product cannibalization and the role of prices the role of brand prices in contributing to product cannibalization is examined price elasticities and reference price theory are used to provide a theoretical foundation and empirical test for the impact of a firm s cheap brand on one of its expensive brands results are consistent with the conclusion that the market share of the company s premium brand was cannibalized by a growth in sales of its cheap brand

maximum likelihood estimation of first passage structural credit risk models correcting for the survivorship bias abstract the survivorship bias in credit risk modeling is the bias that results in parameter estimates when the survival of a company is ignored we study the statistical properties of the maximum likelihood estimator mle accounting for survivorship bias for models based on the first passage of the geometric brownian motion we find that if we neglect the survivorship bias then the drift has a positive bias that may not disappear asymptotically we show that correcting the survivorship bias by conditioning on survival in the likelihood function underestimates the drift therefore we propose a bias correction method for non iid samples that is first order unbiased and second order efficient the economic impact of neglecting or miscorrecting for the survivorship bias is studied empirically based on a sample of more than 13 000 companies over the period 1980 through 2016 inclusive our results point to the important risk of misclassifying a company as solvent or insolvent due to biases in the estimates

conditions that cause risk pooling to increase inventory abstract we say product a is a partial substitute for product b if a fraction of the customers who prefer b are willing to accept a when b is out of stock when demand is uncertain it is intuitive and true that a larger willing to substitute fraction implies larger expected profits a higher willing to substitute fraction allows one to pool the risk of individual products it may also be intuitive that a larger willing to substitute fraction might result in lower optimal total inventory for the full substitution structure several researchers have shown that for certain distributions such as the exponential this latter intuition is not true we show that this full substitution anomaly can occur with any right skewed demand distribution we assume i i d demand distributions unless we indicate otherwise we also show that the anomaly can occur for a number of realistic situations of partial substitution with commonly used demand distributions such as normal exponential poisson and uniform we also demonstrate the anomaly for more than one period with backlogging lost sales more than two products and with setup costs

commonality in product design cost saving valuation change and cannibalization abstract offering a variety of products is important for a firm to attract different consumer segments however high product variety increases production and distribution costs modular product design and parts commonality are approaches used to counter this trend in cost and still offer a variety of products this paper develops a model to examine when modular products should be introduced and how much modularity to offer the model looks at a market consisting of a high segment and a low segment customers choose the product that maximizes their surplus which is defined as the product s utility minus its price presence of commonality affects the utility of a product greater commonality decreases production cost but makes the products more indistinguishable from one another this makes the product more desirable for the low segment but less desirable for the high segment the firm s objective is to design the products and set the prices so as to maximize its profit

pricing risk adjusted deposit insurance an option based model this paper presents a methodology for arriving at empirical estimates of deposit insurance premiums from market data by using isomorphic relationships betweeen equity and a call option and insurance and a put option the data utilizes the market value of equity to solve for the asset value and its volatility market perceptions of fdic bailout policies are explicitly modeled so as to eliminate the bias in inverted values of assets and their volatility sensitivity analyses are performed to show that rank orderings based on premiums are robust to changes in specification thus facilitating allocation of aggregate premium across banks while economists have long argued in favor of risk adjusted deposit insurance as both more equitable and more efficient than the current system of flatrate premiums various recent developments have further contributed to an increasing dissatisfaction with the current system first both the banking industry and the government seem to be tending to the view that deregulation of the banking industry would be necessary in order to meet more sophisticated future demands on the industry as well as desirable as a policy means of stimulating greater competition among banks moreover a sudden rise in the incidence of bank failures 1 and the vulnerability of the u s banks to the socalled international debt crisis have served to bring to the fore concern about the health of the banking industry in the absence of deposit insurance riskier banks will be able to attract deposits only at higher rates and these higher costs of funding serve as built in market regulated incentives to limit excessive risk taking by banks as introduction of deposit insurance makes deposits equally risk free across banks these incentives disappear and regulation and close supervision of the banking industry must necessarily replace them as deterrents to excessive risk taking thus when insurance is offered at a flat premium regulation is designed to ensure that the risk posed to the insurer both asset and financial risk is appropriately uniform

capacity investment under postponement strategies market competition and demand uncertainty we consider duopoly models where firms make decisions on capacity production and price under demand uncertainty capacity and price decisions are made respectively ex ante and ex post demand realizations the interplay between the timings of demand realization and production decision endows firms with different capabilities flexible firms can postpone production decisions until the actual demand curve is observed but inflexible firms cannot under general demand structures and cost functions we characterize the equilibrium for a symmetric duopoly and establish the strategic equivalence of price and quantity competitions when firms are flexible we investigate the stochastic order properties of capacity and profit and show that they both increase for a flexible firm when the market is more volatile we find that flexibility allows a firm to increase investment in capacity and earn a higher profit while benefiting customers by keeping the price in a narrower range strategic equivalence implies that

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

on the effect of demand randomness on inventories and costs we explore analytically cardinal effects of the extent of demand randomness on optimal inventory levels and the associated expected costs to model changes in demand randomness we make extensive use of a mean preserving transformation commonly used in probabilistic microeconomics as well as the notion of risk pooling aggregating independent demands for the single period news vendor model the order quantity and associated costs are shown to depend on the randomness parameter in a simple and highly interpretable manner we show by a simple example that in some situations risk pooling might neither reduce inventories nor move them closer to the mean or median demand the managerial relevance of such analyses is discussed

analysis of an industrial component commonality problem we discuss a case study of an industrial production marketing coordination problem involving component commonality for the product line considered the strategic goal of the company is to move from the current low volume market to a high volume market the marketing department believes that this can be achieved by substantially lowering the end products prices however this requires a product redesign to lower production costs in order to maintain profit margins the redesign decision involves grouping end products into families all products within one family use the same version of some components this paper fits in the stream of recent literature on component commonality where the focus has shifted from inventory cost savings to production and development cost savings further we consider both costs and revenues leading to a profit maximization approach the price elasticity of demand determines the relationship between the price level and number of units sold consequently we integrate information from different functional areas such as production marketing and accounting we formulate the problem as a net present value investment decision we propose a mixed integer nonlinear optimization model to find the optimal commonality decision the recommendation based on our analysis has been implemented in the company in addition the application allows us to experimentally validate some claims made in the literature and obtain managerial insights into the trade offs

the term structure of credit spreads with jump risk abstract default risk analysis is important for valuing corporate bonds swaps and credit derivatives and plays a critical role in managing the credit risk of bank loan portfolios this paper offers a theory to explain the observed empirical regularities on default probabilities recovery rates and credit spreads it incorporates jump risk into the default process with the jump risk a firm can default instantaneously because of a sudden drop in its value as a result a credit model with the jump risk is able to match the size of credit spreads on corporate bonds and can generate various shapes of yield spread curves and marginal default rate curves including upward sloping downward sloping flat and hump shaped even if the firm is currently in a good financial standing the model also links recovery rates to the firm value at default so that the variation in recovery rates is endogenously generated and the correlation between recovery rates and credit ratings before default reported in altman j finance 44 1989 909 can be justified

measuring the frictional costs of online transactions the case of a name your own price channel we study the offers submitted by consumers to a large name your own price nyop online retailer a distinctive feature of this retailer is that it allows consumers to repeatedly submit offers on one and the same product while consumers could identify the threshold price the minimum price for which the retailer is willing to sell by incrementing their offer in small steps in each consecutive round such a strategy would require them to go through many additional online transactions we define frictional cost as the disutility that the consumer experiences when conducting an online transaction such as submitting an offer thus in our setting consumers trade off a direct financial value lower price for frictional costs based on a consumer choice model capturing this trade off we use the observed consumer behavior to reconstruct the frictional cost parameters for the consumers in our sample we show that perhaps contrary to the general wisdom frictional costs in electronic markets are substantial with median values ranging from eur 3 54 for a portable digital music player mp3 to eur 6 08 for a personal digital assistant pda we find that consumers who have gathered experience with the nyop channel in previous transactions exhibit lower frictional costs than consumers who use the channel for the first time surprisingly sociodemographic variables do not help to explain the variation in frictional costs

energy transition towards economic and environmental sustainability feasible paths and policy implications this paper focuses on growth feasibility in an era of increasing scarcity of fossil fuels a stylised dynamic model illustrates the implications of investing in smooth technological progress in the field of renewable energy positive rates of gdp growth sustained by fossil fuels entail on the one hand more income available for r d in renewable energy sources and on the other an acceleration of the exhaustible resource depletion time our model explores such a trade off and highlights the danger of high growth rates policies should target low growth rates stimulate investment in alternative energy sources and discourage consumption growth

probabilistic selling in quality differentiated markets probabilistic selling the sale of synthetic products consisting of a lottery between two distinct goods has been extensively analyzed in horizontal markets in this research we investigate probabilistic selling in quality differentiated markets this is an important new dimension of inquiry because of the widespread prevalence of quality differentiated markets as well as significant differences in the preference structure across these markets in fact this latter consideration casts doubt as to whether probabilistic selling will even emerge in quality differentiated markets we find that probabilistic selling emerges in quality differentiated markets as a way to profitably dispose excess capacity moreover probabilistic selling remains viable even under endogenous quality choice in addition in markets where sellers employ strong quality differentiation the introduction of an intermediate probabilistic good actually causes closer quality levels in a product line and enhances consumer welfare in contrast in markets where sellers employ weak quality differentiation the introduction of an intermediate probabilistic good increases quality separation and degrades consumer welfare overall we view our contribution as one of characterizing the optimality implementation and policy implications of probabilistic selling in quality differentiated markets this paper was accepted by pradeep chintagunta marketing

endogenizing exogenous default barrier models the mm algorithm abstract in this paper we propose a maximization maximization mm algorithm for the assessment of hidden parameters in structural credit risk models step m1 updates the value volatility and expected return on the firm s assets by maximizing the log likelihood function for the time series of equity prices step m2 updates the default barrier by maximizing the equity holders participation in the firm s asset value the main contribution of the method lies in the m2 step which allows for endogenizing the default barrier in light of actual data on equity prices using a large international sample of companies we demonstrate that theoretical credit spreads based on the mm algorithm offer the lowest cds pricing errors when compared to other traditional default barrier specifications smooth pasting condition value maximum likelihood estimate kmv s default point and nominal debt

a barrier option framework for corporate security valuation abstract this paper proposes a framework for corporate security valuation based on path dependent barrier option models instead of the commonly used path independent approach we argue that path dependency is an intrinsic and fundamental characteristic of corporate securities because equity can be knocked out whenever a legally binding barrier is breached a direct implication of this framework is that equity will be priced as a down and out call option we provide empirical validation of the barrier model by showing that implied barriers are statistically and economically significant for a large cross section of industrial firms additional robustness tests confirm that barriers remain significant over a wide range of input variable estimates and finally we apply the barrier option framework to bankruptcy prediction and find that implied failure probabilities dominate z scores in most cases

vrp revisited the impact of behavioural costs in balancing standardisation and variety abstract the objective of this paper is to bring a new element to the academic and industrial debate concerning the optimum level of variety in component design in mass production companies many authors have explored the trade off between functional and variety costs and this could be considered as a well acknowledged management issue at least from an engineering perspective nevertheless while defining the theoretically optimal level of component variety there are other elements more related to operators attitude or to operative conditions which may intervene and prevent effective exploitation of the existing variety these elements have been given scant attention in literature while they may play a relevant role in real organisations in this paper we will present a case study and an analytic model for these behavioural costs in manufacturing environments so as to show how the theoretically optimal amount of variety changes if one takes into account these aspects researchers and practitioners might leverage on this contribution in order to rejuvenate the variety reduction paradigm and to increase their awareness in designing and managing mass production manufacturing processes

optimal safety stock levels of subassemblies and manufacturing components abstract in order to control the time to market and manufacturing costs companies produce and purchase many parts and components before receiving customer orders consequently demand forecasting is a critical decision process using modular product design and super bills of materials are two effective strategies for developing a reliable demand forecasting process they reduce the probability of stockouts in diversified production contexts furthermore managing and controlling safety stocks for pre assembled modules provide an effective solution to the problem of minimizing the effects of forecast errors this paper develops evaluates and applies innovative cost based analytical models so that the optimal safety stock of modular subassemblies and components in assembly to order and manufacturing to order systems respectively can be rapidly quantified the implementation of the proposed models in two industrial case applications demonstrates that they significantly reduce the safety stock inventory levels and the global logistical cost

safety stock optimization in multi stage inventory systems abstract determining appropriate safety stocks in stochastic multi state production distribution systems is a very difficult task approaches for optimal determination of safety stocks regarding cost objectives and service level restrictions which are suitable for practical applications can only be found for a very limited class of multi stage inventory problems like problems of strictly serial structure or special two stage production distribution systems in this paper a procedure for determining the optimal size and distribution of safety stocks in a general serial or divergent production distribution process ruled by a base stock control policy is presented this approach especially allows for taking into account the impact of end item demand correlation on distribution and size of safety stocks by using risk pooling effects in divergent systems a powerful dynamic programming algorithm for solving the safety stock optimization problem is developed and impacts of problem parameter variations on the optimal solution are discussed

application of the scenario aggregation approach to a two stage stochastic common component inventory problem with a budget constraint abstract the purpose of this paper is to study from a new perspective the problem of allocating a given budget among product components that are required for manufacturing the end items in an assemble to order environment since some of the components are common to a number of different end items this constitutes a commonality inventory problem that in fact can be described as a two stage stochastic programming problem we explore the new possibilities made available by the scenario aggregation technique recently proposed by rockafeller and wets in work at the international institute of applied systems analysis iiasa their method was subsequently extended to deal with discrete problems this extension is utilized in the current study

measuring regional resilience towards fossil fuel supply constraints adaptability and vulnerability in socio ecological transformations the case of austria abstract resilience has become a prominent concept to understand system vulnerabilities and flexible ways of adapting to crises recently it gained importance in discussions about the possible peak in oil production peak oil and its consequences which might affect economic performance social well being and political stability and thus also the energy transition to a low carbon economy the paper presents a new way of measuring resilience as absolute resilience related to a best practice model of a resilient society the resilience model is grounded in explicit theoretical assumptions all indicators are justified by theoretical and empirical arguments we present a case study of austrian municipalities and broader scale spatial types which were defined according to their degree of urbanization the mean resilience of austrian municipalities is moderate the difference between resilience values of municipalities is small significant differences between spatial types exist higher resilience is displayed by less urbanized types due to a higher share of agricultural activities and a more favorable level of gdp per capita austria has considerable latitude to improve resilience corresponding policies should target resilience components with the lowest values first a sole focus on regionalization is not recommended these conclusions are applicable to oecd countries in general

stock rationing in an m ek 1 make to stock queue this paper considers the stock rationing problem of a single item make to stock production system with several demand classes and lost sales when demand is poisson and processing time has an erlang distribution we show that a single state variable called work storage level can be employed to completely capture the information regarding inventory level and the status of current production the optimal rationing policy can be characterized by a sequence of monotone critical work storage levels for each demand class there exists a work storage level at or below which it is optimal to start rejecting the demand of this class in anticipation of future arrival of higher priority demands the optimal production policy can also be characterized by a critical work storage level our numerical examples indicate that a critical stock level policy which ignores information on the status of current production performs very well

a threshold inventory rationing policy for service differentiated demand classes motivated by a study of the logistics systems used to manage consumable service parts for the u s military we consider a static threshold based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage stockout and delay costs the scheme operates as a q r policy with the following feature demands from both classes are filled on a first come first serve basis as long as on hand inventory lies above a threshold levelk once on hand inventory falls below this level low priority i e low shortage cost demand is backordered while high priority demand continues to be filled we analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters i e q r andk numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy we next highlight conditions where our policy offers significant savings over traditional round up and separate stock policies encountered in the military and elsewhere finally we develop a lower bound on the cost of the optimal rationing policy numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high technology industries

the strategic perils of delayed differentiation the value of delayed differentiation also known as postponement for a monopolist has been extensively studied in the operations literature we analyze the case of imperfectly competitive markets with demand uncertainty wherein the choice of supply chain configuration i e early or delayed differentiation is endogenous to the competing firms we characterize firms choices in equilibrium and analyze the effects of these choices on quantities sold profits consumer surplus and welfare we demonstrate that purely strategic considerations not previously identified in the literature play a pivotal role in determining the value of delayed differentiation in the face of either entry threats or competition these strategic effects can significantly diminish the value of delayed differentiation in fact under plausible conditions these effects dominate the traditional risk pooling benefits associated with delayed differentiation in which case early differentiation is the dominant strategy for firms even under cost parity with delayed differentiation we extend the main model to study the effects of alternate market structures asymmetric markets and inventory holdback our results in particular that for a broad range of parameter values early differentiation is a dominant strategy even under cost parity with delayed differentiation are robust to these relaxations

the effect of commonality on safety stock in a simple inventory model we examine the effects of component commonality on optimal safety stock levels in a two product two level inventory model the criterion is to minimize system safety stock subject to a service level constraint although our model is specialized its analysis provides insights not available in other multilevel inventory models

component rationing for available to promise scheduling in configure to order systems abstract we address the problem of rationing common components among multiple products in a configure to order system with order configuration uncertainty the objective of this problem is to maximize expected revenue by implementing a threshold rationing policy under this policy a product is available to promise if fulfilling the order for the product will not cause the inventory of any one of its required components to fall below the component s threshold level for that product the problem is modeled as a two stage stochastic integer program and solved using the sample average approximation approach a heuristic is developed to generate good feasible solutions and lower bound estimates using industry data we examine the benefit of component rationing as compared to a first come first served policy and show that this benefit is correlated to the average revenue per product and the variability in the revenue across products whose components are constrained

the costs and benefits of commonality in assemble to order systems with a q r policy for component replenishment abstract in assemble to order systems it has been shown that replacing a number of specific components by a smaller number of general purpose common components can reduce required safety stock levels due to the benefits of risk pooling previous research using single period models has shown that even if the common components are somewhat more expensive than the unique components they replace the benefits of risk pooling often outweigh the added purchasing costs however this has been shown often not to be the case with multiple period models in the long run the added purchasing costs dominate the benefits of risk pooling however both single and multiple period models ignore one of the benefits of commonality order pooling with commonality demand is pooled into a smaller number of components reducing the required number of orders or setups after re optimizing the order quantities and order intervals both the ordering costs and cyclic carrying costs are reduced this paper develops a model to consider the assemble to order environment where components are replenished according to a q r policy results show that order pooling is a significant benefit in many cases it is much more important than the risk pooling benefit in contrast to multiple period models there is often a total cost benefit with commonality even when the common component is several percent more expensive than the unique components it replaces

inventory rationing in a make to stock production system with several demand classes and lost sales this paper considers the stock rationing problem of a single item make to stock production system with several demand classes and lost sales for the case of poisson demands and exponential production times we show that the optimal policy can be characterized by a sequence of monotone stock rationing levels for each demand class there exists a stock rationing level at or below which it is optimal to start rejecting the demand of this class in anticipation of future arrival of higher priority demands a simple queueing model is analyzed to compute the operating cost of a rationing policy in a numerical study we compare the optimal rationing policy with a first come first served policy to investigate the benefit of stock rationing under different operating conditions of the system

just in time component replenishment decisions for assemble to order manufacturing under capital constraint and stochastic demand abstract while just in time ideas have been enthusiastically embraced by manufacturing practitioners the small replenishment batch sizes advocated are difficult to reconcile with the standard management science cost trade off approach in a previous paper by the authors which analysed a multi product manufacturing scenario under deterministic demand this difficulty was diagnosed as being due to the standard assumption that capital for inventory is borrowed and hence boundless when inventory is financed by investors and is thus finite the investment level must be treated as an additional variable in the decision to adopt inventory reduction policies for lean investments which might be chosen to maximise return on investment roi rather than absolute profit or for reasons of flexibility jit replenishment becomes more attractive for certain components than the standard analysis would suggest because the capital formerly invested in these components can be reinvested in the inventory of the remaining batch components to improve efficiencies this paper treats the stochastic version of the same problem develops a tractable solution method for the decision problem and in addition to reinforcing the findings of the previous study reveals several other ways in which jit replenishment and component substitution can improve performance by limiting the cost of dealing with uncertainty the analysis is illustrated using an actual case study of a small manufacturing enterprise seeking to reduce inventory and increase roi

optimal investment in product flexible manufacturing capacity this paper presents a model and an analysis of the cost flexibility tradeoffs involved in investing in product flexible manufacturing capacity flexible capacity provides a firm with the ability to respond to a wide variety of future demand outcomes but at the expense of the increased cost of acquiring flexible manufacturing capacity as compared with dedicated or nonflexible capacity we formulate the product flexible manufacturing capacity investment decision as a two stage stochastic program in the first stage the firm must make its investment decision in manufacturing capacity before the resolution of uncertainty in product demand in the second stage after demand for products are known the firm implements its production decisions constrained by the first stage investments the main contributions of this paper are threefold first we develop a model of the firm s flexible manufacturing investment decision that conceptually captures some of the key characteristics of this complex decision probl

determining near optimal base stock levels in two stage general inventory systems abstract this paper proposes an easily implementable scalable decomposition heuristic for determining near optimal base stocks in two level general inventory systems in this heuristic the general system is decomposed into assembly systems one for each end product for these assembly systems the base stock levels are calculated separately taking into account risk pooling effects for the common components our numerical analyses yield two main insights first the base stock levels determined by the heuristic are close to optimal second considerable improvements can be obtained compared to common sense heuristics

the surface of implied firm s asset volatility abstract this paper analyzes the surface of cds implied firm s asset volatility at the aggregate market level using a sample of european investment grade firms during the 2007 2014 period the term structure of asset implied volatilities is backed out from the term structure of cds spreads while the moneyness dimension is proxied by the ratio of the default barrier to asset value we find both a downward sloping term structure and a negative skew principal component analysis on the entire volatility surface shows that the first four components interpreted as a level a term structure a skew and a moneyness related curvature mode capture 86 of the daily variation in asset implied volatility we also find that the term structure slope is related to market and funding illiquidity investors risk aversion informational frictions demand supply factors and momentum

incentives and commonality in a decentralized multiproduct assembly system in this paper we explore the impact of decentralized decision making on the behavior of multiproduct assembly systems specifically we consider a system where three components two product specific and one common are used to produce two end products to satisfy stochastic customer demands we study the system under both centralized and decentralized decision making in the decentralized system we prove that for any set of wholesale prices there exists a unique pareto optimal equilibrium in the suppliers capacity game we show that the assembler s optimal wholesale prices lie in one of two regions one leads to capacity imbalance and one does not we use these results to derive insights regarding the inefficiencies that decentralization can cause in such systems in particular several of our findings indicate that outsourcing the management of component supplies may inhibit the use of operational hedging approaches for managing uncertainty

the impact of demand aggregation through delayed component allocation in an assemble to order system we consider an assemble to order system in which multiple products are assembled from a common component and a set of product dedicated components component capacities are chosen prior to a finite horizon selling season and the common component is allocated to the products based on observed demands we propose a collection of allocation mechanisms involving varying degrees of demand aggregation ranging from a scheme under which all demands are observed prior to making the allocation decision to allocations made for each arriving demand in this context we explore the impact of the allocation scheme on sales profits and capacity decisions including the degree of capacity imbalance we find that the benefit from increased demand aggregation is closely linked to the degree of capacity imbalance profit gains from delayed allocation tend to be higher in systems in which the optimal capacity portfolio is highly unbalanced when the allocation decision is made after observing all demands we develop insights into what detailed system parameters lead to the largest gains from demand aggregation and also explore the trade offs associated with the choice of an allocation scheme when customers exhibit impatience if the allocation scheme forces them to wait to be served this paper was accepted by ananth iyer operations and supply chain management

the multi location inventory centralization problem with first come first served allocation abstract in this paper the multi location inventory centralization problem is studied each location may be characterized by a unique selling price and unique consequences of stockouts reflecting its market economic structure the practice of such scenarios increases as more firms become involved in global international operations the objective is to determine the initial inventory level which will maximize the expected profit when allocation of inventory is immediate to the time when demand is generated i e first come first served fcfs it is shown that in spite of the fact that inventory allocation is contingent upon customers arrival processes generated in various locations the problem can be expressed as a single location problem where the interarrival process need not be considered furthermore managers should not be averse to centralization fearing that customers from a less profitable location will cannibalize the potential greater profit from other locations

capturing the risk pooling effect through demand reshape the risk pooling effect has been documented to benefit inventory systems by reducing the need for safety stock and consequently lowering costs such as inventory holding and shortage penalty in this paper we propose a new approach called demand reshape to take advantage of the risk pooling effect it is demonstrated that a company can improve its profit by encouraging some of its customers who intended to purchase one product to switch to another the effectiveness of this approach is evaluated in various scenarios and found to be very promising

risk pooling through physical probabilistic selling abstract this paper investigates the impacts of a new type of probabilistic selling p s where the retailer orders specific products and package some as a discounted physical probabilistic product ppp rather than merely a virtual choice we call this p s strategy as physical probabilistic selling p p s the price gap between the specific products and the probabilistic product results in demand reshape i e some customers who originally buy specific products will switch to buying the probabilistic product which decreases aggregate demand uncertainty however the price discount decreases the profit margin considering this trade off we develop a three product newsvendor model to address the question of how to set the price for the ppp and make inventory allocation decisions we prove that there are two effects under p p s namely the risk pooling effect due to demand reshape and the risk diversification effect due to inventory flexibility with demand uncertainty p p s can improve the retailer s profit at lower inventory levels with proper demand reshape induced by the optimal price discount p p s is more profitable with smaller product differentiation higher customer price sensitivity higher demand uncertainty and lower package cost with supply uncertainty we demonstrate through numerical studies that p p s is a viable strategy to combat asymmetrical supply risk that yields higher profits and service levels

the value of flexibility in make to order systems the effect of demand correlation we consider a manufacturer of mass customized modular products who orders components under demand uncertainty and sets prices produces to order and trades excess components in a secondary market after this uncertainty is resolved the sequence of events reflects in a parsimonious fashion the considerable reduction in demand uncertainty between the procurement stage and the selling season typical of industries with long supply lead times and short product life cycles we prove that in contrast to conventional wisdom the value of production flexibility and expected profit increase with demand correlation if and only if commonality between the corresponding products does not exceed a threshold we also prove that the value of flexibility and expected profit may each increase or decrease with demand variability depending on demand correlations and component commonalities across the entire product line finally we prove that when demand shocks are independent the optimal product prices are positively correlated if and only if the degree of commonality between the corresponding products exceeds a threshold

component commonality with service level requirements this paper extends recent results of baker et al baker k r m j magazine h l w nuttle 1986 the effect of commonality on safety stocks in a simple inventory model management sci 32 982 988 in understanding the impact of component commonality on stocking levels under service level constraints a model is formulated for an arbitrary number of products with general joint demand distribution the results obtained are not all intuitive while utilizing commonality is beneficial nothing general can be said about the resulting change in the components stock levels when the cost structure is of a particular simple form though some interesting general patterns do emerge we also discuss the case of using a service level measure where rationing of common components might be required and characterize the implied rationing rule

co production processes with random yields in the semiconductor industry a wide variety of manufacturing operations can be characterized as co production with substitutable demand that is there are many situations in which the availability of two or more items are related and because of randomness in either supply or demand it can be advantageous to substitute one of these items for another our research was motivated by the semiconductor industry where chips are produced in large batches because of the presence of randomness in the process individual chips in a given batch can perform differently because some customers have stricter specifications than others chips within the same batch can be classified and sold as different products according to their measurable performance we model the production and inventory problem as a stochastic dynamic program in which the objective is to minimize the costs of meeting contractual obligations after developing heuristic methods of solving the problem in practice we validate them against a lower bound on the cost of an optim

resilience in the light of energy crises part i a framework to conceptualise regional energy resilience abstract resilience in the light of an energy crisis is the capacity to successfully deal with energy related disruptions while continuing to deliver affordable energy services to society a resilient energy system can rapidly recover from a shock as it is able to reinvent itself but what happens if an energy crisis hits us which functions and structures will be affected shall we protect something in particular do we need to consider further aspects concerning the energy system and how can we address and operationalise these complex considerations these are the questions to be answered within this paper by identifying types of energy crises protective commodities and framework conditions a proposal is introduced to systematically deal with this topic a new approach for assessing the community resilience in case of a fossil energy crisis is originated and presented the regional energy resilience assessment rera