tracking the market dynamic pricing and learning in a changing environment dynamic pricing of commodities without knowing the exact relation between price and demand is a much studied problem most existing studies assume that the parameters describing the market are constant during the selling period this severely reduces their practical applicability since in reality market characteristics may change all the time without the firm always being aware of it in the present paper we study dynamic pricing and learning in a changing market environment we introduce a methodology that enables the price manager to hedge against changes in the market and provide explicit upper bounds on the regret a measure of the performance of the firm s pricing decisions in addition this methodology guides the selection of the optimal way to estimate the market process we provide numerical examples from practically relevant situations to illustrate the methodology

optimal monopolist pricing under demand uncertainty in dynamic markets we examine pricing policy for a monopolist facing uncertain demand in a market characterized by dynamics on the demand side such as diffusion or saturation effects and or on the cost side experience curve effects our model explicitly incorporates the impact of demand uncertainty and thus allows us to analyze the implications of uncertainty on the optimal price path by contrasting the stochastic policy with the corresponding deterministic policy we begin with an analysis of the general model and then focus on several special cases based on well known demand specifications to gain more specific insights and to suggest directional guidelines for dynamic pricing decisions in an uncertain environment in general the interaction among uncertainty demand and or cost dynamics and firm s discount rate thus farsighted firms operating under dynamic market conditions with high demand uncertainty such as high tech companies with innovative products for consumer or industrial markets should attach partic

dynamic pricing with real time demand learning in many service industries the firm adjusts the product price dynamically by taking into account the current product inventory and the future demand distribution because the firm can easily monitor the product inventory the success of dynamic pricing relies on an accurate demand forecast in this paper we consider a situation where the firm does not have an accurate demand forecast but can only roughly estimate the customer arrival rate before the sale begins as the sale moves forward the firm uses real time sales data to fine tune this arrival rate estimation we show how the firm can first use this modified arrival rate estimation to forecast the future demand distribution with better precision and then use the new information to dynamically adjust the product price in order to maximize the expected total revenue numerical study shows that this strategy not only is nearly optimal but also is robust when the true customer arrival rate is much different from the original forecast finally we extend the results to four situations commonly encountered in practice unobservable lost customers time dependent arrival rate batch demand and discrete set of allowable prices

simultaneously learning and optimizing using controlled variance pricing price experimentation is an important tool for firms to find the optimal selling price of their products it should be conducted properly since experimenting with selling prices can be costly a firm therefore needs to find a pricing policy that optimally balances between learning the optimal price and gaining revenue in this paper we propose such a pricing policy called controlled variance pricing cvp the key idea of the policy is to enhance the certainty equivalent pricing policy with a taboo interval around the average of previously chosen prices the width of the taboo interval shrinks at an appropriate rate as the amount of data gathered gets large this guarantees sufficient price dispersion for a large class of demand models we show that this procedure is strongly consistent which means that eventually the value of the optimal price will be learned and derive upper bounds on the regret which is the expected amount of money lost due to not using the optimal price numerical tests indicate that cvp performs well on different demand models and time scales this paper was accepted by assaf zeevi stochastic models and simulation

information asymmetry and traceability incentives for food safety abstract we define traceability by its precision that is the probability of finding the source of a problem we consider a downstream food processor firm principal that sets traceability precision and contingent payments so to induce homogeneous upstream suppliers agents to exert the principal s preferred level of food safety effort we focus on cases in which food safety crises originate from defects in raw material provided by upstream firms to analytically show that high precision can substitute for high intensive contingent payments and vice versa and thus traceability is not an unequivocal signal for safer food contrary to previous results in the literature we also show that government regulation based on mandatory traceability with sanctions may not necessarily lead to safer food while increasing the food processor s costs finally we use our analytical results to give managerial feedbacks for firms adopting and considering traceability

intertemporal generalization of the relationship between material requirements planning and input output analysis abstract the relationship between different approaches for modelling production opportunities has previously been investigated regarding input output analysis and material requirements planning mrp concerning mainly one period cases not taking intertemporal considerations such as inventories the time phasing of orders etc into account this paper focuses on mrp related approaches and input output analysis generalizing previous findings to multi period cases in which inventories and the time allocation of production activities due to lead times are essential ingredients an important concept developed is the generalized input matrix which apart from input requirements also captures all lead times involved by means of z transform operators also derived are two simple stationary economic order quantity formulas for the multi product multi period case treated

a new product growth for model consumer durables this article originally appeared in management science january 1969 volume 15 number 5 pp 215 227 published by the institute of management sciences a growth model for the timing of initial purchase of new products is developed and tested empirically against data for eleven consumer durables the basic assumption of the model is that the timing of a consumer s initial purchase is related to the number of previous buyers a behavioral rationale for the model is offered in terms of innovative and imitative behavior the model yields good predictions of the sales peak and the timing of the peak when applied to historical data a long range forecast is developed for the sales of color television sets

modeling and estimation in changing market environments in many marketing contexts managers and researchers are concerned with modeling the response of performance variables e g sales or market share to one or more decision variables e g advertising or price or other predictor variables modeling efforts in these contexts may consider either the response of an individual entity such as a single consumer or firm or the aggregate response of a collection of entities usually they involve the specification of mathematical models where the unknown parameters are assumed a priori to be constant these unknown parameters are then estimated by fitting the models to available data using some form of regression analysis the rationale for expending effort in this area is the expectation that through activities of this type the decision maker gains understanding of the market process and therefore is able to make better decisions the response of a firm s market performance to decision predictor variables may be moderated by numerous external factors by competitive factors and by the levels of the firm s decision variables for example the sensitivity of sales to price may vary depending on time of year overall economic conditions and or levels of advertising or promotion certain characteristics of marketing research is often concerned with the modeling of market response over time however the nature of the relationships being modeled may change due to shifts in consumer tastes changing marketing strategies competition and other reasons currently used constant parameter models are not capable of adequately reflecting such changing market environments therefore alternate modeling approaches should be considered recent work in statistics and econometrics suggests the appropriateness of variable parameter models for such problems this methodology permits model coefficients to change over time in this paper various potentially useful variable parameter models are discussed reported marketing applications are examined and issues pertaining to the application of this relatively new methodology to marketing problems are investigated professor winer gratefully acknowledges support from the faculty research fund of the graduate school of business columbia university professor wildt was on the faculty of the university of georgia when the paper was written

production management output volatility and good luck abstract this paper models the scale of the technology shocks as a decision variable whose value is determined by the production manager it is shown that smaller shocks enhance profit in several ways and thus the firm has an incentive to adopt more reliable production technologies the adoption of these technologies may account for the good luck hypothesis in which the stabilization of gross domestic product gdp since 1984 is attributed to smaller shocks it differs from this hypothesis in two respects first the reduced volatility should be permanent second the stabilization does not require smaller intrinsic shocks to the economy

production stability in a supply chain environment abstract there is evidence that the growth rate of gdp in the united states stabilized in 1984 and improvements in production management are frequently cited as a source this paper defines the quality of production as the scale of the firm s production shock and assumes that the firm can exercise control over the scale of the shock the firm is assumed to operate in a supply chain environment and the question of interest is what if any influence the adoption of more reliable production techniques by a single firm has for aggregate volatility the results indicate that the adoption of more reliable production techniques by a single firm typically have minor effects on aggregate volatility because the benefit dies out rapidly as the product moves downstream the exceptions are those cases in which the firm adopting the improved technology lies near the end of the chain there is also some benefit when deliveries of materials to the initial firm in the production chain stabilize

dynamic pricing and learning with finite inventories we study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution products are sold during selling seasons of finite length and inventory that is unsold at the end of a selling season perishes the goal of the seller is to determine a pricing strategy that maximizes the expected revenue inference on the unknown parameters is made by maximum likelihood estimation we show that this problem satisfies an endogenous learning property which means that the unknown parameters are learned on the fly if the chosen selling prices are sufficiently close to the optimal ones we show that a small modification to the certainty equivalent pricing strategy which always chooses the optimal price w r t current parameter estimates satisfies regrett olog2t where regrett measures the expected cumulative revenue loss w r t a clairvoyant who knows the demand distribution we complement this upper bound by showing an instance for which the regret of any pricing policy satisfies i log t

on the minimax complexity of pricing in a changing environment we consider a pricing problem in an environment where the customers willingness to pay wtp distribution may change at some point over the selling horizon customers arrive sequentially and make purchase decisions based on a quoted price and their private reservation price the seller knows the wtp distribution pre and postchange but does not know the time at which this change occurs the performance of a pricing policy is measured in terms of regret the loss in revenues relative to an oracle that knows the time of change prior to the start of the selling season we derive lower bounds on the worst case regret and develop pricing strategies that achieve the order of these bounds thus establishing the complexity of the pricing problem our results shed light on the role of price experimentation and its necessity for optimal detection of changes in market response wtp our formulation allows for essentially arbitrary consumer wtp distributions and purchase request patterns

dynamic monopoly pricing under a poisson type uncertain demand this article explores dynamic pricing strategies in the presence of uncertainty diffusion dynamics experience curve effects and a poisson type of uncertainty in the demand are incorporated in a model using the framework of a stochastic control problem the results indicate that the movement of the expected price depends on the relative strength of the contingent effects and the effects of the experience if the direction of the former is opposite to the latter and is substantial enough to dominate it the expected price path will show a pattern different from the one predicted by a deterministic model copyright 1992 by university of chicago press

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

stability of perishable goods in cold logistic chains abstract we consider that production and logistics facilities in the supply chain are positioned between the origin and the supply market or in a part of it any changes in time distance or temperature in the chain could cause the net present value of the activities and their added value in the supply chain to be perturbed in reality the perturbations can be robust the natural question arises is to what are the effects of some perturbations in a supply chain in its production or distribution part on the stability of perishable goods in such systems and what is the appropriate control which keeps the product on the required level of quality and quantity at the final delivery these analyses are especially important to assure the stability of cold chains in the cold chains management ccm what conditions should be fulfilled to assure that after such robust perturbations of parameters and especially time delays lead times and some other delays the behaviour of the logistics chain would still be within the prescribed limits the formulation obtained in the time domain will be compared with the formulation in the frequency space introduced by grubbstrom in his paper on the application of the laplace transform to certain economic problems manage sci 7 1967 558 and with the later studies of his school their model was extended by the authors to the complete logistic chain where location and with it also the distance between the activity cells of logistic chain play an important role

stochastic considerations of grubbstrom molinder model of mrp input output and multi echelon inventory systems abstract in a recent paper grubbstrom and molinder 1994 grubbstrom and molinder studied theoretically the dynamic relationship between mrp input output analysis and multi echelon inventory systems in this paper we upgrade this approach including in the model the uncertainty of external demand and decision theory elements in the model we suppose that we know only the upper and lower bounds of external demand rate and because of lack of information that the external demand is uniformly distributed the complete decision model for our case is considered and the advantages of this approach are demonstrated

discussing the parameters of preservation of perishable goods in a cold logistic chain model the paper discusses the parameters of preservation of perishable goods in cold logistic chains the key parameters are the intensity of deterioration of goods the conservation effect of perishable goods and the delay of activation of the conservation effect the values of these parameters determine the quantity of the product being deteriorated in the logistic chain and the extent to which the deterioration can be alleviated econometric estimation thus presents the quantity effects of preservation procedures whereas the financial effects can be derived using the proper price categories in the calculation of the net present value or the annuity stream in this way one can determine whether the implementation of preservation procedures is more rational than the purchase of an attainable insurance policy

stochastic properties of a production inventory process with planned production using transform methodology abstract we consider a stochastic inventory process in which demand is generated by individual events separated by independent stochastic time intervals whereas production takes place in batches of possibly varying sizes at different points in time the resulting processes are analysed using laplace transform methodology expressions for inventory and stockouts are developed applying the theory of residues an example includes poisson distributed demand intervals assuming costs for set ups for carrying inventory and for stockouts conditions are developed for determining the optimal production policy on the one hand when applying the traditional average cost measure on the other when applying the annuity stream principle

global sensitivity analysis in inventory management abstract this paper deals with the sensitivity analysis sa of inventory management models when uncertainty in the input parameters is given full consideration we make use of sobol function and variance decomposition method for determining the most influential parameters on the model output we first illustrate the method by means of an analytical example we provide the expression of the global importance of demand holding costs order costs of the harris economic order quantity eoq formula we then present the global sa of the inventory management model developed by luciano and peccati 1999 capital structure and inventory management the temporary sale problem international journal of production economics 59 169 178 for the economic order quantity estimation in the context of the temporary sale problem we show that by performing global sa in parallel to the modeling process an analyst derives insights not only on the eoq structure when its expression is not analytically known but also on the relevance of modeling choices as the inclusion of financing policies and special orders

is consumption growth consistent with intertemporal optimization evidence from the consumer expenditure survey in this paper we show that some of the predictions of models of consumer intertemporal optimization are in line with the patterns of nondurable expenditure observed in u s household level data we propose a flexible specification of preferences that allows multiple commodities and yields empirically tractable equations we estimate preference parameters using the only u s micro data set with complete consumption information we show that previous rejections can be explained by the simplifying assumptions made in previous studies we also show that results obtained using good consumption or aggregate data can be misleading

an analytical framework for retailer price and advertising decisions for products with temperature sensitive demand abstractthe demand for weather sensitive products such as beverages ice creams or chocolate varies with changes in temperature yet retailers lack a framework to adapt the marketing mix element

innovation diffusion uncertainty advertising and pricing policies we develop and analyze a normative and structurally stochastic model of innovation diffusion by depicting the market at an aggregate level model dynamics are defined through the flow pattern of individuals that move from the innovation unaware stage to the innovation aware and ultimately to the adopter stages the stochastic evolution of this stage wise transition unfolds according to tractable stochastic processes and is influenced by such factors as price word of mouth and advertisement efforts in this environment techniques of contingent claims analysis and stochastic control theory are employed to obtain optimal pricing or advertising policies that maximize the value of the innovation to account for their optimal adjustment over time these policies are modeled as positive real valued adapted processes given this setting policy adjustments over time i e advertising or pricing are viewed as a value additive sequence of nested real options we present closed form analytic results regarding the optimal policies simulations provide a numeric insight to the models behavior

learning and pricing with models that do not explicitly incorporate competition in revenue management research and practice demand models are used that describe how demand for a seller s products depends on the decisions such as prices of that seller even in settings where the demand for a seller s products also depends on decisions of other sellers the models often do not explicitly account for such decisions it has been conjectured in the revenue management literature that such monopoly models may incorporate the effects of competition because the parameter estimates of the monopoly models are based on data collected in the presence of competition in this paper we take a closer look at such a setting to investigate the behavior of parameter estimates and decisions if monopoly models are used in the presence of competition we consider repeated pricing games in which two competing sellers use mathematical models to choose the prices of their products over the sequence of games each seller attempts to estimate the values of the parameters of a demand model that expresses demand as a function only of its own price using data comprised only of its own past prices and demand realizations we analyze the behavior of the sellers parameter estimates and prices under various assumptions regarding the sellers knowledge and estimation procedures and we identify situations in which a the sellers prices converge to the nash equilibrium associated with knowledge of the correct demand model b the sellers prices converge to the cooperative solution and c the sellers prices have many potential limit points that are neither the nash equilibrium nor the cooperative solution and that depend on the initial conditions we compare the sellers revenues at potential limit prices with their revenues at the nash equilibrium and the cooperative solution and we show that it is possible for sellers to be better off when using a monopoly model than at the nash equilibrium

industry evidence of enhanced production stability since 1984 abstract mcconnell and perez quiros have recently provided evidence that the growth rate of gdp has stabilized since 1984 they conclude that the enhanced stability can be attributed to improvements in inventory management in the durables sector this study examines the behavior of output in two digit sic manufacturing industries in an effort to determine whether this increase in stability is evident in less aggregated data after accounting for changes in demand volatility output stabilized in four of the six 2 digit durables industries modeled here total durables output stabilized by 9 these improvements appear to be the result of milder short run output responses to demand shocks this suggests that output has become less responsive to demand shocks and casts doubt on enhanced flexibility of production that should be characteristic of improved production management

dynamic pricing with a prior on market response we study a problem of dynamic pricing faced by a vendor with limited inventory uncertain about demand and aiming to maximize expected discounted revenue over an infinite time horizon the vendor learns from purchase data so his strategy must take into account the impact of price on both revenue and future observations we focus on a model in which customers arrive according to a poisson process of uncertain rate each with an independent identically distributed reservation price upon arrival a customer purchases a unit of inventory if and only if his reservation price equals or exceeds the vendor s prevailing price we propose a simple heuristic approach to pricing in this context which we refer to as decay balancing computational results demonstrate that decay balancing offers significant revenue gains over recently studied certainty equivalent and greedy heuristics we also establish that changes in inventory and uncertainty in the arrival rate bear appropriate directional impacts on decay balancing prices in contrast to these alternatives and we derive worst case bounds on performance loss we extend the three aforementioned heuristics to address a model involving multiple customer segments and stores and provide experimental results demonstrating similar relative merits in this context

bayesian dynamic pricing policies learning and earning under a binary prior distribution motivated by applications in financial services we consider a seller who offers prices sequentially to a stream of potential customers observing either success or failure in each sales attempt the parameters of the underlying demand model are initially unknown so each price decision involves a trade off between learning and earning attention is restricted to the simplest kind of model uncertainty where one of two demand models is known to apply and we focus initially on performance of the myopic bayesian policy mbp variants of which are commonly used in practice because learning is passive under the mbp that is learning only takes place as a by product of actions that have a different purpose it can lead to incomplete learning and poor profit performance however under one additional assumption a constrained variant of the myopic policy is shown to have the following strong theoretical virtue the expected performance gap relative to a clairvoyant who knows the underlying demand model is bounded by a constant as the number of sales attempts becomes large this paper was accepted by gerard p cachon stochastic models and simulation

has production management improved since 1984 kim and nelson 1999 and others have recently presented evidence of a dramatic decline in the volatility of real gross domestic product gdp when the data are plotted the break date is easily identified as 1984 kim and nelson conclude that the enhanced stability is broadly based but statistical analysis by mcconnell and perez quiros 2000 hereafter mpq points to reductions in inventory volatility in the durables sector as the source of the newfound stability although inventory investment is a very small component of gdp changes in inventory investment are one of the most volatile components of changes in gdp ramey and west 1999 calculate that declines in inventory investment typically account for 49 of reductions in u s gdp during recessions inventories in the durables sector are substantially more volatile than in the nondurables sector and thus inventory investment in this sector is more likely to contribute to macroeconomic instability the 1984 break date is intriguing because it coincides with the rising popularity of new production management techniques such as just in time jit 1 hall 1983 describes jit as an emphasis on producing exactly what is needed and conveying it to where it is needed precisely when required he cites several components to the successful implementation of jit but one of the major components is flexible production implying rapid response and the ability to profitably produce only what is immediately required in this ideal environment no unfilled orders or finished goods are accumulated and whatever raw materials and work in process must be accumulated are quickly processed more generally the more flexible and well coordinated the production process the more quickly output can respond to a demand shock 2 the questions addressed here are as follows 1 is there evidence of structural change in output 2 did the structural change if any occur around 1984 3 did output track demand more closely following the structural change the answers to all three questions must be yes to support the contention that improved production management is responsible for the stabilization of gdp the analysis is carried out at the industry level to identify those industries that satisfy the criteria the quality of production management is measured as the difference between the log of output and the log of new orders both measured monthly new orders represent demand and are equivalent to sales among firms that hold no unfilled orders if the firm achieves the ideal efficiency then output is identical to demand more generally efficiency is reflected in the time required for the firm to return inventories and unfilled orders to their target values following a shock to demand or output an increase in efficiency implies a more rapid output response to demand shocks so that any differences between output and demand are resolved more rapidly structural change is identified with tests for structural change with unknown break dates developed by andrews 1993 and andrews and ploberger 1994 following herrera and pesavento s 2004 industry level analysis the tests allow for multiple breaks their tests for stability are conducted on univariate autoregressive models of sales and inventories by stages of fabrication here the growth rate of output or the difference between the log of output and the log of new orders is the dependent variable allowing for a direct observation of structural change in the variable of interest in addition the models are richer in that variables such as new orders and raw materials are included on the right hand side to determine the sensitivity of the break date to potential sources of any change in output behavior several studies in addition to herrera and pesavento s 2004 have examined industry level data for evidence of structural change that might indicate improvements in production management

income and wealth heterogeneity in the macroeconomy how do movements in the distribution of income and wealth affect the macroeconomy we analyze this question using a calibrated version of the stochastic growth model with partially uninsurable idiosyncratic risk and movements in aggregate productivity our main finding is that in the stationary stochastic equilibrium the behavior of the macroeconomic aggregates can be almost perfectly described using only the mean of the wealth distribution this result is robust to substantial changes in both parameter values and model specification our benchmark model whose only difference from the representative agent framework is the existence of uninsurable idiosyncratic risk displays far less cross sectional dispersion and skewness in wealth than u s data however an extension that relies on a small amount of heterogeneity in thrift does succeed in replicating the key features of the wealth data furthermore this extension features aggregate time series that depart significantly from permanent income behavior

problems with using traditional aggregate inventory to sales ratios abstract changes in traditionally constructed aggregate inventory to sales ratios are shown to not necessarily measure changes in underlying subsector inventory behavior this is because while traditionally constructed aggregate inventory to sales ratios can be viewed as the weighted average of the underlying subsector inventory to sales ratios the aggregation weights vary over time reflecting shifts in the composition of sales across the subsectors for example aggregate ratios can increase when most of the underlying subsectors are reducing inventory to sales ratios this is shown to have been the case for the us retail sector as a solution to this measurement problem the use of fixed weight aggregate inventory sales ratios is proposed these should help business cycle analysts and researchers better gauge the condition of inventories

firm performance under just in time and traditional proxies for profit maximization abstract when the profit function is too complex to maximize directly firms must rely on some other performance criterion to guide work station activity simplification is achieved by emphasizing either flow or stock management flow management seeks to ensure that no work station is starved by available inputs stock management seeks to minimize inventories this paper develops a model to assess the performance of these two approaches for a firm that can carry both input and output inventories the model includes shocks to both demand and production and the possibility of a stockout is explicitly reflected in the optimization problem stock management dominates flow management when carrying costs are sufficiently large when carrying costs are moderate the strategy of simply ignoring shocks to demand and capacity dominates both stock and flow management the flow management approach is superior only when carrying costs are very small

adaptive data driven inventory control with censored demand based on kaplan meier estimator using the well known product limit form of the kaplan meier estimator from statistics we propose a new class of nonparametric adaptive data driven policies for stochastic inventory control problems we focus on the distribution free newsvendor model with censored demands the assumption is that the demand distribution is not known and there are only sales data available we study the theoretical performance of the new policies and show that for discrete demand distributions they converge almost surely to the set of optimal solutions computational experiments suggest that the new policies converge for general demand distributions not necessarily discrete and demonstrate that they are significantly more robust than previously known policies as a by product of the theoretical analysis we obtain new results on the asymptotic consistency of the kaplan meier estimator for discrete random variables that extend existing work in statistics to the best of our knowledge this is the first application of the kaplan meier estimator within an adaptive optimization algorithm in particular the first application to stochastic inventory control models we believe that this work will lead to additional applications in other domains

dynamic and targeted bundle pricing of two independently valued products abstract bundling is when two or more products are offered as a single unit and at a price lower than the sum of the individual prices of the products we study a multi segment market in which a retailer aims to clear the inventory of an item by bundling it with a second product which is independently valued we investigate the question of how dynamic and segment specific bundle pricing impacts retailer s revenue we develop a revenue model that integrates the dynamic and segment specific aspects of the pricing decisions and present a computational study to analyze their revenue impact relative to a price promotion for the individual item only the computational results indicate that the bundle offers are most effective when the initial inventory of the item under consideration is high the results also demonstrate that dynamic pricing is beneficial when the initial inventory of the item is low an additional revenue improvement is observed when the price of the bundle is dynamically optimized in the computational study segment specific pricing is observed to have no direct impact on revenue when prices are static segment specific and dynamic pricing however can bring about substantial revenue improvements that are an increasing function of the initial inventory level of the item we consider the correlation in consumers valuations of the bundled products and show that dynamically priced and segment specific bundle offers yield a robust revenue performance mitigating the potentially revenue diminishing impact of positive correlation in consumers valuations of the products

has inventory management in the us become more efficient and flexible a macroeconomic perspective abstract this paper examines the seeming eradication of evidence for improved inventory management since the early 1980s suggested by the aggregate data in the january 1993 revision of the bureau of economic analysis inventory and sales estimates for us manufacturing and trade it analyzes inventory sales output orders ratios at the published level of detail to determine whether at least some components continue to show clear evidence of increased long run efficiency after 1982 further it investigates three other potential avenues of improved inventory management greater cyclical flexibility adjusting of inventory levels more fully to cyclical peaks and troughs faster adjustment to near term desired levels and diminished buffer stock behavior for each aspect and each inventory component several indicators are examined jointly to assess the evidence for improved management the incidence of positive assessments is then viewed across components to judge their overall role substantial evidence for improved long run efficiency is largely confined to materials and work in process inventories in certain manufacturing industries rising inventory sales ratios for other components centered in retail trade are offsetting elements significantly greater cyclical flexibility and faster speeds of adjustment are more widespread although again centered in manufacturing there is virtually no evidence of diminished buffer stock behavior

dynamic pricing under a general parametric choice model we consider a stylized dynamic pricing model in which a monopolist prices a product to a sequence of t customers who independently make purchasing decisions based on the price offered according to a general parametric choice model the parameters of the model are unknown to the seller whose objective is to determine a pricing policy that minimizes the regret which is the expected difference between the seller s revenue and the revenue of a clairvoyant seller who knows the values of the parameters in advance and always offers the revenue maximizing price we show that the regret of the optimal pricing policy in this model is theta sqrt t by establishing an omega sqrt t lower bound on the worst case regret under an arbitrary policy and presenting a pricing policy based on maximum likelihood estimation whose regret is cal o sqrt t across all problem instances furthermore we show that when the demand curves satisfy a well separated condition the t period regret of the optimal policy is log t numerical experiments show that our policies perform well

trend breaks in us inventory to sales ratios abstract this paper documents econometrically that us inventory to sales ratios have time trends and that there have been significant breaks in these time trends at both the aggregate and industry level using techniques developed by bai rev econ stat 1997 551 and by bai and perron econometrica 66 1 1998 47 we simultaneously estimate the time trend parameters and the dates of statistically significant breaks in those trends using data from 1967 through 2001 it is estimated that aggregate manufacturing and trade inventory to sales ratio trended upwards at a 0 76 year rate before 1985 q3 and has trended downwards at a 1 29 year rate since then downtrends are estimated to have begun in manufacturing ratios in 1983 wholesalers in 1985 and retailers in 1990 before the mid 1990s nearly all the reductions in ratios occurred in industries carrying durable goods examination of the timing and possible explanations of trend breaks for the 20 two digit manufacturing industries suggests that breaks are much more likely to have occurred in recessions and may be related to changes in the variance of the industry s sales growth rate

dynamic pricing with an unknown demand model asymptotically optimal semi myopic policies we consider a monopolist who sells a set of products over a time horizon of t periods the seller initially does not know the parameters of the products linear demand curve but can estimate them based on demand observations we first assume that the seller knows nothing about the parameters of the demand curve and then consider the case where the seller knows the expected demand under an incumbent price it is shown that the smallest achievable revenue loss in t periods relative to a clairvoyant who knows the underlying demand model is of order t in the former case and of order log t in the latter case to derive pricing policies that are practically implementable we take as our point of departure the widely used policy called greedy iterated least squares ils which combines sequential estimation and myopic price optimization it is known that the greedy ils policy itself suffers from incomplete learning but we show that certain variants of greedy ils achieve the minimum asymptotic loss rate to highlight the essential features of well performing pricing policies we derive sufficient conditions for asymptotic optimality

cost of business cycles with indivisibilities and liquidity constraints it is almost universally agreed that individuals face incomplete insurance markets and cannot perfectly insure against the idiosyncratic risk in this paper simple general equilibrium models with incomplete insurance markets are examined in order to assess the impact of imperfect insurance on the magnitude of the welfare costs of business cycles two versions of incomplete insurance markets are considered and certain statistical properties of the equilibrium stochastic processes in these environments are compared with those of a perfect insurance economy

inventory investment and sectoral characteristics in some oecd countries this paper discusses the effects of sectoral structure on the long run macroeconomic inventory behaviour of national economies data on 15 oecd countries are included in the analysis which is based on correlation and cluster analysis methodologies the study is part of a long term research project exploring factors influencing the inventory behaviour of national economies first we introduce some basic characteristics of macroeconomic inventory formation in the 15 oecd countries we argue that our previous results on the existence of specific characteristic features of macroeconomic inventory investment are justified hence it makes sense to study the factors influencing these features we then examine the contribution of various sectors to the production of in the countries involved and the relationship between sectoral structure and inventory intensity annual inventory change gross value added we find that the high share of agriculture and manufacturing increases inventory intensity that the increasing share of services has a negative effect and that the role of construction and trade is not obvious the relatively low stability of the statistical results warns us to be cautious with our judgements further case by case analysis would be required to obtain more solid results

dynamic pricing in the presence of inventory considerations research overview current practices and future directions the benefits of dynamic pricing methods have long been known in industries such as airlines hotels and electric utilities where the capacity is fixed in the short term and perishable in recent years there has been an increasing adoption of dynamic pricing policies in retail and other industries where the sellers have the ability to store inventory three factors contributed to this phenomenon 1 the increased availability of demand data 2 the ease of changing prices due to new technologies and 3 the availability of decision support tools for analyzing demand data and for dynamic pricing this paper constitutes a review of the literature and current practices in dynamic pricing given its applicability in most markets and its increasing adoption in practice our focus is on dynamic intertemporal pricing in the presence of inventory considerations

inventory allocation and customer travelling problem in spatial duopoly abstract the paper is a theoretical study about connecting inventory allocation and market area for the goods defined by customers travelling decisions influenced by the expected shortages of goods in the paper inventories in spatial models bogataj international journal of production economics 45 1996 337 342 2 we have emphasized the need for connecting inventory and location analysis this problem was studied further by h j girlich in his paper on the metric transportation problems and their solution girlich lecture notes of the international postgraduate summer school vol 2 1995 pp 13 24 which gives us proper foundations for our present research the study is influenced by grubbstrom and molinder s work on mrp optimization for details see grubbstrom management science 13 7 1967 558 567 grubbstrom the mathematical scientist 16 1991 118 129 grubbstrom international journal of production economics forthcoming grubbstrom international encyclopaedia of business and management 1996 grubbstrom and molinder proceedings of the eight international working seminar on production economics 1994 grubbstrom and molinder international journal of production economics 35 1994 299 31 6 11 the annuity stream approach has been applied in the environment of spatial duopoly where the optimal ordering policy depends on the interaction between the prices and shortages of goods in the studied duopolies customer travelling problem ctp is defined which determines the market area for allocated inventories

inventory dynamics time lags and efficiency measures abstract standard measures employed to examine efficiency such as production efficiency in manufacturing are static in nature standard methods typically employ a stock flow approach to measure turnover and delay this is a first estimate but an inadequate approach since production processes are time dependent and dynamic this study examines theoretical issues concerning the standard method of measuring efficiency indices and introduces a refined dynamic measurement methodology the standard and proposed methodologies are applied to financial data for us tire and rubber goods industry to demonstrate the empirical differences between the two measures

monopolist pricing with dynamic demand and production cost this paper deals with pricing of a new product over time by a monopolist who maximizes the discounted profit stream the interdependency of cost and demand on cumulative production makes the problem inherently dynamic cost is assumed to be declining with cumulative production learning curve effect while demand is a function of price and cumulative sales representing word of mouth and saturation effects the paper addresses this problem in a general framework that includes several previous results as special cases and provides new insights in other situations while the learning curve and word of mouth effect cause prices to be lower than the price that maximizes immediate revenues the saturation factor has the opposite effect the price path over time is affected by these factors and the interest rate we characterize the price path under several different situations and interpret the results for policy guidelines