gender bias and the availability of business loans abstract social structure values and gender socialization have undoubtedly disadvantaged women in the process of preparing for a career in business and there is a widely held view that women are subject to discrimination by financial institutions however the evidence to verify this belief has largely been from studies where women have claimed that they were subject to discrimination in the loan situation without either supporting evidence or control data from a sample of male loan applicants two experiments were carried out using a goldberg type procedure to test the belief that women are unfairly discriminated against when seeking a loan to establish a business venture carefully constructed scenarios of an application for loan finance to purchase a commercial enterprise were mailed to loan officers of major trading bank branches the scenarios were identical in all respects except for the sex and education level of applicants loan officers were asked whether or not they would approve loan finance for the proposed business purchase and to indicate factors that contributed to their decisions significant differences in response to female and male applicants were observed in both experiments in experiment i university education both sexes were equally likely to obtain a loan but education was considered a more important factor for the female applicant than for the male in experiment ii high school education the female applicant was less likely to obtain a loan than the male applicant the results support the widely held perception that women can experience gender discrimination when seeking start up capital such discriminatory behavior by loan officers may not be and probably is not intentional rather the pervasiveness of the social construction of differential gender roles in western culture is such that it is more likely that discrimination is unconscious and consequently more difficult to change

housing conditions and their structural determinants comparisons within the enlarged eu housing conditions vary widely across the eu and the fact that new member states are lagging behind in this regard has even come onto the european policy agenda this article examines housing conditions as an outcome of complex social developments and highlights specific reasons why housing conditions vary so much within the eu thus the specific impact is observed of factors which have been identified in the literature as characterising distinctive housing models the eastern european housing model the southern european housing model and the distinction between cost renting and homeowning countries further the impact of these factors along with general socioeconomic development is empirically assessed by a linear regression model based on the eqls 2003 dataset the results clearly support the thesis of economic development playing a decisive role with it being the biggest single factor explaining variations in housing conditions across the eu followed by the significant influence of policy choice

land use and density in cities with congestion abstract it was well documented that monocentric spatial models with congestion require driving tolls to generate market efficiency because driving and location are equivalent tolling congestion is the same as regulating density this paper shows that internalizing the congestion externality always requires upward adjustments to market density which are greatest at the urban center this holds whether or not transportation capacity is optimally provided simulations suggest optimal cities should have central densities that are orders of magnitude greater than market cities

residential construction using the urban growth model to estimate housing supply abstract this article presents an empirical model of housing supply derived from urban growth theory this approach describes new housing construction as a function of changes in house prices and costs rather than as a function of the levels of those variables which previous studies have used empirical tests support this specification over the leading alternative models our estimates show that a 10 rise in real prices leads to an 0 8 increase in the housing stock which is accomplished by a temporary 60 increase in the annual number of starts spread over four quarters

impact of information sharing and lead time on bullwhip effect and on hand inventory abstract this work analyzes a two echelon warehouse retailer serial supply chain to study the impact of information sharing is and lead time on bullwhip effect and on hand inventory the customer demand at the retailer is assumed to be an autoregressive ar 1 process both the echelons use a minimum mean squared error mmse model for forecasting lead time demand ltd and follow an adaptive base stock inventory policy to determine their respective order quantities for the cases of without is and inter as well as intra echelon is expressions for the bullwhip effect and on hand inventory for the warehouse are obtained considering deterministic lead time the results are compared with the previous research work and an easy analysis of the various bullwhip effect expressions under different scenarios is done to understand the impact of is on the bullwhip effect phenomenon it is shown that some part of bullwhip effect will always remain even after sharing both inter as well as intra echelon information further with the help of a numerical example it is shown that the lead time reduction is more beneficial in comparison to the sharing of information in terms of reduction in the bullwhip effect phenomenon

production chains and aggregate output volatility abstract a production chain s aggregate output volatility depends upon a number of factors including the number of firms in a chain the management strategy of the firms the point at which products are differentiated lead times and the persistence of demand shocks the influence of these factors is quantified here with an n firm model of the production chain under pure production to stock pts the firms in the chain respond simultaneously to a demand shock producing a positive covariance across firms that raises aggregate volatility under production to order pto the chain s response to a demand shock is staggered but when demand shocks are persistent there is a catch up effect that raises the volatility of each firm s production above that of a firm that under pts nevertheless pto chains typically exhibit less volatility than pts chains thanks to the covariance effect further simulations demonstrate that the production chain stabilizes as the number of production cycles in an observation period increases

bounded growth of the bullwhip effect under a class of nonlinear ordering policies abstract this paper analyzes the bullwhip effect in multi echelon supply chains under a general class of nonlinear ordering policies a describing function approach from control theory is used to derive closed form formulas to predict amplification of order fluctuations along the supply chain it is proven that with consideration of nonlinearity in the ordering policy the magnitude of the bullwhip effect will eventually become bounded after growing through the first few stages of the supply chain it is also proven that the average customer demand as well as the demand fluctuation frequency would directly affect the bounded magnitude while the suppliers demand forecasting method has no effect at all for illustration analytical results for a class of order up to policies are derived and verified by numerical simulations the proposed modeling framework holds the promise to not only explain empirical observations but also serve as the basis for developing counteracting strategies against the bullwhip effect

measuring the bullwhip effect for supply chains with seasonal demand components abstract a bullwhip measure for a two stage supply chain with an order up to inventory policy is derived for a general stationary sarma p q p q s demand process explicit expressions for several sarma models are obtained to illustrate the key relationship between lead time and seasonal lag it is found that the bullwhip effect can be reduced considerably by shortening the lead time in relation to the seasonal lag value

analysis of compound bullwhip effect causes abstract this research investigates compound causes of the bullwhip effect bwe by considering an inventory system with multiple price sensitive demand streams joint price and demand dynamics are captured by a vector time series process that incorporates the stochastic co movements in price and demand we study two bwe measures one for each demand stream individually and one for the aggregated demand we show that demand parameters including demand autocorrelation cross correlation and price sensitivity serve as root causes of the bwe we prove that the impact of these parameters on the bwe can be additively decomposed conditions are established under which a pair of simultaneous compound causes may attenuate or dampen the bwe when demand streams are aggregated we derive a pooling factor that quantifies the impact of demand aggregation on order stability when positive the pooling factor corresponds to a synergy effect that captures the gain in the stability of the pooled orders conditions for the existence of the synergy effect are obtained for several special cases involving a zero leadtime we also discuss how our analytical findings can be managerially applied to bullwhip mitigation strategies

providing a measure for bullwhip effect in a two product supply chain with exponential smoothing forecasts abstract in this paper a two product and two echelon supply chain is considered in order to quantify the bullwhip effect demands of the products are correlated and are represented by a first order vector autoregressive model retailer uses order up to ordering policy for replenishment of stocks and utilizes exponential smoothing forecast method to predict demand in lead time period according to the mentioned assumptions an equation is derived for bullwhip effect measurement and then a numerical example is presented for a better perception of the bullwhip effect behavior when the parameters change a comparison of the bullwhip effect measure has been done when two main forecasting methods i e exponential smoothing and moving average are used and empirical results are provided at last a cost analysis is conducted based on shortage and holding cost under different bullwhip effect measures

supply chain coordination for the joint determination of order quantity and reorder point using credit option abstract decisions regarding order quantity and reorder point are two major challenges in supply chain inventory management in this paper a coordination model of the joint determination of these two decision variables is proposed a decentralized supply chain consisting of one buyer and one supplier in a multi period setting is investigated demand and lead times are uncertain in our model an incentive scheme based on credit option has been developed to encourage the buyer to participate in the coordination model in this model the downstream member has the option of using credit to purchase goods during the credit time subject to its commitment to a jointly agreed order quantity and reorder point the credit time is determined in such a way that the two parties have incentives to participate the proposed incentive scheme can share the benefits of coordination between the two members based on their bargaining power the proposed model shows that the coordination of the reorder point together with order quantity can increase the overall chain profitability as well as each member s profitability

the impact of forecasting methods on the bullwhip effect abstract this paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first order autoregressive process describes the customer demand and an order up to inventory policy characterizes the replenishment decision a bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean squared forecasting error for the specified demand process similar measures are obtained for the moving average and exponential smoothing methods the findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process moreover a simple rule is established to help managers select a forecasting method that yields the lowest inventory cost

inventory control under temporal demand heteroscedasticity abstract this paper studies an inventory control problem when the variance of demand is time varying and exhibits temporal heteroscedasticity we use a first order autoregressive process to characterize the dynamic changes in the level of demand over time and a garch 1 1 structure to describe the changes in the variance of demand under these demand settings we quantify the effect of a temporal heterogeneous variance on inventory performance for a system controlled via an order up to level policy we show that the effect of temporal heteroscedasticity on the forecasting accuracy can be additively decomposed from the total forecasting error variance the decomposition is used to derive the absolute and relative cost deviations when the temporal heteroscedasticity is ignored the relationship of these cost deviations to demand autocorrelation and replenishment leadtime is investigated computational results show that ignoring temporal heteroscedasticity can increase firm s inventory costs by as much as 30 when demand autocorrelation is highly positive

a time series framework for supply chain inventory management we consider a supply chain in which the underlying demand process can be described in a linear state space form inventory is managed at various points of the chain members based on local information that each member observes and continuously updates the key feature of our model is that it takes into account the ability of the members to observe subsets of the underlying state vector and adopt their forecasting and replenishment policies accordingly this enables us to model situations in which the members are privy to certain explanatory variables of the demand with the latter possibly evolving according to a vector autoregressive time series for each member we identify an associated demand evolution model for which we propose an adaptive inventory replenishment policy that utilizes the kalman filter technique we then provide a simple methodology for assessing the benefits of various types of information sharing agreements between members of the supply chain we also discuss inventory positioning and cost performance assessment in the supply chain our performance metrics and inventory target levels are usually presented in matrix forms allowing them to accommodate a relatively large spectrum of linear demand models and making them simple to implement several illustrations for possible applications of our models are provided

taming the bullwhip effect whilst watching customer service in a single supply chain echelon we study a generalised order up to policy that has highly desirable properties in terms of order and inventory variance and customer service levels it generates we quantify exactly the variance amplification in replenishment orders i e the bullwhip effect and the variance of inventory levels over time for i i d and the weakly stationary auto regressive ar moving average ma and auto regressive moving average arma demand processes we demonstrate that high customer service as measured by fill rate and smooth replenishments need not increase inventory cost substantially we observe that in some instances of the arma demand pattern this comes at the expense of a relatively small increase in safety stock whilst in other instances inventory levels can actually be reduced

inventories stock outs and production smoothing if stock outs are ignored and if demand shocks are additive then optimal behaviour requires that the marginal cost of production mc be equated with the expected marginal revenue of increasing expected sales by one unit emr however with more general demand shocks and still ignoring stock outs the excess of mc over emr has the same sign as the covariance of the slope of the demand curve and the marginal valuation of inventory the equality of emr and mc is also broken by taking account of stock outs even if demand shocks are additive if there is a production lag then taking account of stock outs implies that optimal behaviour will be characterized by production smoothing even if the cost of production is linear two alternative definitions of production smoothing are presented and optimal behaviour in the presence of stock outs displays each type of smoothing it is a well known proposition that a firm producing a storable good under conditions of increasing marginal cost will tend to smooth the time profile of its production relative to the time profile of its sales the incentive to smooth production arises from the fact that the cost function is a convex function of the level of production for a given average level of production average costs can be reduced by reducing the variation in production of course if the cost function is linear in the level of production then this incentive to smooth production disappears however we will demonstrate in this paper that if the possibility of stock outs is explicitly incorporated into the firm s dynamic optimization problem i e if we impose a non negativity constraint on inventories and if there is a lag in production then optimal behaviour can be characterized by production smoothing even if the cost function is linear

on the calculation of safety stocks when demand is forecasted the inventory control literature generally assumes that the demand distribution and all its parameters are known in practical applications it is often suggested to estimate the demand variance either directly or based on the one period ahead forecast errors the variance of the lead time demand essential for safety stock calculations is then obtained by multiplying the estimated per period demand variance by the length of the lead time however this is flawed since forecast errors for different periods of the lead time are positively correlated even if the demand process itself does not show process auto correlation as a result these traditional procedures lead to safety stocks that are too low this paper presents corrected lead time demand variance expressions and reorder levels for inventory systems with a constant lead time where demand fluctuates around a constant level firstly we derive the exact lead time forecast error of mean demand conditional on the true demand variance secondly we derive for normally distributed demand the correct reorder level under uncertainty of both the demand mean and variance we show how the results can be implemented in inventory models and particularly discuss batch ordering policies combined with moving average and exponential smoothing forecasts we find that traditional approaches can lead to safety stocks that are up to 30 percent too low and service levels that are up to 10 percent below the target

a note on the econometric use of constant dollar inventory series abstract one dollar of finished goods inventories does not represent the same amount of physical goods as one dollar of sales when department of commerce constant dollar series are used this can cause seriously biased regression estimates

optimal policies for multiechelon inventory problems with markov modulated demand this paper considers a multistage serial inventory system with markov modulated demand random demand arises at stage 1 stage 1 orders from stage 2 etc and stage n orders from an outside supplier with unlimited stock the demand distribution in each period is determined by the current state of an exogenous markov chain excess demand is backlogged linear holding costs are incurred at every stage and linear backorder costs are incurred at stage 1 the ordering costs are also linear the objective is to minimize the long run average costs in the system the paper shows that the optimal policy is an echelon base stock policy with state dependent order up to levels an efficient algorithm is also provided for determining the optimal base stock levels the results can be extended to serial systems in which there is a fixed ordering cost at stage n and to assembly systems with linear ordering costs

a unified theory of the dynamics of closed loop supply chains we investigate the dynamics of a closed loop supply chain with first order auto regressive ar 1 demand and return processes we assume these two processes are cross correlated the remanufacturing process is subject to a random triage yield remanufactured products are considered as goodas new and used to partially satisfy market demand newly manufactured products make up the remainder we derive the optimal linear policy in our closed loop supply chain setting to minimise the manufacturer s inventory costs we show that the lead time paradox can emerge in many cases in particular the auto and cross correlation parameters and variances of the error terms in the demand and the returns as well as the remanufacturing lead time all influence the existence of the lead time paradox finally we propose managerial recommendations for manufacturers

the stabilizing effect of inventory in supply chains this paper presents a hierarchical model framework for the analysis of the stabilizing effect of inventories in multiechelon manufacturing distribution supply chains this framework is used to compare the variance of demand to the variance of replenishment orders at different echelons of the system e g retailer wholesaler empirical data and experience with management games suggest that in most industries inventory management policies can have a destabilizing effect by increasing the volatility of demand as it passes up through the chain the bullwhip effect our model helps to explain these observations and indicates mechanisms that can promote stabilization the analysis results also define sufficient conditions for the existence of stabilization and relate these conditions to the optimality of myopic control policies

making loan decisions in banks straight from the gut when a business owner approaches a bank for a loan for their business they might hope that a well established bureaucratic procedure would ensure that their application was processed with stipulated rules and impersonal criteria they might expect that two bank officials evaluating the same proposal for a loan would reach the same decision however research shows that both quantifiable data and gut feelings are used in the decision in this research analysis of interviews with senior managers and both individual and focus group interviews with bank loan officers reveals that there are no set criteria or stipulated rules the interviews demonstrate how and why nonquantifiable data is used and why different bank officials can reach different conclusions on the same loan proposal while these bank loan officers do not appear to be discriminatory against female business owners the lending criteria and process allows significant room for discrimination it appears questionable whether bank lending is seen as an ethical and fair process

analysis of the bullwhip effect in a multiproduct setting with interdependent demands the bullwhip effect has been extensively studied primarily based on the analysis of various single product models with a few exceptions we extend the single product analysis to the multiproduct setting of interdependent demand streams with auto correlation and cross product correlation as well as contemporaneous correlation across forecasting errors we find that interdependency between demand streams plays a critical role in determining the existence and magnitude of the bullwhip effect specifically we consider two operating environments a the firm orders product specific materials so that the ordering decision is based on the product level and b the firm orders generic materials so that the order decision is based on the category level we show that even with demand pooling a firm operating at the category level can experience a larger bullwhip effect and a larger order variance under certain conditions that depend on the number of products in the category and the demand dependencies

the effect of information sharing on supply chain stability and the bullwhip effect this paper analyzes the bullwhip effect in multi stage supply chains operated with linear and time invariant inventory management policies and shared supply chain information such information includes past order sequences and inventory records at all supplier stages the paper characterizes the stream of orders placed at any stage of the chain when the customer demand process is known and ergodic and gives an exact formula for the variance of the orders placed the paper also derives robust analytical conditions based only on inventory management policies to predict the presence of the bullwhip effect and bound its magnitude these results hold independently of the customer demand the general framework proposed in this paper allows for any inventory replenishment policies any ways of sharing and utilizing information and any customer demand processes it is also shown as a special case that sharing customer demand information across the chain significantly reduces but does not completely eliminate the bullwhip effect

bayes solution to dynamic inventory models under unknown demand distribution this paper considers the periodic review inventory problem for which one or more parameters of the demand distribution are unknown with a known prior distribution chosen from the natural conjugate

the production and inventory behavior of the american automobile industry understanding inventory movements is central to an understanding of business cycles this paper presents an empirical study of the behavior of inventories in the automobile industry it finds that inventory behavior is well explained by the assumption of intertemporal optimization with rational expectations the underlying cost structure appears to have substantial costs of changing production as well as substantial costs of being away from target inventory thelatter being a function of current sales given this cost structure whether inventory behavior is stabilizing or destabilizing depends on the characteristics of the demand process in the automobile industry inventory behavior is destabilizing the variance of production is larger than the variance of sales

measure of bullwhip effect in supply chains the case of high order autoregressive demand process abstract bullwhip effect the phenomenon in which variance of demand is amplified when moving upstream has attracted the attention of many researchers for the last few decades although the main sources that cause bullwhip effect have been identified quantifying the bullwhip effect still remains a challenge in the past measuring the bullwhip effect for supply chains with autoregressive demand process has been conducted by some researchers however most past researches focused mainly on the simple ar 1 model in many practical situations autoregressive models with higher order should be employed because they might better represent the demand process up to now very little effort has been spent on this matter therefore this research is conducted to fill this gap by first dealing with ar 2 demand process and investigating the behavior of the developed measure with respect to autoregressive coefficients and order lead time extension to the general ar p demand process is then considered

efficiency pricing tenancy rent control and monopolistic landlords this paper presents a model of tenancy rent control where rent increases on and evictions of sitting tenants are prohibited but nominal rents for new tenants are unrestricted if there is any inflation landlords prefer to take short staying tenants if there is no way for landlords to tell a tenant s type an adverse selection problem arises if landlords have monoply power then they may prefer not to raise the rent even when there is excess demand for housing these efficiency rents show that tenancy rent control can give rise to equilibria that look as if there were a flat ceiling on rents

a measure of bullwhip effect in supply chains with a mixed autoregressive moving average demand process abstract in this paper we quantify the impact of the bullwhip effect the phenomenon in which information on demand is distorted as moving up a supply chain for a simple two stage supply chain with one supplier and one retailer assuming that the retailer employs a base stock inventory policy and that the demand forecast is performed via a mixed autoregressive moving average model arma 1 1 we investigate the effects of the autoregressive coefficient the moving average parameter and the lead time on the bullwhip effect

value of information in capacitated supply chains we incorporate information flow between a supplier and a retailer in a two echelon model that captures the capacitated setting of a typical supply chain we consider three situations 1 a traditional model where there is no information to the supplier prior to a demand to him except for past data 2 the supplier knows the s s policy used by the retailer as well as the end item demand distribution and 3 the supplier has full information about the state of the retailer order up to policies continue to be optimal for models with information flow for the finite horizon the infinite horizon discounted and the infinite horizon average cost cases study of these three models enables us to understand the relationships between capacity inventory and information at the supplier level as well as how they are affected by the retailer s s s values and end item demand distribution we estimate the savings at the supplier due to information flow and study when information is most beneficial

gender disparity in angel financing this study uses unique hand collected data from a televised entrepreneurial pitch competition to examine gender differences in obtaining angel financing results indicate that while the yield rates between male and female teams do not differ a gender disparity in the amount of angel funding does in fact exist female teams receive less capital and provide more equity relative to their male counterparts even when controlling for typical determinants of investment such as industry and prior company success further we find that female teams receive investments with lower valuations than their male counterparts largely because they initially offer higher equity stakes for less capital thus this suggests that limitations to angel financing of female entrepreneurial ventures may be partly self imposed

inventory control in a fluctuating demand environment we present an inventory model where the demand rate varies with an underlying state of the world variable this variable can represent economic fluctuations or stages in the product life cycle for example we derive some basic characteristics of optimal policies and develop algorithms for computing them in addition we show that certain monotonicity patterns in the problem data are reflected in the optimal policies

information distortion in a supply chain the bullwhip effect this article originally appeared in management science april 1997 volume 43 number 4 pp 546 558 published by the institute of management sciences consider a series of companies in a supply chain each of whom orders from its immediate upstream member in this setting inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions this paper claims that the information transferred in the form of orders tends to be distorted and can misguide upstream members in their inventory and production decisions in particular the variance of orders may be larger than that of sales and distortion tends to increase as one moves upstream a phenomenon termed bullwhip effect this paper analyzes four sources of the bullwhip effect demand signal processing rationing game order batching and price variations actions that can be taken to mitigate the detrimental impact of this distortion are also discussed

inventories and the structure of macro models the message of this paper can be summed up in two words inventories matter they matter empirically in the sense that inventory developments are of major importance in the propagation of business cycles and they matter theoretically in the sense that recognition of their existence changes the structure of a variety of theoretical macromodels in some fairly important ways this paper is mainly about the implications of inventories for the structure of theoretical macro models but i begin by demonstrating the empirical importance of inventories in business fluctuations this abstract was borrowed from another version of this item

the variability of aggregate demand with s s inventory policies this paper develops a general theory of the aggregate implications of s s inventory policies it is shown that s s policies add to the variability of demand with the variance of orders exceeding the variance of sales overall the s s theory contradicts the widely held notion that retail inventories act as a buffer protecting manufacturers from fluctuating sales in 1951 arrow harris and marschak 3 introduced the s s form of inventory policy the policies are designed for retailers of finished goods who face economies of scale when placing orders with their suppliers to pursue an s s inventory policy the retailer establishes a lower stock point s and an upper stock point s no order is placed until inventories fall to s or below whereupon they are restored to the maximum of s a general proof of the optimality of these s s inventory policies was provided by scarf 13 at the microeconomic level the model has been extensively investigated formulae are available to compute optimal policies e g ehrhardt 6 and these policies are xidely used in industry e g schwartz ed 14 in addition the model has been extended to increasingly complex demand environments e g karlin and fabens 11 in contrast little is known about the macroeconomic implications of s s policies several recent papers have begun to correct this deficiency akerlof has suggested that pursuit of constant threshold money holding policies of the s s variety might be responsible for the observed low short run income elasticity of the demand for money akerlof 1 and akerlof and milbourne 2 in the operations research literature ehrhardt schultz and wagner 7 analyzed the demand environment of a wholesaler supplying several retailers they required that the distinct retailers have independent sales ruling out the analysis of common factors in sales finally simulation results of blinder 4 suggested a role for the s s model in understanding retail sector inventories however the theoretical difficulties with the model remained unresolved blinder commented if firms have a technology that makes the s s rule optimal aggregation across firms is inherently difficult indeed it is precisely this difficulty which has prevented the s s model from being used in empirical work to date blinder 4 p 459 in this paper we present a general theory of the aggregate implications of s s policies our central finding is that s s policies add to the variability of demand with the variance of orders exceeding the variance of sales this result holds even in the presence of common factors in retail sales in addition a close connection

the bullwhip effect progress trends and directions the bullwhip effect refers to the phenomenon where order variability increases as the orders move upstream in the supply chain this paper provides a review of the bullwhip literature which adopts empirical experimental and analytical methodologies early econometric evidence of bullwhip is highlighted findings from empirical and experimental research are compared with analytical and simulation results assumptions and approximations for modelling the bullwhip effect in terms of demand forecast delay replenishment policy and coordination strategy are considered we identify recent research trends and future research directions concerned with supply chain structure product type price competition and sustainability

reduction of the value of information sharing as demand becomes strongly auto correlated information sharing has been identified in the academic literature as one of the most important levers to mitigate the bullwhip effect in supply chains a highly cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain when the downstream demand is autoregressive of order one is an increasing function of the autoregressive parameter of the demand in this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero we also show that this maximum value of the autoregressive parameter can be as high as 0 7 which represents a common value that may be encountered in many practical contexts this means that large benefits of information sharing cannot be assumed for those stock keeping units skus with highly positively auto correlated demand instead equally careful analysis is needed for these items as for those skus with less strongly auto correlated demand

housing investment in the united states a supply determined model of housing investment is estimated from quarterly data over the 1963 83 period the model is built on dynamic marginal cost pricing considerations and allows short and long run supply elasticities to differ these are estimated as 1 0 and 3 0 respectively but most of the long run response occurs within 1 year rapid adjustment speed and the sizable long run elasticity of supply are important factors in understanding the volatility of housing investment the data also suggest some anomalies in the expected present value theory of asset pricing for housing capital

the role of forecasting on bullwhip effect for e scm applications abstract the bullwhip effect represents the information distortion in customer demand between orders to supplier and sales to the buyer demand forecasting is one of the main causes of the bullwhip effect the purpose of this study is to analyze the impact of exponential smoothing forecasts on the bullwhip effect for electronic supply chain management e scm applications a simulation model is developed to experiment the different scenarios of selecting right parameters for the exponential smoothing forecasting technique it is found that longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in e scm in contrast increased seasonality helps to reduce the bullwhip effect the most significant managerial implication of this study lies in the need to reduce lead times along the e supply chain to mitigate the bullwhip effect while high seasonality would reduce the forecast accuracy it has a positive influence on the reduction of bullwhip effect e scm managers are therefore strongly suggested to utilize exponential smoothing by selecting lower values for and and a mid value for to keep the bullwhip ratio low while at the same time to increase forecast accuracy

real estate regulations in accra some macroeconomic consequences ghana has been one of the most rapidly growing economies in sub saharan africa this growth has been aided by ghana s improving policy environment in light of this the paper addresses the question of why given its higher level of per capita income and relatively strong growth the housing conditions of the poor in accra are considerably worse than those in a number of other african cities with lower incomes there are not many data available to answer this question so the method is indirect and takes two approaches first a variant of the monocentric city model is used to calculate accra s housing supply elasticity relative to those of other similarly sized african cities the model suggests that housing supply responsiveness is considerably lower in accra a result consistent with the observed higher housing costs secondly a number of traditional housing demand and reduced form equations are estimated for accra and the other cities this allows the formation of a quantitative judgment about accra

comparing the information acquisition strategies of venture capital and commercial lenders a computer based experiment abstract owners and financial planners in new ventures prefer using internal sources of capital as much as possible because they are uncertain about how to obtain external financing and how the involvement of others will impact their ventures because undercapitalization and financial problems are at the center of nearly all business failures it would appear useful for owners and financial planners to reduce the uncertainty surrounding external financing obtaining information about one source of this uncertainty a lack of understanding of the decision processes followed by venture capitalists is the focus of research in this paper and a growing body of literature to further this line of study we investigate the differences in decision behavior of venture capitalists using bankers as a benchmark for comparison in cases in which debt and debt related financing are sought to the extent that venture capitalists have unique decision processes owners and financial planners might improve their ability to obtain financing through knowledge of the unique features of venture capitalists decision processes in addition venture capitalists might improve their decision effectiveness if made aware of systemic biases in their decision procedures using a computer software package to trace information acquisition processes we found that venture capitalists acquired less information and followed a pattern of acquisition that was deeper within categories of information than bankers in addition venture capitalists showed a stronger preference for strategic data and less interest in historical financial data both groups minimized the use of financial forecasts and followed decision processes persistently across different types of companies start up and well established the implications of this study for practice are two fold first if the owners or financial planners of a new or relatively new venture are seeking financing from external sources they should package the business plan and request in a manner that is consistent with the source of financing for example requests from venture capitalists should highlight strategic information such as descriptions of the product or process patentability prospects product market and management team less emphasis should be placed on financial information particularly financial projections in contrast requests for financing by banks should highlight historical financial information such differences between venture and bank financing may lead individuals who are seeking financing to conclude that because historical financial information is of primary importance to bankers bank financing should be sought after the business has developed a positive financial history and trend this would confirm intuition and research findings that venture financing is the primary source of external financing in the early stages of a new venture second bankers and venture capitalists like all decision makers who have developed a degree of expertise in a particular specialty should attempt to gain some insight into their decision processes the goal of obtaining this information would be to provide feedback on processes such as information acquisition which tend to become automatic over time with this knowledge bankers and venture capitalists could examine any biases in their behavior with the ultimate goal of improving performance this paper also has important implications for researchers in particular we have demonstrated that computer based approaches for studying decision behavior offer promise for interesting explorations into important issues such as how venture capitalists make decisions the computer minimizes researcher intrusion in the decision task and permits the collection of process data from samples large enough to permit statistical analyses in addition the subjects determine the length of the task and the direction of the search much as they would in practice which increases the external validity of the research method

an arima supply chain model this paper presents a multistage supply chain model that is based on autoregressive integrated moving average arima time series models given an arima model of consumer demand and the lead times at each stage it is shown that the orders and inventories at each stage are also arima and closed form expressions for these models are given the paper also discusses the causes of the bullwhip effect a phenomenon in which variation in demand produces larger variations in upstream orders and inventory this discussion reveals how different modeling can lead to different insights because they make different assumptions about the cause of the bullwhip effect these observations are used to develop managerial insights about reducing the bullwhip effect

modeling and analysis of cash flow bullwhip in supply chain abstract the bullwhip effect that occurs in supply chain inventory can distort demand forecasts and lead to inefficiencies such as excessive inventory stock outs and backorders in this paper we theorize that inventory bullwhip also leads to cash flow bullwhip cfb specifically this paper focuses on studying cfb by developing mathematical and simulation models to analyze the relationship between inventory and cash flow bullwhip by using cash conversion cycle ccc as a metric the mathematical models for inventory bullwhip are developed for two stage and generic multi stage supply chains and then by extending these inventory models the cfb models are developed for two stage cfb predicted by the proposed mathematical models approximately differ 14 from detailed simulation models we find that increasing variability increases inventory and cash flow bullwhip along with lead time whereas increasing the demand observation period has the opposite effect the average marginal impact of the bullwhip effect on the cfb is approximately 20 additionally the cfb is also an increasing function of an expected value of inventory and a decreasing function of an expected value of demand

the bullwhip effect in supply chain networks this paper analyzes the propagation and amplification of order fluctuations i e the bullwhip effect in supply chain networks operated with linear and time invariant inventory management policies the supply chain network is allowed to include multiple customers e g markets any network structure with or without sharing information the paper characterizes the stream of orders placed by any supplier for any stationary customer demand processes and gives exact formulas for the variance of the orders placed and the amplification of order fluctuations the paper also derives robust analytical conditions based only on inventory management policies to predict the presence of the bullwhip effect for any network structure any inventory replenishment policies and arbitrary customer demand processes numerical examples show that the analytical results accurately quantify the bullwhip effect managerial insights are drawn from the analysis the methodology presented in this paper generalizes those in previous studies for serial supply chains

inventories and sticky prices note in a recent contribution to this review alan blinder provides an interesting analysis of the relationship between optimal inventory decisions and the process of price adjustment arguing that inventory permits separation of production and sale decisions and allows the firm greater flexibility in responding to anticipated demand disturbances blinder shows that the responsiveness of relative prices depends critically upon the cost of storage and the temporal structure of the demand shocks few economists would fault the intuitive substance of blinder s basic proposition and the proposition is justified with characteristic precision the analysis however is considerably less general than blinder maintains the formal argument of his paper relies upon a simple model of a monopolist capable of backlogging orders and storing unsold goods as the model is constructed order backlogs assume a role of fundamental importance in any stationary equilibrium this feature of the model vitiates blinder s extension of his result to situations in which order backlogs are prohibited the basic monopoly model developed in sections i and ii of blinder s paper places no restriction upon the sign of inventory negative inventory is interpreted as net unfilled orders while no distinction is drawn between reductions in gross inventory and additions to the order backlog as a result the cost of holding inventory is symmetric around an arbitrary minimum point the only role of inventory is to permit the time paths of production and sales to differ gross inventory allows production to antedate sales while order backlogs generate revenue before production costs are borne under these circumstances if future costs and revenues are discounted it is natural to expect any stationary equilibrium level of net inventory to be negative this can be shown to be true of blinder s model it is useful to distinguish in general between the nonstochastic stationary level of inventory n and the stochastic stationary level n the former is realized when the current expected demand disturbance eo is zero and production equals sales the latter which differs from customary usage represents the level of inventory expected to prevail when adjustment to the current nonzero expected demand disturbance is complete if the demand disturbance is not a random walk so that p 1 in blinder s 5 the two equilibria coincide relatively little attention is devoted to either stationary solution because blinder s main interest is in the optimal current solution level n1 the stochastic stationary level is crucially important however since it represents the goal toward which the current choice must provide an optimal first step to verify that both nand n are negative whenever production is strictly positive note that blinder s necessary condition 7 with the coefficient cl set equal to zero together with the definition of xa as the deviation of the shadow value of inventory q from its nonstochastic stationary value q implies

research on bullwhip effect in energy efficient air conditioning supply chain abstract this paper investigates the energy efficient air conditioning supply chain which is composed of one supplier midea and two retailers i e suning and gome with a view of market share we measure the impact of retail prices variability in the two echelon supply chain on the bullwhip effect suning and gome are assumed to possess the autonomy of choosing prices and separately acquire various market shares according to which the relationship between the two prices is simply quantified the order up to inventory policy and the moving average forecasting method are respectively employed by the two retailers furthermore we cast light on how factors like price market share lead time and autoregressive coefficient affect bullwhip effect the results indicate that it s inadvisable to conduct large fluctuation on price besides demand dates that are more historical may actually reduce the bullwhip effect we also find that the bullwhip effect will be bigger when the competition becomes fiercer and there s a necessity for retailers to take measures to reduce the influence of competitors prices

analysis of the bullwhip effect in two parallel supply chains with interacting price sensitive demands abstract this paper offers insights into how the bullwhip effect in two parallel supply chains with interacting price sensitive demands is affected in contrast to the situation of a single product in a serial supply chain in particular this research studies two parallel supply chains each consisting of a manufacturer and a retailer and the external demand for a single product depends on its price and the other s price in a situation in which each price follows a first order autoregressive process in this paper we propose an analytical framework that incorporates two parallel supply chains and we explore their interactions to determine the bullwhip effect we identify the conditions under which the bullwhip effect is amplified or lessened with interacting price sensitive demands relative to the situation without interaction

inventories and the volatility of production a stylized fact associated with inventory behavior is that the variance of production exceeds the variance of sales this paper presents a model of production decisions with demand uncertainty that incorporates no nnegativity constraints on inventories even with no productivity shocks optimal behavior by the firm is consistent with this stylized fact either if demand exhibits positive serial correlation or if the firm can backlog excess demand the reason is that a demand shock affects both the actual inventory level given unchanged production and the desired level production must replenish the stock and adjust to the new desired level copyright 1987 by american economic association

conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing abstract a reverse bullwhip effect in pricing rbp occurs when an amplification of price variability takes place moving from the upstream suppliers to the downstream customers in a supply chain in this study we investigate rbp conditions for supply chains where joint replenishment and pricing decisions are made commencing with a single stage supply chain in which a retailer faces a random and price sensitive demand we extend the results to a multi stage supply chain using a leader follower game theoretical framework we discuss rbp conditions for supply chains where newsvendor and continuous review inventory policies are employed and present numerical examples for commonly used demand functions

funding new business ventures are decision makers biased against women entrepreneurs abstract women have been leaving large corporations in increasing numbers in recent years to start their own businesses however they have not been succeeding at the same rate as their male counterparts one potential barrier to a successful new venture is access to startup capital anecdotal evidence suggests that women starting their own businesses may have more difficulty obtaining financial support than men in a loan decision simulation this study systematically tested the allegations of female entrepreneurs that bank loan officers are more likely to grant loans to make a counteroffer and to make larger counteroffers to male entrepreneurs compared to female entrepreneurs under identical circumstances loan officers usually make funding decisions on the basis of information gathered from an interview and a business plan while venture capitalists often screen proposals on the basis of a business plan alone a second purpose of this study was to determine whether the mode of presentation business plan versus business plan with interview increased the male or female entrepreneur s probability of successfully obtaining a loan a third purpose of this study was to examine the effects of the decision maker s previous experience on funding decisions the recommendations of experienced loan officers versus inexperienced undergraduate students were compared in order to determine how experience and accountability influence loan decisions the study consisted of a 2 2 2 research design with three independent variables loan officers and undergraduate students either read a business plan or read a business plan and watched a videotape of an interview between a loan officer and a male or female entrepreneur who was seeking a loan to start a business participants then indicated the likelihood that they would recommend approval of the loan make a counteroffer of a smaller amount and the magnitude of the counteroffer there was no evidence that sex stereotypes influenced business funding decisions with respect to the amount of counteroffer a significant three way interaction was obtained between entrepreneurial gender presentation format and participant status loan officers made larger counteroffers to the female compared to the male when they read the business plan and watched the interview students made larger counteroffers to the male compared to the female when they read the business plan and observed the interview loan officers were significantly more cautious and conservative than students in their funding decisions failure to support allegations of bias against women entrepreneurs is discussed in terms of possible unrealistic expectations regarding the ease of obtaining startup capital further research is needed to examine this explanation one implication of these findings is that female entrepreneurs should seek opportunities to meet with loan officers to present their business proposals in the interview the female has the opportunity to address questions of motivation and competence on the other hand bankers may make more impartial decisions when relying on information in the business plan alone where financial considerations would have greater weight finally the results suggest that studies using students as proxies for bank loan officers have very limited generalizability

an empirically simulated investigation of the impact of demand forecasting on the bullwhip effect evidence from u s auto industry this study empirically examines the impacts of three major aspects of demand forecasting on the magnitude of the bullwhip effect three research questions are addressed to investigate the association between 1 forecast accuracy 2 aggregate forecasting and 3 responsive forecasting and the bullwhip effect using forecasted demand generated from popular time series forecasting models and real life demand data the study investigates the relationship between the forecasted results and the consequential bullwhip effect the findings show that the forecasting methods used lead to the variation of the bullwhip effect moreover the lead time reduction and the stable demand forecast are beneficial to reduce the bullwhip effect however our empirical results differ from previous findings in two ways i improving forecast accuracy does not necessarily reduce the bullwhip effect and ii aggregate forecasting does not always reduce the bullwhip effect

the multivariate bullwhip effect abstract a multivariate bullwhip expression for m products with an order up to inventory policy is developed the demand models under consideration are differenced stationary vector time series with a wold representation for which general forecasting formulas are available resulting in a large class of possible models including nonstationary ones examples are provided for common demand models and implemented on sales data it is found that the multivariate approach gives rise to mechanisms for understanding and reducing the bullwhip effect through horizontal information sharing particularly for the nonstationary demand case in the stationary setting a more nuanced approach to bullwhip reduction can be achieved by managing the relationship between cross correlations and lead times a method of determining whether a multivariate or univariate approach generates a lower bullwhip effect is proposed

managing supply chain demand variability with scheduled ordering policies this paper studies supply chain demand variability in a model with one supplier and n retailers that face stochastic demand retailers implement scheduled ordering policies orders occur at fixed intervals and are equal to some multiple of a fixed batch size a method is presented that exactly evaluates costs previous research demonstrates that the supplier s demand variance declines as the retailers order intervals are balanced i e the same number of retailers order each period this research shows that the supplier s demand variance will generally decline as the retailers order interval is lengthened or as their batch size is increased lower supplier demand variance can certainly lead to lower inventory at the supplier this paper finds that reducing supplier demand variance with scheduled ordering policies can also lower total supply chain costs

impacts of forecast inventory policy and lead time on supply chain inventory a numerical study abstract this paper first proposes the use of metaheuristic to combine with exponential smoothing methods in forecasting future demands and in determining the optimal inventory policy values for each node in a supply chain network based on historical demand or order streams without the need of any prior knowledge about the demand distribution or distribution fitting the effects of five demand forecasting methods two inventory policies and three lead times on the total inventory cost of a 3 echelon serial supply chain system are then investigated the effect of sharing the demand information for planning the inventories is also compared with that of no sharing for testing 15 quarterly and 15 monthly time series were taken from the m3 competition and are considered as the multi item demand streams to be fulfilled in the supply chain the results indicate that 1 the damped pegel forecasting method is the best in terms of prediction errors because it outperforms others in three of five measures followed by the simple exponential smoothing that wins one of the remaining two and ties the damped pegel in one 2 the supply chain inventory cost increases with increasing lead time and echelon level of the supply chain when the s s policy is used but not the r q policy 3 the r q inventory policy generally incurs lower supply chain inventory cost than the s s policy 4 sharing demand information reduces inventory cost and the reduction is higher for s s than for r q 5 the best demand forecasting method for minimizing inventory cost varies with the inventory policy used and lead time and 6 the correlation between forecasting errors and inventory costs is either negligible or minimal

demand fluctuation and chaotic behaviour by interaction between customers and suppliers this paper presents an investigation on simulation of interaction between customers and suppliers in a three tier supply chain system in the simulation customers respond to the price discount offer made by the supplier and the supplier makes adjusts the price according to stock held the simulation shows that the behaviour of such interaction exhibits deterministic chaos it is found that the attractors of the model move with the environment and the initial states thus the bifurcating points in such a system are unable to provide a guideline in system design to avoid chaos

coordinating lead times and safety stocks under autocorrelated demand we consider a supply chain in which orders and lead times are linked endogenously as opposed to assuming lead times are exogenous this assumption is relevant when a retailer s orders are produced by a supplier with finite capacity and replenished when the order is completed the retailer faces demands that are correlated over time either positively or negatively which may for example be induced by a pricing or promotion policy the auto correlation in demand affects the order stream placed by the retailer onto the supplier and this in turn influences the resulting lead times seen by the retailer since these lead times also determine the retailer s orders and its safety stocks which the retailer must set to cover lead time demand there is a mutual dependency between orders and lead times the inclusion of endogenous lead times and autocorrelated demand represents a better fit with real life situations however it poses some additional methodological issues compared to assuming exogenous lead times or stationary demand processes that are independent over time by means of a markov chain analysis and matrix analytic methods we develop a procedure to determine the distribution of lead times and inventories that takes into account the correlation between orders and lead times our analysis shows that negative autocorrelation in demand although more erratic improves both lead time and inventory performance relative to iid demand positive correlation makes matters worse than iid demand due to the endogeneity of lead times these effects are much more pronounced and substantial error may be incurred if this endogeneity is ignored

a novel time varying bullwhip effect metric an application to promotional sales abstract bullwhip effect is a problem of paramount importance that reduces competitiveness of supply chains around the world a significant effort is being devoted by both practitioners and academics to understand its causes and to reduce its pernicious consequences nevertheless limited research has been carried out to analyse potential metrics to measure it that typically are summarized in the coefficient of variation ratio of different echelons demand this work proposes a new metric based on a time varying extension of the aforementioned bullwhip effect metric by employing recursive estimation algorithms expressed in the state space framework to provide at each single time period a real time bullwhip effect estimate in order to illustrate the results a case study based on a serially linked supply chain of two echelons from the chemical industry is analysed particularly this metric is employed to analyse the effect of promotional campaigns on the bullwhip effect on a real time fashion the results show that effectively the bullwhip effect is not constant along time but interestingly it is reduced during the promotional periods and it is bigger before and after the promotion takes place

impact of market demand mis specification on a two level supply chain this paper investigates the impact of mis specifying the market demand process on a serially linked two level supply chain box jenkins models are used to represent both the true and a mis specified market demand processes it is shown that the impact of mis specification on cost is minor if the supply chain tries to minimise the market demand forecast errors furthermore our analysis suggests that mis specification does not always result in additional costs a managerial insight is revealed poor forecast accuracy is not always bad for the total supply chain costs in other words employing more accurate forecasting methods may actually result in higher total supply chain costs

stochastic financial analytics for cash flow forecasting abstract accurate cash flow forecasting is essential for successful management of firms and it becomes especially critical during uncertain market and credit conditions without accurate cash flow forecasting a firm may fail to meet its short term obligations and risk bankruptcy accurate cash flow forecasting can be limited by a number of factors including changes in macro economic conditions that influence liquidity in the economy customer payment behavior that can vary from time to time as well by industry and dynamics of the particular supply chain itself we develop stochastic financial analytics for cash flow forecasting for firms by integrating two models 1 markov chain model of the aggregate payment behavior across all customers of the firm using accounts receivable aging and 2 bayesian model of individual customer payment behavior at the individual invoice level as the stochastic dynamics of cash flow evolves every day the forecast can be updated every time an invoice is paid the proposed model is back tested using empirical data from a small manufacturing firm and found to differ 3 6 from actual monthly cash flow and differs approximately 2 4 compared to actual annual cash flow the forecast accuracy of the proposed stochastic financial analytics model is found to be considerably superior to other techniques commonly used furthermore in computer simulation experiments the proposed model is found to be largely robust to supply chain dynamics including when subjected to severe bullwhip effect the proposed model has been implemented in excel which allows it to be easily integrated with the accounts receivable aging data making it practicable for small and large firms

the bullwhip effect in capacitated supply chains with consideration for product life cycle aspects abstract this paper presents an analysis of the bullwhip effect and net stock amplification in a three echelon supply chain considering step changes in the production rates during a product s life cycle demand the analysis is focused around highly complex and engineered products e g automobiles that have relatively long production life cycles and require significant capital investment in manufacturing using a simulation approach we analyze three stages of the product life cycle including low volumes during product introduction peak demand and eventual decline toward the end of the life cycle parts of the simulation model have been adopted by a major north american automotive oem as part of a scenario analysis tool for strategic supply network design and analysis the simulation results show that performance of a system as a whole deteriorates when there is a step change in the life cycle demand while restriction in production capacity does not significantly impact the bullwhip effect it increases the net stock amplification significantly for the supply chain setting under consideration furthermore a number of important managerial insights are presented based on sensitivity analysis of interaction effect of capacity constraints with other supply chain parameters

the demand for housing in developing countries empirical estimates from household data cities in developing countries are growing at extraordinary rates often compressing into decades the urbanization process that has taken centuries in developed countries in coping with this growth public authorities have devised a wide range of policy instruments to influence the rate and character of city expansion to meet the needs of people for shelter and urban services and to allocate resources in ways that redistribute both the costs and benefits of urban growth ideally such policy formulation should be informed by a careful understanding of the behavior of urban markets in fact little information on market behavior is available to the policymakers of developing countries such basic information is needed for improved project design and even more important for improved sector wide policies this paper reports on research conducted at the world bank to increase understanding of developing country housing markets in particular of housing demand behavior while the overall project examines both the demand for housing characteristics and the demand for housing as a composite good this paper addresses only the latter the objectives of this paper are 1 to review briefly previous evidence on housing demand parameters in developing countries 2 to present new evidence on housing demand parameters based on application of standardized models and comparable variable definitions in 16 cities in eight developing countries colombia egypt el salvador ghana india jamaica korea and the philippines and 3 to examine similarities and differences among cities in housing demand and in a preliminary way offer explanations for place to place differences limited comparisons are also made to two u s cities in order to begin comparison of developing and developed country market behavior

british planning policy and access to housing some empirical estimates there is evidence that the implementation of the planning system creates scarcity rents for land in different uses by acting as a constraint on land supply this paper provides for 1984 estimat

bullwhip effect measurement and its implications the bullwhip effect or demand information distortion has been a subject of both theoretical and empirical studies in the operations management literature in this paper we develop a simple set of formulas that describe the traditional bullwhip measure as a combined outcome of several important drivers such as finite capacity batch ordering and seasonality our modeling framework is descriptive in nature as it features certain plausible approximations that are commonly employed in practical inventory systems the results are nonetheless compelling and can be used to explain various conflicting observations in previous empirical studies building on the theoretical framework we discuss the managerial implications of the bullwhip measurement we show that the measurement can be completely noninformative about the underlying supply chain cost performance if it is not linked to the operational details such as decision intervals and leadtimes specifically we show that an aggregated measurement over relatively long time periods can mask the operational level bullwhip in addition we show that masking also exists under product or location aggregation in some illustrative cases

the effect of replenishment policies on the bullwhip effect a transfer function approach an important phenomenon in supply chain management known as the bullwhip effect suggests that demand variability increases as one moves up a supply chain this paper examines the influence of different replenishment policies on the occurrence of the bullwhip effect the paper demonstrates that certain replenishment policies can in themselves be inducers of the bullwhip effect while others inherently lower demand variability the main causes of increase in variability are projections of future demand expectations which result in over exaggerated responses to changes in demand we suggest that through appropriate selection and use of certain replenishment rules the bullwhip effect can be avoided subsequently allowing supply chain management costs to be lowered

inventory performance under staggered deliveries and autocorrelated demand production plans often span a whole week or month even when independent production lots are completed every day and service performance is tallied daily such policies are said to use staggered deliveries meaning that the production rate for multiple days are determined at a single point in time assuming autocorrelated demand and linear inventory holding and backlog costs we identify the optimal replenishment policy for order cycles of length p with the addition of a once per cycle audit cost we optimize the order cycle length p via an inverse function approach in addition we characterize periodic inventory costs availability and fill rate as a consequence of staggering deliveries the inventory level becomes cyclically heteroskedastic this manifests itself as ripples in the expected cost and service levels nevertheless the cost optimal replenishment policy achieves a constant availability by using time varying safety stocks this is not the case with suboptimal constant safety stock policies where the availability fluctuates over the cycle

economics of multihabitation housing conditions household occupancy and household structure under rent control inflation and nonmarketability of ownership rights abstract multihabitation in terms of sharing facilities in a dwelling or extended family occupancy is common in parts of the third world this paper uses the ghanaian housing market to assess the impact of multihabitation on house condition and on household occupancy rates per room as distinct from the influence of other factors on these variables multivariate statistical techniques form the method of analysis and the models have a high predictive accuracy the impacts of current government policies such as rent control on house condition and occupancy rates is also discussed along with cultural attitudes to ownership and obligations to the extended family

inventories and sticky prices more on the microfoundations of macroeconomics the role of inventories in making prices sticky is studied by analyzing a dynamic linear quadratic model of a monopoly firm facing stochastic demand but able to store its finished goods in inventory it is shown that in contrast to the usual presumption firms that exhibit the smallest output responses to demand fluctuations may also exhibit the smallest price fluctuations specifically firms which have very flexible inventory storage facilities or are subjected to very transitory demand shocks will rely on inventories as buffers and will change neither production nor price very much on the other hand firms which have very inflexible storage facilities or whose demand shocks are quite permanent will display large swings in both price and output the standard assumption about inventory carrying costs that has been used in the literature that they are linear is shown to imply that production is impervious to fluctuations in demand it is also established that prices may respond more strongly to positive demand shocks than to negative ones if it is impossible to hold negative inventories i e to have unfilled orders the model offers an explanation for stickiness in relative prices however under certain circumstances it may help explain the persistence of inflation this abstract was borrowed from another version of this item

can the production smoothing model of inventory behavior be saved the production smoothing model of inventory behavior has a long and venerable history and theoretical foundations that seem very strong yet certain overwhelming facts seem not only to defy explanation within the production smoothing framework but actually to argue that the basic idea of production smoothing is all wrong most prominent among these is the fact that the variance of detrended production exceeds the variance of detrended sales this paper first documents the stylized facts then it derives the production smoothing model rigorously and explains how the model can be amended to make it consistent with the facts finally it reviews the theoretical and empirical evidence and tries to draw some tentative conclusions

characterization of the bullwhip effect in linear time invariant supply chains some formulae and tests the authors analyze the bullwhip effect in multistage decentralized supply chains operated with linear and time invariant inventory management policies the focus is on robustness the supply chain is modeled as a single input single output control system driven by arbitrary customer demands the authors derive robust analytical conditions to predict the presence of the bullwhip effect and bound its magnitude based only on the way inventories are managed these results hold independently of the customer demand the authors also characterize the stream of orders placed at any stage of the chain when the customer demand process is known and ergodic and give an exact formula for the variance of the orders placed this formula generalizes existing results by broadening the class of inventory replenishment policies and customer demand processes to which it applies the authors also show that the bullwhip effect can be mitigated by introducing commitments for future orders into the ordering policies

measuring and avoiding the bullwhip effect a control theoretic approach an important contributory factor to the bullwhip effect i e the variance amplification of order quantities observed in supply chains is the replenishment rule used by supply chain members first the bullwhip effect induced by the use of different forecasting methods in order up to replenishment policies is analysed variance amplification is quantified and we prove that the bullwhip effect is guaranteed in the order up to model irrespective of the forecasting method used thus when production is inflexible and significant costs are incurred by frequently switching production quantities up and down order up to policies may no longer be desirable or even achievable in the second part of the paper a general decision rule is introduced that avoids variance amplification and succeeds in generating smooth ordering patterns even when demand has to be forecasted the methodology is based on control systems engineering and allows important insights to be gained about the dynamic behaviour of replenishment rules