crises but the degree of impact was likely to decrease should a similar outbreak occurs in contrast the impact from the internal political chaos was relatively small when it occurred for the first time but would be greater if it recurred the indian ocean tsunami of 2004 had a huge impact but recovery was faster than that of other crises the 9 11 event made a minimal impact on thai tourism based on the results it is suggested that solving the internal politics should be the first priority if government aims to enhance thailand s tourism industry in addition the measures used for solving crises should be designed to fit each foreign tourist markets diverse responsiveness

modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention abstract this paper presents the use of time series sarima and marima with interventions in forecasting tourism demand using ten arrival series for hong kong augmented dickey fuller tests indicated that all the series were seasonal nonstationary significant interventions such as relaxation of the issuance of out bound visitors visas the asian financial crisis the handover and the bird flu epidemic were all empirically identified with significant test results and expected signs the forecasts obtained using models that capture stochastic nonstationary seasonality and interventions sarima and marima with intervention analysis are compared with other eight time series models and were found to have the highest accuracy

forecasting u s tourist arrivals using optimal singular spectrum analysis this study examines the potential advantages of using singular spectrum analysis ssa for forecasting tourism demand to do this it examines the performance of ssa forecasts using monthly data for tourist arrivals into the unites states over the period 1996 to 2012 the ssa forecasts are compared to those from a range of other forecasting approaches previously used to forecast tourism demand these include arima exponential smoothing and neural networks the results presented show that the ssa approach produces forecasts which perform statistically significantly better than the alternative methods in forecasting total tourist arrivals into the u s forecasts using the ssa approach are also shown to offer a significantly better forecasting performance for arrivals into the u s from individual source countries of the alternative forecasting approaches exponential smoothing and feed forward neural networks in particular were found to perform poorly the key conclusion is that singular spectrum analysis ssa offers significant advantages in forecasting tourist arrivals into the us and is worthy of consideration for other forecasting studies of tourism demand

forecasting the impact of renewable energies in competition with non renewable sources abstract the diffusion dynamics of traditional and clean energy systems in the energy mix are studied in a competition modeling where their interacting life cycles are jointly described competition has only been considered recently since diffusion competition models are not easy to be implemented data are represented by yearly consumptions in mtoe of traditional sources coal oil gas and nuclear systems and a selection of renewable sources hydroelectric wind and solar power for the us europe china and india from 1965 to 2014 for each case we will investigate whether the diffusion level of traditional sources sustains or prevents the spread of renewables and vice versa for the us and europe we will take into account the link between the 2008 2009 financial crisis and the slowdown in consumptions as a matter of fact the energy sector is characterized by uncertainty due to the depletion of finite energy sources the technological and economical problems of renewables and the hypothesis of shale gas as a possible bridge to renewables that could delay the spread of latter ones in this scenario six year forecasts are provided until 2020

nonlinear production path and an alternative reserves estimate for south asian natural gas abstract natural gas is a finite resource that may be estimated directly through geophysical methodologies or indirectly through historical production data the rapid growth in consumption of this limited natural resource strictly connected to the oil economy may lead to its imminent depletion and a related economic crisis the transition to a new economy based on renewable and sustainable energy resources is a crucial challenge for the next decades at world and regional levels with different dynamics therefore an accurate forecast of the availability of natural gas is important to ensure a sustainable energy policy providing essential information about the timing of this transition postulating a finite life cycle of recoverable resources in this paper we investigate the natural gas production of four neighboring south asian states bangladesh india myanmar and pakistan we use a number of homogeneous diffusion models with convenient extensions and check the model validation in terms of prediction capability the results indicate that india and myanmar have already extracted more than 50 of their ultimately recoverable natural gas resources urr whereas good prospects for natural gas extraction remain in the near future for bangladesh and pakistan the four neighboring asian states can build a sustainable power reserve system for natural gas to meet their increasing demand within a medium term horizon some further policy implications are also suggested in this paper

the german energy transition modeling competition and substitution between nuclear power and renewable energy technologies abstract this paper studies some quantitative aspects of the energy transition in germany the energiewende which envisages the complete abandonment of nuclear power and a strong reliance on photovoltaic and wind energy for electricity provision the major aim is to shed light on and measure with indirect tools the possible social effects on competition and substitution dynamics characterizing such transition in doing so an analysis on the innovation diffusion framework is proposed through the application of two diffusion models for a duopolistic competition unrestricted and standard ucrcd to the annual time series of consumption of nuclear and renewables wind and solar energy in germany in order to test empirically the presence of such substitution effect the obtained results confirm this conjecture and show that renewables have exerted a significant and measurable effect in determining the observed decline of nuclear power consumption in particular we find that the diffusion of renewables wind and solar is characterized by a high within word of mouth testifying the widespread belief of germans towards the energy transition while the parallel diffusion of nuclear power is characterized by a highly negative cross word of mouth due to the competing role exerted by renewables

modeling and forecasting natural gas demand in bangladesh natural gas is the major indigenous source of energy in bangladesh and accounts for almost one half of all primary energy used in the country per capita and total energy use in bangladesh is still very small and it is important to understand how energy and natural gas demand will evolve in the future we develop a dynamic econometric model to understand the natural gas demand in bangladesh both in the national level and also for a few sub sectors our demand model shows large long run income elasticity around 1 5 for aggregate demand for natural gas forecasts into the future also show a larger demand in the future than predicted by various national and multilateral organizations even then it is possible that our forecasts could still be at the lower end of the future energy demand price response was statistically not different from zero indicating that prices are possibly too low and that there is a large suppressed demand for natural gas in the country

optimal cartel trigger price strategies abstract a dynamical model of industry equilibrium is described in which a cartel deters deviations from collusive output levels by threatening to produce at cournot quantities for a period of fixed duration whenever the market price falls below some trigger price in this model firms can observe only their own production level and a common market price the market demand curve is assumed to have a stochastic component so that an unexpectedly low price may signal either deviations from collusive output levels or a downward demand shock

a fractionally integrated autoregressive moving average approach to forecasting tourism demand the primary aim of this paper is to incorporate fractionally integrated arma p d q arfima models into tourism forecasting and to compare the accuracy of forecasts with those obtained by previous studies the models are estimated using the volume of monthly international tourist arrivals in singapore empirical findings demonstrate the evidence that the approach we propose generates relatively lower sample mean absolute percentage errors mapes this study also deals with the volatile data faced by a forecaster we use the asian financial crisis and the september 11 event as examples of economic and political shocks with respect to the objective of shaving the coefficient mape forecasts based on the selected arfima models dominate convincingly

non stationary demand forecasting by cross sectional aggregation in this paper the relative effectiveness of top down td versus bottom up bu approaches is compared for cross sectionally forecasting aggregate and sub aggregate demand we assume that the sub aggregate demand follows a non stationary integrated moving average ima process of order one and a single exponential smoothing ses procedure is used to extrapolate future requirements such demand processes are often encountered in practice and ses is one of the standard estimators used in industry in addition to being the optimal estimator for an ima process theoretical variances of forecast error are derived for the bu and td approach in order to contrast the relevant forecasting performances the theoretical analysis is supported by an extensive numerical investigation at both the aggregate and sub aggregate level in addition to empirically validating our findings on a real dataset from a european superstore the results demonstrate the increased benefit resulting from cross sectional forecasting in a non stationary environment than in a stationary one valuable insights are offered to demand planners and the paper closes with an agenda for further research in this area

multiple items procurement under stochastic nonstationary demands abstract in the consumer goods wholesaling and retailing industry a large number of stock keeping units must be managed on a regular basis the items are typically purchased in families each family being associated with a specific external vendor and usually there are some constraints on family order quantities and there are frequent opportunities to buy at a temporary low price the demand for an item is often stochastic and not stationary in this paper by computing procurement plans over rolling planning horizons we transform this difficult sequential decision problem into a multi period static decision problem under risk the problem is initially formulated as a stochastic program with simple recourse and a branch and bound algorithm is designed to solve an equivalent deterministic program a piecewise concave approximation is proposed to reduce this program to a linear program with one 0 1 variable per planning period the performances of the algorithms are studied in two simulation experiments the simulations show that when planning over a rolling horizon the approach proposed yields excellent results

the folk theorem with imperfect public information the authors study repeated games in which players observe a public outcome that imperfectly signals the actions played they provide conditions guaranteeing that any feasible individually rational payoff vector of the stage game can arise as a perfect equilibrium of the repeated game with sufficiently little discounting the central condition requires that there exist action profiles with the property that for any two players no two deviations one by either player give rise to the same probability distribution over public outcomes the results apply to principal agent partnership oligopoly and mechanism design models and to one shot games with transferable utilities copyright 1994 by the econometric society

long term forecasting of natural gas production abstract natural gas is an important energy source for power generation a chemical feedstock and residential usage it is important to analyse the future production of conventional and unconventional natural gas analysis of the literature determined conventional urr estimates of 10 700 18 300 ej and the unconventional gas urr estimates were determined to be 4250 11 000 ej six scenarios were assumed with three static where demand and supply do not interact and three dynamic where it does the projections indicate that world natural gas production will peak between 2025 and 2066 at 140 217 ej y 133 206 tcf y natural gas resources are more abundant than some of the literature indicates

retracted factors affecting commercial energy consumption in pakistan progress in energy the purpose of this study is to identify major macroeconomic factors that enhance energy consumption for pakistan through the cointegration error correction model and granger causality tests over a 32 year time period i e between 1980 and 2011 the study employed the bivariate cointegration technique to estimate the long run relationship between the variables an error correction model was used to determine the short run dynamics of the system while granger causality test was used to find the directions between these variables the study investigates the relation between four energy consumption variables i e oil petroleum consumption gas consumption electricity consumption and coal consumption and four macroeconomic factors which have further sub classifications i e balance of payment bop factors i e exports imports trade deficit worker s remittances and current account balance fuel factors i e carbon dioxide emissions natural resource depletion and net forest depletion agricultural crops yield per hectare i e wheat rice sugarcane maize and cotton and industrial production items i e beverages cigarettes motor tyres motor tubes cycle tyres and cycle tubes in order to manage robust data analysis the result confirms the long run relationship between total commercial energy consumption and macroeconomic factors in pakistan as oil petroleum consumption increases exports fuel factors agricultural crops yield per hectare and industrial items however the intensity of these factors are different in nature carbon dioxide emissions net forest depletion beverages motor tyres and motor tubes are more elastic with oil petroleum consumption however oil petroleum consumption decreases trade deficit and workers remittances in pakistan gas electricity and coal consumption increases agricultural crops yield per hectare and industrial production which shows that as agriculture and industry modernizes energy demand increases energizing the food production chain is an essential feature of agricultural development which is a prime factor in helping to achieve food security in pakistan the empirical results only moderately support the conventional view that energy consumption has significant long run casual effect on macroeconomic variables in pakistan the present study finds evident of unidirectional causality between the commercial energy consumption factors and macroeconomic factors in pakistan however there is some bidirectional causality exist which is running between electricity consumption ec and exports ec to imports ec to carbon emissions ec to natural resource depletion nrd and ec to wheat the results conclude that macroeconomic variables tend to positively respond to total primary energy consumption this indicates that increasing total commercial energy consumption may cause growth variables which show that pakistan is an input driven economy

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

yearly monthly and weekly seasonality of tourism demand a decomposition analysis abstract annual seasonal variations in tourism demand have been a central theme in literature however annual seasonality is not the only time based inequality in tourism flows that has important implications on policy making decisions at destinations within the context of tourism this study aims to make an in depth analysis of intra monthly and intra weekly tourism demand using the entropy and relative redundancy measures as alternative seasonality indicators to the gini coefficient in order to provide new tools to manage tourism and propose new action policies at these frequencies in comparison with the gini coefficient the entropy measure is simpler to compute and it is easily decomposable using the case study of air arrivals and departures to and from the balearic islands results show the appropriateness of entropy and relative redundancy as seasonal indicators but also as a new information tools for tourism seasonality analysis

forecasting natural gas supply in china production peak and import trends china s natural gas consumption has increased rapidly in recent years making china a net gas importer as a nonrenewable energy the gas resource is exhaustible based on the forecast of this article china s gas production peak is likely to approach in 2022 however china is currently in the industrialization and urbanization stage and its natural gas consumption will persistently increase with china s gas production peak china will have to face a massive expansion in gas imports as the largest developing country china s massive imports of gas will have an effect on the international gas market in addition as china s natural gas price is still controlled by the government and has remained at a low level the massive imports of higher priced gas will exert great pressure on china s gas price reform

optimal cartel equilibria with imperfect monitoring abstract there exist optimal symmetric equilibria in the green porter model 4 8 having an elementary intertemporal structure such an equilibrium is described entirely by two subsets of price space and two quantities the only production levels used by firms in any contingency the central technique employed in the analysis is the reduction of the repeated game to a family of static games

the seasonal cycle and the business cycle almost all recent research on macroeconomic fluctuations has worked with seasonally adjusted or annual data this paper takes a different approach by treating seasonal fluctuations as worthy of study in their own right our results show that seasonal fluctuations are an important source of variation in all macroeconomic quantity variables but are small or entirely absent in both real and nominal price variables the timing of the seasonal fluctuations consists of increases in the second and fourth quarters a large decrease in the first quarter and a mild decrease in the third quarter the paper demonstrates that with respect to each of several major stylized facts about business cycles the seasonal cycle displays the same characteristics as the business cycle in some cases even more dramatically than the business cycle that is we find that at seasonal frequencies as well as at business cycle frequencies output movements across broadly defined sectors move together the timing of production and the

forecasting tourism demand with arma based methods abstract the forecast of tourism volume in the form of arrivals is of special importance for tourism and other hospitality industries because it is an indicator of future demand thereby providing basic information for subsequent planning and policy making in this paper three univariate arma based models are applied to tourism demand as represented by the number of world wide visitors to hong kong japan korea taiwan singapore thailand the philippines australia and new zealand the study employs both monthly and quarterly time series generated from nine principal tourist destinations in asian pacific region in the forecasting exercise to ensure the reliability of the forecasting evaluation forecasting performance based on disaggregated arrival series in a particular destination is examined as well the general impression is that the arma based models perform very well and in some cases the magnitude of mean absolute percentage error is lower than 2 level

vision 2023 forecasting turkey s natural gas demand between 2013 and 2030 abstract natural gas is the primary source for electricity production in turkey however turkey does not have indigenous resources and imports more than 98 0 of the natural gas it consumes in 2011 more than 20 0 of turkey s annual trade deficit was due to imported natural gas estimated at us 20 0 billion turkish government has very ambitious targets for the country s energy sector in the next decade according to the vision 2023 agenda previously we have estimated that turkey s annual electricity demand would be 530 000 gwh at the year 2023 considering current energy market dynamics it is almost evident that a substantial amount of this demand would be supplied from natural gas however meticulous analysis of the vision 2023 goals clearly showed that the information about the natural gas sector is scarce most importantly there is no demand forecast for natural gas in the vision 2023 agenda therefore in this study the aim was to generate accurate forecasts for turkey s natural gas demand between 2013 and 2030 for this purpose two semi empirical models based on econometrics gross domestic product gdp at purchasing power parity ppp per capita and demographics population change were developed the logistic equation which can be used for long term natural gas demand forecasting and the linear equation which can be used for medium term demand forecasting fitted to the timeline series almost seamlessly in addition these two models provided reasonable fits according to the mean absolute percentage error mape criteria turkey s natural gas demand at the year 2030 was calculated as 76 8 billion m 3 using the linear model and 83 8 billion m 3 based on the logistic model consequently found to be in better agreement with the official turkish petroleum pipeline corporation botas forecast 76 4 billion m 3 than results published in the literature

the forecasting of international expo tourism using quantitative and qualitative techniques this study predicts the number of visitors to an international tourism expo to be held in korea in 2012 an unprecedented event for the host city forecasting demand for such a mega event has received only limited attention in the literature unlike most studies forecasting international tourism demand forecasting expo demand involves using both quantitative forecasting models and qualitative technique because of data limitations combining quantitative techniques with willingness to visit wtv surveys predicts the expo demand at 8 9 million visitors in comparison using the delphi method experts predict expo demand at 6 8 million visitors for this study the delphi method provides more conservative estimates than estimates from combining quantitative techniques with wtv policy implications presented are directed toward expo planners and practitioners in terms of demand and supply side application of these results in the decision making process and future challenges surrounding demand forecasting

management of natural gas resources and search for alternative renewable energy resources a case study of pakistan abstract energy usage in pakistan has increased rapidly in past few years due to increase in economic growth inadequate and inconsistent supply of energy has created pressure on the industrial and commercial sectors of pakistan and has also affected environment demand has already exceeded supply and load shedding has become common phenomenon due to excessive consumption of energy resources it would become difficult to meet future energy demands this necessitates proper management of existing and exploration of new energy resources energy resource management is highly dependent on the supply and demand pattern this paper highlights the future demands production and supply of energy produced from natural gas based on economic and environmental constraints in pakistan with special emphasis on management of natural gas an attempt has been made by proposing a suitable course of action to meet the rising gas demand a mechanism has been proposed to evaluate pakistan s future gas demand through quantitative analysis of base worst and best chosen option co 2 emission for all cases has also been evaluated the potential constraints and possible solutions to develop alternative renewable energy resources in the country have also been discussed this work will be fruitful for the decision makers responsible for energy planning of the country this work is not only helpful for pakistan but is equally important to other developing countries to manage their energy resources

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

analyzing and forecasting tourism demand with arar algorithm abstract this study investigates the arar model and its usefulness as a forecast generating mechanism for tourism demand for nine major tourist destinations in the asian pacific region the analysis is conducted on monthly inflow of international visitors covering the period 1975 01 2006 12 in monthly series we consider 6 12 18 and 24 months ahead forecasting horizons the accuracy of the forecasts in most cases is robust to the forecasting horizon based on such forecasting performance metric as mean absolute percentage error mape and root mean square error rmse the study is further expanded by including quarterly series in the forecasting exercise to ensure the reliability of the forecasting evaluation the 2 4 6 and 8 quarters ahead forecasting horizons are investigated a comparison between forecasts generated by monthly and quarterly data reveals that the performance is broadly similar finally the forecasts of arar are compared with those of seasonal arima which has been proven reliable in many forecasting contexts indeed arar model can be deemed as credible alternatives when modeling and forecasting tourism demand

a cross country comparison of seasonal cycles and business cycles in a recent paper barsky and miron 1989 examine the seasonal fluctuations in the u s economy they show that the key stylized facts about the business cycle characterize the seasonal cycle as well and they suggest that the interpretation of many of these stylized facts over the seasonal cycle is easier than interpretation over the business cycle the reason is that the ultimate sources of seasonal cycles are more readily identifiable than those of business cycles this paper uses the cross country variation in seasonal patterns to pin down the ultimate sources of seasonal variation more precisely than is possible from examination of u s data alone we conclude that a christmas shift in preferences and synergies across agents are the key determinants of the seasonal patterns around the world the paper also establishes that across developed countries the key observations about aggregate variables that characterize the business cycle also characterize the seasonal cycle thus the similarity of the seasonal cycle and the business cycle demonstrated by barsky and miron 1989 for the united states is a robust stylized fact this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item this abstract was borrowed from another version of this item

cournot outcome and optimal collusion an example abstract we give an example of a repeated cournot oligopoly game with price uncertainty in which the optimal collusion is the cournot outcome thus there is no advantage from dynamic collusion the example is quite robust with respect to probability specifications and the number of firms

the relevance of business cycles in forecasting international tourist arrivals abstract casual empiricism suggests that there may be a cyclical trend associated with international tourist arrivals in which variation around the linear trend can be formed by the interaction with other cyclical phenomena this paper employs a simple model that incorporates a linear trend and sine function to capture these two characteristics in forecasting international tourist arrivals in hong kong the model is extended to include a set of sine functions through the application of fourier analysis to account for situations in which more than one phenomenon may be present in the time series the forecasting accuracy of the model is compared with other forecasting approaches evaluation of the results using the mean absolute percentage error measure show that the forecasting performance of the extended model with a linear trend and two sine functions is superior in terms of accuracy when compared with other forecasting models

the impact of aggregation level on forecasting performance abstract most operations decisions are based on some kind of forecast of future demand thus forecasting is definitely a very traditional area in the operations and inventory management literature while literature concerning forecast explores the adoption of various qualitative and quantitative methods this paper tries to design new solutions to improve forecasting accuracy by focusing on the forecasting process that uses such algorithms in particular when forecasting demand one should always make clear exactly what he she is trying to forecast in terms of the time bucket i e the period of time over which demand is aggregated the forecasting horizon the set of items the demand refers to e g forecasting demand for a single item can be much harder than forecasting demand for a group of items the set of locations the demand refers to e g demand at the single store level is much less predictable than the demand for a whole chain of stores traditionally these features of the final output of forecasting also influence the forecasting process indeed when one wants to forecast demand at single store single item single day level it seems natural to analyse demand and causal factors at the same level of aggregation on the contrary in this paper we aim at showing that first of all often aggregating and or disaggregating data in the forecasting process can lead to substantial improvements second the choice of the appropriate level of aggregation depends on the underlying demand generation process in addition most forecasting algorithms tend to focus on a single demand variable on the contrary we can analyse analogous time series to improve the effectiveness of the forecasting process clustering techniques can be used to identify such homologous time series such clusters of homologous time series can provide on the one hand the sample size required to gain good statistical confidence and on the other hand relatively homogeneous data in the paper we use sales data from a food retailer at a very detailed level to test our hypotheses this claims for relevance for both practitioners and researchers

adaptive inventory control for nonstationary demand and partial information this paper examines several different policies for an inventory control problem in which the demand process is nonstationary and partially observed the probability distribution for the demand in each period is determined by the state of a markov chain the core process however the state of this core process is not directly observed only the actual demand is observed by the decision maker given this demand process the inventory control problem is a composite state partially observed markov decision process pomdp which is an appropriate model for a number of dynamic demand problems in practice managers often use certainty equivalent control cec policies to solve such a problem however this paper presents results that demonstrate that there are other practical control policies that almost always provide much better solutions for this problem than the cec policies commonly used in practice the computational results also indicate how specific problem characteristics influence the performance of each of the alternative policies