the multi item single period problem with an initial stock of convertible units abstract this paper deals with the situation of a number of end items each facing uncertain demand in a single period of interest besides being able to purchase units of the end items there is also available a stock of units that can be converted into end items but at unit costs that depend on the specific end item efficient solution procedures are presented for two situations i where the end item demand distributions are assumed known illustrated for the case of normally distributed demand and ii a distribution free approach where only the first two moments of the distributions are assumed known computational results for a set of problems are presented

modeling a multi attribute utility newsvendor with partial backlogging abstract traditional newsvendor models usually focus on single profit maximization or cost minimization approaches however making a monetary estimate of the consequences of lost sales as a result of shortages is often a difficult task for many practitioners besides there is still a lack of an explicit account of decision making judgments on the multiple consequences of making decisions with regard to order quantities in order to deal with this problem this paper presents a multi attribute utility model for the newsvendor problem with regard to profit the impacts of service level on corporate image and on customers goodwill and the impact on the environment arising from the disposal of unsold products demand is partially backlogged according to a decreasing exponential function of the waiting time the fundamental principles and limitations related to the application of the model built are also discussed

forecasting demand for single period products a case study in the apparel industry the problem considered is that of forecasting demand for single period products before the period starts we study this problem for the case of a mail order apparel company that needs to order its products pre season the lack of historical demand data implies that other sources of data are needed advance order data can be obtained by allowing a selected group of customers to pre order at a discount from a preview catalogue judgments can be obtained from purchase managers or other company experts in this paper we compare several existing and new forecasting methods for both sources of data the methods are generic and can be used in any single period problem in the apparel or fashion industries among the pre order based methods a novel top flop approach provides promising results for a small group of products from the case company expert judgment methods perform better than the methods based on advance demand information the comparative results are obviously restricted to the specific case study and additional testing is required to determine whether they are valid in general

pricing and the news vendor problem a review with extensions in the newsvendor problem a decision maker facing random demand for a perishable product decides how much of it to stock for a single selling period this simple problem with its intuitively appealing solution is a crucial building block of stochastic inventory theory which comprises a vast literature focusing on operational efficiency typically in this literature market parameters such as demand and selling price are exogenous however incorporating these factors into the mode l can provide an excellent vehicle for examining how operational problems interact with marketing issues to influence decision making at the firm level in this paper we examine an extension of the newsvendor problem in which stocking quantity and selling price are set simultaneously we provide a comprehensive review that synthesizes existing results for the single period problem and develop additional results to enrich the existing knowledge base we also review and develop insight into a dynamic inventory extension of this problem and motivate the applicability of such models

new light on the impressionistic view of the balancing item in australia s balance of payments accounts recently fausten and brooks offered what they refer to as an impressionistic view of the temporal evolution of australia s balancing item which is a measure of the accuracy of the balance of payments accounts they claim that the balancing item has been increasing in magnitude and volatility violating with increasing frequency internationally agreed acceptability criteria for smallness in the present paper it is shown that fausten and brooks results derive from data that incorporates excessively a dynamically asymmetric concentration of revisions and is therefore unsuitable for statistical analysis this paper develops and empirically evaluates a model of the process of revisions of balance of payments data this model illustrates that dynamically inconsistent time series of the balancing item such as that employed by fausten and brooks are bound to generate an artificial impression that it follows an explosive time trend subsequently it is illustrated that when alternative dynamically c

a generalized model of operations reversal for fashion goods operations reversal is a process design principle that involves switching two consecutive stages of the manufacturing process to improve process performance in this paper we investigate conditions under which operations reversal can be used to reduce the variability as measured by the variance and standard deviation of production volumes at the intermediate stage of the manufacturing process we generalize the operations reversal model of lee and tang 1998 to explicitly incorporate two important characteristics of fashion goods markets heterogeneity among customers and unpredictability of customer preferences we also present a new approach to modeling the operations reversal problem

joint optimal determination of process mean production quantity pricing and market segmentation with demand leakage abstract the selection of an optimal process mean is an important problem in production planning and quality control research most of the previous studies in the field have analyzed the problem for a fixed exogenous price however in many realistic situations besides product quality product pricing is a paramount factor that determines the purchase behavior in the market in the experts opinion an integrated framework that incorporates pricing as a decision tool could significantly improve a firm s profitability most of the manufacturing firms yield products with distinguishable characteristics and therefore it is desirable to sell these products on the market at differentiated prices whereas the market segmentation achieved using differentiated prices is often imperfect a firm may experience demand leakages thus an optimal price decision must incorporate demand leakage effects for the firm to benefit from its differentiated pricing strategy in this paper these issues are addressed by proposing an optimal framework for joint determination of process mean pricing production quantity and market segmentation using differentiated pricing this research discusses a production process that manufactures multi class grade products based on their quality attribute the products are sold in primary and secondary market at differentiated prices while experiencing demand leakages the nonconforming items are reworked at an additional cost mathematical models are developed to address the problem under both price dependent deterministic and stochastic demand situations we propose a harmony search meta heuristic for solving the models a numerical experimentation is presented to study the significance of the proposed integrated decision framework

modelling intra urban location preferences under rational expectations the purpose of this paper is to 1 extend the traditional generalised linear expenditure system as it has been applied in location theory by including rational expectations in the formulation 2 rank intra urban places in accordance with households location preferences 3 investigate the impact of location preferences on housing demand and urban growth and 4 study the role of price and expenditure expectations on the formation of housing demand the theoretical model was tested for seven departments of the region of attica greece using monthly data for the period july 1977 october 1988 the full information maximum likelihood procedure was used to estimate the model the findings provide useful information including guidelines for government policies concerning income housing price and interest rate subsidies

risk preferences and robust inventory decisions abstract recently in inventory management instead of maximizing expected profit or minimizing expected cost risk averse objective functions have been used for determining the optimal order quantity we use the well known newsvendor model to determine the optimal order quantity for an objective function with two risk parameters which can describe risk neutral risk averse as well as risk taking behaviour of the inventory manager this approach can also be applied to situations in which the demand distribution cannot be specified uniquely we consider robust optimization procedures maximin and minimax regret to determine optimal order quantities if the set of potential demand variables can be partially ordered by stochastic dominance rules

evaluating predictions of change this article applies a technique developed by robert c merton 1981 and roy d henriksson and robert c merton 1981 for evaluating the market timing of financial managers to macroeconomic predictions of change this methodology may be used to determine whether the predictions may be of value to the user as an illustration the methodology is applied to a set of real gross national product forecasts copyright 1990 by the university of chicago

forecasting and inventory management of short life cycle products in this paper we provide an integrated framework for forecasting and inventory management of short life cycle products the literature on forecasting and inventory management does not adequately address issues relating to short life cycle products we first propose a growth model that can be used to obtain accurate monthly forecasts for the entire life cycle of the product the model avoids limiting data requirements of traditional methods instead it extracts relevant information from past product histories and utilizes the information on total life cycle sales and the peak sales timing using disguised demand data from a personal computer pc manufacturer we validate the model next we model the inventory management problem for the short life cycle environment the uncertainty in demand is modeled through the uncertainty in the realized values of the parameters of the forecasting model the high cost of terminal inventory shortages and rapidly changing procurement costs are all included in the model extensions to the basic model are also developed using optimal control theory we derive a solution that provides valuable information on procurement cutoff time and terminal service levels a detailed example explains the characteristics of the policy and its relevance in decision making many of the issues covered in the models were brought to our attention while implementing a forecasting model at a pc manufacturer the benchmark monthly forecasts and the associated inventory levels provide information that can be very helpful in planning and controlling marketing sales and production

reducing the cost of demand uncertainty through accurate response to early sales traditionally fashion products have incurred high losses due to stockouts and inventory obsolence because long lead times coupled with a concentrated selling season force all or at least most production to be committed before demand information is available under a quick response system lead times are shortened sufficiently to allow a greater portion of production to be scheduled in response to initial demand we model and analyze the decisions required under quick response and give a method for estimating the demand probability distributions needed in our model we applied these procedures with a major fashion skiwear firm and found that cost relative to the current informal response system was reduced by enough to increase profits by 60 relative to the cost that would have been incurred if no response were used optimized response reduces cost by enough to roughly quadruple profits

demand uncertainty and supplier s returns policies for a multi store style good retailer abstract as demand uncertainty grows in the marketplace a critical issue today in most purchase contract negotiations between an independent retailer of a style good and its supplier is the provision of a returns policy i e a commitment by the supplier to buy back unsold inventory of the good at the end of its selling season management science research on the strategic role and optimal design of returns policies has grown in recent years but so far offers little treatment of how exactly the retailer s optimal order quantity decisions are affected by demand uncertainty and how a supplier s returns policy can influence these decisions employing the traditional newsboy problem modeling framework the authors investigate these issues considering a supplier who faces a retailer with two or more store outlets with normally distributed and possibly correlated demands to facilitate their analyses the authors employ a methodology based on special error function representations of the highly nonlinear objective functions of the retailer and supplier utilizing this approach the authors are able to provide explicit insights into how a the buyer s total order quantity decision is affected by the variability in demand b buyback prices in combination with wholesale prices can influence the buyer s order quantity response to demand uncertainty c demand uncertainty moderates the effects of the buyback and wholesale prices d supplier s optimal combination of actions are affected by demand variability e retailer s and supplier s expected profits behave in response to changes in the supplier s actions under different levels of demand variability

robust price setting newsvendor model with interval market size and consumer willingness to pay we consider a price setting newsvendor problem with partial information the newsvendor does not know the price dependent probability distribution of demand but is able to estimate lower and upper limits of the market size and consumer willingness to pay the objective is to minimize the maximum loss in expected profit or minimax regret we derive closed form expressions for optimal quantity and price and identify managerial insights

a bayesian approach to determine the value of information in the newsboy problem abstract the potential benefits of demand forecasting in a newsboy problem are to decrease the risk of overstocking or shortage but forecasting is usually not free in this paper a model to help the decision maker in a newsboy problem to assess the value of information is presented first two cases on available demand information are considered to develop an upper bound of the cost that the decision maker would spend on forecasting then a bayesian approach to forecasting is proposed and evai the expected value of additional information is computed to help the decision maker in deciding whether to use the extra information finally the relationship between the evai and model parameters is discussed

the effect of advertising on the distribution free newsboy problem abstract advertising is very important for the newsboy problem because the shelf life of the newsboy product is short and advertising may increase sales to avoid overstocking in this paper models to study the effect of advertising are developed for the distribution free newsboy problem where only the mean and variance of the demand are known as in khouja and robbins 2003 it is assumed that the mean demand is an increasing and concave function of advertising expenditure three cases are considered 1 demand has constant variance 2 demand has constant coefficient of variation and 3 demand has an increasing coefficient of variation this paper provides closed form solutions or steps to solve the problem numerical results of the model are also compared with those from other papers the effects of model parameters on optimal expenditure on advertising optimal order quantity and the lower bound on expected profit are derived or discussed

an analysis of a panel of spanish gdp forecasts this article undertakes an analysis of the forecasts included in the panel of spanish forecasts in order to highlight the fact that the predictions made and the errors committed by the entities participating on this panel contain information that is particularly useful in analysing the evolution of the spanish economy here a study is undertaken of the gdp growth forecasts for the spanish economy for the period 2000 to 2002 made in distinct forecast time horizons specifically it analyses whether the forecasts are optimistic or pessimistic and whether new information concerning the variable being predicted is used efficiently in revising earlier forecasts

an integrated revenue management framework for a firm s greening pricing and inventory decisions abstract there is a growing interest on developing efficient ways of incorporating environmental considerations into business practices in order to meet both consumers demand for green products services and the firms sustainable profitability the main contribution of this article is in developing an integrated revenue management framework to address a firm s greening investment effort pricing and inventory decisions it is assumed that the firm inaugurates a green product along with its existing product even though the firm offers both the green and regular product at differentiated prices the market segmentation as a result of this price differentiation is regarded as imperfect this imperfect market segmentation causes a demand leakage mainly due to the heterogeneity among the customers willingness to pay these effects are included in our proposed model and simplified analytical solutions are developed to solve the same additional scenarios where a firm experiences a price dependent stochastic demand with an unknown distribution is also modeled this scenario is addressed using a distribution free approach based on scarf s rule the performance of the proposed methods and the significance of the modeling framework are finally corroborated through several simulations this analysis provides a sustainable environment production and retailing framework while still augmenting profitability using fundamental tools from revenue management

newsvendor problem with clearance pricing abstract the newsvendor nv problem assumes that the salvage clearance price at which the leftover inventory is disposed of is a given parameter of the problem in this paper we relax this assumption and consider the nv problem with the salvage clearance price as a decision variable we have drawn from the literatures on the nv problem and clearance markdown dynamic pricing to develop three stochastic models in this paper in the first model we assume that while the seasonal demand is exogenous and stochastic the end of season demand is endogenous and deterministic the second model extends the first model by assuming that the end of season demand is endogenous and stochastic finally the third model considers that both the seasonal and end of season demands are endogenous and stochastic we have provided solution procedures for solving the stochastic optimization problems we have also performed sensitivity analyses to assess the sensitivity of the optimal expected profit and order quantity to different problem parameters specifically we have found that the optimal expected profit is most sensitive to the variable cost per unit mean seasonal demand and market potential of end of season demand our models will be useful for retailers of products with a short selling season and a short end of season period for clearance sale of leftover inventory such that there is a single replenishment opportunity at the beginning of the season and a single opportunity for setting the salvage price for clearance sale based on the leftover inventory and end of season demand pattern the paper is concluded with possible directions for future research

the reliability of u s gross national product two aspects of reliability revisions and errors need separate analysis revisions in gross national product gnp estimates are large in relation to the size of changes that matter to businesses and policy makers nevertheless preliminary estimates convey a lot of information about what the revised estimates will show errors in gnp estimates can plausibly be either larger or smaller than revisions the distinction between gathering errors and adjustment errors helps us understand a the absence of any measure of the size of gnp errors and b the ways in which national income statisticians go about reducing errors these ideas suggest several guidelines for improving gnp estimates

product selection for newsboy type products with normal demands and unequal costs abstract in this paper we consider two newsboy type products with unequal prices and costs both demands are independent and follow normal distributions with unknown parameters and we study the product selection problem which deals with comparing two products and selecting the one that has a significantly higher profitability in which the profitability is defined to the probability of achieving a target profit under the optimal ordering policy the statistical hypothesis testing methodology is performed to tackle this selection problem critical value of the test is calculated to determine the selection decision sample size required for a designated power and confidence level is also investigated an application example on comparing english teaching magazines is presented to illustrate the practicality of our approach

data revisions and forecasting the relationship between two sets of gnp data the earliest and the first revisions is examined this comparison enables us to determine whether the early numbers are valuable to forecasters the analysis uses two methods the first is based on a technique which has been used to evaluate whether financial and economic forecasts are valuable to the users the second approach uses time series techniques we conclude that revisions to the 15 day estimates that occur when the 45 day numbers are released are successful and that the 15 day numbers are useful to forecasters

the distribution free newsboy problem with resalable returns we study the case of a catalogue internet mail order retailer selling style goods and receiving large numbers of commercial returns returned products arriving before the end of the selling season can be resold if there is sufficient demand a single order is placed before the season starts excess inventory at the end of the season is salvaged and all demands not met directly are lost since little historical information is available it is impossible to determine the shape of the distribution of demand therefore we analyze the distribution free newsboy problem with returns in which only the mean and variance of demand are assumed to be known we derive a simple closed form expression for the distribution free order quantity which we compare to the optimal order quantities when gross demand is assumed to be normal lognormal or uniform we find that the distribution free order rule performs well when the coefficient of variation cv is at most 0 5 but is far from optimal when the cv is large

the distribution free newsboy problem extensions to the shortage penalty case abstract in the classical newsboy problem no cost is assumed if the ordered quantity is less than the demand however in reality failure to meet demand is always associated with a penalty the aim of this work is to extend the analysis of the distribution free newsboy problem to the case when shortage cost is taken into consideration the analysis is based on the assumption that only the mean and variance of demand are known but its particular probability distribution is not a model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand the following cases are considered the single product case the fixed ordering cost case the random yield case and the resource constrained multi product case

a risk tolerance analysis for a joint price differentiation and inventory decisions problem with demand leakage effect abstract price differentiation is a commonly used practice in revenue management rm to improve a firm s profitability however most studies in the literature have considered a risk neutral firm to demonstrate the benefits of price differentiation the main contribution of this paper is in considering several important objectives while determining the optimal product prices and order production quantities for a risk adjusted firm with demand leakage effects in the presence of a price dependent stochastic demand the objectives considered include the maximization of a firm s expected profit and maximizing the probability of exceeding the risk adjusted expected revenue closed form expressions for optimal product prices and production quantities are derived for several of these objectives a numerical study is also presented to calibrate the impact of a firm s risk tolerance and other factors such as demand leakage market demand variability on the firm s profitability and its optimal decision

decision bias in the newsvendor problem with a known demand distribution experimental evidence in the newsvendor problem a decision maker orders inventory before a one period selling season with stochastic demand if too much is ordered stock is left over at the end of the period whereas if too little is ordered sales are lost the expected profit maximizing order quantity is well known but little is known about how managers actually make these decisions we describe two experiments that investigate newsvendor decisions across different profit conditions results from these studies demonstrate that choices systematically deviate from those that maximize expected profit subjects order too few of high profit products and too many of low profit products these results are not consistent with risk aversion risk seeking preferences prospect theory preferences waste aversion stockout aversion or the consequences of underestimating opportunity costs two explanations are consistent with the data one subjects behave as if their utility function incorporates a preference to reduce ex post inventory error the absolute difference between the chosen quantity and realized demand two subjects suffer from the anchoring and insufficient adjustment bias feedback and training did not mitigate inventory order errors we suggest techniques to improve decision making

an integrated approach to price differentiation and inventory decisions with demand leakage abstract price differentiation is among widely practiced tools in revenue management rm in which a seller offers same or slightly different products or services at different prices to its customers earlier research studies have shown that the benefits from price differentiation are evident when the market segmentation is assumed to be perfect in a perfect market segmentation customers associated with a market segment do not move between market segments however it is not uncommon to observe that a market segmentation a firm operates in is seldom prefect and due to imperfect segmentation customers move between market segments which is also referred to as demand leakage in addition the firms predominantly experience stochastic demand and thus a firm experiences both the short sales and leftovers due to demand uncertainty this research proposes a model to address the issue of an optimal market segmentation using price differentiation as a tool we also establish an integrated framework for pricing order and production quantity allocation decisions in each market segment when a firm experiences demand leakage from one market segment to another and faces price dependent stochastic demand the model is analyzed to determine an optimal decision framework on pricing order quantity allocation and market segmentation using the proposed price differentiation due to the complexity of the problem both the hierarchical and joint optimization approaches are developed a simplified closed form optimal solution to the problem is outlined in the case of hierarchical approach the model is also analyzed for a situation in which the distribution of the price dependent stochastic demand is unknown and a distribution free approach is utilized to address the problem it is identified that the use of distribution free approach also results in a closed form optimal solution to the problem a numerical study is presented to demonstrate the performance of the model and solution approaches the benefits of the optimal market segmentation using a differentiation price are also highlighted along with the proposed integrated optimal decision framework when a firm experiences demand leakage