a new decision rule for lateral transshipments in inventory systems this paper deals with a single echelon inventory system consisting of a number of parallel local warehouses facing compound poisson demand there are standard holding and backorder costs as well as ordering costs at all warehouses normally the warehouses replenish from an outside supplier however lateral transshipments between the warehouses are also possible such transshipments take no time but incur additional costs when a demand occurs at a warehouse the question is whether the whole demand or part of it should be covered by a lateral transshipment from another warehouse given a set of alternative decisions our decision rule minimizes the expected costs under the assumption that no further transshipments will take place this rule is then used repeatedly as a heuristic a simulation study illustrates how the suggested technique performs under different conditions

reducing the mean supply delay of spare parts using lateral transshipments policies lateral transshipment has been studied lately as a promising policy for increasing the performances of multi echelon spare parts inventory system by lateral transshipment spare parts can be moved from one location with excess inventory to another location at the same echelon in shortage with the aim of reducing supply delays of spare parts this paper will examine the relative effectiveness of two lateral shipments approaches in reducing the mean supply delay msd of a non repairable item with respect to a classical policy of no lateral shipments a simulation model of a two echelon supply network has been implemented and an experiment has been performed by varying different parameters of the supply network such as the number of warehouses locations at the lower echelon the supply lead time from the central depot the spare parts demand uncertainty and the size variability of the warehouses results show appreciable reductions of msd when lateral shipments are allowed with respect to the classical policy in almost every network configuration

enhanced lateral transshipments in a multi location inventory system in managing an inventory network two approaches to the pooling of stock have been proposed reactive transshipments respond to shortages at a location by moving inventory from elsewhere within the network while proactive stock redistribution seeks to minimize the chance of future stockouts this paper is the first to propose an enhanced reactive approach in which individual transshipments are viewed as an opportunity for proactive stock redistribution we adopt a quasi myopic approach to the development of a strongly performing enhanced reactive transshipment policy in comparison to a purely reactive approach to transshipment service levels are improved while a reduction in safety stock levels is achieved the aggregate costs incurred in managing the system are significantly reduced especially so for large networks moreover an optimal policy is determined for small networks and it is shown that the enhanced reactive policy substantially closes the gap to optimality

two interval inventory allocation policies in a one warehouse n identical retailer distribution system for a system of n identical retailers we construct a model for determining warehouse inventory allocation policies which minimize system lost sales per retailer between system replenishments an allocation policy is specified by a the number of withdrawals from warehouse stock b the intervals between successive withdrawals c the quantity of stock to be withdrawn from the warehouse in each interval and d the division of withdrawn stock among the retailers we show that in the case of two withdrawals available stock in each interval should be divided to balance retailer inventories we also develop an infinite retailer model and use it to determine two interval allocation heuristics for n retailer systems simulation tests suggest that the infinite retailer heuristic policies are near optimal for as few as two retailers simulation tests indicate that the risk pooling benefits of allocation policies with two well chosen intervals are comparable to those of base stock policies with four equal intervals

a semi markov decision problem for proactive and reactive transshipments between multiple warehouses abstract lateral transshipments are an effective strategy to pool inventories we present a semi markov decision problem formulation for proactive and reactive transshipments in a multi location continuous review distribution inventory system with poisson demand and one for one replenishment policy for a two location model we state the monotonicity of an optimal policy in a numerical study we compare the benefits of proactive and different reactive transshipment rules the benefits of proactive transshipments are the largest for networks with intermediate opportunities of demand pooling and the difference between alternative reactive transshipment rules is negligible

cointegration analysis of german and british tourism demand for greece abstract germany and great britain are traditionally two of the most important sources of tourism for greece the purpose of this paper is to investigate changes in the long run demand for tourism to greece by these two countries in order to explain the demand for tourism we are using a number of leading macroeconomic variables including income in origin countries germany and great britain tourism prices in greece and transportation cost and exchanges rates between the three countries annual data from the three countries covering the period from 1960 to 2000 are employed augmented dickey fuller test for unit root is examined in the univariate framework and johansen s maximum likelihood procedure is used to test the cointegration method and to estimate the number of cointegrating vectors of var model error correction models are estimated to explain german and british demand for tourism to greece

forecasting international tourist flows to australia a comparison between the direct and indirect methods this paper compares between the use of direct and indirect forecasting of international tourist flows to australia the indirect method is applicable when time series is a contemporaneous aggregate of others which is often the case for tourist flows time series in this case forecasts are generated by aggregating those of the component variables of aggregation an alternative is the direct method whereby forecasts are generated directly from the aggregated variable this paper uses seasonal arima models regression based models and harvey s structural time series models to compare the accuracy of the two forecasting methods we find evidence strongly in favour of the indirect method using monthly time series for international tourist arrivals to australia

risk pooling along a fixed delivery route using a dynamic inventory allocation policy this paper examines static and dynamic policies for replenishing and allocating inventories amongst n retailers located along a fixed delivery route each retailer faces independent normally distributed period demand and incurs a proportional holding or backorder cost on end of period net inventory a warehouse places a system replenishment order every m periods which is received after a fixed leadtime of t periods immediately upon receipt a delivery vehicle leaves the warehouse with the system replenishment quantity and travels to the retailers along a fixed route with fixed leadtimes between successive retailers the warehouse holds no inventory under the static policy allocations are determined for all retailers simultaneously at the moment the delivery vehicle leaves the warehouse under the dynamic policy allocations are determined sequentially upon arrival of the delivery vehicle at each retailer our major analytical results under appropriate dynamic static allocation assumptions are 1 optimal allocations under each policy involve bringing each retailer s normalized inventory to a corresponing normalized system inventory 2 optimal system replenishments are base stock policies 3 the minimum expected cost per cycle of dynamic static policy can be derived from an equivalent dynamic static composite retailer given this we prove that the risk pooling incentive a simple measure of the benefit from adopting dynamic allocation policies is always positive our simulation tests confirm that dynamic allocation policies yield lower costs than static policies regardless of whether or not their respective allocation assumptions are valid however the magnitude of the cost savings is very sensitive to some system parameters

the effects of selling packaged goods on inventory decisions in this paper we study within a newsboy type modeling framework the common business practice of retail firms to sell products not only as independent items but also as part of multiproduct packets packaged goods our emphasis is on understanding the effects of such practices on the inventory decisions of the firm we provide insights on the resulting level of suboptimality when inventory decisions are made with demand information only on the independent items and without accounting for the demand substitution structure induced between independent items and packaged goods our stylized model studies an environment with two products that are not direct substitutes for each other sold either independently or as part of a packet that contains one unit of each we provide necessary and sufficient optimality conditions for this model and suggest an efficient numerical search for obtaining the optimal stocking levels an extensive computational study allowed us to provide insights on the nature of the optimal stocking policies the suboptimality of independent newsboy policies the effects of demand correlation among individual products and multiproduct packets and the determining role of induced substitution structure among products during stockout occasions on the profitability of the inventory system

dynamic capacity management with substitution we examine a multiperiod capacity allocation model with upgrading there are multiple product types corresponding to multiple classes of demand and the firm purchases capacity of each product before the first period within each period after demand arrives products are allocated to customers customers who arrive to find that their product has been depleted can be upgraded by at most one level we show that the optimal allocation policy is a simple two step algorithm first use any available capacity to satisfy same class demand and then upgrade customers until capacity reaches a protection limit so that in the second step the higher level capacity is rationed we show that these results hold both when all capacity is salvaged at the end of the last demand period as well as when capacity can be replenished in the latter case an order up to policy is optimal for replenishment although finding the optimal protection limits is computationally intensive we describe bounds for the optimal protection limits that take little effort to compute and can be used to effectively solve large problems using these heuristics we examine numerically the relative value of strictly optimal capacity and dynamic rationing the value of perfect demand information and the impact of demand and economic parameters on the value of optimal substitution

approximate dynamic programming for lateral transshipment problems in multi location inventory systems abstract companies commonly allocate their inventories across multiple locations based on their historical sales rates however random fluctuations in customer purchases such as those caused by weather conditions and other external factors might cause significant deviations from expected demand leading to excess stock in some locations and stockouts in others to fix this mismatch companies often turn to lateral transshipments e g the movement of stock between locations of the same echelon in this paper we examine multi location inventory systems under periodic review with multiple opportunities for proactive transshipments within one order cycle if stockouts occur demand is lost with no opportunity to backorder the objective of our model is to find an optimal policy that indicates the sources and the destinations of transshipments as well as the number of units to maximise the profit of the network we create a dynamic program that can in principal be solved to optimality using bellman s equation however the size of the state and decision spaces makes it impossible to find the optimal policy for real world sized problem instances thereby we use forward approximate dynamic programming to find a near optimal transshipment policy finally we conduct an extensive numerical study to gauge the performance of our transshipment policy for small size instances we compare our policy to the optimal one for larger scale instances we consider other practically oriented heuristics our numerical experiments show that our proposed algorithm performs very well compared to state of the art methods in the literature

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

concentration changes and large firm small firm efficiency differences evidence from us manufacturing industries 1990 concentration changes and large firm small firm efficiency differences evidence from us manufacturing industries applied economics vol 22 no 1 pp 131 142

the routed inventory pooling problem with three non identical retailers abstract we consider a single period inventory problem with three non identical retailers in which items can be pooled at a predetermined point in time since multiple items are often pooled with a single visit to each retailer we use a predetermined shortest route for redistribution we derive cost expressions for this routed pooling policy as well as for the no pooling and complete pooling policies which serve as benchmarks in a numerical investigation we analyze how much of the pooling benefits can be captured if the route for redistribution is fixed furthermore we investigate how stock is distributed among retailers at the beginning of the period and we look into the influence of a retailer s size and position in the route on expected costs

cost competition new evidence on an old issue the relation between cost changes and market share changes is examined for five size ranked cohorts of firms in us manufacturing industries cost reductions are expected to yield market share increases via associated price reductions it was found that this is indeed the case although the realation is not strong a 10 cost reduction produces roughly a 2 market share increase an estimated which for various reason is most likely a lower bound cost reductions are also associated with both price reductions and price cost margin increases

tourism demand modelling and forecasting a review of recent research abstract this paper reviews the published studies on tourism demand modelling and forecasting since 2000 one of the key findings of this review is that the methods used in analysing and forecasting the demand for tourism have been more diverse than those identified by other review articles in addition to the most popular time series and econometric models a number of new techniques have emerged in the literature however as far as the forecasting accuracy is concerned the study shows that there is no single model that consistently outperforms other models in all situations furthermore this study identifies some new research directions which include improving the forecasting accuracy through forecast combination integrating both qualitative and quantitative forecasting approaches tourism cycles and seasonality analysis events impact assessment and risk forecasting

price leadership and dynamic aspects of oligopoly in u s manufacturing this study which covers a sample of 314 four digit industries taken from an exhaustive set of 450 four digit industries shows that increases in concentration associated with rising productivity occur mainly in low concentration industries while decreases in concentration associated with rising productivity occur mainly in high concentration industries the empirical results of this study indirectly lend support to a plausible hypothesis that a small group of firms makes a big impact on the productivity of an initially unconcentrated industry and thereby concentrates it later the small firms imitate the now big firms and concentration goes down while productivity keeps rising

managing and reallocating inventory across two markets with local information abstract consider a firm that controls inventory centrally for two separate markets that are managed by regional managers having local demand information the central planner provides a dedicated inventory level to each market to ensure a minimum service level but can reallocate inventory once associated demands are filled how should such a firm solicit regional managers to share their local information so inventory levels can be set efficiently in this paper we study a forecast sharing game in such a firm where demand information lies within regions and inventory is managed by a central decision maker we show that incentives are misaligned and truthful information sharing is not an equilibrium we study two potential ways to improve the system a regional managers directly place orders rather than simply passing demand forecasts or b a pricing scheme for inventory reallocations is imposed we show that under direct ordering a unique pure strategy bayesian nash equilibrium exists and makes retailers place orders based on their true forecasts although the requested order quantities are not system optimal e g some inventory pooling benefits are lost under an endogenous transfer pricing mechanism set by the central planner we find that a first best truth telling equilibrium is possible under certain conditions we conduct a numerical study to examine the different cases and find that when the critical fractile is high direct ordering results in lower inventories while the reverse is true when the critical fractile is low expected profit comparisons show the value of local information

optimal joint replenishment and transshipment policies in a multi period inventory system with lost sales mismatch between supply and demand when the uncertainty of the demand is high and the supply lead time is relatively long such as seasonal good markets can result in high overstocking and understocking costs in this paper we propose transshipment as a powerful mechanism to mitigate the mismatch between the supply and demand we consider a finite horizon multi period inventory system where in each period two retailers have the option to replenish their inventory from a supplier if there is any supply or via transshipment from the other retailer each retailer observes nonnegative stochastic demand with general distribution in each period and incurs overstocking understocking costs as well as costs for replenishment and transshipment that may be time dependent we study a stochastic control problem where the objective is to determine the optimal joint replenishment and transshipment policies so as to minimize the total expected cost over the season we characterize the structure of the optimal policy a

who benefits from transshipment exogenous vs endogenous wholesale prices this paper studies how transshipments affect manufacturers and retailers considering both exogenous and endogenous wholesale prices for a distribution system where a single manufacturer sells to multiple identical cost retailers we consider both the manufacturer being a price taker and the manufacturer being a price setter in a single period setup under multivariate normal demand distribution in the case of the manufacturer being a price taker we provide several analytical results regarding the effects of key parameters on order quantities and profits in the case of the manufacturer being a price setter we characterize the stackelberg game that arises and provide several insights into how the game dynamics are affected by transshipments specifically we find that risk pooling makes retailers order quantities less sensitive to the wholesale price set by the manufacturer hence in general the manufacturer benefits from retailers transshipments by charging a higher wholesale price while retailers are often worse off the paper captures the effect of demand correlation and the effect of the number of retailers throughout and it illustrates the findings by a numerical example we also provide an interactive web page for numerical experiments

dynamic balancing of inventory in supply chains abstract we consider the dynamic version of the classic problem of allocation of inventories to a set of retailers to rectify the imbalance of inventories amongst them while most research is focussed on analyzing different allocation strategies with a predetermined time of shipment static policy we investigate the benefit of using real time demand inventory information to schedule rebalancing shipments in a retail network we model the dynamic rebalancing problem that has two decisions the timing of the balancing shipments and determination of the new stocking levels at the retailers as a dynamic program dp we obtain structural properties for the optimal allocation rebalancing and timing strategies we also present conditions under which a greedy heuristic to decide how much to ship from one retailer to another is optimal the dp for determining the optimal timing and quantity of shipments has a very large state space we present an algorithm to solve this dp efficiently we also provide a heuristic solution procedure to the dynamic problem that performs very close to optimal numerical results show that dynamic allocation policies can lead to substantial benefits over the static policy especially in systems in which the starting inventories at the retailers are balanced or when high service levels are required

stocking decisions for low usage items in a multilocation inventory system this research shows that organizations with a number of sister plants warehouses or other stocking points can profit from the concept of proactive use of transshipments as an element of their inventory control policy for certain types of parts employing transshipments can significantly reduce the total inventory needed throughout the entire collection of stocking points the study is motivated by a real life situation involving a large utility company having 29 power generating plants in five southeastern states where there are thousands of parts that are commonly used at multiple plants at present each plant operates independently and maintains enough stock to meet its own requirements transshipments take place between plants whenever there is an emergency requirement for a part but no explicit consideration is given to this effect while deciding on stocking levels at different plants in the case we examined by setting stocking levels to explicitly take account of transshipments total system cost could be reduced by about 70 over the company s decentralized policy in general this work considers a single echelon n location continuous review inventory system in which complete pooling of stock is permitted among the locations a model is developed for slow moving expensive and consumable parts that are common to two or more locations a one for one ordering policy and queueing theory allow development and solution of a system of equations for the probability distribution of net inventory at each location a heuristic procedure is also developed to determine cost effective stocking levels actual data from the utility company are used to demonstrate the applicability of the model savings achieved as a result of pooling are reported

a management orientated approach to combination forecasting of tourism demand abstract volatility exponential smoothing regression and naive 2 models are considered singly and in combination in terms of forecasting demand for international tourism these models generate accurate predictions of tourism flows but their prime utility is when combined with other models usually models are combined by means of purely statistical criteria we show that goal programming gp offers an alternative flexible approach to model combination gp offers planners a practical solution to tourism forecasting problems since the method is more adaptable than conventional minimisation of prediction error by permitting practitioners to prioritise a series of management related goals forecasters can focus on longer and short term goals minimising forecast under and over estimation and or concentrate on prediction errors in tourism flows at various times of the year

a note on the profit concentration relation the efficiency view of the well known industrial concentration profits relation postulates that efficient firms achieve both high market share and high profits incidentally creating a positive correlation between concentration and profit levels a necessary implication is a positive relation between share and profit changesfor all firms large and small this hypothesis is tested using five size ranked cohorts of firms in four digit us manufacturing industries a positive correlation is found between shart and profit change for all cohorts consistent with the efficiency hypothesis

optimal joint inventory and transshipment control under uncertain capacity in this paper we address the optimal joint control of inventory and transshipment for a firm that produces in two locations and faces capacity uncertainty capacity uncertainty e g due to downtime quality problems yield etc is a common feature of many production systems but its effects have not been explored in the context of a firm that has multiple production facilities we first characterize the optimal production and transshipment policies and show that uncertain capacity leads the firm to ration the inventory that is available for transshipment to the other location and characterize the structure of this rationing policy then we characterize the optimal production policies at both locations which are defined by state dependent produce up to thresholds we also describe sensitivity of the optimal production and transshipment policies to problem parameters and in particular explain how uncertain capacity can lead to counterintuitive behavior such as produce up to limits decreasing for locations that face stochastically higher demand we finally explore through a numerical study when the optimal policy is most likely to yield significant benefits compared to simple policies

optimal replenishment and rework with multiple unreliable supply sources we study a production inventory system with multiple unreliable supply sources through inspection and rework the system can improve the quality of the units received from the supply sources there are two interleaved decisions the replenishment quantities from the sources and the inspection rework quantities among the units received we show the optimal solution to the replenishment decision can be efficiently derived from a greedy algorithm and inspection rework is optimally applied to a single source identified by the algorithm furthermore in the case of linear cost functions it is optimal to place orders from two supply sources i e dual sourcing the results extend to the infinite horizon case where an order up to policy is optimal the model also readily adapts to situations in which the supply imperfection takes the form of a reduced delivery quantity yield loss

the multiperiod multilocation inventory problem this paper studies the structure of optimal policies in general multiperiod multilocation inventory problems with proportional costs it is shown that the multiperiod problem has the same generic form in each period as a one period problem hence properties of the one period problem are inherited by the multiperiod formulation in particular the form of the optimal policy can be characterized in the special case of a leontief system structure and for a somewhat more general class it is shown that base stock policies are optimal for certain initial states for the stationary problem some results are derived about the monotonicity of the sequence of base stock vectors

managing inventories with one way substitution a newsvendor analysis abstract this paper presents an insightful approach to analyze two item periodic inventory systems with one way substitution the objective is to minimize the expected total cost per period which consists of expected purchasing costs expected inventory holding costs expected shortage costs and expected adjustment costs this approach helps derive the optimality conditions in both single period and infinite horizon settings and yields useful insights into the impact of substitution on the service level the optimality of a borderline case in which the order up to level of the inflexible item is reduced to zero and the pivotal role of the purchasing cost

approximations of dynamic multilocation production and inventory problems consider a central depot or plant which supplies several locations experiencing random demands orders are placed or production is initiated periodically by the depot the order arrives after a fixed lead time and is then allocated among the several locations the depot itself does not hold inventory the allocations are finally received at the demand points after another lag unfilled demand at each location is backordered linear costs are incurred at each location for holding inventory and for backorders also costs are assessed for orders placed by the depot the object is to minimize the expected total cost of the system over a finite number of time periods this system gives rise to a dynamic program with a state space of very large dimension we show that this model can be systematically approximated by a single location inventory problem all the qualitative and quantitative results for such problems can then be applied

estimating demand by using sales information inaccuracies encountered abstract demand data is integral to a company s overall information requirement this is particularly true for manufacturers and retailers with regard to capacity production and inventory planning notwithstanding the implicit inaccuracies encountered companies are predisposed to employ sales data as a primary source of information for estimating future demand in this paper by adopting a two product setting we measure inventory cost inaccuracies that arise from using sales data in estimating demand by analyzing these costs we also explore the conditions under which the resulting inaccuracies are either lessened or become acute in this context the determining rule of an induced substitution structure between the two products during stockout occasions is explicitly analyzed we use a newsboy framework in a two product environment wherein one product may be taken as a direct substitute for the other we provide necessary and sufficient optimality conditions and an extensive computational study to illustrate and support our findings and to provide additional insights on the conditions characterizing optimal stocking policies

entry timing in a secondary market when to trade abstract in volatile long lead time and short selling season markets a secondary market enables buyers to update their inventory during the selling season the decision of when to update involves complicated trade offs between forecast accuracy expected lost sales and average purchasing cost we use a two stage inventory replenishment model to identify the optimal trading time across different scenarios across most scenarios the optimal trading time is around the midpoint of the season and is sensitive to the expected profit margin and demand forecast errors we discuss the impacts of the timing decision on upstream suppliers sales and channel performance in terms of sales revenue and supply demand mismatch costs specifically secondary market trading always reduces upstream suppliers sales no matter when trading occurs but trading at an optimal time can maximize a secondary market s profit gain over the no trade scenario through reducing supply demand mismatch

multi location transshipment problem with capacitated transportation abstract we consider coordination among stocking locations through replenishment strategies that take explicitly into consideration transshipments transfer of a product among locations at the same echelon level we incorporate transportation capacity such that transshipment quantities between stocking locations are bounded due to transportation media or the location s transshipment policy we model different cases of transshipment capacity as a capacitated network flow problem embedded in a stochastic optimization problem under the assumption of instantaneous transshipments we develop a solution procedure based on infinitesimal perturbation analysis to solve the stochastic optimization problem where the objective is to find the policy that minimizes the expected total cost of inventory shortage and transshipments such a numerical approach provides the flexibility to solve complex problems investigating two problem settings we show the impact of transshipment capacity between stocking locations on system behavior we observe that transportation capacity constraints not only increase total cost they also modify the inventory distribution throughout the network

product diversion to a direct competitor a manufacturer will often limit competition among downstream partners by authorizing only a select group of retailers to carry its product however it is not uncommon for authorized retailers to create an additional competitor by diverting units to an unauthorized seller this paper presents an analytical model that demonstrates how diversion from authorized retailers to an unauthorized direct competitor can occur under circumstances not considered by the prior literature in fact diversion can represent a prisoner s dilemma whereby retailers diminish their own profit by selling to the unauthorized direct seller the authorized retailer s profit loss actually increases as the per unit diversion costs incurred by the authorized retailer decrease the model also shows that the unauthorized direct seller earns greater profit by strategically procuring a unilaterally constraining quantity even though this procurement strategy results in an equivalent increase in the quantity sold by the retailers combined the results identify a new reason for diversion and its consequences for retailers and the unauthorized direct seller

optimal production pricing and substitution policies in continuous review production inventory systems abstract we consider the optimal production pricing and substitution policies of a continuous review production inventory system with two products a high end product and a low end product each product has its associated customer stream however the demands for the low end product may be satisfied by the high end product we formulate the problem as a markov decision process and characterize the structure of the optimal control policy which specifies when to produce for each product when to use the high end product as a substitute and how to set the optimal prices we show that a base stock production policy is optimal however the optimal base stock level for each product depends on the inventory level of the other product and it features a monotonic property we also demonstrate that the optimal substitution policy is a rationing policy with the rationing level depending on the total inventory amount we find that the optimal prices can be either decreasing or increasing in the inventory levels depending on the forms of demand functions furthermore we utilize numerical experiments to investigate the impact of different system characteristics on the benefits of using substitution and dynamic pricing finally we investigate when the dynamic pricing strategy and the substitution strategy are complements or substitutes

dynamic capacity management with general upgrading this paper studies a capacity management problem with upgrading a firm needs to procure multiple classes of capacities and then allocate the capacities to satisfy multiple classes of customers that arrive over time a general upgrading rule is considered i e unmet demand can be satisfied using multistep upgrade no replenishment is allowed and the firm has to make the allocation decisions without observing future demand we first characterize the structure of the optimal allocation policy which consists of parallel allocation and then sequential rationing specifically the firm first uses capacity to satisfy the same class demand as much as possible then considers possible upgrading decisions in a sequential manner we also propose a heuristic based on certainty equivalence control to solve the problem numerical analysis shows that the heuristic is fast and delivers close to optimal profit for the firm finally we conduct extensive numerical studies to derive insights into the problem it is foun

international tourism and export instability export diversification has been suggested as a strategy for decreasing the level of export earnings instability which is experienced by many developing countries in recent years the international tourism sector has made an increasingly important contribution to the economies of many low income countries this article examines whether diversification into the non traditional tourism sector has succeeded in decreasing the instability of export earnings it was found that although tourism has the advantage of high growth rates and is a major source of foreign currency receipts earnings from international tourism did not bring about a significant decrease in the instability of export earnings of most of the developing and industrialised countries considered furthermore a net increase in the instability of earnings from tourism and merchandise exports occurred in a number of countries and may be a particular problem in small open developing economies

predicting tourism demand using fuzzy time series and hybrid grey theory abstract forecasting tourism demand in a capacity constrained service industry has been a major theme in this field this study presents two models that can be used to predict tourism demand both two models are based on artificial intelligent ai neural network theory was first applied to tourism demand forecasting in 2000 and empirically tested using the raw data from hong kong this work provides empirical evidence using grey theory and fuzzy time series which do not need large sample and long past time series these ai models are estimated for tourist arrivals to taiwan from hong kong united states and germany during the period of 1989 2000 gm 1 1 model achieves an accurate forecast when the sample data show a stable increase trend nevertheless the markov modification model can efficiently improved the gm 1 1 model when the sample data show significant fluctuations

back propagation learning in improving the accuracy of neural network based tourism demand forecasting abstract traditional tourism demand forecasting techniques concentrate predominantly on multivariate regression models and univariate time series models these single mathematical function based forecasting techniques although they have achieved a certain degree of success in tourism forecasting are unable to represent the relationship of demand for tourism as accurate as a multiprocessing node based feed forward neural network previous research has demonstrated that using a feed forward neural network can accomplish a higher forecasting accuracy than the regression and time series techniques for a set of linearly separable tourism demand data this research extends the applicability of neural networks in tourism demand forecasting by incorporating the back propagation learning process into a non linearly separable tourism demand data empirical results indicate that utilizing a back propagation neural network outperforms regression models time series models and feed forward neural networks in terms of forecasting accuracy

multi location transshipment problem with capacitated production abstract we consider coordination among stocking locations through replenishment strategies that explicitly take into account lateral transshipments i e transfer of a product among locations at the same echelon level our basic contribution is the incorporation of supply capacity into the traditional transshipment model our goal is to analyze the impact on system behavior and on stocking locations performance of the fact that the supplier may fail to fulfill all the replenishment orders we therefore formulate the capacitated supply scenario as a network flow problem embedded in a stochastic optimization problem which is solved through a sample average approximation method we find that depending on the production capacity system behavior can vary drastically moreover in a production inventory system we find evidence that either capacity flexibility i e extra production or transshipment flexibility i e pooling is required to maintain a desired level of service

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

a comparison of three different approaches to tourist arrival forecasting abstract forecasting plays a major role in tourism planning the promotion of tourism projects involving substantial sums of money requires an estimate of future demand and market penetration the commitment to developing tourism would be much easier if it were possible to analyse current and past tourist traffic and predict the nature of changes in tourism demand these extrapolative approaches to forecasting require historical data this paper investigates the application of three time series forecasting techniques namely exponential smoothing univariate arima and elman s model of artificial neural networks ann to predict travel demand i e the number of arrivals from different countries to hong kong exponential smoothing and arima are two commonly used statistical time series forecasting techniques the third approach neural networks is an artificial intelligence technique derived from computer science according to the analysis presented in this paper neural networks seems to be the best method for forecasting visitor arrivals especially those series without obvious pattern

modelling us tourism demand for european destinations abstract an almost ideal demand system model is used to examine us demand for tourism in european destinations the model provides policy makers with useful information concerning the sensitivity of tourism demand to changes in relative prices exchange rates and expenditure the results show that price competitiveness is important for us demand for france italy and spain but is relatively unimportant for the uk france and italy are regarded as substitutes by us tourists as are spain and italy as us expenditure rises the market shares of spain and the uk decline while france and italy benefit the demand modelling and forecasting indicate that in the absence of a tourism price index the choice between alternative price indices does not have a significant effect on the results

a multiechelon inventory model with fixed replenishment intervals this paper develops a new model for studying multiechelon inventory systems with stochastic demand for the model we assume that each site in the system orders at preset times according to an order up to policy that delivery times are deterministic and that the demand processes are stochastic with independent increments we introduce a new scheme for allocating stock in short supply which we call virtual allocation and which permits significant tractability we exercise the model on a set of test problems for two echelon systems to get insight into the structure of good policies the primary findings are that both the central warehouse upper echelon and the retail sites lower echelon should hold safety stock but that most of the safety stock should be at the retail sites consequently the central warehouse will stock out with high probability furthermore we show that the virtual allocation rule is near optimal for the set of test problems

optimal policies for inventory systems with lateral transshipments using lateral transshipments can be beneficial in order to improve service levels and to reduce system costs this paper deals with a single echelon inventory system with two identical locations demands are generated by stationary and independent poisson processes in general if a demand occurs at a location and there is no stock on hand the demand is assumed to be backordered or lost however in this paper lateral transshipments serve as an emergency supply in case of stock out in this paper the rule for lateral transshipments is given while the ordering policies for normal replenishments are optimized the transshipment rule is to always transship when there is a shortage at one location and stock on hand at the other first we assume that the locations apply r q policies for normal replenishments and show that the optimal policies are not necessarily symmetric even though the locations are identical this means that one cannot in general assume that the optimal policy is symmetric under symmetric assumptions second we relax the assumption of r q policies and derive the optimal replenishment policy using stochastic dynamic programming

modelling the uncertainty in monthly international tourist arrivals to the maldives abstract the indian ocean tsunami of 26 december 2004 made clear the devastating short term impact in lost lives as well as the longer term impact in lost livelihoods and an uncertain future tourism was one of the more obvious non human casualties of this tragic natural phenomenon tourism is the principal industry in the maldives accounting for more than 30 of gdp and more than 60 of foreign exchange earnings as over 55 of government tax revenue arises from tourism related taxes and monthly government budget financing depends largely on international tourist arrivals the monitoring of daily weekly and monthly international tourist arrivals is essential for fiscal policy evaluation over 600 000 tourists visited the maldives in 2004 this paper examines the time series properties of monthly international tourist arrivals to the maldives from eight major tourist source countries namely italy germany uk japan france switzerland austria and the netherlands from 1 january 1994 to 31 december 2003 monthly international tourist arrivals and the associated uncertainty are estimated for the eight principal tourist source countries univariate and multivariate time series models of conditional volatility or uncertainty are estimated and tested the conditional correlations are estimated and examined to ascertain whether there is specialization diversification or segmentation in the international tourism demand shocks from the major tourism source countries to the maldives the estimated static conditional correlations for monthly international tourist arrivals as well as for the respective transformed series were found to be significantly different from zero but also relatively low this indicates that the government of the maldives and the major tour operators that organise tourist vacations have to emphasise their marketing efforts independently of each tourist source country

how to order and transship in multi location inventory systems the simulation optimization approach abstract the efficient control of multi location inventory systems with lateral transshipments has become increasingly important however existing models are analytically solvable only under simplifying assumptions there is a variety of heuristics to find approximate solutions but interdependencies between ordering and transshipment decisions for continuous time are not addressed thus we suggest using simulation optimization in our paper we describe a widely adaptable simulation model for mapping highly complex multi location inventory systems with lateral transshipments by applying this model to a special case from the literature and to some examples we show its validity and generality

tourism forecasting to combine or not to combine abstract existing non tourism related literature shows that forecast combination can improve forecasting accuracy this study tests this proposition in the tourism context by examining the efficiency of combining forecasts based on three different combination methods the data used for this study relate to tourist arrivals in hong kong from the top ten tourism generating countries regions the forecasts are derived from four different forecasting models autoregressive integrated moving average arima model autoregressive distributed lag model adlm error correction model ecm and vector autoregressive var model all forecasts are ex post and the empirical results show that the relative performance of combination versus single model forecasts varies according to the origin destination tourist flow under consideration which parallels previous findings regarding the relative performance of individual forecasting methods the results also vary with the combination techniques used furthermore although the combined forecasts do not always outperform the best single model forecasts almost all the combined forecasts are not outperformed by the worst single model forecasts this suggests that forecast combination can considerably reduce the risk of forecasting failure this conclusion also implies that combined forecasts are likely to be preferred to single model forecasts in many practical situations

optimal and approximate policies in multiperiod multilocation inventory models with transshipments this paper examines the effects on the optimal ordering policy and its cost of allowing for interactions among retail outlets specifically transshipments are allowed as recourse actions occurring after demands are realized but before they must be satisfied the resultant savings in holding and shortage costs are balanced against the costs of transshipment a base stock ordering policy is optimal for this model if the final period base stock order up to point is nonnegative then it will be the base stock order up to point for all periods unfortunately it can be found analytically only for two special cases where either the cost parameters are equal at every outlet or there are only two outlets these two special cases are used to validate a heuristic solution technique employing monte carlo integration which is then compared to an easily calculated base policy in order to gauge the contribution of this model the additional savings from using this heuristic policy are significant particularly for problems with many retail outlets and low transshipment costs

combining volatility and smoothing forecasts of uk demand for international tourism abstract univariate volatility models are applied to uk tourism demand to the country s most popular international destinations volatility is a concept borrowed from finance the fact that significant volatility models are found for ten of the twelve destinations examined shows that the volatility concept has relevance to tourism demand volatility models are able to quantify the impacts of positive and negative shocks on tourism demand the impacts of negative shocks vary in magnitude and duration according to the destination involved and the nature of the shock the forecasting capability of these models has never been assessed in the tourism field they are shown to generate highly accurate forecasts but become optimal when combined with forecasts obtained from exponential smoothing models two methods of combining individual forecasts are considered bias in individual volatility and smoothing models and in combinations of them is examined

an inventory model with unidirectional lateral transshipments this paper deals with a continuous review inventory system with poisson demand in which lateral transshipments are allowed in case of a shortage at a location another location acts as a supplier if it is possible a common assumption in earlier papers is that transshipments are allowed between all locations this network configuration may however not be the best choice for many reasons one such reason is that it may be difficult to establish contracts between locations regarding the design of the transshipment policy another reason is that a system with many transshipment links is much more complex than a system with few transshipment links in this paper we study a system where transshipments are allowed only in one direction this may be a reasonable policy if the locations have very different backorder lost sales costs our approach is relatively simple and fast and works well in most cases

cost parametric analysis of lateral transshipment policies in two echelon supply chains abstract in this paper we examine the cost effects of two lateral intra echelon transshipment approaches in a two echelon supply chain network with a single supply source at the higher echelon and multiple retail locations at the lower through a series of simulation experiments under different operating conditions an important finding is that either of the proposed lateral shipment approaches is considerably superior to a policy of no such shipments albeit at the expense of increased transportation activity further an ad hoc emergency transshipment approach appears to be significantly more effective in terms of several important criteria as compared to a more systematic transshipment technique based on stock level equalization

emergency lateral transshipments in a two location inventory system with positive transshipment leadtimes abstract we consider a single echelon continuous review inventory system for spare parts with two parallel locations each location faces independent poisson demand and backorders are allowed in this paper we consider the possibility of lateral transshipments between the locations the transshipment leadtime is positive and deterministic and there is an additional cost for making a transshipment we suggest a transshipment policy which is based on the timing of all outstanding orders and develop and solve a heuristic model by using theory and concepts from doubly stochastic poisson processes and also partial differential equations a simulation study indicates that our heuristic works very well and that the relative cost increase of disregarding the transshipment leadtime may be quite high our results also indicate that it is in general worth the effort of reducing the transshipment leadtime even if it is already relatively short

inventory sharing and rationing in decentralized dealer networks an increasing number of manufacturers have started to pursue a strategy that promotes inventory sharing among the dealers in their distribution network in this paper we analyze a decentralized dealer network in which each independent dealer is given the flexibility to share his inventory we model inventory sharing as a multiple demand classes problem in which each dealer faces his own customer demand with high priority and inventory sharing requests from other dealers with low priority assuming that each dealer uses a base stock and threshold rationing policy for his inventory stocking and inventory sharing decisions we explicitly model the interactions between the dealers through inventory sharing and obtain aclosed form cost function for each dealer based on the steady state distribution of the inventory levels at the two dealers we then provide a detailed supermodularity analysis of the inventory sharing and inventory rationing game in which each dealer has a two dimensional strategy set stocking level and rationing level we show that the full sharing game in which dealers precommit to sharing all of their on hand inventory and the fixed sharing level game in which dealers precommit to sharing a portion of their on hand inventory are supermodular and thus a pure strategy nash equilibrium is guaranteed to exist for the rationing game in which dealers precommit to their stocking levels we show that there exists a dominant strategy equilibrium on the dealers sharing rationing levels finally a comprehensive computational study is conducted to highlight the impact of the manufacturer s incentives subsidies and or transshipment fees on the dealers sharing behavior

an index heuristic for transshipment decisions in multi location inventory systems based on a pairwise decomposition in multi location inventory systems transshipments are often used to improve customer service and reduce cost determining optimal transshipment policies for such systems involves a complex optimisation problem that is only tractable for systems with few locations consequently simple heuristic transshipment policies are often applied in practice this paper develops an approximate solution method which applies decomposition to reduce a markov decision process model of a multi location inventory system into a number of models involving only two locations the value functions from the subproblems are used to estimate the fair charge for the inventory provided in a transshipment this estimate of the fair charge is used as the decision criterion in a heuristic transshipment policy for the multi location system a numerical study shows that the proposed heuristic can deliver considerable cost savings compared to the simple heuristics often used in practice

balancing retailer inventories this paper examines the optimality of inventory balancing in a one warehouse n retailer distribution system facing stochastic demand for a single product over t successive time intervals in particular we consider the division of predetermined quantities of warehouse stock among retailers in each interval balancing attempts to bring the retailer inventories to the same normalized with respect to first interval demand net inventory level when the demand distribution over the t periods is symmetric with respect to all pairs of retailers and retailer cost over the t intervals is a convex function of the t shipments we show that balancing divisions are optimal the required convexity condition is shown to be satisfied for some familiar cost functions when shortages are backordered and lost however for other cost functions the convexity condition is satisfied under backordering but not under lost sales we also consider the nonidentical retailer demands are not symmetric case and provide examples

a semi markov model with holdout transshipment policy and phase type exponential lead time in this paper a semi markov decision model of a two location inventory system with holdout transshipment policy is reviewed under the assumption of phase type exponential replenishment lead time rather than exponential lead time the phase type exponential lead time more closely approximates fixed lead time as the number of phases increases unlike past research in this area which has concentrated on the simple transshipment policies of complete pooling or no pooling the research presented in this paper endeavors to develop an understanding of a more general class of transshipment policy in addition we propose an effective method to approximate the dynamic holdout transshipment policy