bureaucratic minimal squawk behavior theory and evidence from regulatory agencies this paper develops a model in which a desire to avoid criticism prompts otherwise public spirited bureaucrats to behave inefficiently decisions are taken to keep interest groups quiet and to keep mistakes out of the public eye the policy implications of this minimal squawk behavior are at odds with the view that agencies should be structured to minimize the threat of capture an empirical test using data from us state public utility commissions rejects the capture hypothesis and is consistent with the squawk hypothesis longer puc terms of office are associated with a higher incidence of rate reviews and lower household electricity bills jel d73 l51 l97 l98

optimal dynamic pricing of inventories with stochastic demand over finite horizons in many industries managers face the problem of selling a given stock of items by a deadline we investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm s objective is to maximize expected revenues examples that fit this framework include retailers selling fashion and seasonal goods and the travel and leisure industry which markets space such as seats on airline flights cabins on vacation cruises and rooms in hotels that become worthless if not sold by a specific time we formulate this problem using intensity control and obtain structural monotonicity results for the optimal intensity resp price as a function of the stock level and the length of the horizon for a particular exponential family of demand functions we find the optimal pricing policy in closed form for general demand functions we find an upper bound on the expected revenue based on analyzing the deterministic version of the problem and use this bound to prove that simple fixed price policies are asymptotically optimal as the volume of expected sales tends to infinity finally we extend our results to the case where demand is compound poisson only a finite number of prices is allowed the demand rate is time varying holding costs are incurred and cash flows are discounted the initial stock is a decision variable and reordering overbooking and random cancellations are allowed

optimal dynamic price selection under attraction choice models abstract we present a single resource finite horizon markov decision process approach for a firm that seeks to maximize expected revenues by dynamically adjusting the menu of offered products and their prices to be selected from a finite set of alternative values predetermined as a matter of policy consumers choose among available products according to an attraction choice model a special but widely applied class of discrete choice models the fractional substructure inherent to attraction choice models enables the derivation of structural properties that significantly simplify the computation of an optimal policy we show that the more capacity or less time is remaining the lower are the optimal prices we develop an exact solution procedure for preprocessing and recursively solving price selection problems that clearly outperforms current revenue management approaches with respect to computational complexity furthermore we demonstrate that the potential revenue improvements from dynamic compared to fixed pricing can be significant ranging from 4 5 up to 149 for selected examples from the literature extensions to multiple resources and to related discrete choice models are discussed

a market discovery algorithm to estimate a general class of nonparametric choice models we propose an approach for estimating customer preferences for a set of substitutable products using only sales transactions and product availability data the underlying demand framework combines a general nonparametric discrete choice model with a bernoulli process of arrivals over time the choice model is defined by a discrete probability mass function pmf on a set of possible preference rankings of alternatives and it is compatible with any random utility model an arriving customer is assumed to purchase the available option that ranks highest in her preference list the problem we address is how to jointly estimate the arrival rate and the pmf of the rank based choice model under a maximum likelihood criterion since the potential number of customer types is factorial we propose a market discovery algorithm that starts with a parsimonious set of types and enlarge it by automatically generating new types that increase the likelihood value numerical experiments confirm the potential of our proposal for a realistic data set in the hospitality industry our approach improves the root mean square errors between predicted and observed purchases computed under independent demand model estimates by 67 to 93 this paper was accepted by serguei netessine operations management

truth effort and the legal battle in lawsuits relative success depends upon two main factors the true degree of fault and the efforts invested on eachside a proposed litigation success function displays thisdependence while satisfying other essential properties undertwo different protocols nash cournot and stackelberg solutions are obtained for the litigation efforts proportionate success and values of the lawsuit on each side outcomes are evaluated in terms of two normative criteria i achieving justice interpreted as equality between defendantfault and relative plaintiff success and ii minimizingaggregate litigation cost achievement of these aims isdetermined by the decisiveness of litigation effort relativeto true fault

revenue management of callable products a callable product is a unit of capacity sold to self selected low fare customers who willingly grant the capacity provider the option to call the capacity at a prespecified recall price we analyze callable products in a finite capacity setting with two fare classes where low fare customers book first and show that callable products provide a riskless source of additional revenue to the capacity provider an optimal recall price and an optimal discount fare booking limit for the two period problem are obtained numerical examples show the benefits from offering callable products can be significant especially when high fare demand uncertainty is large extensions to multifare structures network models overbooking and to other industries are discussed

constrained assortment optimization for the nested logit model we study assortment optimization problems where customer choices are governed by the nested logit model and there are constraints on the set of products offered in each nest under the nested logit model the products are organized in nests each product in each nest has a fixed revenue associated with it the goal is to find a feasible set of products i e a feasible assortment to maximize the expected revenue per customer we consider cardinality and space constraints on the offered assortment which limit the number of products and the total space consumption of the products offered in each nest respectively we show that the optimal assortment under cardinality constraints can be obtained efficiently by solving a linear program the assortment optimization problem under space constraints is np hard we show how to obtain an assortment with a performance guarantee of 2 under space constraints this assortment also provides a performance guarantee of 1 1 when the space requirement of each produc

robust assortment optimization in revenue management under the multinomial logit choice model we study robust formulations of assortment optimization problems under the multinomial logit choice model the novel aspect of our formulations is that the true parameters of the logit model are assumed to be unknown and we represent the set of likely parameter values by a compact uncertainty set the objective is to find an assortment that maximizes the worst case expected revenue over all parameter values in the uncertainty set we consider both static and dynamic settings the static setting ignores inventory consideration whereas in the dynamic setting there is a limited initial inventory that must be allocated over time we give a complete characterization of the optimal policy in both settings show that it can be computed efficiently and derive operational insights we also propose a family of uncertainty sets that enables the decision maker to control the trade off between increasing the average revenue and protecting against the worst case scenario numerical experiments show that our robust approach combined with our proposed family of uncertainty sets is especially beneficial when there is significant uncertainty in the parameter values when compared to other methods our robust approach yields over 10 improvement in the worst case performance but it can also maintain comparable average revenue if average revenue is the performance measure of interest

the effect of market segmentation with demand leakage between market segments on a firm s price and inventory decisions abstract in this paper we address the simultaneous determination of price and inventory replenishment in a newsvendor setting when the firm faces demand from two or more market segments in which the firm can set different prices we allow for demand leakage from higher priced segments to lower priced segments and assume that unsatisfied demand can be backlogged we examine the case where the demands occur concurrently without priority and are met from a single inventory we consider customer s buy down behavior explicitly by modeling demand leakage as a function of segment price differentiation and characterize the structure of optimal inventory and pricing policies

the market for lawyers and quality layers in legal services we study the functioning of the market for lawyers considering the strategic interaction among litigants lawyers and judges we investigate the value of legal representation and of systems of quality certification such as the queen s counsel system in our setting higher quality lawyers obtain better quality evidence and are better able to interpret it judges receive information from the lawyers and have reputational concerns we show that reputational concerns generate a decision bias in favor of certified lawyers and that this causes misallocation of lawyers at the market equilibrium as a result whereas a higher quality of lawyers increases welfare public information over quality may be welfare reducing

game theoretic pricing models in hotel revenue management an equilibrium choice based conjoint analysis approach abstract this paper explores a game theoretically founded approach to conjoint analysis that determines equilibrium room rates under differentiated price competition in an oligopolistic hotel market competition between hotels is specified in terms of market share functions that can be estimated using multinomial logit models of consumer choice the approach is based on choice based conjoint analysis that permits the estimation of attributes weights part worths for an additive utility formulation of the utility function from this room rates that equilibrate the market conditioned on the differences in services and facilities offered by competing hotels can be determined the approach is illustrated by an example

equilibrium loan pricing under the bank client relationship abstract we determine the loan interest rate policy of a lender who is better informed about a client than other potential lenders the informational advantage possessed by the informed lender derives from the durability of information acquired as a result of an extant relationship given heterogeneous potential loan rate offers to the client by competitive lenders and client search costs the incumbent lender s policy of loan interest rate offers is examined we show that the optimal loan rate will exceed the incumbent lender s cost of funds and will exceed the average offer of competing lenders the potential lenders will offer loan rates that are exceeded by their cost of funds implying immediate losses in order to attract the client and to thereby earn expected profits in the future finally we show that the expected remaining duration of a lender client relationship is decreasing in the existing length of the relationship thus clients that have been with a particular lender longer will be more likely to leave and establish a relationship with another lender

a general attraction model and sales based linear program for network revenue management under customer choice this paper addresses two concerns with the state of the art in network revenue management with dependent demands the first concern is that the basic attraction model bam of which the multinomial logit mnl model is a special case tends to overestimate demand recapture in practice the second concern is that the choice based deterministic linear program currently in use to derive heuristics for the stochastic network revenue management problem has an exponential number of variables we introduce a generalized attraction model gam that allows for partial demand dependencies ranging from the bam to the independent demand model idm we also provide an axiomatic justification for the gam and a method to estimate its parameters as a choice model the gam is of practical interest because of its flexibility to adjust product specific recapture our second contribution is a new formulation called the sales based linear program sblp that works for the gam this formulation avoids the exponential number of variables in the earlier choice based network rm revenue management approaches and is essentially the same size as the well known lp formulation for the idm the sblp should be of interest to revenue managers because it makes choice based network rm problems tractable to solve in addition the sblp formulation yields new insights into the assortment problem that arises when capacities are infinite together these contributions move forward the state of the art for network revenue management under customer choice and competition

a nonparametric approach to modeling choice with limited data choice models today are ubiquitous across a range of applications in operations and marketing real world implementations of many of these models face the formidable stumbling block of simply identifying the right model of choice to use because models of choice are inherently high dimensional objects the typical approach to dealing with this problem is positing a priori a parametric model that one believes adequately captures choice behavior this approach can be substantially suboptimal in scenarios where one cares about using the choice model learned to make fine grained predictions one must contend with the risks of mis specification and overfitting underfitting thus motivated we visit the following problem for a generic model of consumer choice namely distributions over preference lists and a limited amount of data on how consumers actually make decisions such as marginal information about these distributions how may one predict revenues from offering a particular assortment of choices an outcome of our investigation is a nonparametric approach in which the data automatically select the right choice model for revenue predictions the approach is practical using a data set consisting of automobile sales transaction data from a major u s automaker our method demonstrates a 20 improvement in prediction accuracy over state of the art benchmark models this improvement can translate into a 10 increase in revenues from optimizing the offer set we also address a number of theoretical issues among them a qualitative examination of the choice models implicitly learned by the approach we believe that this paper takes a step toward automating the crucial task of choice model selection this paper was accepted by yossi aviv operations management

how the market solves an assignment problem the matching of lawyers with legal claims in the market for lawyers observable data on promotion and turnover can be explained by reference to the idea that there is positive assortative mating of lawyers and legal claims there is a scale of resources effect under which it is optimal to assign larger claims to lawyers of higher quality in a law firm the institution of tenure performs a sorting function lawyers found to be of high quality are given tenured positions and the rest leave the value of legal claims handled by a firm determines its sorting problem which in turn determines its promotion ladder and turnover

flight to quality in banking and economic activity abstract recent explanations of the transmission mechanism of monetary policy have emphasized that riskier lower net worth borrowers are more dependent on bank lending than larger less risky borrowers evidence from the federal reserve s survey on terms of bank lending indicates that the proportion of relatively high quality new loans safe moves countercyclically and granger causes gdp and inventory investment in the aftermath of a tightening of monetary policy the safe variable increases and in turn policy tends to relax once safe has risen

optimal fences and joint price and inventory decisions in distinct markets with demand leakage abstract this paper evaluates the simultaneous determination of price and inventory replenishment when a firm faces demand from distinct market segments a firm utilizes fences such as advance or nonrefundable payment to maintain separation of its market segments however fences are imperfect and allow a degree of demand leakage from the higher priced to the lower priced market segment we investigate the optimal structure of joint price and inventory decisions with fencing and demonstrate that more segments is not necessarily better especially when demand uncertainty is high in the presence of lost sales we also show the impact of imperfect fences on the firm s profitability and evaluate how fencing costs affect the optimal fencing decision

the exponomial choice model a new alternative for assortment and price optimization we investigate the use of a canonical version of a discrete choice model due to daganzo 1979 daganzo c 1979 multinomial probit the theory and its application to demand forecasting academic press new york in optimal pricing and assortment planning in contrast to multinomial and nested logit the prevailing choice models used for optimizing prices and assortments this model assumes a negatively skewed distribution of consumer utilities an assumption we motivate by conceptual arguments as well as published work the choice probabilities in this model can be derived in closed form as an exponomial a linear function of exponential terms the pricing and assortment planning insights we obtain from the exponomial choice ec model differ from the literature in two important ways first the ec model allows variable markups in optimal prices that increase with expected utilities second when prices are exogenous the optimal assortment may exhibit leapfrogging in prices i e a product can be s

integration of pricing and capacity allocation for perishable products abstract for years pricing and capacity allocation decisions in most revenue management models have been carried out independently this article presents a comprehensive model to integrate these two decisions for perishable products we assume that the supplier sells the same products to different micro markets at distinct prices throughout the sales season the supplier faces decisions as to which micro markets or customer classes should be served and at what prices we show that i at any time a customer class is active being served if and only if the price offered is over a threshold level but the optimal price may not be the highest one of the supplier s choice ii when the price decision is made in conjunction with inventory it is similar to the procedure shown in pure pricing models i e the optimal price comes from a subset of prices that forms a maximum increasing concave envelope iii because of dynamic changes in the optimal prices the nested price structure does not necessarily hold in general and needs to be redefined and iv the optimal pricing and capacity control policy is based on a sequence of threshold points that incorporate inventory price and demand intensity numerical examples are provided

blood platelet inventory management with protection levels abstract we consider a discrete time inventory system for a perishable product where demand exists for product of different ages an example of such a product is blood platelets in addition to the classical costs for inventory holding outdating and shortage our model includes substitution mismatch costs incurred when a demand for a certain aged item is satisfied by a different aged item we propose a simple inventory replenishment and allocation heuristic to minimize the expected total cost over an infinite time horizon in our heuristic inventory of the newest items is replenished in fixed quantities and the newest items are protected for future use by limiting some substitutions when making allocation decisions according to a critical level policy we model our problem as a markov decision process mdp derive the costs of our heuristic policy and computationally compare this policy to extant near optimal policies in the literature our extensive computational study shows that our policy leads to superior performance compared to existing heuristics in the literature particularly when supplies are limited

strategic and tactical price decisions in hotel revenue management abstract dynamic pricing techniques allow using a number of variables in a tactical way compared to standard catalogue prices this study merges in a conceptual model the relevance of the tactical and the strategic dimension of these variables classified according to their tangible reputational or contextual nature to empirically validate the hypotheses a database of 21 596 price observations was retrieved from booking com the study presents a hedonic price function using the shapley owen decomposition of the r squared to elicit the importance of each group of factors further a hierarchical cluster analysis measures the presence of heterogeneity across operators the results show that online reputation is gaining importance over the traditional star rating despite the tangible variables remain of paramount importance the findings suggest the relevant role of contextual variables in short run price variations the players operating in the tourism and hospitality industries should integrate these findings when designing pricing strategies

performance and governance in microfinance institutions accepted version of article published in the journal journal of banking finance published version available on science direct http dx doi org 10 1016 j jbankfin 2008 11 009

the market for lawyers it is hardly news but the plethora of bad jokes about lawyers should be the tip off that the 1980s were a boom market for legal services data always lag behind a little and mine are no exception the current recession is not included but although the price of lawyers time in the mid1980s had not attained the all time heights of the late 1960s and early 1970s it was traveling fast in that direction the harder problem is understanding why the data are described in light of some fundamental economic ideas much important research on the economics of occupational choice has been done by economists who were at or associated with the university of chicago milton friedman s doctoral dissertation published with simon kuznets l was a remarkable pioneering empirical study of incomes from independent professional practice contrasting medicine with law some important aspects of that study were clarified and extended by h gregg lewis 2 david blank and george stigler s study of scientists and engineers was one of the first empirical studies of a subject that is still a great concern of public policy 3 t w schultz and gary becker devel

managerial incentive problems a dynamic perspective the paper studies how a person s concern for a future career may influence his or her incentives to put in effort or make decisions on the job in the model the person s productive abilities are revealed over time through observations of performance there are no explicit output contingent contracts but since the wage in each period is based on expected output and expected output depends on assessed ability an implicit contract links today s performance to future wages an incentive problem arises from the person s ability and desire to influence the learning process and therefore the wage process by taking unobserved actions that affect today s performance the fundamental incongruity in preferences is between the individual s concern for human capital returns and the firm s concern for financial returns the two need be only weakly related it is shown that career motives can be beneficial as well as detrimental depending on how well the two kinds of capital returns are aligned it is well understood by now that informational externalities may place special demands on the organization of economic exchange simple price mediated markets will frequently fail in the presence of asymmetric information in that case more elaborate contractual arrangements have to be used as substitutes for the price system lately considerable effort has been devoted to the analysis of contracting under incomplete information with the objective to understand the range of economic institutions that emerge in response to the failure of the price system the analysis of moral hazard has played a prominent role in this development moral hazard problems arise when for some reason or another transacting parties cannot contract contingent on the delivery of the good for instance in buying labour services it may be that the amount of labour supplied is not directly observable precluding a simple exchange of wage for labour as a partial remedy to this problem an imperfect mutually observed signal about the supply of labour can be used as a proxy in the contract frequently output is taken as such a proxy the drawback is that output is often influenced by other factors than labour input which induce undesirable risk into the contract one is therefore faced with a tradeoff between allocating risk associated with incomplete observability and providing incentives for a proper supply of labour gaining insight into this tradeoff is important not only for understanding contracting in the small e g managerial incentive schemes but also because it is closely related to the fundamental tension between equity and efficiency in the society as a whole while our understanding of moral hazard has advanced a lot in past years it is clear that much work remains an important question that has received little attention until

a constructive approach to estimating pure characteristics demand models with pricing discrete choice demand models are important and fundamental tools for understanding consumers choice behavior and for analyzing firms operations and pricing strategies in these models products are often described as a vector of observed characteristics a consumer chooses the product that maximizes her utility assumed to be a function of the observed product characteristics and the consumer s preference over these product characteristics one central task in the demand estimation literature is to infer based on observed data consumers preferences on product characteristics we consider such an estimation problem for pure characteristics models a class of random coefficients demand models without the idiosyncratic logit error term in a consumer s utility function the absence of the logit error term and the use of numerical integration to approximate the integral in aggregate market shares lead to a nonsmooth formulation of approximated market share equations as a result solving the approximated

joint inventory and markdown management for perishable goods with strategic consumer behavior in this paper we formulate and analyze a novel model on a firm s dynamic inventory and markdown decisions for perishable goods we consider a dynamic stochastic setting where every period consists of two phases clearance phase and regular sales phase in the clearance phase the firm decides how much to order for regular sales as well as whether to markdown some or all of the leftover inventory from the previous period that will be disposed otherwise since strategic consumers may buy the product during clearance sales for future consumption markdown may cannibalize future sales at regular price hence the firm needs to make a trade off between product spoilage and intertemporal demand substitution we show that the firm should either put all of the leftover inventory on discount or dispose all of it and the choice depends on the amount of leftover inventory from the previous period in particular the firm should introduce markdown when the amount of leftover inventory is higher than a certain th

revenue sharing in airline alliances we propose a two stage game theoretic approach to study the operations of an airline alliance in which independent carriers managing different reservation and information systems can collaboratively market and operate codeshare and interline itineraries in the first stage game airlines negotiate fixed proration rates to share the revenues generated by such itineraries in the second stage game airlines operate independent inventory control systems to maximize their own expected revenues we derive a revenue sharing rule that is i an admissible outcome of the first stage negotiation in the sense that no airline coalition has enough incentives to secede from the grand alliance and ii efficient for the second stage game in the sense that the decentralized system can achieve the same revenues as a central planner managing the global alliance network our numerical study shows that the proposed proration rates can lead to a significant increase in revenues with respect to other rules commonly used

banks as multioutput oligopolies an empirical evaluation of the retail and corporate banking markets the distinction between retail and corporate banking markets is of much importance in real life banking organizations the two markets differ with respect to concentration the importance of informational asymmetries and the extent of customer mobility within a standard conjectural variation model estimated on cost efficient banks as well as on the full sample of banks the authors empirically characterize the strategic behavior in each of these markets and also focus on cross market interactions to see whether initial moves in one market affect the equilibrium in the other market they compare their findings to the predictions that would follow from merely considering concentration ratios such as the herfindahl index

dynamic pricing when consumers are strategic analysis of posted and contingent pricing schemes abstract we study dynamic pricing policies for a monopolist selling perishable products over a finite time horizon to strategic buyers buyers are strategic in the sense that they anticipate the firm s price policies it is expensive and administratively difficult for most brick and mortar retailers to change prices placing limits on the number of price changes and the types of pricing policies they can adopt the simplest policy is to commit to a set of price changes a more complex alternative is to let the price depend on sales history we investigate two pricing schemes that we call posted and contingent pricing using the posted pricing scheme the firm announces a set of prices at the beginning of the horizon in the contingent pricing scheme price evolution depends upon demand realization our focus is on the posted pricing scheme because of its ease of implementation counter to intuition we find that neither a posted pricing scheme nor a contingent pricing scheme is dominant and the difference in expected revenues of these two schemes is small limiting the number of price changes will result in a decrease in expected revenues we show that a multi unit auction with a reservation price provides an upper bound for expected revenues for both pricing schemes numerical examples suggest that a posted pricing scheme with two or three price changes is enough to achieve revenues that are close to the upper bound dynamic pricing is only useful when strategic buyers perceive scarcity we study the impact of scarcity and derive the optimal stocking levels for large markets finally we investigate whether or not it is optimal for the seller to conceal inventory or sales information from buyers a firm benefits if it does not reveal the number of units it has available for sale at the beginning of the season or subsequently withholds information about the number of units sold

revenue management with limited demand information in this paper we consider the classical multifare single resource leg problem in revenue management for the case where demand information is limited our approach employs a competitive analysis which guarantees a certain performance level under all possible demand scenarios the only information required about the demand for each fare class is lower and upper bounds we consider both competitive ratio and absolute regret performance criteria for both performance criteria we derive the best possible static policies which employ booking limits that remain constant throughout the booking horizon the optimal policies have the form of nested booking limits dynamic policies which employ booking limits that may be adjusted at any time based on the history of bookings are also obtained we provide extensive computational experiments and compare our methods to existing ones the results of the experiments demonstrate the effectiveness of these new robust methods

perishable asset revenue management with markovian time dependent demand intensities many industries face the problem of selling a fixed stock of items over a finite horizon these industries include airlines selling seats before planes depart hotels renting rooms before midnight theaters selling seats before curtain time and retailers selling seasonal items with long procurement lead times given a sunk investment in seats rooms or winter coats the objective for these industries is to maximize revenues in excess of salvage value when demand is price sensitive and stochastic pricing is an effective tool to maximize expected revenues in this paper we address the problem of deciding the optimal timing of price changes within a given menu of allowable possibly time dependent price paths each of which is associated with a general poisson process with markovian time dependent predictable intensities we show that a set of variational inequalities characterize the value functions and the optimal possibly random time changes in addition we develop an efficient algorithm to compute the optimal value functions and the optimal pricing policy

assortment optimization under variants of the nested logit model we study a class of assortment optimization problems where customers choose among the offered products according to the nested logit model there is a fixed revenue associated with each product the objective is to find an assortment of products to offer so as to maximize the expected revenue per customer we show that the problem is polynomially solvable when the nest dissimilarity parameters of the choice model are less than one and the customers always make a purchase within the selected nest relaxing either of these assumptions renders the problem np hard to deal with the np hard cases we develop parsimonious collections of candidate assortments with worst case performance guarantees we also formulate a convex program whose optimal objective value is an upper bound on the optimal expected revenue thus we can compare the expected revenue provided by an assortment with the upper bound on the optimal expected revenue to get a feel for the optimality gap of the assortment by using this approach our computational experiments test the performance of the parsimonious collections of candidate assortments that we develop

transformation of optimization problems in revenue management queueing system and supply chain management abstract for revenue optimization problems in the literature on revenue management supply chain management and queueing systems some assumptions such as concavity of revenue functions or increasing generalized failure rate are often needed to ensure the problems to be analytically tractable we show that these assumptions are not necessary for this we present and study a parametric revenue maximization problem to unify some problems in the literature without the usual assumptions we transform the problem into an equivalent one where the revenue function is increasing continuous and concave we then apply the transformation method to a continuous time revenue management problem and conclude that the monotone results are robust to demand function and allowable price set also we apply the transformation method to study a parametric cost minimization problem we further apply our method to two optimal control problems in queueing systems and an inventory control problem in a supply chain with price only contract

high price or low price an experimental study on a markdown pricing policy abstract this study examines whether strategic customers behavioral patterns remain consistent in different pricing scenarios under a markdown pricing policy these customers decision patterns have been widely discussed because they significantly influence the expected monetary output contrary to rational assumptions the behavioral research literature indicates that customers behavioral biases manifest in their reference dependency risk and loss attitudes and fill rate misperceptions however the relationship between behavioral biases and various pricing scenarios has not been carefully examined accordingly we conducted laboratory experiments to observe customers behavioral performance in a series of pricing scenarios to provide pricing suggestions for sellers our experimental results demonstrate that behavioral factors reflecting risk and loss attitudes as well as reference dependency can clearly describe customers behavioral biases meanwhile our estimation shows that the degrees of risk and loss attitude are not constant but depend on price settings the lower the full price in the initial period the higher the degrees of aversion to both risk and loss given such behavioral patterns we suggest that sellers should set their full prices lower than the normative value when the fill rate in period two is low and set them higher than the normative value when the fill rate in period two is high

revenue management with partially refundable fares we introduce and analyze an intertemporal choice model where customer valuations are uncertain and evolve over time the model leads directly to the study of call options on capacity that are similar to partially refundable fares we show that the capacity provider earns significantly higher revenues by selling real options on capacity than on low to high pricing we also investigate the social implications and show that the use of options is both socially optimal and socially efficient

information and bank credit allocation abstract private information obtained by lenders leads to borrower capture to the extent that such information cannot be communicated credibly to outsiders we analyze how this capture affects the loan portfolio allocation of informed lenders first we show that banks charge higher interest rates and finance relatively less creditworthy borrowers in market segments with greater information asymmetries second when faced with greater competition from outside lenders banks reallocate credit toward more captured borrowers flight to captivity third if borrower quality and captivity are sufficiently correlated an increase in the competitiveness of uninformed lenders can worsen the informed lender s overall loan portfolio the model explains observed consequences of financial liberalizations

financial system architecture this article builds a theory of financial system architecture we ask what is a financial market what is a bank and what determines the economic role of each starting with basic assumptions about primitives the types of agents and the nature of the informational asymmetries we provide a theory that explains which agents coalesce to form banks and which trade in the capital market it is shown that borrowers of higher observable qualities access the financial market moreover a financial system in its infancy will be bank dominated and increased financial market sophistication diminishes bank lending article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

the assortment packing problem multiperiod assortment planning for short lived products motivated by retailers frequent introduction of new items to refresh product lines and maintain their market shares we present the assortment packing problem in which a firm must decide in advance the release date of each product in a given collection over a selling season our formulation models the trade offs among profit margins preference weights and limited life cycles a key aspect of the problem is that each product is short lived in the sense that once introduced its attractiveness lasts only a few periods and vanishes over time the objective is to determine when to introduce each product to maximize the total profit over the selling season even for two periods the corresponding optimization problem is shown to be np complete as a result we study a continuous relaxation of the problem that approximates the problem well when the number of products is large when margins are identical and product preferences decay exponentially its solution can be characterized it is optimal to introduce products with slower decays earlier the structural properties of the relaxation also help us to develop several heuristics for which we establish performance guarantees we test our heuristics with data on sales and release dates of women s handbags from an accessories retailer the numerical experiments show that the heuristics perform very well and can yield significant improvements in profitability this paper was accepted by yossi aviv operations management

network revenue management with inventory sensitive bid prices and customer choice we develop an approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the markov decision process with a non linear function which is separable across resource inventory levels this approximation can exhibit significantly improved accuracy compared to currently available methods it further allows for arbitrary aggregation of inventory units and thereby reduction of computational workload yields upper bounds on the optimal expected revenue that are provably at least as tight as those obtained from previous approaches computational experiments for the multinomial logit choice model with distinct consideration sets show that policies derived from our approach can outperform some recently proposed alternatives and we demonstrate how aggregation can be used to balance solution quality and runtime

optimal starting times for end of season sales and optimal stopping times for promotional fares many industries face the problem of selling a fixed stock of items over a finite horizon these industries include airlines selling seats before planes depart hotels renting rooms before midnight theaters selling seats before curtain time and retailers selling seasonal goods such as air conditioners or winter coats before the end of the season given a fixed number of seats rooms or coats the objective for these industries is to maximize revenues in excess of salvage value when demand is price sensitive and stochastic pricing is an effective tool to maximize revenues in this paper we address the problem of deciding the optimal timing of a single price change from a given initial price to either a given lower or higher second price under mild conditions we show that it is optimal to decrease resp to increase the initial price as soon as the time to go falls below resp above a time threshold that depends on the number of yet unsold items

optimal pricing for a multinomial logit choice model with network effects we consider a seller s problem of determining revenue maximizing prices for an assortment of products that exhibit network effects customers make purchase decisions according to a multinomial logit choice model modified to incorporate network effects so that the utility each individual customer gains from purchasing a particular product depends on the market s total consumption of that product in the setting of homogeneous products we show that if the network effect is comparatively weak then the optimal pricing decision of the seller is to set identical prices for all products however if the network effect is strong then the optimal pricing decision is to set the price of one product low and to set the prices of all other products to a single high value this boosts the sales of the single low price product in comparison to the sales of all other products we also obtain comparative statics results that describe how optimal prices and sales levels vary with a parameter that determines the strengt

the determinants and profitability of switching costs in chinese banking this article models the determinants of bank switching costs in china in terms of bank characteristics and non bank variables it also determines the contribution of switching costs to banks profits using a sample of 151 banks over the period 2003 2013 it reports a positive relationship between bank profitability and switching costs the main result is that bank size measured by total assets has a complex relationship with switching costs competition between small banks creates the incentive for lock in and increased switching costs whereas very large banks are less exercised by lock in and switching costs

revenue management under a general discrete choice model of consumer behavior customer choice behavior such as buy up and buy down is an important phenomenon in a wide range of revenue management contexts yet most revenue management methodologies ignore this phenomenon or at best approximate it in a heuristic way in this paper we provide an exact and quite general analysis of this problem specifically we analyze a single leg reserve management problem in which the buyers choice behavior is modeled explicitly the choice model is very general simply specifying the probability of purchase for each fare product as a function of the set of fare products offered the control problem is to decide which subset of fare products to offer at each point in time we show that the optimal policy for this problem has a quite simple form namely it consists of identifying an ordered family of efficient subsets s 1 s m and at each point in time opening one of these sets s k where the optimal index k is increasing in the remaining capacity x and decreasing in the remaining time that is the more capacity or less time available the further the optimal set is along this sequence we also show that the optimal policy is a nested allocation policy if and only if the sequence of efficient sets is nested that is s 1 s 2 s m moreover we give a characterization of when nesting by fare order is optimal we also develop an estimation procedure for this setting based on the expectation maximization em method that jointly estimates arrival rates and choice model parameters when no purchase outcomes are unobservable numerical results are given to illustrate both the model and estimation procedure

an analysis of bid price controls for network revenue management bid prices are becoming an increasingly popular method for controlling the sale of inventoryin revenue management applications in this form of control threshold or bid prices are set for the resources or units of inventory seats on flight legs hotel rooms on specific dates etc and a product a seat in a fare class on an itinerary or room for a sequence of dates is sold only if the offered fare exceeds the sum of the threshold prices of all the resources needed to supply the product this approach is appealing on intuitive and practical grounds but the theory underlying it is not well developed moreover the extent to which bid price controls represent optimal or near optimal policies is not well understood using a general model of the demand process we show that bid price control is not optimal in general and analyze why bid price schemes can fail to produce correct accept deny decisions however we prove that when leg capacities and sales volumes are large bid price controls are asymptotically optimal provided the right bid prices are used we also provide analytical upper bounds on the optimal revenue in addition we analyze properties of the asymptotically optimal bid prices for example we show they are constant over time even when demand is nonstationary and that they may not be unique

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

demand estimation and ordering under censoring stock out timing is almost all you need retailers facing uncertain demand can use observed sales to update demand estimates however such learning is limited by the amount of inventory carried when demand exceeds inventory i e when a stock out event occurs a retailer in general cannot observe actual demand we propose using observations on the timing of sales occurrences in a bayesian fashion to learn about demand and we analyze this learning method for a multiperiod newsvendor setting we find that as previously shown with the use of only stock out event observations the optimal order quantity with timing observations is greater than the optimal order quantity with full demand observations we prove this result using a novel methodology from the statistics literature on comparison of experiments although the optimal over ordering with timing observations tends to be less than that with only stock out event observations in most cases we do observe cases where the opposite is true such cases correspond to high demand uncertainty and low margins where marginal learning from timing observations is significantly higher than using only a stock out event in an extensive numerical study we find that on average and with respect to uncensored demand observations the use of timing observations eliminates 76 1 of the loss in expected profit from using only stock out event observations we show that for poisson and normal demand with unknown mean the proposed learning method is tractable as well as intuitively appealing the information contained in the timing of sales occurrences is fully captured by a single number the timing of stock out we also investigate checkpoint models in which the newsvendor can make observations only at predetermined times in a period and illustrate its convergence to the models with timing and stock out event observations

dynamic pricing of multiple home delivery options abstract online grocers accept delivery bookings and have to deliver groceries to consumers residences grocery stores operate on very thin margins therefore a critical question that an online grocery store needs to address is the cost of home delivery operations in this paper we develop a markov decision process based pricing model that recognizes the need to balance utilization of delivery capacity by the grocer and the need to have the goods delivered at the most convenient time for the customer the model dynamically adjusts delivery prices as customers arrive and make choices the optimal prices have the following properties first the optimal prices are such that the online grocer gains the same expected payoff in the remaining booking horizon regardless of the delivery option independently chosen by a consumer second with unit order sizes delivery prices can increase due to dynamic substitution effects as there is less time left in the booking horizon

dynamic capacity management with uncertain demand and dynamic price inspired from practices of chinese real estate firms we study dynamic capacity management problems for a firm that sells homogeneous goods over a finite or infinite selling horizon provided that demand is uncertain retail price is exogenous but changes according to an auto regressive process and there is holding cost for remaining inventory in each period the capacity problems facing the firm include to determine an initial stock at the beginning of the selling season and to allocate the remaining quantity for the current and future sale in each period to maximize the firm s total expected discounted profit by using markov decision processes we show the optimality of a so called save up to level policy i e it is optimal to allocate as much as the save up to level to future periods if possible in each period and the existence of the optimal initial stock moreover we characterize monotone properties of the optimal save up to level and the optimal initial stock numerical analysis shows that compared to the policy with zero save up to level i e always allocating all the remaining inventory to the current period the advantage of the policy proposed in the present paper is significant when price rising trend is large holding cost is low initial price is high or demand variation is either high or low

coordinating clearance markdown sales of seasonal products in retail chains in this paper we propose a methodology to set prices of perishable items in the context of a retail chain with coordinated prices among its stores and compare its performance with actual practice in a real case study we formulate a stochastic dynamic programming problem and develop heuristic solutions that approximate optimal solutions satisfactorily to compare this methodology with current practices in the industry we conducted two sets of experiments using the expertise of a product manager of a large retail company in chile in the first case we contrast the performance of the proposed methodology with the revenues obtained during the 1995 autumn winter season in the second case we compare it with the performance of the experienced product manager in a simulation game setting in both cases our methodology provides significantly better results than those obtained by current practices

overselling in a competitive environment boon or bane in this paper we study the practice of overselling in a competitive environment where late arriving consumers value the good higher than early arriving ones but the former s arrival is uncertain we show that overselling is a dominant strategy for the firms however it can lead to a prisoners dilemma situation in which all firms are worse off overselling we further show that only when demand from the late consumers far exceeds the supply and there is a sufficiently high profit margin from reselling does overselling result in a pareto dominant outcome for the firms

the roles of reputation and transparency on the behavior of biased experts we analyze situations in which an expert is biased toward some decision but cares also about his reputation in the market for experts the information the expert reveals decreases as his bias moves toward stronger preference for the status quo we show that it is optimal to publicly disclose both the expert s contribution and his identity surprisingly revealing the intensity of the expert s bias doesn t always improve the information he reveals in equilibrium the presence of a second expert raises the first expert s incentives to report truthfully when reports are public but reduces them when they are secret in particular having an option to call another expert may be detrimental in terms of information production if reports are not public finally sequential consultation of experts reduces the information obtained when reports are public but raises it when they are secret

cargo capacity management with allotments and spot market demand we consider a problem faced by an airline that operates a number of parallel flights to transport cargo between a particular origin to destination pair the airline can sell its cargo capacity either through allotment contracts or on the spot market where customers exhibit choice behavior between different flights the goal is to simultaneously select allotment contracts among available bids and find a booking control policy for the spot market to maximize the sum of the profit from the allotments and the total expected profit from the spot market we formulate the booking control problem on the spot market as a dynamic program and construct approximations to its value functions which can be used to estimate the total expected profit from the spot market we show that our value function approximations provide upper bounds on the optimal total expected profit from the spot market and they allow us to solve the allotment selection problem through a sequence of linear mixed integer programs with a special structure furthermore the value function approximations are useful for constructing a booking control policy for the spot market with desirable monotonic properties computational experiments show that the proposed approach can be scaled to realistic problems and provides well performing allotment allocation and booking control decisions

pricing and operational recourse in coproduction systems coproduction systems in which multiple products are produced simultaneously in a single production run are prevalent in many industries such systems typically produce a random quantity of vertically differentiated products this product hierarchy enables the firm to fill demand for a lower quality product by converting a higher quality product in addition to the challenges presented by random yields and multiple products coproduction systems often serve multiple customer classes that differ in their product valuations furthermore the sizes of these classes are uncertain employing a utility maximizing customer model we investigate the production pricing downconversion and allocation decisions in a two class stochastic demand stochastic yield coproduction system for the single class case we establish that downconversion will not occur if prices are set optimally in contrast we show that downconversion can be optimal in the two class case even if prices are set optimally we consider the benefit of postponing certain operational decisions e g the pricing or allocation rule decisions until after uncertainties are resolved we use the term recourse to denote actions taken after uncertainties have been resolved we find that recourse pricing benefits the firm much more than either downconversion or recourse allocation do implying that recourse demand management is more valuable than recourse supply management special cases of our model include the single class and two class random yield newsvendor models

revenue management for low cost providers low cost providers have emerged as important players in many service industries the most predominant being low cost or the so called discount airlines this paper presents models and results leading toward understanding the revenue management outlook for a discount pricing firm a framework and model is formulated specifically for the airline industry but is generalizable to low cost providers in similar revenue management settings we formulate an optimal pricing control model for a firm that must underprice to capture a segment of exogenous demand two specific model formulations are considered a continuous deterministic version and a discrete stochastic version structural results are derived for the deterministic case providing insight into the general form of optimal underpricing policies the stochastic results support the structural insight from the deterministic solution and illuminate the effect of randomness on the underpricing policies

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

exploiting old customers and attracting new ones the case of bank deposit pricing abstract recent theoretical contributions suggest that deposit interest rates should be higher in geographic areas characterized by greater in migration and lower for depositors at banks with greater shares of existing or so called locked in depositors these hypotheses are tested using a rich data set obtained for the spanish banking industry results confirm that all else equal banks offer higher deposit rates in territories characterized by greater in migration and also that they tend to offer lower rates the larger the number of their locked in depositors these findings confirm the existence of the trade off between exploiting old customers and attracting new ones

switching costs and relationship profits in bank lending abstract this paper studies how the cost of switching banks affects the profits available from relationship based lending when the relationship produces inside information lower switching cost compounds the adverse selection problem discouraging outsider banks to depress loan rates the adverse selection effect eases off along with higher switching cost leading to more aggressive bidding and thereby reduction in insider profits above a certain threshold however the adverse selection effect vanishes completely and the insider profits turn increasing in the switching cost the model predicts that the availability of relationship credit is non monotonously related to the magnitude of the switching cost

job mobility and the market for lawyers this paper studies the life cycle career choices of law school graduates using unique data from the university of michigan law school the model assumes that these graduates act according to the optimal solution of a dynamic optimization problem in which they sequentially choose among five employment sectors the employment sectors are differentiated by pecuniary and nonpecuniary returns promotion and dismissal probabilities and the extent of transferability of human capital the estimation of the model reveals a self selection mechanism based on unobserved heterogeneity in abilities and expected future returns which plays a critical role in reproducing the sector specific nonmonotonic separation hazards observed in the data the underlying self selection mechanism also has implications for policy interventions in the market for lawyers such as loan forgiveness programs

investment moral hazard and occupational licensing i analyse occupational licensing as an input regulation that requires minimum levels of human capital investment by professionals by raising professionals training levels licensing helps alleviate moral hazard problems associated with the provision of high quality services i also consider certification whereby consumers are provided information about professionals training levels i show that licensing and certification tend to benefit consumers who value quality highly at the expense of those who do not licensing may raise total surplus if sellers investments are not observable but is pareto worsening if training levels are observable certification may however lead to excessive investment as a signalling device and thus be pareto inferior to either licensing or to a policy of laissez faire

strategic customer behavior facing possible stockout an experimental study abstract this paper studies strategic customer behavior in a monopolistic seller system given the stock quantity and the selling prices a customer chooses either to buy at the full price to certainly obtain a product or to wait for a discount with the risk of stockout we model the behavior of strategic customers as a customer game it is shown that the customer game may have multiple nash equilibria specifically in the condition of weak incentive compatibility the trembling hand perfect equilibrium is all wait which is inconsistent with the all buy assumption in the literature we conduct laboratory experiments to investigate behavior of strategic customers the results show that customers behaviors exhibit a deviation from nash equilibria using a framework of quantal response equilibrium we develop behavioral models to effectively characterize the behavior of strategic customers

reservation and allocation policies for influenza vaccines abstract this research investigates the impact of alternative allocation mechanisms that can be employed in the context of vaccine inventory rationing available vaccine inventory can be allocated to arrivals from high priority target groups such as healthcare professionals and low priority non target groups demand classes using partitioned allocation pa standard nesting sn and theft nesting tn in any one of the mechanisms a part of the available inventory is reserved for the exclusive use of the high priority demand class they differ however in how the unreserved portion of the inventory is utilized under pa demand from the high low priority class consumes only the reserved unreserved quantity under sn demand from the high priority class first consumes the reserved quantity once and if this quantity is exhausted high priority demand competes with low priority demand for the remaining inventory under tn the sequence of allocation is reversed both demand classes first compete for the unreserved inventory once this portion of inventory is exhausted high priority demand is fulfilled from the reserved inventory and low priority demand is rejected we develop service level probability of fulfilling the entire demand and fill rate fraction of demand fulfilled expressions for all three allocation mechanisms based on these expressions numerical analyses are conducted to illustrate which allocation mechanism a health planner should choose depending on the availability of vaccines and how the health planner should set the reserved quantity for the high priority class we observe that 1 there exist certain conditions under which one of the allocation mechanisms outperforms the others and 2 this effect is determined by the decision maker s choice of the performance measure

airline seat allocation with multiple nested fare classes this paper addresses the problem of determining optimal booking policies for multiple fare classes that share the same seating pool on one leg of an airline flight when seats are booked in a nested fashion and when lower fare classes book before higher ones we show that a fixed limit booking policy that maximizes expected revenue can be characterized by a simple set of conditions on the subdifferential of the expected revenue function these conditions are appropriate for either the discrete or continuous demand cases these conditions are further simplified to a set of conditions that relate the probability distributions of demand for the various fare classes to their respective fares the latter conditions are guaranteed to have a solution when the joint probability distribution of demand is continuous characterization of the problem as a series of monotone optimal stopping problems proves optimality of the fixed limit policy over all admissible policies a comparison is made of the optimal solutions

a multiproduct dynamic pricing problem and its applications to network yield management a firm has inventories of a set of components that are used to produce a set of products there is a finite horizon over which the firm can sell its products demand for each product is a stochastic point process with an intensity that is a function of the vector of prices for the products and the time at which these prices are offered the problem is to price the finished products so as to maximize total expected revenue over the finite sales horizon an upper bound on the optimal expected revenue is established by analyzing a deterministic version of the problem the solution to the deterministic problem suggests two heuristics for the stochastic problem that are shown to be asymptotically optimal as the expected sales volume tends to infinity several applications of the model to network yield management are given numerical examples illustrate both the range of problems that can be modeled under this framework and the effectiveness of the proposed heuristics the results provide several fundamental insights into the performance of yield management systems

the benefits of lending relationships evidence from small business data this paper empirically examines how ties between a firm and its creditors affect the availability and cost of funds to the firm we analyze data collected in a survey of small firms by the small business administration the primary benefit of building close ties with an institutional creditor is that the availability of financing increases we find smaller effects on the price of credit attempts to widen the circle of relationships by borrowing from multiple lenders increases the price and reduces the availability of credit in sum relationships are valuable and appear to operate more through quantities rather than prices

price guarantees in dynamic pricing and revenue management we present a new model for revenue management of product sales that incorporates both dynamic pricing and a price guarantee the guarantee provides customers with compensation if prior to a fixed future date the price of the product drops below a level specified at the time of purchase we consider the problem of simultaneously determining optimal dynamic price and guarantee policies for items from a fixed stock when demand depends both on the price and on the parameters of the price guarantee the model can be used for pricing any items with limited availability over a fixed time horizon we formulate this model as a discrete time optimal control problem prove the existence of its optimal solution explore some of the structural properties of the solution present lower bounding heuristics for solving the problem and report numerical results

an integrated product planning model for pricing and bundle selection using markov decision processes and data envelope analysis abstract when bundling products during the product planning stage there are a number of possible combinations that can be offered to customers consider a firm that offers n distinctive products then there are 2 n n 1 possible bundling combinations now if we wish to make pricing and bundle selection decisions keeping in my mind limited inventory and a finite time horizon then the size of the state space could be very large and finding an optimal solution could be impossible to tackle this issue we formulate an integrated model that utilizes a markov decision process and data envelope analysis bundle selections are made using data envelope analysis in each decision epoch once the efficient bundles are selected they are priced by solving a markov decision process using dynamic programming numerical examples are solved to exhibit the model s potential in solving real world problems

improved bid prices for choice based network revenue management one of the latest developments in network revenue management rm is the incorporation of customer purchase behavior via discrete choice models many authors presented control policies for the booking process that are expressed in terms of which combination of products to offer at a given point in time and given resource inventories however in many implemented rm systems most notably in the hotel industry bid price control is being used and this entails the problem that the recommended combination of products as identified by these policies might not be representable through bid price control if demand were independent from available product alternatives an optimal choice of bid prices is to use the marginal value of capacity for each resource in the network but under dependent demand this is not necessarily the case in fact it seems that these bid prices are typically not restrictive enough and result in buy down effects we propose 1 a simple and fast heuristic that iteratively improves on an initial guess for the bid price vector this first guess could be for example dynamic estimates of the marginal value of capacity moreover 2 we demonstrate that using these dynamic marginal capacity values directly as bid prices can lead to significant revenue loss as compared to using our heuristic to improve them finally 3 we investigate numerically how much revenue performance is lost due to the confinement to product combinations that can be represented by a bid price the heuristic is not restricted to a particular choice model and can be combined with any method that provides us with estimates of the marginal values of capacity in our numerical experiments we test the heuristic on some popular networks examples taken from peer literature we use a multinomial logit choice model which allows customers from different segments to have products in common that they consider to purchase in most problem instances our heuristic policy results in significant revenue gains over some currently available alternatives at low computational cost

structural properties of markov modulated revenue management problems abstract the admission decision is one of the fundamental categories of demand management decisions in the dynamic model of the single resource capacity control problem the distribution of demand does not explicitly depend on external conditions however in reality demand may depend on the current external environment which represents the prevailing economic financial social or other factors that affect customer behavior we formulate a markov decision process mdp to maximize expected revenues over a finite horizon that explicitly models the current environment we derive some structural results of the optimal admission policy including the existence of an environment dependent thresholds and a comparison of threshold levels in different environments we also present some computational results which illustrate these structural properties finally we extend some of the results to a related dynamic pricing formulation

the wrong kind of transparency in a model of career concerns for experts when is a principal hurt from observing more information about her agent this paper introduces a distinction between information on the consequence of the agent s action and information directly on the agent s action when the latter kind of information is available the agent faces an incentive to disregard useful private signals and act according to how an able agent is expected to act a priori this conformist behavior hurts the principal in two ways the decision made by the agent is less likely to be the right one discipline and ex post it is more difficult to evaluate the agent s ability sorting the paper identifies a necessary and sufficient condition on the agent signal structure under which the principal bene ts from committing not to observe the agent s action the paper also shows the existence of strategic complementarities between information on action and information on consequence the results on the distinction between action and consequence are then used to interpret existing disclosure policies in delegated portfolio management in particular they are consistent with hitherto puzzling evidence that mutual funds systematically overperform pension funds

relying on the information of interested parties we investigate the conventional wisdom that competition among interested parties attempting to influence a decisionmaker by providing verifiable information elicits all relevant information we find that if the decisionmaker is strategically sophisticated and well informed about the relevant variables and about the preferences of the interested party or parties competition may be unnecessary to achieve this result if the decisionmaker is unsophisticated or not well informed competition is not generally sufficient if the interested parties interests are sufficiently opposed however or if the decisionmaker is seeking to advance the parties welfare then competition can reduce or even eliminate the decisionmaker s need for prior knowledge about the relevant variables and for strategic sophistication in other settings only the combination of competition among information providers and a sophisticated skepticism is sufficient to allow effective decisionmaking

the d level nested logit model assortment and price optimization problems we consider assortment and price optimization problems under the d level nested logit model in the assortment optimization problem the goal is to find the revenue maximizing assortment of products to offer when the prices of the products are fixed using a novel formulation of the d level nested logit model as a tree of depth d we provide an efficient algorithm to find the optimal assortment for a d level nested logit model with n products the algorithm runs in o d n log n time in the price optimization problem the goal is to find the revenue maximizing prices for the products when the assortment of offered products is fixed although the expected revenue is not concave in the product prices we develop an iterative algorithm that generates a sequence of prices converging to a stationary point numerical experiments show that our method converges faster than gradient based methods by many orders of magnitude in addition to providing solutions for the assortment and price optimization problems

revenue management under customer choice behaviour with cancellations and overbooking abstract in many application areas such as airlines and hotels a large number of bookings are typically cancelled explicitly taking into account cancellations creates an opportunity for increasing revenue motivated by this we propose a revenue management model based on talluri and van ryzin 2004 that takes cancellations into account in addition to customer choice behaviour moreover we consider overbooking limits as these are influenced by cancellations we model the problem as a markov decision process and propose three dynamic programming formulations to solve the problem each appropriate in a different setting we show that in certain settings the problem can be solved exactly using a tractable solution method for other settings we propose tractable heuristics since the problem faces the curse of dimensionality numerical results show that the heuristics perform almost as good as the exact solution however the model without cancellations can lead to a revenue loss of up to 20 percent lastly we provide a parameter estimation method based on newman et al 2014 this estimation method is fast and provides good parameter estimates the combination of the model the tractable and well performing solution methods and the parameter estimation method ensures that the model can efficiently be applied in practice