economies of scale in energy use in adult only households the residential sector is responsible for 18 of australia s primary energy use thus improved knowledge about household energy use is vital to future energy management this study examines economies of scale in energy use and expenditure among adult only households and across three adult only household types significant economies of scale are found in all cases small households suffer a double penalty of greater per capita energy use and higher charge per unit of energy with older households the most affected the trend towards smaller average household size means that economies of scale are continually being lost offsetting gains in energy efficiency achieved through other means

utility covariances and context effects in conjoint mnp models experimental conjoint choice analysis is among the most frequently used methods for measuring and analyzing consumer preferences the data from such experiments have been typically analyzed with the multinomial logit mnl model however there are several problems associated with the standard mnl model because it is based on the assumption that the error terms of the underlying random utilities are independent across alternatives choice sets and subjects the multinomial probit model mnp is well known to alleviate this assumption of independence of the error terms accounting for covariances in utilities in modeling choice experiments with the mnp is important because variation of the coefficients in the choice model may occur due to context effects previous research has shown that subjects utilities for alternatives depend on the choice context that is the particular set of alternatives evaluated simonson and tversky s tradeoff contrast principle describes the effect of the choice context on attribute importance and patterns of choice they distinguish local contrast effects which are caused by the alternatives in the offered set only and background contrast effects which are due to the influence of alternatives previously considered in choice experiments these effects are hypothesized to cause correlations in the utilities of alternatives within and across choice sets respectively the purpose of this study is to develop an mnp model for conjoint choice experiments this model is important for a more detailed study of choice patterns in those experiments in developing the mnp model for conjoint choice experiments several hurdles need to be taken related to the identification of the model and to the prediction of holdout profiles to overcome those problems we propose a random coefficients rc model that assumes a multivariate normal distribution of the regression coefficients with a rank one factor structure on the covariance matrix of these regression coefficients the parameters in this covariance matrix can be used to identify which attributes and levels of attributes are potentional sources of dependencies between the alternatives and choice sets in a conjoint choice experiment we present several versions of this model moreover for each of these models we allow utilities to be either correlated or independent across choice sets the independent probit ip model is used as a benchmark given the dimensionality of the integrations involved in computing the choice probabilities the models are estimated with simulated likelihood where simulations are used to approximate the integrals involved in the choice probabilities we apply and compare the models in two conjoint choice experiments in both applications the random coefficients mnp model that allows choices in different choice sets to be correlated rc displays superior fit and predictive validity compared with all other models we hypothesize that the difference in fit occurs because the rc model accommodates correlations among choice sets that are caused by background contrast effects whereas the model that treats choice sets as independent irc accounts for local contrast effects only the irc model shows superior model fit compared with the ip model but its predictions are worse than those of the ip model we find differences in the importance of local and background contrast effects for choice sets containing different numbers of alternatives the background contrast effect may be stronger for smaller choice sets whereas the local contrast effect may be stronger for bigger choice sets we illustrate the differences in simulated market shares that are obtained from the rc irc and ip models in three hypothetical situations product modification product line extension and the introduction of a me too brand in all of those situations substantially different market shares are predicted by the three models which illustrates the extent to which erroneous predictions may be obtained from the misspecified irc and ip models

price promotions in choice models promotions are used in marketing to increase sales and drive profits by temporarily decreasing the price per unit of a good some price promotions apply to all quantities 20 off some have limits on the number of units that can be purchased at a reduced price and others only offer the discount if the volume purchased is sufficiently high we develop a model of price promotions in the context of a direct utility model where its effects are incorporated through the budget constraint price promotions complicate the estimation and analysis of direct utility models because they induce kinks and points of discontinuity in the budget set we propose a bayesian approach to addressing these irregularities and demonstrate the ability of the direct utility model to be used in counterfactual analyses of price promotions we investigate the stability of utility function estimates for consumers under alternative price promotions and find that the majority of the effect of a price promotion is through the budget s

a model of product line design and introduction sequence with reservation utility abstract cannibalization is a major concern for a firm when designing a product line in addition external options from outside the firm s product line may also play a significant role in this paper we investigate the impact of external options represented by reservation utility on product line design and introduction sequence we find that a heterogeneous reservation utility defines the relative attractiveness of segments and corresponding product line b reservation utility makes it more favorable to introduce products sequentially rather than simultaneously c aggregating segments is an effective way to mitigate cannibalization when it becomes too difficult to manage with different values of reservation utility across multiple segments and d introducing products in a non monotone order of quality can improve profit from simultaneous introduction when the value of reservation utility of a middle segment is particularly high

optimal admission and scholarship decisions choosing customized marketing offers to attract a desirable mix of customers each year in the postsecondary education industry schools offer admission to nearly 3 million new students and scholarships totaling nearly 100 billion this is a large understudied targeted marketing and price discrimination problem this problem falls into a broader class of configuration utility problems cups which typically require an approach tailored to exploit the particular setting this paper provides such an approach for the admission and scholarship decisions problem the approach accounts for the key distinguishing feature of this industry schools value the average features of the matriculating students such as percent female percent from different regions of the world average test scores and average grade point average thus as in any cup the value of one object i e student cannot be separated from the composition of all of the objects other students in the enrolling class this goal of achieving a class with a desirable set of average characteristics greatly complicates the optimization problem and does not allow the application of standard approaches we develop a new approach that solves this more complex optimization problem using an empirical system to estimate each student s choice and the focal school s utility function we test the approach in a field study of an mba scholarship process and implement adjusted scholarship decisions using a holdout sample we provide evidence that the methodology can lead to improvements over current management decisions finally by comparing our solution to what management would do on its own we provide insight into how to improve management decisions in this setting

the augmented latent class model incorporating additional heterogeneity in the latent class model for panel data abstract marketing researchers have actively sought to account for the heterogeneity in households preferences and responses to marketing mix elements e g price promotion when analyzing scanner panel data this is because not doing so biases response coefficient estimates that can potentially alter the conclusions drawn from such analyses in this article the authors present an extension to the latent class model lcm that accounts for additional heterogeneity by allowing households preferences to be a continuous mixture of segment level preferences the authors show how their model generalizes the lcm by the mere addition of s 1 parameters where s refers to the number of segments because a limitation of the traditional lcm is that it does not adequately account for heterogeneity in responses across households the authors model mitigates this criticism leveled at the lcm they then compare their model with the traditional lcm and the equivalent continuous mixture random effects models in

measuring investment performance with a stochastic parameter regression model abstract this paper develops a generalization of the hildreth and houck 1968 random coefficient model for use in evaluating the macroforecasting ability of portfolio managers most studies have assumed that astute managers ignore the strength of the market trend and create a binary portfolio beta with one value during up markets and a lower value during down markets in contrast this paper examines a model in which the superior manager adjusts beta period by period according to changing market conditions the findings indicate that portfolio managers are not superior macroforecasters

a probabilistic choice model for market segmentation and elasticity structure marketing scholars commonly characterize market structure by studying the patterns of substitution implied by brand switching though the approach is useful it typically ignores the destabilizing

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

the individual travel cost method with consumer specific values of travel time savings the treatment of the opportunity cost of travel time in travel cost models has been an area of research interest for many decades our analysis develops a methodology to combine the travel distance and travel time data with respondent specific estimates of the value of travel time savings vtts the individual vtts are elicited with the use of discrete choice stated preference methods the travel time valuation procedure is integrated into the travel cost valuation exercise to create a two equation structural model of site valuation since the travel time equation of the structural model incorporates individual preference heterogeneity the full structure model provides a travel cost site demand model based upon individualized values of time the methodology is illustrated in a study of recreational birdwatching more specifically visits to a stork village in poland we show that the usual practice of basing respondents vtts on 1 3 of their wage rate is largely unfounded and propose alternatives including a separate component of the travel cost survey aimed at valuation of respondents vtts or as a second best asking if they wish if their journey was shorter and for those who do use full hourly wage as an indicator of their vtts

modelling household energy expenditures using micro data this paper is concerned with the empirical modeling of domestic demand for energy in the united kingdom at the level of the individual household a two stage budgeting model of household demand for energy conditional on durable ownership is developed at the first stage income is allocated between energy and nonenergy consumption while at the second stage energy expenditure is disaggregated the second stage allocation is assumed to be between gas electricity and a composite good other fuels estimation takes place using a sample of some 50 000 households drawn from the annual u k family expenditure survey for the years 1972 83 a source that has not been fully exploited in the analysis of energy demand to date copyright 1989 by royal economic society

testing for nonstationarity of market risk an exact test and power considerations this paper reexamines the issue of common stock market risk stationarity by applying a newly available exact test for random walk regression coefficients for each eight year subperiod tested in the 1951 1974 interval betas for individual new york stock exchange listed stocks appeared to be nonstationary the statistical powers of the exact test and of locally most powerful tests are compared to the power of the test employed previ ously by sunder these power considerations are cited to explain the differences between test results obtained here and those reported by sunder

experimenting with purchase history based price discrimination many purchases of differentiated goods are repeated giving sellers the opportunity to engage in price discrimination based upon the shopper s previous behavior by either offering loyalty discounts to repeat buyers or introductory rates to new customers recent theoretical work suggests that loyalty discounts can be profitable to sellers when customer preferences are not stationary and sellers can pre commit to prices for repeat buyers but otherwise returning customers can be expected to pay the same or more than new buyers this paper reports behavior in controlled laboratory experiments designed to empirically test the impact of these factors on pricing strategies the results generally support the comparative static predictions of the theoretical model when customer preferences are fixed over time sellers attempt to lure customers from their rival price pre commitment for repeat shoppers when buyer preferences vary over time resulted in modest loyalty pricing but the discounts are not as prevalent as predicted as sellers rarely price below cost behaviorally price pre commitment to loyal customers is found to reduce prices overall

customized advertising via a common media distributor we show that when a single media content distributor such as a television cable company or an internet provider delivers advertising messages on behalf of multiple competing brands it can sometimes utilize customized advertising to implement monopoly pricing even though such monopolistic pricing can be implemented with varying degrees of customization of commercials product revenues and consumer surplus are highest when the distributor chooses the highest level of customization feasible consumers would obviously prefer aggressive price competition in product markets however given that collusion on prices is facilitated anyway when the distributor acts as a common agent the welfare of consumers is enhanced when commercials are better aligned with their preferences

a new test of the relationship between regulatory change in financial markets and the stability of beta risk of depository institutions the us economy experienced major regulatory changes in the banking and finance industry with the passage of five major acts over the period 1980 to 1991 this has generated an extensive literature investigating the effects of these changes on the us banking industry in particular this body of research has examined the share market reaction to regulatory changes as well as their impact on the risk return market value and profitability of banking industry stocks generally it has been found that the regulatory changes have had a substantial impact although the effect has not been uniform across all depository institutions this paper extends this literature by analysing the stability of a sample of eighteen us banking industry stock betas across five periods a pre regulatory change period a monetary experiment period a deregulation period a reregulation period and a post regulatory change period based on an analysis of weekly returns we find that the level of bank risk has increased further we also find a tendency towards greater beta instability in both the monetary experiment and deregulation samples the degree of beta instability is lowest in the pre regulatory change and post regulatory change samples overall the monetary experiment and regulatory change coincided with an increased tendency towards beta instability we also compare our results to a randomly selected control sample of non banks and find some more general effects of regulatory change on individual stock betas

dynamic targeted pricing with strategic consumers abstract we investigate in this paper whether dynamic targeted pricing based on consumer purchase history could benefit a practicing firm even when consumers are strategic in that they actively seek to avail themselves of a low price in the future such strategic behavior on the part of consumers has been shown in the literature to render such dynamic targeted pricing unprofitable even for a monopoly firm we show that dynamic targeted pricing can benefit competing firms when they actively pursue customer recognition based on consumer purchase history this is because in order to pursue customer recognition competing firms need to price high to screen out price sensitive consumers and hence price competition is moderated as a result all competing firms can become better off with targeted pricing than without even when consumers behave strategically interestingly because of this competition moderation effect the paradoxical outcome occurs where dynamic targeted pricing may not benefit a monopolist but it may benefit competing firms we also show that dynamic targeted pricing can expand the market such that social welfare unambiguously improves

intertemporal price discrimination with two products we study the two product monopoly profit maximization problem for a seller who can commit to a dynamic pricing strategy we show that if consumers valuations are not strongly ordered then optimality for the seller can require intertemporal price discrimination the seller offers a choice between supplying a complete bundle now or delaying the supply of a component of that bundle until a later date for general valuations we establish a sufficient condition for such dynamic pricing to be more profitable than mixed bundling so we show that the established no discrimination across time result does not extend to two product sellers under standard taste distributions

the impact of heterogeneity in purchase timing and price responsiveness on estimates of sticker shock effects the notion that individuals have an internal reference price against which they compare observed prices is well supported by several psychological theories empirically several papers in the marketing literature employing scanner panel data have modeled the impact of reference prices on brand choice via the sticker shock formulation in which consumers evaluate choice alternatives using differences between shelf prices and reference prices most of the studies reported thus far have not accounted for heterogeneity in price response among consumers and have typically imputed reference prices from the shelf prices of brands that a consumer is supposed to have observed on previous purchases in the category since category marketing activity can differentially affect the purchase timing of households we argue that this measure of reference price may follow certain systematic patterns across consumers and when combined with unaccounted for price response heterogeneity may result in a spurious sticker shock effect specifically we show that estimates of sticker shock are biased upward if households that are price sensitive in the brand choice decision are also more responsive to category promotion activity in their purchase timing decision we discuss some general conditions under which the bias occurs and conduct a simulation experiment to confirm our specific hypotheses our simulation results show that changes in purchase timing are a critical determinant of the bias in the sticker shock effect we also show that unaccounted for price response heterogeneity can in itself result in a biased sticker shock parameter however this requires very large differences in price sensitivities across consumers far greater than what is normally observed we develop a hierarchical bayes version of the nested logit model which models heterogeneity via individual level parameters in a continuous random effects framework we estimate the model on scanner panel data from the yogurt and ketchup categories we find in both categories that the 95 probability interval of the posterior distribution of the mean sticker shock coefficient contains the value zero therefore at least for the data used in this study there is no evidence for the sticker shock effect at the aggregate level in contrast the corresponding coefficient from a standard model which ignores this heterogeneity is highly significant and supports the existence of a possibly spurious sticker shock effect consistent with our explanation of the underlying cause of the bias households that are more price sensitive in the choice decision are also found to be more responsive to category promotion activity in their decision to purchase in the category the results highlight the measurement problems associated with imputing reference prices from past prices since the frequency duration and price level of a retailer s promotional program depend on its size and prevalence accurate estimates of the sticker shock effect are essential for formulating optimal promotion strategies an adequate accounting of consumer heterogeneity is critical to this effort

timing decisions and the behavior of mutual fund systematic risk the investment performance of professionally managed portfolios in general and mutual funds in particular has been the subject of considerable attention in finance fama 9 has suggested that overall portfolio performance be broken down in such a manner that the individual sources of performance can be identified two basic sources are 1 the ability of the portfolio manager to forecast price movements of individual common stocks relative to stocks in general selectivity or microforecasting and 2 the ability to forecast the direction of the stock market relative to fixed income securities timing or macroforecasting

embedded premium promotion why it works and how to make it more effective in this paper we define an embedded premium ep as an enhancement that involves a social cause added on to a product or service we characterize ep as a sales promotion strategy and juxtapose it with traditional approaches such as discounts and rebates across three experiments using a nationwide internet panel and employing stated measures and model based inference we find that at low denominations ep is more effective than an equivalent price discount we describe how an ep s social association may influence consumer choice quite differently than price promotions and contrary to the asymmetric price promotion effect documented in the promotions literature we find that ep benefits an unknown brand more than a known brand our hierarchical bayes approach uncovers heterogeneity in ep effectiveness that can be explained by affinity toward the focal charity personal motivations and demographic markers an identifiable segment of individuals prefer the other over self suggesting possible ep optimization and segmentation strategies two such strategies customization and coverage are empirically tested and the former is shown to be very effective our findings have broad implications for brand managers with regard to resource allocation and ep program return on investment roi as well as important social welfare implications

research note consumer addressability and customized pricing the increasing availability of customer information is giving many firms the ability to reach and customize price and other marketing efforts to the tastes of the individual consumer this ability is labeled as consumer addressability consumer addressability through sophisticated databases is particularly important for direct marketing firms catalog retailers such as l l bean and land s end credit card issuing banks and firms in the long distance telephone market we examine the strategic implications of consumer addressability on competition between database direct marketing firms we address questions such as in a competitive environment how should firms invest in addressability will future improvements in the degree of addressability increase or mitigate the intensity of competition between the firms will greater addressability always be beneficial for firms we model competition between two firms in a market where consumers differ on a horizontal attribute of product differentiation the market comprises consumers located on a linear attribute space and firms located at the ends of the line we represent the degree of addressability or the reach of a firm s database as the proportion of consumers at each point in the market who are in the firm s database consequently the firm can offer these consumers customized prices consumer addressability creates two effects that govern the competition between firms a surplus extraction effect because a firm might address a consumer who is not reached by its competitor and a competitive effect that is created by the set of consumers who can be addressed by both firms the key results of the paper pertain to when the addressability decision is endogenous when the extent of market differentiation or consumer heterogeneity in preferences for a product brand attribute as well as the incremental cost of addressability are sufficiently large firms make symmetric investments in equilibrium given high costs firms choose sufficiently low levels of addressability low addressability and high levels of market differentiation both help reduce price competition which facilitates symmetric choice of addressability by the firms in equilibrium however when market differentiation and the cost of incremental addressability become small firms face the prospect of destructive competition as a result they strategically differentiate in their choice of addressability to mitigate this competition interestingly even in the extreme case when incremental addressability is costless not every firm chooses full addressability in equilibrium this has useful implications for direct marketing given that the advances in information technology should improve the ability of firms to address their consumers it might indeed not be desirable for all direct marketing firms to indefinitely pursue greater addressability as costs of doing so decline the analysis also shows an interesting effect of market differentiation in addressable markets equilibrium profits can decrease with an increase in market differentiation when the marginal cost of addressability is sufficiently high finally we discuss the competitive outcome that would result when firms compete with addressable as well as uniform posted prices

modeling consumer demand for variety consumers are often observed to purchase more than one variety of a product on a given shopping trip the simultaneous demand for varieties is observed not only for packaged goods such as yogurt or soft drinks but in many other product categories such as movies music compact disks and apparel multinomial mn choice models cannot be applied to data exhibiting the simultaneous choice of more than one variety the random utility interpretation of either the mn logit or probit model uses a linear utility specification that cannot accommodate interior solutions with more than one variety alternative chosen to analyze data with multiple varieties chosen requires a nonstandard utility specification standard demand models in the economics literature exhibit only interior solutions we propose a demand model based on a translated additive utility structure the model nests the linear utility structure while allowing for the possibility of a mixture of corner and interior solutions where more than one but not all varieties are selected we use a random utility specification in which the unobservable portion of marginal utility follows a log normal distribution the distribution of quantity demanded the basis of the likelihood function is derived from these log normal random utility errors the likelihood function for this class of models with mixtures of corner and interior solutions is a mixed distribution with both a continuous density portion and probability mass points for the corners the probability mass points must be calculated by integrals of the log normal errors over rectangular regions we evaluate these high dimensional integrals using the ghk approximation we employ a bayesian hierarchical model allowing household specific utility parameters our utility specification related to the approach of wales and woodland 1983 who employ a translated quadratic utility function wales and woodland were only able to study at the most three varieties because there was no practical way to evaluate the utility function at that time in addition the quadratic utility specification is not a globally valid utility function making welfare computations and policy experiments questionable hendel 1999 and dube 1999 present an alternative approach in the utility function which is constructed by summing up over unobservable consumption occasions while only one variety is consumed on each occasion the marginal utilities of varieties change over the consumption occasions giving rise to a simultaneous purchase of multiple varieties our bayesian inference approach allows us to obtain individual household estimates of utility parameters household utility estimates are used to compute the value of each variety we compute a compensating value for the removal of each flavor that is we compute the monetary equivalent of the household s loss in utility from removal of a flavor these calculations show that households highly value popular flavors and would incur substantial utility losses from removal of these flavors from the yogurt assortment next we consider the implications of our model for retailer assortment and pricing policies given limited shelf space only a subset of the possible varieties can be displayed for purchase at any one time if consumers value variety then a retailer with lower variety must compensate the consumers in some way such as a lower price level we see this trade off between price and variety across different retailing formats discount or warehouse format retailers often have both lower variety and lower prices to measure this trade off we explore the utility loss from reduction in variety and find the reductions in price that will compensate for this utility loss these price reduction calculations must be based on a valid utility structure heterogeneity in tastes is critical in these utility computations and policy experiments we find that a relatively small fraction of households with extreme preferences dominate the compensating value computations that is some households are observed to purchase mostly or exclusively one variety these households must be heavily compensated for the removal of this variety from the assortment in some retailing contexts customization of the assortment is possible at the customer level we show that such customization virtually eliminates any utility loss from reduction in variety

on the optimal product line selection problem with price discrimination product line design decisions are determinant for a firm s market success and simultaneously very costly to implement and change to evaluate the profitability of a design a number of mathematical programming approaches have been proposed in the last three decades typically nonlinear integer optimization problems that can only be tackled heuristically for real world instances recently chen and hausman 2000 efficiently exploited the fractional programming properties of a stylized model for product line and price selection with the objective to maximize contribution given homogeneous customer behavior by an aggregate multinomial logit choice model we extend the approach of chen and hausman chen k d w h hausman 2000 technical note mathematical properties of the optimal product line selection problem using choice based conjoint analysis management sci 46 2 327 332 to determine an optimal product line under a personalized or group pricing strategy in markets with multiple heterogeneous consumers such that total profit including fixed costs is maximized personalized group pricing is a growing discrimination strategy that more and more businesses are realizing is not only very profitable but also often implementable in the era of e business our problem formulation allows to incorporate commonly applied attraction choice models including the multinomial logit the bradley terry luce and approximately the first choice model though the problem is generally nonlinear we show that the fractional substructure resulting from attraction choice models can still be exploited to globally solve real world instances in reasonable time

product line selection and pricing under a share of surplus choice model abstract product line selection and pricing decisions are critical to the profitability of many firms particularly in today s competitive business environment in which providers of goods and services are offering a broad array of products to satisfy customer needs we address the problem of selecting a set of products to offer and their prices when customers select among the offered products according to a share of surplus choice model a customer s surplus is defined as the difference between his utility willingness to pay and the price of the product under the share of surplus model the fraction of a customer segment that selects a product is defined as the ratio of the segment s surplus from this particular product to the segment s total surplus across all offered products with positive surplus for that segment we develop a heuristic procedure for this non concave mixed integer optimization problem the procedure utilizes simulated annealing to handle the binary product selection variables and a steepest ascent style procedure that relies on certain structural properties of the objective function to handle the non concave continuous portion of the problem involving the prices we also develop a variant of our procedure to handle uncertainty in customer utilities in computational studies our basic procedures perform extremely well producing solutions whose objective values are within about 5 of those obtained via enumerative methods our procedure to handle uncertain utilities also performs well producing solutions with expected profit values that are roughly 10 higher than the corresponding expected profits from solutions obtained under the assumption of deterministic utilities

domestic fuel expenditure an analysis of three national surveys abstract this paper analyses the fuel expenditure data in three surveys looking particularly at the importance of household income multivariate data analysis techniques show that household size the size and type of accomodation and the presence of central heating are more direct influences on fuel expenditure than income changes in income have little independent effect on fuel expenditure once the size of the house size of household and heating system are determined

seasonal variation in residential electricity demand evidence from survey data in this paper we estimate twelve monthly electricity demand equations for households using a detailed microdata set the microdata are based largely on a detailed 1975 survey of us households and incude variables enabling us to measure block price schedules family income socio demographic variables appliance stocks housing characteristics and heating and cooling degree days of single family units we find that price elasticities are higher in absolute value during peak periods of demand income elasticity estimates show no discernible seasonal pattern our disaggregated data also allow us to estimate the seasonal usage patterns of several electricity using appliances the estimates follow expected patterns

discrete choice models with multiple unobserved choice characteristics since the pioneering work by daniel mcfadden utility maximization based multinomial response models have become important tools of empirical researchers various generalizations of these models have been developed to allow for unobserved heterogeneity in taste parameters and choice characteristics here we investigate how rich a specification of the unobserved components is needed to rationalize arbitrary choice patterns in settings with many individual decision makers multiple markets and large choice sets we find that if one restricts the utility function to be monotone in the unobserved choice characteristics then up to two unobserved choice characteristics may be needed to rationalize the choices

the welfare effects of coordinated assignment evidence from the new york city high school match abstract coordinated single offer school assignment systems are a popular education reform we show that uncoordinated offers in nyc s school assignment mechanism generated mismatches one third of

behavior based pricing production efficiency and quality differentiation in a two period vertical duopoly we examine how behavior based price discrimination bpd affects the firms endogenous quality differentiation and profits the firms relative production efficiency defined as the ratio between their unit cost difference and quality difference plays a crucial role with exogenous product qualities bpd always decreases the profits of the more efficient firm but increases those of the sufficiently less efficient firm anticipating its period 2 disadvantage in price discrimination the less efficient firm competes more vigorously and also gains more in period 1 than its competitor for the sufficiently less efficient firm its period 1 gain dominates its period 2 loss and its total profits increase with endogenous quality choices bpd does not alter the low end quality at the lower bound of the quality space but increases the high end quality enlarging quality differentiation this is because under bpd each firm s profit gain decreases or its profit loss increas

measuring market power in the ready to eat cereal industry the ready to eat cereal industry is characterized by high concentration high price cost margins large advertising to sales ratios and numerous introductions of new products previous researchers have concluded that the ready to eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense nonprice competition this paper empirically examines this conclusion in particular i estimate price cost margins but more importantly i am able empirically to separate these margins into three sources i that which is due to product differentiation ii that which is due to multi product firm pricing and iii that due to potential price collusion the results suggest that given the demand for different brands of cereal the first two effects explain most of the observed price cost margins i conclude that prices in the industry are consistent with noncollusive pricing behavior despite the high price cost margins leading firms are able to maintain a portfolio of differentiated products and influence the perceived product quality it is these two factors that lead to high price cost margins

how to compute optimal catalog mailing decisions we develop estimate and test a response model of order timing and order volume decisions of catalog customers and derive a bayes rule for optimal mailing strategies the model integrates the when and how much components of the response incorporates the mailing decision of the firm and uses a bayesian framework to determine the optimal mailing rule for each catalog customer the bayes rule we propose for optimal mailing strategy allows for a broad set of objectives to be realized across the time horizon such as profit maximization customer retention and utility maximization with or without risk aversion we find that optimizing the objective function over multiple periods as opposed to a single period leads to higher expected profits and expected utility our results indicate that the cataloguer is well advised to send fewer catalogs than its current practice in order to maximize expected profits and utility

model selection for the mixed logit with bayesian estimation in this paper the mixed logit ml using bayesian methods was employed to examine willingness to pay wtp to consume bread produced with reduced levels of pesticides so as to ameliorate environmental quality from data generated by a choice experiment model comparison used the marginal likelihood which is preferable for bayesian model comparison and testing models containing constant and random parameters for a number of distributions were considered along with models in preference space and wtp space as well as those allowing for misreporting we found strong support for the ml estimated in wtp space little support for fixing the price coefficient a common practice advocated and adopted in the environmental economics literature and weak evidence for misreporting

understanding responses to contradictory information about products although prior literature has examined reactions to drastic negative news we examine the situation in which decision makers receive contradictory information about products and they have to decide whether to persist with or abandon product usage we investigate physician reactions to conflicting information concerning the cardiovascular risk of avandia a diabetes drug we examine how beliefs about both drug effectiveness and drug safety are updated and speculate that experience expertise and self efficacy impact how such information is integrated with current quality beliefs unlike previous bayesian learning models we consider that some signals such as positive and negative news releases and the firm s marketing effort may be biased in that they provide an opinionated point of view the results show interesting differences in how physician types specialists hospital based primary care physicians heavy and light prescribers update their beliefs and the information sources they use to do so we find evidence that safety issues about avandia resulted in spillover concern to close competitor actos the results have implication for determining who should be targeted and what vehicles should be used if a firm is faced with a situation where consumers are in a quandary because of receiving conflicting messages

imperfect price discrimination market structure and efficiency we introduce a flexible third degree price discrimination framework by modeling the information firms possess about consumers locations preferences on the salop circle as a partition higher information quality is translated into a partition refinement in the limit we obtain the perfect price discrimination paradigm we show that the free entry equilibrium number of firms exhibits a u shape as a function of the quality of information this implies that imperfect price discrimination generates the most efficient free entry outcome jel classification d43 l11 l43 discrimination imparfaite par les prix structure de marche et efficacite les auteurs produisent un cadre d analyse flexible de la discrimination par les prix au troisieme degre en modelisant l information que les firmes possedent a propos de la localisation preferences comme base de decoupage dans un cercle de salop une plus grande qualite d information se traduit par un decoupage plus fin a la limite on obtient le paradigme parfait de discrimination par les prix on montre que le nombre de firmes en equilibre quand l entree est libre est une fonction en forme de u dans son rapport avec la qualite de l information cela implique que la discrimination imparfaite par les prix engendre le resultat le plus efficace quand l entree est libre

the shopping basket a model for multicategory purchase incidence decisions consumers make multicategory decisions in a variety of contexts such as choice of multiple categories during a shopping trip or mail order purchasing the choice of one category may affect the selection of another category due to the complementary nature e g cake mix and cake frosting of the two categories alternatively two categories may co occur in a shopping basket not because they are complementary but because of similar purchase cycles e g beer and diapers or because of a host of other unobserved factors while complementarity gives managers some control over consumers buying behavior e g a change in the price of cake mix could change the purchase probability of cake frosting co occurrence or co incidence is less controllable other factors that may affect multi category choice may be unobserved household preferences or observed household demographics we also argue that not accounting for these three factors simultaneously could lead to erroneous inferences we then develop a conceptual framework that incorporates complementarity co incidence and heterogeneity both observed and unobserved as the factors that could lead to multi category choice we then translate this framework into a model of multi category choice our model is based on random utility theory and allows for simultaneous interdependent choice of many items this model the multivariate probit model is implemented in a hierarchical bayes framework the hierarchy consists of three levels the first level captures the choice of items for the shopping basket during a shopping trip the second level captures differences across households and the third level specifies the priors for the unknown parameters we generalize some recent advances in markov chain monte carlo methods in order to estimate the model specifically we use a substitution sampler which incorporates techniques such as the metropolis hit and run algorithm and the gibbs sampler the model is estimated on four categories cake mix cake frosting fabric detergent and fabric softener using multicategory panel data the results disentangle the complementarity and co incidence effects the complementarity results show that pricing and promotional changes in one category affect purchase incidence in related product categories in general the cross price and cross promotion effects are smaller than the own price and own promotions effects the cross effects are also asymmetric across pairs of categories i e related category pairs may be characterized as having a primary and a secondary category thus these results provide a more complete description of the effects of promotional changes by examining them both within and across categories the co incidence results show the extent of the relationship between categories that arises from uncontrollable and unobserved factors these results are useful since they provide insights into a general structure of dependence relationships across categories the heterogeneity results show that observed demographic factors such as family size influence the intrinsic category preference of households larger family sizes also tend to make households more price sensitive for both the primary and secondary categories we find that price sensitivities across categories are not highly correlated at the household level we also find some evidence that intrinsic preferences for cake mix and cake frosting are more closely related than preferences for fabric detergent and fabric softener we compare our model with a series of null models using both estimation and holdout samples we show that both complementarity and co incidence play a significant role inpredicting multicategory choice we also show how many single category models used in conjunction may not be good predictors of joint choice our results are likely to be of interest to retailers and manufacturers trying to optimize pricing and promotion strategies across many categories as well as in designing micromarketing strategies we illustrate some of these benefits by carrying out an analysis which shows that the true impact of complementarity and co incidence on profitability is significant in a retail setting our model can also be applied to other domains the combination of item interdependence and individual household level estimates may be of particular interest to database marketers in building customized cross selling strategies in the direct mail and financial service industries

residential energy use abstract the energy information administration recently published data they collected from the national interim energy consumption survey niecs niecs includes detailed information on 4081 individual households demographic characteristics energy related features of the structure heating equipment and appliances therein recent conservation actions taken by the household and fuel consumption and costs for the april 1978 march 1979 one year period this data set provides a new and valuable resource for analysis we summarized and analysed the niecs data on household energy consumption total energy use electricity use and use of the primary space heating fuel the regression equations constructed explain roughly half the variation in energy use among households these equations contain 10 or fewer independent variables the most important of which are fuel price year house was built floor area and heating degree days

heuristics for pricing and positioning a product line using conjoint and cost data designing and pricing a product line is the very essence of every business in recent years quantitative methods to assist managers in this task have been gaining in popularity conjoint analysis is already widely used to measure preferences for different product profiles and build market simulation models in the last few years several papers have been published that suggest how to optimally choose a product line based on such data we formalize this problem as a mathematical program where the objective of the firm is either profit or total welfare unlike alternative published approaches we introduce fixed and variable costs for each product profile the number of products to be introduced is endogenously determined on the basis of their desirability fixed and variable costs and in the case of profits their cannibalization effect on other products while the problem is difficult np complete we show that the maximum welfare problem is equivalent to the uncapacitated plant location problem which can be solved very efficiently using the greedy interchange heuristic based on past published experience with this problem and on simulations we perform we show that optimal or near optimal solutions are obtained in seconds for large problems we develop a new greedy heuristic for the profit problem and its application to simulated problems shows that it too runs quickly and with better performance than various alternatives and previously published heuristics we also show how the methodology can be applied taking existing products of both the firm and the competition into account

a shifting regimes approach to the stationarity of the market model parameters of individual securities recent studies indicate that the widespread assumption of parameter stationarity in empir ical applications of asset pricing models may be inappropriate this paper investigates the feasibility of modeling parameter instability as a sequence of persistent stable regimes reeursive residual and log likelihood techniques are combined to detect and locate shift points the results indicate that regime shifts are widespread frequent and often large enough to significantly effect empirical findings the nature of the shifts appears to be a rotation of the regression line indicating that correction of both alpha and beta parameters is required

the economics of house heating further findings abstract this paper applies the consumption model developed in scott 1 to a further set of data the findings cast fresh light on the relationship between insulation and energy consumption in houses the main finding being that once houses have been insulated to a certain standard further insulation does not significantly affect energy consumption estimates of income elasticity and the effect of household size are also presented

customer recognition in experience vs inspection good markets we study the effects of customer recognition and behavior based price discrimination bpd in a two period experience good duopoly with a discrete value distribution and we investigate the role of consumers ex ante valuation uncertainty in dynamic price competition through comparison with an inspection good duopoly several results are reached first the firms may reward repeat purchase when the probability of a high value is relatively low and when the high low value difference is large otherwise they may engage in poaching second bpd frequently increases each firm s total profits even in the poaching equilibrium these results contrast with the inspection good duopoly and the driver is that consumers period 2 product preference depends on their realized values in period 1 third consumers ex ante valuation uncertainty may increase or decrease firm profits without bpd and it weakly increases firm profits with bpd relative to the inspection good duopoly this paper was accepted by j miguel

individual marketing with imperfect targetability our research investigates the competitive ramifications of individual marketing and information management in today s information intensive marketing environments the specific managerial issues we address are as follows first what kinds of incentive environments do competing firms face when they can only target individual customers imperfectly second does the improvement in an industry s targetability intensify price competition in the industry such that all competing firms become worse off third should a firm share its customer knowledge so as to improve its rival s targetability fourth how should an information vendor sell its information that can improve a firm s targetability finally do competing firms have the same incentives to invest in their own targetability to answer those questions we develop a simple model a la narasimhan 1988 in which each of the two competing firms have their own loyal customers and compete for common switchers we assume that each firm can classify its own loyal customers and switchers correctly only with a less than perfect probability this means that each firm s perceived customer segmentation differs from the actual customer segmentation based on their perceived reality these two competing firms engage in price competition as an extension we also allow the competing firms to make their investment decisions to acquire targetability we show that when individual marketing is feasible but imperfect improvements in targetability by either or both competing firms can lead to win win competition for both even if both players behave noncooperatively and the market does not expand win win competition results from the fact that as a firm becomes better at distinguishing its price insensitive loyal customers from the switchers it is motivated to charge a higher price to the former however due to imperfect targetability each firm mistakenly perceives some price sensitive switchers as price insensitive loyal customers and charges them all a higher price these misperceptions thus allow its competitors to acquire those mistargeted customers without lowering their prices and hence reduce the rival firm s incentive to cut prices this effect softens price competition in the market and qualitatively changes the incentive environment for competing firms engaged in individual marketing a prisoner s dilemma occurs only when targetability in a market reaches a sufficiently high level this win win perspective on individual marketing has many managerial implications first we show that superior knowledge of individual customers can be a competitive advantage however this does not mean that a firm should always protect its customer information from its competitors to the contrary we find that competing firms can all benefit from exchanging individual customer information with each other at the nascent stage of individual marketing when firms targetability is low indeed under certain circumstances a firm may even find it profitable to give away this information unilaterally however as individual marketing matures as firms targetability becomes sufficiently high further improvements in targetability will intensify price competition and lead to prisoner s dilemma therefore it is not only prudent politics but also a business imperative for an industry to seize the initiative on the issue of protecting customer privacy so as to ensure win win competition in the industry second we show that the firm with a larger number of loyal customers tends to invest more in targetability when the cost of acquiring targetability is high however the firm with a smaller loyal base can through information investment acquire a higher level of targetability than the firm with a larger loyal base as long as the cost of acquiring targetability is not too high as the cost further decreases competing firms will all have more incentives to increase their investments in targetability until they achieve the highest feasible level third an information vendor should make its information available nonexclusively exclusively when its information is associated with a low high level of targetability when the vendor does sell its information exclusively it should target a firm with a small loyal following if it can impart a high level of targetability to that firm finally our analysis shows that an information intensive environment does not doom small firms in fact individual marketing may provide a good opportunity for a small firm to leapfrog a large firm the key to leapfrogging is a high level of targetability or customer knowledge

optimal financial aid policies for a selective university our paper provides a model of optimal financial aid policies for a selective university the model implies that the financial aid package to be offered to each category of admitted applicants depends on the elasticity of the fraction who accept offers of admission with respect to the financial aid package offered them the propensity of the category to enroll the elasticity of the category s average quality with respect to the number admitted and the relative weight the university assigns them in the utility function while the latter must be determined subjectively the former parameters are subject to empirical estimation we conclude with a study of one institution s data and illustrate how they may be estimated these estimates are then applied to illustrate what the optimal financial aid policy would be for the university

observed and unobserved preference heterogeneity in brand choice models this paper extends the scanner based choice literature by explicitly incorporating individual level brand preference data we illustrate our model using a unique data set that combines survey and scanner data collected from the same individuals the addition of individual specific brand preference information significantly improves fit and prediction furthermore this observed heterogeneity better explains choice than does unobserved heterogeneity in the standard scanner model s parameters more importantly we find that the standard model underestimates the importance of consumers brand preferences and overestimates both brand loyalties and price sensitivities brand loyalty is overestimated because models without preference information confound state dependence heterogeneity and preference effects price sensitivities are inflated because the average preference based consumer is implicitly assumed to be more willing to switch from his preferred brand than is the real preference based consumer further standard models overestimate the heterogeneity in price and loyalty sensitivities and misidentify both price and loyalty sensitive consumers the managerial implications of our findings and the applicability of our methodology when survey data are collected infrequently and for only a subsample of consumers are pursued we demonstrate that even under these circumstances better populationwide pricing and promotion decisions are identified and more accurate targeting results

market segmentation and collusive behavior abstract the recent literature on oligopolistic third degree price discrimination has been primarily concerned with rival firms incentives to acquire customer specific information and the consequences of such information on firm profitability and welfare this literature has taken mostly a static view of the interaction between competing firms in contrast in this paper we investigate the impact of customer specific information on the likelihood of tacit collusion in a dynamic game of repeated interaction this issue is very important because competitive price discrimination usually leads to a cutthroat price competition prisoners dilemma among firms firms therefore may seek ways to soften competition and sustain higher prices our main result is that collusion becomes more difficult as the firms ability to segment consumers improves

morphological analysis of energy services paving the way to quality differentiation in the power sector abstract the activation of the still predominantly passive demand side is necessary to further guarantee a stable power system in the short term and ensure capacity adequacy in the long run a system with a high share of generators with nearly no marginal costs requires new services that facilitate transmitting the right economic signals to the system stakeholders to this end we refine the notion of energy services and propose a framework to systematically design quality differentiated energy services for consumers this approach facilitates a value based economic assessment of energy services that deviates from the marginal cost paradigm we further illustrate pricing options for these new energy service products and outline infrastructural needs and additional use case specific product properties moreover we discuss how the morphological approach can be formalised using a mathematical programming formulation and introduce a complexity measure that facilitates assessing potential adoption obstacles for end consumers additionally we illustrate the practical applicability of these findings by using a prototypical implementation of a decision support system to foster differentiated energy services we recommend a more lenient regulatory regime lowering the barriers for new market entrants

multichoice logit modeling incomplete preference rankings of classical concerts in this article we develop an econometric model to analyze data on incomplete information on preferences the available information consists of groups of alternatives that are preferred to other groups of alternatives only for the most preferred group is a full ranking observed the resulting model is estimated on data concerning preferences on classical concerts

the informational role of product trade ins for pricing durable goods this research theorizes that sellers of durable goods can utilize inferences about the buyer s willingness to pay based not only on her decision to trade in the old good but also on its characteristics we find empirical support for this theory using transaction data for new car purchases the results support the notion that dealers infer a higher willingness to pay and charge higher prices to consumers who trade in a used vehicle than to those who do not we also find that dealers charge even higher prices to those consumers who trade in used cars that are similar to the new one

practice prize winner a nested logit model of product and transaction type choice for planning automakers pricing and promotions we develop a consumer response model to evaluate and plan pricing and promotions in durable good markets we discuss its implementation in the u s automotive industry which spends about 45 billion each year in price promotions the approach is based on a random effects multinomial nested logit model of product e g a vehicle model such as hyundai tucson and transaction type choice transaction types include combinations of acquisition types e g purchase versus lease and pricing instruments cash rebates reduced apr financing lease payment discounts we estimate the model using hierarchical bayes methods to capture response heterogeneity at the local market level we find key characteristics unique to durable good markets first consumers are heterogeneous in both their brand and transaction type preferences second consumers differ in their overall price sensitivity as well as in their relative sensitivity to alternative pricing instruments e g cash discounts reduced monthly payments third the most effective pricing programs tend to be those in which automakers offer consumers a menu of options to choose from e g a choice among a cash discount reduced interest rate financing or a lease payment discount we illustrate the model through an empirical application to a sample of data drawn from j d power transaction records in the entry suv segment and discuss examples of actual implementations

first degree price discrimination goes to school personalized pricing is widely discussed but seldom observed making studies of its efficacy rare yet first degree price discrimination is common in the pricing of higher education and i use data on prices and the characteristics of students admitted to a professional graduate program at a public university to estimate a matriculation demand function i then derive linear pricing functions that maximize revenue for a target number of students by allowing these functions to depend on progressively richer sets of observables i explore the effect of personalization of pricing on profit tailoring prices to a one dimensional measure of student quality would raise revenue by 2 2 per cent above the revenue with uniform pricing pricing based on both student quality and state residency raises revenue by 8 4 per cent and further tailoring based on available observables raises prices 9 0 per cent above the maximum revenue under uniform pricing pricing that obeys current statutory tuition limits raises revenue less but still by just over half as much i also infer the welfare weights that the pricing process implicitly attaches to student characteristics

similarities in choice behavior across product categories differences between consumers in sensitivity to marketing mix variables have been extensively documented in the scanner panel data all studies of consumer heterogeneity focus on a specific category of products and ignore the fact that the purchase behavior of panel households is often observed simultaneously in multiple categories if sensitivity to marketing mix variables is a common consumer trait then one should expect to see similarities in sensitivity across multiple categories the goal in this paper is to measure the covariance of both observed linked to measured characteristics of households and unobserved heterogeneity in marketing mix sensitivity across multiple categories measurement of correlation in sensitivities across categories will serve to guide the interpretation of the literature on household heterogeneity if there is a large correlation one can be more confident that sensitivity to marketing variables is a fundamental household pr operty and not simply a category specific anomaly detection of correlation in sensitivities across categories requires an appropriate methodology that can handle the high dimensional covariance structures and properly account for uncertainty in estimatio n for example a simple approach might be to fit a brand choice model to each of the available categories in turn ignoring the data in the other categories for each category household parameter estimates could be obtained for the parameters corresponding to price display and feature sensitivity these parameter estimates could be viewed as data and the correlations across categories could be computed such a procedure could induce a downward bias in the estimation of correlation dueto the independent sampling errors which are present in each parameter estimate we develop a hierarchical model structure that introduces an explicit correlation structure across categories and utilizes the data in multiple categories at the same time to reduce the size of the covariance matrix we use a variance components approach we introduce household specific demographic variables to decompose the correlation across categories into that which can be ascribed to observable and unobservable sources shopping behavior variables such as shopping frequency and market basket size as well as intensity of shopping in a category are also included in the model using data on five categories we find substantial and statistically important correlations ranging from 32 for price sensitivities to 58 for feature sensitivity these correlations are much larger than the correlations obtained with the state of the art techniques available prior to our work we attribute our ability to detect substantial correlations to our method which involves the joint use of multiple category data in a parsimonious and efficient manner unlike previous studies with panel data household demographic variables are found to be strongly related to price sensitivity higher income households are less price sensitive and large families are more price sensitive shopping behavior variables are also important in explaining price sensitivity households that visit the store often are more price sensitive households with larger market baskets are less price sensitive confirming the view of bell and lattin 1998 heavy user households tend to be both less price sensitive and less display sensitive the evidence presented here of substantial correlations validates in part the notion that sensitivity to marketing mix variables is a consumer trait and is not unique to specific product categories it also opens the possibility of using information across categories in making inferences about consumer brand preference and marketing mix sensitivity providing a richer source of information for target marketing

the perils of behavior based personalization behavior based personalization has gained popularity in recent years whereby businesses offer personalized products based on consumers purchase histories this paper highlights two perils of behavior based personalization in competitive markets first although purchase histories reveal consumer preferences competitive exploitation of such information damages differentiation similar to the classic finding that behavior based price discrimination intensifies price competition with endogenous product design there is yet a second peril it emerges when forward looking firms try to avoid the first peril by suppressing the information value of purchase histories ideally if a market leader serves all consumers on day 1 purchase histories contain no information about consumer preferences however knowing that their rivals are willing to accommodate a market leader firms are more likely to offer a mainstream design at day 1 which jeopardizes differentiation based on this understanding i investigate how the perils of behavior based personalization change under alternative market conditions such as firms better knowledge about their own customers consumer loyalty and inertia consumer self selection and the need for classic designs

zooming in on paid search ads a consumer level model calibrated on aggregated data we develop a two stage consumer level model of paid search advertising response based on standard aggregated data provided to advertisers by major search engines such as google or bing the proposed model uses behavioral primitives in accord with utility maximization and allows recovering parameters of the heterogeneity distribution in consumer preferences the model is estimated on a novel paid search data set that includes information on the ad copy to that end we develop an original framework to analyze composition and design attributes of paid search ads our results allow us to correctly evaluate the effects of specific ad properties on ad performance taking consumer heterogeneity into account another benefit of our approach is allowing recovery of preference correlation across the click through and conversion stage based on the estimated correlation between price and position sensitivity we propose a novel contextual targeting scheme in which a coupon is offered to a consumer depending on the position in which the paid search ad was displayed our analysis shows that total revenues from conversion can be increased using this targeting scheme while keeping cost constant

a combined approach for segment specific market basket analysis abstract market baskets arise from consumers shopping trips and include items from multiple categories that are frequently chosen interdependently from each other explanatory models of multicategory choice behavior explicitly allow for such category purchase dependencies they typically estimate own and across category effects of marketing mix variables on purchase incidences for a predefined set of product categories because of analytical restrictions however multicategory choice models can only handle a small number of categories hence for large retail assortments the issue emerges of how to determine the composition of shopping baskets with a meaningful selection of categories traditionally this is resolved by managerial intuition in this article we combine multicategory choice models with a data driven approach for basket selection the proposed procedure also accounts for customer heterogeneity and thus can serve as a viable tool for designing target marketing programs a data compression step first derives a set of basket prototypes which are representative for classes of market baskets with internally more distinctive complementary cross category interdependencies and are responsible for the segmentation of households in a second step segment specific cross category effects are estimated for suitably selected categories using a multivariate logistic modeling framework in an empirical illustration significant differences in cross effects and price elasticities can be shown both across segments and compared to the aggregate model

the value of purchase history data in target marketing an important aspect of marketing practice is the targeting of consumer segments for differential promotional activity the premise of this activity is that there exist distinct segments of homogeneous consumers who can be identified by readily available demographic information the increased availability of individual consumer panel data open the possibility of direct targeting of individual households the goal of this paper is to assess the information content of various information sets available for direct marketing purposes information on the consumer is obtained from the current and past purchase history as well as demographic characteristics we consider the situation in which the marketer may have access to a reasonably long purchase history which includes both the products purchased and information on the causal environment short of this complete purchase history we also consider more limited information sets which consist of only the current purchase occasion or only information on past product choice without causal variables proper evaluation of this information requires a flexible model of heterogeneity which can accommodate observable and unobservable heterogeneity as well as produce household level inferences for targeting purposes we develop new econometric methods to implement a random coefficient choice model in which the heterogeneity distribution is related to observable demographics we couple this approach to modeling heterogeneity with a target couponing problem in which coupons are customized to specific households on the basis of various information sets the couponing problem allows us to place a monetary value on the information sets our results indicate there exists a tremendous potential for improving the profitability of direct marketing efforts by more fully utilizing household purchase histories even rather short purchase histories can produce a net gain in revenue from target couponing which is 2 5 times the gain from blanket couponing the most popular current electronic couponing trigger strategy uses only one observation to customize the delivery of coupons surprisingly even the information contained in observing one purchase occasion boasts net couponing revenue by 50 more than that which would be gained by the blanket strategy this result coupled with increased competitive pressures will force targeted marketing strategies to become much more prevalent in the future than they are today

unit trust objectives and investor choice the widespread use by unit trusts of terms such as income gorwth or balanced portfolio to describe their investment aims suggests that such descriptions accurately characterize the type ans particularly the rist return characteristics of unit trust portfolios this study examines the usefulness of such objectives and finds little evidence that they are helpful to investors it is generally difficult if not impossible to distinguish on the basis of different objectives between the returns or the risk of unit trusts that invest predominantly in uk equities although objectives do distinguish between trusts that invest heavily in overseas or fixed interest securities attempts to identify a meaningful grouping or trusts on the basis of their return before and after adjustment for risk were unsuccessful

personalized pricing and quality differentiation we develop an analytical framework to investigate the competitive implications of personalized pricing pp whereby firms charge different prices to different consumers based on their willingness to pay we embed pp in a model of vertical product differentiation and show how it affects firms choices over quality we show that firms optimal pricing strategies with pp may be nonmonotonic in consumer valuations when the pp firm has high quality both firms raise their qualities relative to the uniform pricing case conversely when the pp firm has low quality both firms lower their qualities although many firms are trying to implement such pricing policies we find that a higher quality firm can actually be worse off with pp while it is optimal for the firm adopting pp to increase product differentiation the non pp firm seeks to reduce differentiation by moving in closer in the quality space while pp results in a wider market coverage it also leads to aggravated price competition between firms because this entails a change in equilibrium qualities the nature of the cost function determines whether firms gain or lose by implementing such pp policies despite the threat of first degree price discrimination we find that pp with competing firms can lead to an overall increase in consumer welfare

designing a family of development intensive products faced with fragmented markets saturated and demanding customers and global competition firms increasingly must design and offer a line of innovative quality differentiated products to target customers with differing willingness to pay wtp in this context designing a special class of products that we term development intensive products dips for which the fixed costs of development far outweigh the unit variable costspresents some unique managerial challenges examples of such development intensive offerings abound in a number of industries including the pharmaceutical information and entertainment sectors of the economy our contributions in this paper are threefold a to show that managerial insights from the traditional approach to product line design developed for unit variable cost intensive products do not carry over to dips b to present new mechanisms and managerial guidelines for designing a family of products for which development costs cannot be ignored and c to illustrate the insights with an extended industry example we find that the design approach based on degrading or subtracting value from a high end product to obtain a subsumed low end edition shown in the literature to be an effective approach for designing unit cost intensive products can be inappropriate for dips this limitation of value subtraction has implications for the number of variants and the sequence in which they are developed as an alternative to a subsumed product design strategy we propose and examine the overlapped product design approach in which a low end product is not completely subsumed within its high end counterpart but differentiated on additional vertical quality dimensions our results both explain the recent challenges of firms with subsumed low end products and guide them in designing a product line to successfully address emerging low end market segments

valuing customer portfolios with endogenous mass and direct marketing interventions using a stochastic dynamic programming decomposition the customer relationship management allocation in marketing budgets is potentially misleading when it uses individual customer lifetime value estimations from historical data planned marketing interventions would change the purchasing behavior of different customers and history based decisions would thus be suboptimal to cope with this inherent endogeneity we model the optimal allocation of the marketing mix by accounting simultaneously for mass interventions and direct marketing interventions for each customer this is a large stochastic dynamic problem that in general is computationally rather intractable as a result of the curse of dimensionality we present an algorithm to derive the optimal marketing policies how the firm should allocate its marketing resources and the expected present value of those decisions which maximize the long term profitability of firms this allows the firm to value customers segments and helps the firm to target those that maximize long term profitability given the optimal marketing resources allocation we apply the proposed approach in the context of a kitchen appliance manufacturer the results identify the most effective marketing policies and the endogenous customer values it is in this context that we also dynamically identify the most profitable customer and the short and long term effects of marketing activities on each customer

uk unit trust performance 1980 1989 a passive time varying approach abstract this paper indirectly tests the efficient markets hypothesis by analysing the performance of 30 authorised unit trusts from 1980 through 1989 the risk return relationship of the funds is allowed to vary in a generalised manner thus allowing for passive structural change in underlying economic relationships our findings suggest that 21 of the 30 trusts in the sample were able to supply investment opportunities to the individual investor which were superior to a buy and hold strategy

a choice model for packaged goods dealing with discrete quantities and quantity discounts utility maximizing solutions to economic models of choice for goods with either discrete quantities or non linear prices cannot always be obtained using standard first order conditions such as kuhn tucker and roy s identity when quantities are discrete there is no guarantee that derivatives of the utility function are equal to derivatives of the budget constraint moreover when prices are nonlinear as in the case of quantity discounts first order conditions can be associated with the minimum rather than the maximum value of utility in these cases the utility function must be directly evaluated to determine its maximum this evaluation can be computationally challenging when there exist many offerings and when stochastic elements are introduced into the utility function in this paper we provide an economic model of demand for substitute brands that is flexible parsimonious and easy to implement the methodology is demonstrated with a scanner panel data set of light beer purchases the model is used to explore the effects of price promotions on primary and secondary demand and the utility of product assortment

on the strategic choice of spatial price policy the strategic incentives with respect to the choice of price policy in spatial competition are analyzed in a duopoly model price discrimination emerges as the unique equilibriu m outcome in games with either simultaneous choice of policy and pric e or sequential choice where firms may commit first to uniform mill p ricing before the actual market stage nevertheless profits may be h igher with uniform pricing the authors models are applied to analyz e some common business practices that arise in geographical pricing like the basing point system and in the pricing of varieties or opti ons from a base product in a product differentiation context copyright 1988 by american economic association

a segment level hazard approach to studying household purchase timing decisions the increasing availability of customer level data and the willingness of marketers to customize the timing of their offers to consumers makes the accurate segment level description of household purchase timing decisions a compelling issue in this paper we employ a finite mixture accelerated failure time model to identify and characterize household segments in terms of their purchasing rates and their propensity to accelerate purchases due to marketing mix activities such an approach also promises to alleviate possible aggregation problems arising from the use of a common hazard rate for all households an application to household panel data suggested that infrequent buyers show higher propensity to accelerate than frequent buyers do and that positive duration effects are underestimated when not accounting for segment specific hazard rates copyright 2002 john wiley sons ltd