decomposing promotional effects with a dynamic structural model of flexible consumption abstract in this article the authors offer a methodology to decompose the effects of price promotions into brand switching stockpiling and change in consumption by explicitly allowing for consumer heterogeneity in brand preferences and consumption needs they develop a dynamic structural model of a household that decides when what and how much to buy as well as how much to consume to maximize its expected utility over an infinite horizon by making certain simplifying assumptions the authors reduce the dimensionality of the problem they estimate the proposed model using household purchase data in the canned tuna and paper towels categories the results from the model offer insights into the decomposition of promotional effects into its components this could help managers make inferences about which brand s sales are more responsive to stockpiling or increase in consumption expansion and how temporary price cuts affect future sales contrary to previous literature the authors find that brand swi

econometric models for marketing decisions ance of aggregation biases and so on franses 2005 provides an inventory of commonly used diagnostic tests franses see table 2 for 1998 2000 and table 3 for 2001 2003 also shows that there is a paucity of actual use of diagnostic tests in articles published in jmr such paucity may suggest that researchers have a disincentive to conduct all relevant tests for example it might be imagined that though researchers prefer to publish a valid model rather than one that is invalid publishing an invalid model is still preferred to not publishing one especially if it is difficult for readers to detect model deficiencies given data constraints it is virtually impossible for researchers to accommodate all possible nuances thus researchers rely on theories and experience to decide which aspects are the most critical to include in a model with accumulating empirical evidence in the literature the expectation is that future modeling efforts will be more informed and thus likely to provide increasingly useful i e valid and reliable results however i urge researchers to consult the checklist that franses provides and to conduct all diagnostic tests when appropriate in applied econometrics there are three possible reasons for specific tests not to be used first researchers may argue convincingly that a test does not apply in the model s context for example testing the null hypothesis of zero autocorrelation in the error term in a model of purely cross sectional data is irrelevant separately i note that the use of generalized least squares rather than ordinary least squares to accommodate serial correlation in time series data is a technical correction that is not convincing unless the researcher can justify how serial correction logically arises for an otherwise correctly specified model second some tests may not yet be available for cases other than linear models and normally distributed errors third researchers may argue that the violation of a particular assumption does not invalidate the substantive results for example consistency of ordinary least squares does not require normality of the error term in all other cases it is the researchers responsibility to conduct and show appropriate diagnostic tests the model cannot be assumed to be valid unless proper diagnostic tests fail to reject the assumptions because all models are incomplete representations of reality a central question is how can a model that is superior to a meaningful alternative e g judgment or a simpler representation than the proposed model be obtained if the interest of the researcher is to discover how marketing activities affect purchases or other responses as in a causal model any comparison to a model without marketing variables seems useless still it might be argued that beginning with the august 2003 issue journal of marketing research jmr has published one or more comments on the lead article followed by a rejoinder i have asked experts to provide commentary on one article in each issue that i believe has especially relevant content for researchers and managers in the current issue the lead article is an invited paper for which i also asked several experts to provide comments in all cases i provide an opportunity for the author s of the original article to prepare a rejoinder in the same issue my hope is that such related reflections and commentaries on a current topic will enhance the value of jmr to readers although i see no reason to entice authors to express strong disagreements about specific issues i expect that such collections of articles will enable readers to become more informed about differences in perspectives that researchers with substantial expertise and experience have on important issues

long run effects of promotion depth on new versus established customers three field studies we use the results of three large scale field experiments to investigate how the depth of a current price promotion affects future purchasing of first time and established customers while most previous studies have focused on packaged goods sold in grocery stores we consider durable goods sold through a direct mail catalog the findings reveal different effects for first time and established customers deeper price discounts in the current period increased future purchases by first time customers a positive long run effect but reduced future purchases by established customers a negative long run effect overall the results show evidence of several long run effects forward buying selection customer learning and increased deal sensitivity short run metrics that ignore these effects overstate the overall change in demand for established customers the implication is that if prices are set based on short run elasticity then they will be too low among first time customers the short run metrics underestimate the total increase in demand if prices are set based on short run elasticity then they will be too high

please or squeeze brand performance implications of constrained and unconstrained multi item promotions existing research on price promotions typically investigates the effects of single product promotions however brand managers often promote multiple items simultaneously to bolster the performance of a complete brand line this paper investigates the brand performance implications of such multi item promotions we distinguish between two types of multi item promotions traditional unconstrained multi item promotions that grant a discount irrespective of the size or composition of the purchase set and constrained multi item promotions that require consumers to purchase specific quantities self bundling or even predetermined combinations fixed bundling of promoted items using a normative consumer decision model the authors analyze the relative effectiveness of these promotions in terms of unit sales and revenue impact and show that promotion performance is moderated by consumers preference for variety the authors find that unconstrained multi item promotions outperform single item promotions especially in markets without variety seeking in markets with variety seeking unconstrained multi item promotions are not as effective in stealing extra sales from competition because consumers prefer to spread their purchases across all items including competitive ones however in those markets self bundling promotions are particularly effective because they force consumers to adopt larger amounts of the promoted items at the expense of competitors finally in neither type of market does fixed bundling substantially improve promotion performance

a model of how discounting high priced brands affects the sales of low priced brands drawing on a consumer preference distribution structure postulated in analytical modeling research the author develops a separate effects model that separates the total discount effect of a compet

sales quantity surcharge and consumer inattention quantity surcharges occur when retailers carry a product in two sizes and offer a promotion on the small size the large size then costs more per unit than the small one when quantity surcharges occur sales of the large size decline only slightly even though the same quantity can be purchased for less we document this behavior in two data sets and four product categories it is consistent with the notion of passive shoppers found in the industrial organization literature and the notion of rational inattention in macroeconomics we discuss implications for consumer decision making demand estimation and firm pricing

optimizing retail assortments retailers face the problem of finding the assortment that maximizes category profit this is a challenging task because the number of potential assortments is very large when there are many stock keeping units skus to choose from moreover sku sales can be cannibalized by other skus in the assortment and the more similar skus are the more this happens this paper develops an implementable and scalable assortment optimization method that allows for theory based substitution patterns and optimizes real life large scale assortments at the store level we achieve this by adopting an attribute based approach to capture preferences substitution patterns and cross marketing mix effects to solve the optimization problem we propose new very large neighborhood search heuristics we apply our methodology to store level scanner data on liquid laundry detergent the optimal assortments are expected to enhance retailer profit considerably 37 3 and this profit increases even more to 43 7 when sku prices are optimized simultaneously

patient or physician oriented marketing what drives primary demand for prescription drugs abstract the authors analyze primary demand effects of marketing efforts directed at the physician detailing and professional journal advertising versus marketing efforts directed at the patient direct to consumer advertising the analysis covers 86 categories or approximately 85 of the u s pharmaceutical market during the 2001 2005 period primary demand effects are rather small in contrast with the estimated sales effects for individual brands by using a new brand level method to estimate primary demand effects with aggregate data the authors show that the small effects are due to intense competitive interactions during the observation period but not necessarily to low primary demand responsiveness in contrast with previous studies the authors also find that detailing is more effective in driving primary demand than direct to consumer advertising a category sales model cannot provide such insights in addition a category sales model likely produces biased predictions about period by perio

accounting for primary and secondary demand effects with aggregate data discrete choice models of aggregate demand such as the random coefficients logit can handle large differentiated products categories parsimoniously while still providing flexible substitution patterns however the discrete choice assumption may not be appropriate for many categories in which we expect consumers may purchase more than one unit of the selected item we derive the aggregate demand system corresponding to a discrete continuous household level model of demand we also propose a method of simulated moments procedure that provides consistent estimates of the structural parameters when only aggregate data are available the procedure also enables the researcher to control both for the potential endogeneity of marketing variables as well as potential heterogeneity in consumer tastes using our aggregate estimates we can measure the decomposition of price elasticities into incidence brand choice and purchase quantity components we also propose several empirical tests to assess the validity of the discrete continuous demand system versus that of the logit model in several simulation experiments we demonstrate the robustness of this model across datasets in which quantity choices may or may not be important our empirical calibration to store level data in the refrigerated orange juice category indicates a considerable improvement in fit of the observed aggregate sales using the discrete continuous model

an empirical analysis of price discrimination mechanisms and retailer profitability abstract retailers typically engage in some form of price discrimination to increase profitability in this article the authors compare the impact on retailer profitability of two price discrimination mechanisms quantity discounts based on package size second degree price discrimination and store level pricing or micromarketing third degree price discrimination whereas the latter has been well addressed in the marketing literature there is limited empirical research on the use of quantity discounts for price discrimination using store level sales data the authors estimate a structural demand model accounting for parameter heterogeneity and price endogeneity they combine the parameter estimates with a model of retailer pricing to conduct optimal pricing and profitability simulations under several scenarios ranging from constraining the retailer not to engage in any form of price discrimination to the least restrictive scenario of setting nonlinear price schedules specific to each store the pr

asymmetric and neighborhood cross price effects some empirical generalizations this paper provides some empirical generalizations regarding how the relative prices of competing brands affect the cross price effects among them particular focus is on the asymmetric price effect and the neighborhood price effect the asymmetric price effect states that a price promotion by a higher priced brand affects the market share of a lower priced brand more so than the reverse the neighborhood price effect states that brands that are closer to each other in price have larger cross price effects than brands that are priced farther apart the main objective of this paper is to test if these two effects are generalizable across product categories and to assess which of these two effects is stronger while the neighborhood price effect has not been rigorously tested in past research the asymmetric price effect has been validated by several researchers however these tests of asymmetric price effect have predominantly used elasticity as the measure of cross price effect the cross price elasticity measures the percentage change in market share or sales of a brand for 1 change in price of a competing brand we show that asymmetries in cross price elasticities tend to favor the higher priced brand simply because of scaling effects due to considering percentage changes furthermore several researchers have used logit models to infer asymmetric patterns we also show that inferring asymmetries from conventional logit models is incorrect to account for potential scaling effects we consider the absolute cross price effect defined as the change in market share percentage points of a target brand when a competing brand s price changes by one percent of the product category price the advantage of this measure is that it is dimensionless hence comparable across categories and it avoids scaling effects we show that in the logit model with arbitrary heterogeneity in brand preferences and price sensitivities the absolute cross price effect is symmetric we develop an econometric model for simultaneously estimating the asymmetric and neighborhood price effects and assess their relative strengths we also estimate two alternate models that address the following questions i if i were managing the ith highest priced brand which brand do i impact the most by discounting and which brand hurts me the most through price discounts ii who hurts whom in national brand vs store brand competition based on a meta analysis of 1 060 cross price effects on 280 brands from 19 different grocery product categories we provide the following empirical generalizations 1 the asymmetric price effect holds with cross price elasticities but tends to disappear with absolute cross price effects 2 the neighborhood price effect holds with both cross price elasticities and absolute cross price effects and is significantly stronger than the asymmetric price effect on both measures of cross price effects 3 a brand is affected the most by discounts of its immediately higher priced brand followed closely by discounts of its immediately lower priced brand 4 national brands impact store brands more so than the reverse when the cross effect is measured in elasticities but the asymmetric effect does not hold with absolute effects store brands hurt and are in turn hurt the most by the lower priced national brands that are adjacent in price to the store brands 5 cross price effects are greater when there are fewer competing brands in the product category and among brands in nonfood household products than among brands in food products the implications of these findings are discussed

incorporating demographic variables in brand choice models an indivisible alternatives framework incorporating demographic variables in brand choice models is conceptually appealing and has numerous managerial benefits retailers and brand managers can assess geodemographic variations in demand and marketing mix response in order to implement micromarketing strategies for example a retailer planning to locate a new outlet can get some sense of the differences in demand patterns and price and promotion sensitivities in the new trading area in order to make initial stocking inventory pricing and promotion decisions for existing outlets retailers can fine tune the assortment and merchandising activities in a category to match local market conditions similarly a packaged goods manufacturers would benefit from getting a sense of whether they should stress promotional activity for one part of a brand s product line in some retail trading areas and other parts of the brand s line in other retail trading areas unfortunately a general finding across existing studies is that the impact of demographic variables on brand choice is neither strong nor consistent these findings are puzzling given that one would expect certain demographic variables such as income to have some influence on brand choice behavior moreover hoch et al hoch s j b d kim a j montgomery p e rossi 1995 determinants of store level price elasticity j marketing res 32february 17 29 using store level data find that a relatively small set of demographic variables is much more influential than competitive variables in explaining differences in price sensitivity across retail trading areas in light of such contradictory findings there is a need for a better conceptualization of the role of income and other demographic variables in household purchasing and this is the primary objective of this study this paper presents a microeconomic based framework called the indivisible alternatives ida framework to model household brand choice a key aspect of the ida framework is that it explicitly models alternatives in the market as being indivisible while past work has either explicitly or implicitly assumed perfect divisibility indivisibilities force a household s selection of a brand size and its level of category expenditure into a single joint decision hence demographic variables that influence category expenditure e g income also influence the choice of a brand size in addition since alternatives in the category come in several discrete sizes indivisibilities introduce differences in holding costs in the choice of a brand size combination consequently demographic factors that influence holding costs through consumption rate differences e g household size impact the choice of a brand size in a product category in this manner indivisibilities in market offerings naturally lead to differences in choice behavior across households that can be linked to demographic factors in a logical fashion in empirical applications to two different scanner panel data sets ketchup and ground coffee the proposed framework compares favorably with two benchmark specifications in terms of both goodness of fit and predictive validity the results from these product categories indicate that a household s price sensitivity is inversely related to its income level and that factors such as household size and seasonality which are likely to influence consumption rates make households more or less willing to buy larger package sizes income elasticity estimates from the model confirm that ceteris paribus households with lower incomes will have a higher propensity to purchase private labels and generic brands and a lower propensity to purchase national brands compared with households with higher incomes the micromarketing potential of the ida framework is explored in market simulations conducted for two different zip codes within a metropolitan area that vary with respect to income levels and other demographic factors the results indicate that for the product categories studied there are substantial differences across market areas in their response to the retail promotion of very large and very small package sizes within the same brand s product line the differences in response suggest that it may be beneficial to customize promotional programs to market areas based on their underlying demographic composition finally our findings suggest a link between household income and deal proneness that is conditional on other demographic variables and the expenditure required for the brand size in question specifically we find that smaller households with lower income levels are more likely to respond to promotions for smaller less expensive items within a category while larger households with higher incomes are more likely to respond to promotions for larger more expensive items within a category

the category demand effects of price promotions although price promotions have increased in both commercial use and quantity of academic research over the last decade most of the attention has been focused on their effects on brand choice and brand sales by contrast little is known about the conditions under which price promotions expand short run and long run category demand even though the benefits of category expansion can be substantial to manufacturers and retailers alike this paper studies the category demand effects of consumer price promotions across 560 consumer product categories over a 4 year period the data describe national sales in dutch supermarkets and cover virtually the entire marketing mix i e prices promotions advertising distribution and new product activity we focus on the estimation of main effects i e the dynamic category expansive impact of price promotions as well as the moderating effects of marketing intensity and competition both conduct and structure on short and long run promotional effectiveness the research design uses modern multivariate time series analysis to disentangle short run and long run effects first we conduct a series of unit root tests to determine whether or not category demand is stationary or evolving over time the results are incorporated in the specification of vector autoregressive models with exogenous variables varx models the impulse response functions derived from these varx models provide estimates of the short and long term effects of price promotions on category demand these estimates in turn are used as dependent variables in a series of second stage regressions that assess the explanatory power of marketing intensity and competition several model validation tests support the robustness of the empirical findings we present our results in the form of empirical generalizations on the main effects of price promotions on category demand in the short and the long run and through statistical tests on how these effects change with marketing intensity and competition the findings generate an overall picture of the power and limitations of consumer price promotions in expanding category demand as follows category demand is found to be predominantly stationary either around a fixed mean or a deterministic trend although the total net short term effects of price promotions are generally strong with an average elasticity of 2 21 and a more conservative median elasticity of 1 75 they rarely exhibit persistent effects instead the effects dissipate over a time period lasting approximately 10 weeks on average and their long term impact is essentially zero by contrast the successful introduction of new products into a category is more frequently associated with a permanent category demand increase several moderating effects on price promotion effectiveness exist more frequent promotions increase their effectiveness but only in the short run the use of nonprice advertising reduces the category demand effects of price promotions both in the short run and in the long run competitive structure matters as well the less oligopolistic the category the smaller the short run effectiveness of price promotions at the same time we find that the dominant form of competitive reaction either in price promotion or in advertising is no reaction short run category demand effectiveness of price promotions is lower in categories experiencing major new product introductions finally both the short and long run price promotion effectiveness is higher in perishable product categories the paper discusses several managerial implications of these empirical findings and suggests various avenues for future research overall we conclude that the power of price promotions lies primarily in the preservation of the status quo in the category

estimating a stockkeeping unit level brand choice model that combines household panel data and store data abstract the marketing literature has addressed the issues of heterogeneity and endogeneity when estimating a choice model with household level panel data when using these data at the stockkeeping unit or the universal product code level choices for each item in each of the time periods under consideration cannot be observed without such information it is difficult to control for item and time period specific unmeasured characteristics because there is no information on alternatives during those periods in which they are not purchased by any of the panelists in general when a product category has many alternatives each with fairly small shares the household sample may not contain sufficient choices for each alternative thus negatively affecting the ability to control for endogeneity with household data in contrast because aggregate store level data for those stores in which the panel makes purchases are the aggregation of purchases by all households visiting the stores the data contain the

is 75 of the sales promotion bump due to brand switching no only 33 is abstract several researchers have decomposed sales promotion elasticities based on household scanner panel data a key result is that the majority of the sales promotion elasticity approximately 74 on average is attributed to secondary demand effects brand switching and the remainder is attributed to primary demand effects timing acceleration and quantity increases the authors demonstrate that this result does not imply that if a brand gains 100 units in sales during a promotion the other brands in the category lose 74 units the authors offer a complementary decomposition measure based on unit sales the measure shows the ratio of the current cross brand unit sales loss to the current own brand unit sales gain during promotion the authors report empirical results for this measure they also derive analytical expressions that transform the elasticity decomposition into a decomposition of unit sales effects these expressions show the nature of the difference between the two decompositions to ga

riding the waves revealing the impact of intrayear category demand cycles on advertising and pricing effectiveness abstractgoing beyond traditional seasonality this research introduces the concept of the intrayear category demand cycle this phenomenon reflects demand cycles most consumer packaged goods categories experience throughout the year with periods of higher demand following periods of lower demand the author argues that acknowledging the existence of these cycles and understanding their impact on both advertising and pricing effectiveness and practice is critical for marketers specifically the author demonstrates how both advertising and price elasticities and observed advertising and prices evolve along these cycles for a unique set of 252 brands ranging from high advertising high priced premium mass brands to low advertising low priced value niche brands in 61 consumer packaged goods categories overall both advertising efectiveness and observed advertising are found to be stronger at demand peaks surprisingly consumer reactions to price decreases are weaker at demand peaks whereas reactions

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

the rational effect of price promotions on sales and consumption we explore the rational effect of price variation on sales and consumption in markets where consumers are uncertain about the future price of goods we first derive an optimal ordering policy which expresses the amount a consumer should purchase and consume in a given period as a function of the observed price of the good the distribution of future prices and the nature of his or her inventory this policy extends previous normative models of inventory control such as those by golabi 1985 and kalymon 1970 to the case where the amount to consume in a given period is an explicit decision variable and prices follow a first order stochastic process we then use this model to explore how changes in the long run frequency and temporal correlations of price promotions should normatively affect the contemporaneous relationship between purchase consumption and price among the predictions which follow from the model are that consumption should rationally increase with the size of existing inventories the short term sensitivity of sales to prices should be greater than that of consumption to price and this discrepancy increases with decreases in the temporal correlation of price deals and the long term relative frequency of price deals

local versus central wage bargaining with endogenous investments investment behavior may depend on whether wage bargaining takes place centrally or locally at the firm level the outcome of the wage bargain will in turn depend on previous investments ignoring other differences between the two bargaining regimes endogenous investments imply that wages are lower and profits higher under local wage bargaining than under central bargaining this does not necessarily imply that employment is highest under local bargaining since investments may differ in the two cases with a nash bargaining solution however reasonable assumptions imply that employment is highest under local wage bargaining

measuring the impact of promotions on brand switching when consumers are forward looking abstract logit choice models have been used extensively to study promotion response this article examines whether brand switching elasticities derived from these models are overestimated as a result of rational consumer adjustment of purchase timing to coincide with promotion schedules and whether a dynamic structural model can address this bias using simulated data the authors first show that if the structural model is correct brand switching elasticities are overestimated by stand alone logit models a nested logit model improves the estimates but not completely second the authors estimate the models on real data the results indicate that the structural model fits better and produces sensible coefficient estimates the authors then observe the same pattern in switching elasticities as they do in the simulation third the authors predict sales assuming a 50 increase in promotion frequency the reduced form models predict much higher sales levels than does the dynamic structural model the autho

research note estimating heterogeneous price thresholds a brand choice model with heterogeneous price threshold parameters is used to investigate a three regime piecewise linear stochastic utility function the model is used to explore the relationships between aspects of consumer price sensitivity and price thresholds using hierarchical bayes modeling with the markov chain monte carlo mcmc method this study contributes to the modeling literature on discontinuous likelihoods in choice models the empirical application using our scanner panel data set shows that the reference effect and loss aversion are more marked after price thresholds are taken into heterogeneous price response models furthermore loss aversion is attenuated by using price thresholds than by an aggregate homogeneity model without price thresholds

the multi product price setting newsvendor with resource capacity constraints abstract in this paper we consider a newsvendor problem commonly encountered in retail stores that cater to budget sensitive shoppers the newsvendor sells multiple products and in addition to determining order quantities must also determine the selling price of each product sold the demand for each product is of a stochastic nature and depends on the demands of other products i e is cross elastic we transform the objective function into a form that is amenable to developing integer programming solutions and then develop a numeric optimization procedure rooted in the nelder mead search technique we obtain encouraging numerical results on some small scale and large scale problems to the best of our knowledge this is the first work that produces implementable solutions for a scenario that is particularly relevant to retailers catering to budget sensitive customers who are abundant in the current economy

the effect of promotion on consumption buying more and consuming it faster the authors empirically demonstrate the existence of flexible consumption rates in packaged goods products how this phenomenon can be modeled and its importance in assessing the effectiveness of

invited paper learning models an assessment of progress challenges and new developments learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes and that they learn about these attributes over time in this survey we describe the literature on learning models that has developed over the past 20 years using the model of erdem and keane as a unifying framework erdem t keane m 1996 decision making under uncertainty capturing dynamic brand choice processes in turbulent consumer goods markets marketing sci 15 1 1 20 we describe how subsequent work has extended their modeling framework and applied learning models to a wide range of different products and markets we argue that learning models have contributed greatly to our understanding of consumer behavior in particular in enhancing our understanding of brand loyalty and long run advertising effects we also discuss the limitations of existing learning models and potential extensions one key challenge is to disentangle learning as a source of

price induced patterns of competition this research focuses on how price changes influence the observed pattern of brand competition the paper begins with a basic utility model formulation and examines the implications of three major classes of preference distributions on the expected patterns of competition a price tier model is proposed to operationalize the theory and to allow predictive testing the price tier model is estimated on 28 brands across four product categories the results show a specific asymmetric pattern of price competition higher price higher quality brands steal share from other brands in the same price quality tier as well as from brands in the tier below however lower price lower quality brands take sales from their own tier and the tier below brands but do not steal significant share from the tiers above the results are consistent with a bimodal preference distribution with the regular price indifference point being located toward the lower quality end of the preference distribution for the categories analyzed

semiparametric analysis to estimate the deal effect curve abstract the marketing literature suggests several phenomena that may contribute to the nature of the relationship between sales and price discounts these phenomena can produce complex nonlinearities and interactions in the deal effect curve that are best captured with a flexible approach because a fully nonparametric regression model suffers from the curse of dimensionality the authors propose a semiparametric regression model store level sales over time are modeled as a nonparametric function of own and cross item price discounts and a parametric function of other predictors the authors compare the predictive validity of the semiparametric model with that of two parametric benchmark models and obtain superior performance the results for three product categories indicate threshold and saturation effects for both ownand cross item temporary price cuts the authors also find that the nature of the own item curve depends on other items price discounts comparisons with restricted model specification

practice prize reports the practice prize reports consist of one article with two parts as follows sinha ashish j jeffrey inman yantao wang joonwook park attribute drivers a factor analytic choice map approach for understanding choices among skus and tellis gerard j rajesh k chandy deborah macinnis pattana thaivanich modeling the microeffects of television advertising which ad works when where for how long and why

new empirical generalizations on the determinants of price elasticity abstract the importance of pricing decisions for firms has fueled an extensive stream of research on price elasticities in an influential meta analytical study tellis 1988 summarized price elasticity research findings until 1986 however empirical generalizations on price elasticity require modifications because of 1 changes in market characteristics i e characteristics of brands product categories and economic conditions and 2 changes in the research methodology used to assess price elasticities therefore the authors present a meta analysis of price elasticity with new empirical generalizations on its determinants across a set of 1851 price elasticities based on 81 studies the average price elasticity is 2 62 a salient finding is that over the past four decades sales elasticities have significantly increased in magnitude whereas share and choice elasticities have remained fairly constant the authors find that accommodating price endogeneity has a strong magnitude increasing impa

recovering stockkeeping unit level preferences and response sensitivities from market share models estimated on item aggregates abstract the authors propose a new approach to obtaining stockkeeping unit sku level preferences and response sensitivities the authors distinguish an attribute level model in which the unit of analysis is the market share for an alternative created by aggregation e g colgate toothpaste from a truly disaggregate sku level model and they establish an analytical relationship between parameters that they obtain from the two models the authors show that sku level parameters can be recovered by calculation from estimated attribute level parameters circumventing the need for direct estimation of the more complex sku level model they calibrate the store data market share model using 98 weeks of data for ten brands and 168 skus of toothpaste rather than estimate 168 preference parameters when there is an outside alternative in addition to the 168 inside ones it is only necessary to estimate ten brand preference parameters from which the 168 parameters can be computed as long as share and mar

try it you will like it does consumer learning lead to competitive price promotions there is strong evidence that consumers learn from their brand consumption experiences and continuously update their brand purchase probabilities however in explaining why established competitive brands continuously compete through periodic price promotions most of the existing theories do not attribute this phenomenon to underlying consumer learning yet try it you will like it is often the stated rationale of the practicing marketing manager in offering consumers a price promotion on a brand this paper examines the connection between consumer learning and the offering of price promotions the consumer model specified is markovian in nature and encompasses in addition to consumer learning other empirical findings such as the increase in product class consumption in response to price reductions the consumer models used in the existing game theoretic approaches to this problem are shown to be mostly special cases of the proposed model it is demonstrated that for the commonly used price response functions the existence of consumer learning at a level of intensity consistent with that identified in empirical works makes it optimal for competing brands to periodically offer price promotions moreover it is shown that the competing brands should promote in different periods as opposed to head to head

estimating cannibalization rates for pioneering innovations to evaluate the success of a new product managers need to determine how much of its new demand is due to cannibalizing the firm s other products rather than drawing from competition or generating primary demand we introduce a time varying vector error correction model to decompose the base sales of a new product into its constituent sources the model allows managers to estimate cannibalization effects and calculate the new product s net demand which may be considerably less than its total demand we apply our methodology to the introduction of the lexus rx300 using detailed car transaction data this case is especially interesting because the lexus rx300 was the first crossover sport utility vehicle suv implying that its demand could come from both the luxury suv and the luxury sedan categories because lexus was active in both categories there was a double cannibalization potential we show how the contribution of the different demand sources varies over time and discuss the managerial implications for both the focal brand and its competitors

a retail store sku promotions optimization model for category multi period profit maximization consumer promotions are an important element of competitive dynamics in retail markets and make a significant difference in the retailer s profits but no study has so far included all the elements that are required to meet retail business objectives we extend the existing literatures by considering all the basic requirements for a promotional decision support system dss reliance on operational store level data only the ability to predict sales as a function of prices and the inclusion of other promotional variables affecting the category the new model delivers an optimizing promotional schedule at stock keeping unit sku level which maximizes multi period category level profit under the constraints of business rules typically applied in practice we first develop a high dimensional distributed lag demand model which integrates both cross sku competitive promotion information and cross period promotional influences we estimate the model by proposing a two stage sign constrained regularization approach to ensure realistic promotional parameters based on the demand model we then build a nonlinear integer programming model to maximize the retailer s category profits over a planning horizon under constraints that model important business rules the output of the model provides optimized prices display and feature advertising planning together with sales and profit forecasts empirical tests over a number of stores and categories using supermarket data suggest that our model generates accurate sales forecasts and increases category profits by approximately 17 and that including cross item and cross period effects is also valuable

a general theory of pass through in channels with category management and retail competition i provide a general formulation of the channel pass through problem as a comparative static of the retail price equilibrium and i analyze the impact of category management and retail competition on pass through focusing on brand and retailer differences and the nature of the cost change being passed through whether it is brand specific retailer specific both or neither with category management a retailer s response to a brand specific cost change is not limited to that brand in general a retailer will also change the prices of other brands the cross brand effect can be positive or negative and depending on its sign it either enhances or attenuates pass through i explain the cross brand effect as an interaction between two forces a demand substitution force that pushes for a negative cross brand effect and a strategic complementarity force that pushes for a positive cross brand effect retail competition adds another layer of strategic complementarity causing other retailers to respond even for retailer specific cost changes and increasing pass through of categorywide cost changes but its effect for brand specific cost changes is ambiguous i apply the theory to two commonly used demand functions linear demand and nested logit and show that they have significantly different pass through properties the paper concludes with a discussion of how the theory relates to the empirical literature including the companion piece by besanko et al besanko d j p duba s gupta 2005 own brand and cross brand retail pass through marketing sci 24 1 123 137

planning marketing mix strategies in the presence of interaction effects companies spend millions of dollars on advertising to boost a brand s image and simultaneously spend millions of dollars on promotion that many believe calls attention to price and erodes brand equity we believe this paradoxical situation exists because both advertising and promotion are necessary to compete effectively in dynamic markets consequently brand managers need to account for interactions between marketing activities and interactions among competing brands by recognizing interaction effects between activities managers can consider interactivity trade offs in planning the marketing mix strategies on the other hand by recognizing interactions with competitors managers can incorporate strategic foresight in their planning which requires them to look forward and reason backward in making optimal decisions looking forward means that each brand manager anticipates how other competing brands are likely to make future decisions and then by reasoning backward deduces one s own optimal decisions in response to the best decisions to be made by all other brands the joint consideration of interaction effects and strategic foresight in planning marketing mix strategies is a challenging and unsolved marketing problem which motivates this paper this paper investigates the problem of planning marketing mix in dynamic competitive markets we extend the lanchester model by incorporating interaction effects constructing the marketing mix algorithm that yields marketing mix plans with strategic foresight and developing the continuous discrete estimation method to calibrate dynamic models of oligopoly using market data both the marketing mix algorithm and the estimation method are general so they can be applied to any other alternative model specifications for dynamic oligopoly markets thus this dual methodology augments the decision making toolkit of managers empowering them to tackle realistic marketing problems in dynamic oligopoly markets we illustrate the application of this dual methodology by studying the dynamic lanchester competition across five brands in the detergents market where each brand uses advertising and promotion to influence its own market share and the shares of competing brands empirically we find that advertising and promotion not only affect the brand shares own and competitors but also exert interaction effects i e each activity amplifies or attenuates the effectiveness of the other activity normatively we find that large brands underadvertise and overspend on promotion while small brands underadvertise and underpromote finally comparative statics reveal managerial insights into how a specific brand should respond optimally to the changes in a competing brand s situation more generally we find evidence that competitive responsiveness is asymmetric

investment spending and interest rate policy the case of financial liberalisation in turkey the purpose of the present study is to analyse the impact of interest rate policy on investment spending in turkey over a period which covers years of both financial repression and financial liberalisation the model presented suggests that investment will be positively correlated with below equilibrium interest rates and negatively correlated with above equilibrium rates the model is tested using a switching regime model with an unknown equilibrium rate of interest the results suggest that setting interest rates too high may be as detrimental to economic health as setting them too low moreover there is evidence of an autonomous downward shift in the investment function during the liberalisation period which may have resulted from heightened uncertainty during the period

predicting competitive response to a major policy change combining game theoretic and empirical analyses this research uses procter gamble s value pricing initiative as a context for testing whether actual competitor and retailer response to a major policy change can be predicted using a game theoretic model we first estimate demand functions for p g and competitor brands from the period before value pricing was initiated we then formulate a dynamic manufacturer retailer stackelberg model that includes p g a national brand competitor and a retailer the model takes p g s move as given and prescribes the price and promotion response of the competitors and the retailer we substitute the estimated demand parameters into the model to obtain prescriptions for each competitor and the retailer and see whether these prescriptions are related to the actual response we find that the dynamic game theoretic model calibrated with empirical estimates of demand parameters has significant predictive power we also test the predictive power of two benchmark models the first is based on the reaction function approach of leeflang and wittink leeflang peter s h wittink dick r 1992 diagnosing competitive reactions using aggregated scanner data internat j res marketing9 39 57 and the second is a simplification of our dynamic model where the retailer is not strategic the dynamic game theoretic model performs better than either benchmark

competitive reactions to advertising and promotion attacks how do competitors react to each other s price promotion and advertising attacks what are the reasons for the observed reaction behavior we answer these questions by performing a large scale empirical study on the short run and long run reactions to promotion and advertising shocks in over 400 consumer product categories over a four year time span our results clearly show that the most predominant form of competitive response is passive in nature when a reaction does occur it is usually retaliatory in the same instrument i e promotion attacks are countered with promotions and advertising attacks are countered with advertising there are very few long run consequences of any type of reaction behavior by linking reaction behavior to both cross and own effectiveness we further demonstrate that passive behavior is often a sound strategy while firms that do opt to retaliate often use ineffective instruments resulting in spoiled arms accommodating behavior is observed in only a minority of cases and often results in a missed sales opportunity when promotional support is reduced the ultimate impact of most promotion and advertising campaigns depends primarily on the nature of consumer response not the vigilance of competitors

an integrated choice model incorporating alternative mechanisms for consumers reactions to in store display and feature advertising the marketing literature has suggested two prominent decision mechanisms through which in store display and feature advertising can affect brand choice which i call the price cut proxy effect and the consideration set formation effect the primary objective of this study is to propose an integrated brand choice model that incorporates these two possible behavioral mechanisms which have been shown to work by previous research the model allows consumers to use various combinations of the decision mechanisms with different probabilities and thus enables one to jointly assess the extent to which each effect might occur in actual purchase data and to investigate how consumers might differ in their tendencies to engage in these decision processes by incorporating these likely behavioral mechanisms the proposed model alleviates the problems caused by multicollinearity and produces sensible parameter estimates for the joint effects of promotion vehicles in store display feature ad and price discount which contributes to better managerial decision making

the long term effects of price promotions on category incidence brand choice and purchase quantity abstract to what extent do price promotions have a long term effect on the components of brand sales namely category incidence brand choice and purchase quantity the authors answer this question by using persistence modeling on weekly sales data of a perishable and a storable product derived from a scanner panel their analysis reveals first that permanent promotion effects are virtually absent for each sales component next the authors develop and apply an impulse response approach to estimate the promotional adjustment period and the total dynamic effects of a price promotion specifically they calculate the long term equivalent of gupta s 1988 14 84 2 breakdown of promotional effects because of positive adjustment effects for incidence but negative adjustment effects for choice the authors find a reversal of the importance of category incidence and brand choice 66 11 23 for the storable product and 58 39 3 for the perishable product the authors discuss the implications of the findings an

winners and losers in a major price war abstract although retail price wars have received much business press and some research attention it is unclear how they affect consumer purchase behavior this article studies an unprecedented price war in dutch grocery retailing that started in fall 2003 initiated by the market leader to halt its sliding market share the authors investigate the short and long term effects of the price war on store visits on spending and on the sensitivity of these decisions to weekly prices and price image they use a unique data set with consumer hand scan and perceptual data for a national panel of 1821 households covering two years before and two years after the price war started although the price war initially entailed more shopping around and increased spending spending per visit ultimately dropped because consumers redistributed their purchases across stores the price war made consumers more sensitive to weekly prices and price image which helped both the chain that showed an improvement in price image

decomposing the sales promotion bump with store data sales promotions generate substantial short term sales increases to determine whether the sales promotion bump is truly beneficial from a managerial perspective we propose a system of store level regression models that decomposes the sales promotion bump into three parts cross brand effects secondary demand cross period effects primary demand borrowed from other time periods and category expansion effects remaining primary demand across four store level scanner datasets we find that each of these three parts contribute about one third on average one extension we propose is the separation of the category expansion effect into cross store and market expansion effects another one is to split the cross item effect total across all other items into cannibalization and between brand effects we also allow for a flexible decomposition by allowing all effects to depend on the feature display support condition and on the magnitude of the price discount the latter dependence is achieved by local polynomial regression we find that feature supported price discounts are strongly associated with cross period effects while display only supported price discounts have especially strong category expansion effects while the role of the category expansion effect tends to increase with higher price discounts the roles of cross brand and cross period effects both tend to decrease

estimating the impact of consumer expectations of coupons on purchase behavior a dynamic structural model we examine the basic premise that consumers may anticipate future promotions and adjust their purchase behavior accordingly we develop a structural model of households who make purchase decisions to minimize their expenditure over a finite period the model allows for future expectations of promotions to enter the purchase decision households with adequate inventory of the product may face a trade off of buying in the current period with a coupon or defer the purchase until next period given their expectations of future promotions thus we provide a framework for examining the impact of consumer expectations on choice behavior the target audiences for our paper are a empirical researchers who intend to make structural models part of their applied research agenda and b managers who value and seek to understand the impact of consumers coupon expectations on current purchase behavior our research objective is to provide an empirical framework to examine whether and to what extent consumers anticipate future coupon promotions and adjust purchase behavior the central premise of our approach is that a rational consumer minimizes the present discounted value of the cost of a purchase where cost in a single period consists of purchase price inventory holding cost gains from coupons and potential stockout cost we aim to test whether our hypotheses regarding the various elements of the cost structure are supported and that whether consumers take into account future discounted cost when making current purchase decisions the research methodology we adopt is relatively new in econometrics and known as the estimable stochastic structural dynamic programming method the methodology amounts to incorporating a maximum likelihood routine embedded in a dynamic programming problem the dynamic programming problem is solved several times within a maximum likelihood iteration for each value of the state space elements and for each value of the parameters in the parameter set the state space in our model consists of purchase and nonpurchase alternatives in each time period coupon availability and no coupon availability in each time period level of inventory in each time period for each household and consumption rate of each household we use scanner panel data on purchases in the disposable diaper product category and promotions we estimate the inventory holding and stockout costs brand specific value of coupons and consumers expectations of future coupons the key insights and lessons learned can be summarized as follows 1 our results are consistent with the notion that consumers hold beliefs about future coupons and that such beliefs affect the purchase decision we find that the dynamic optimization model performs significantly better than a single period optimization model and a naive benchmark model 2 we find a high and significant stockout cost consistent with the essential nature of the product category our estimate of the holding cost yields a reasonable annualized percentage value when converted to the cost of capital we find that consumer valuation of coupons differ markedly across brands 3 our empirical evidence supports the notion that consumers hold beliefs about future coupon availability we also find that the expectations about future coupons estimated endogenously differ depending upon whether or not a coupon was available in the current period thus the proposed model structure yields rich managerial insights and facilitates several what if scenarios a possible limitation of our model and estimable structural models in general is the computational cost while it is possible to conceptually extend the state space to accommodate variations across households and add a richer parameter structure each addition multiplies the size of the state space and the computation time for this reason we have kept the state space as tight as possible and refrained from additions that would otherwise enable us to incorporate heterogeneity in consumer decisions for example we assumed that consumers are similar other than reflected by their purchase behavior we built a category purchase incidence model rather than a brand choice model we refrained from including unobserved heterogeneity in the parameters we chose to opt out of modeling autocorrelation and other time dependent error term patterns in the likelihood function thus we have made an effort to build a structural model that reasonably reflects consumer purchase behavior without requiring expensive computation currently there are developments in econometrics to approximate the computation of the valuation functions without sacrificing much accuracy when these methods are well developed we expect that structural models will become more commonplace in marketing

a simultaneous approach to the whether what and how much to buy questions consumer s purchase decisions of whether to buy what to buy and how much to buy are examined simultaneously based on a consumer utility maximization problem an unobservable threshold price about which a consumer pivots from nonpurchase to purchase can be deduced with any model specification the interrelationships between purchase decisions can be explicitly derived the model is applied to coffee purchasing data in addition by suppressing the nonpurchase options the model is compared with an alternative approach appearing in the marketing literature

commercial use of upc scanner data industry and academic perspectives the authors report the findings from an exploratory investigation of the use of upc scanner data in the consumer packaged goods industry in the u s the study examines the practitioner community s view of the use of scanner data and compares these views with academic research forty one executives from ten data suppliers packaged goods manufacturers and consulting firms participated in wide ranging in person interviews conducted by the authors the interviews sought to uncover key questions practitioners would like to answer with scanner data how scanner data is applied to these questions and the industry s perspective regarding the success that the use of scanner data has had in each area the authors then compare and contrast practitioners views regarding the resolution of each issue with academic research this produces a 2 2 classification of each question as resolved or unresolved from the perspectives of industry and academia along the diagonal of the 2 2 issues viewed as unresolved by both groups are important topics for future research issues deemed resolved by both groups are correspondingly of lower priority in the off diagonal cells industry and academics disagree these topics should be given priority for discussion information exchange and possible further research practitioners reported that scanner data analysis has had the most success and been most widely adopted for decision making in consumer promotions i e coupons trade promotions and pricing for example logit and regression models applied to scanner data have revealed very low average consumer response to coupons which has directly led to reduced couponing activity managers also reported high levels of comfort with and impact from analyses of trade promotions and price elasticities while industry views most of the issues in these areas to be resolved academic research raises concerns about a number of practices in common commercial use these include price threshold analysis and trade promotion evaluation using baseline and incremental sales in product strategy advertising and distribution management practitioners reported that the use of scanner data has had more limited development success and impact in the case of new product decisions scanner data use has been slow to develop due to the inherent limitations of historicaldata for these decisions and a heavy reliance on traditional primary research methods in advertising scanner data is widely analyzed with models but confusion among practitioners is very high due to controversies about methods e g what level of data aggregation is best and conflicting results in distribution and retail management scanner data use has tremendous potential but a mixed track record to date thus practitioners view the use of scanner data as unresolved for most issues in product strategy advertising and distribution this view is largely though not entirely consistent with academic research which has only begun to address many of the key questions raised by practitioners in light of the large number of unresolved issues and mixed record of scanner data use to date the authors offer aseries of specific recommendations for immediate and long term research priorities that are likely to have the greatest impact on commercial utilization of upc scanner data topics of immediate priority include price thresholds and gaps baseline and incremental sales base price elasticity competitive reactions measurement of advertising effects management of brand equity rationalization of product assortments and category management long term priorities include a greater emphasis on profitability versus sales or market share developing prescriptive models versus descriptive models and the need for industry standards

there is no aggregation bias why macro logit models work in this article we examine the aggregation properties of nested logit models to understand their exceptional macro level performance the problem of aggregating micro logit models involves integrating nonlinear functions of model parameters over a distribution of consumer heterogeneity the aggregation problem is analyzed using a mixture of analytic and simulation techniques with the simulation experiments using actual panel data to calibrate the distribution of heterogeneity we conclude that the practice of fitting aggregate logit models is theoretically justified under the following three conditions 1 all consumers are exposed to the same marketing mix variables 2 the brands are close substitutes and 3 the distribution of prices is not concentrated at an extreme value these conditions are frequently met in store level scanner data

investigating purchase incidence brand choice and purchase quantity decisions of households we develop a comprehensive utility maximizing framework to study the impact of marketing variables on the category purchase brand choice and purchase quantity decisions of households for frequently purchased packaged goods the model allows for dependence among the three decisions while ensuring that these decisions provide in combination the greatest possible utility to the household by accounting for variations in reservation prices and intrinsic brand preferences across households the modeling framework explicitly captures the effects of unobserved heterogeneity on all three purchase decisions the principal empirical finding from analyzing the a c nielsen data for the yogurt product category is that the substantive implications for the effects of marketing variables are sensitive to whether these effects are determined conditional or unconditional on a product category purchase our results show that reservation prices and intrinsic brand preferences vary across households and not accounting for these variations in the estimation could lead to biased estimates for the coefficients of the marketing variables a comparison of our results to those obtained from a nested logit model of purchase incidence and brand choice reveals that our proposed model performs better using both a formal statistical test as well as the criterion of predictive validity in a holdout sample of panelists further the purchase quantity model compares favorably with two alternative models of quantity choice in the validation sample

measuring consumer and competitive impact with elasticity decompositions abstract marketing investments are designed to change consumer behavior in ways that help goods compete in the marketplace previous research has focused on using elasticity decompositions to measure how these investments affect either consumer decision making or competing goods on the one hand decision based decompositions attribute the growth in own good demand to changes in the consumers decision making processes on the other hand unit based and share based decompositions attribute the same growth to either rivalrous or nonrivalrous sources the objective of this article is to provide a clear and accurate method that simultaneously attributes the growth in own good demand to changes in 1 consumers decisions 2 competitive demand and 3 competitive market share the author accomplishes this by settling some confusion about what the decision and share based decompositions mean by discussing how each of the decompositions are related to the others and by discussing the research questions th

price competition under stockpiling and flexible consumption abstract conventional wisdom suggests that the main effect of price promotion is on brand switching i e secondary demand however some recent studies demonstrate that the primary demand expansion effect can be considerably larger than previously believed a significant driver of this primary demand effect is consumer stockpiling in response to price promotions indeed experimental studies have shown that additional inventory on hand can lead to an endogenous increase in consumption the authors develop a model of price competition between firms in response to the stockpiling and subsequent consumption dynamics of consumers in this setting the flexible consumption effect causes more intense price competition deeper promotions and an increase in the frequency of promotions the authors use two years of scanner panel data from eight product categories and 4313 stockkeeping units to test three implications of the theoretical model they find strong support for each

the decomposition of promotional response an empirical generalization price promotions are used extensively in marketing for one simple reason consumers respond the sales increase for a brand on promotion could be due to consumers accelerating their purchases i e buying earlier than usual and or buying more than usual and or consumers switching their choice from other brands purchase acceleration and brand switching relate to the primary demand and secondary demand effects of a promotion gupta 1988 captures these effects in a single model and decomposes a brand s total price elasticity into these components he reports for the coffee product category that the main impact of a price promotion is on brand choice 84 and that there is a smaller impact on purchase incidence 14 and stockpiling 2 in other words the majority of the effect of a promotion is at the secondary level 84 and there is a relatively small primary demand effect 16 this paper reports the decomposition of total price elasticity for 173 brands across 13 different product categories on average we find that 25 of the elasticity is due to primary demand expansion i e purchase acceleration and 75 to secondary demand effects or brand switching thus while gupta s finding that the majority of promotional response stems from brand switching is supported the average magnitude of the effect appears to be smaller than first thought more important there is ample evidence that promotions have a significant primary demand effect the relative emphasis on purchase acceleration and brand switching varies systematically across categories and the second goal of the paper is to explain this variation as a function of exogeneous covariates in doing this we recognize that promotional response is the consumer s reaction to a price promotion and therefore develop a framework for understanding variability in promotional response that is based on the consumer s perspective of the benefits from a price promotion these benefits are posited to be a function of i category specific factors ii brand specific factors and iii consumer characteristics the framework is formalized as a generalized least squares meta analysis in which the brand s price elasticity is the dependent variable several interesting results emerge from this analysis category specific factors brand specific factors and consumer demographics explain a significant amount of the variance in promotional response for a brand at both the primary and secondary demand levels category specific factors have greater influence on variability in promotional response and its decomposition than do brand specific factors there are several instances where exogenous variables do not affect total elasticities yet significantly affect individual components of total elasticity in fact the lack of a significant relationship between the variables and total elasticity is often due to offsetting effects within two or more of the three behavioral components of elasticity this is particularly true for brand specific factors which typically have no effect on total elasticity yet have important effects on the individual behaviors there is some evidence to suggest that not all promotion related increases in primary demand are due to forward buying in some cases promotions appear to increase consumption we use these results to illustrate how category and brand specific factors work to drive primary and secondary demand elasticities in different directions in short this paper offers an empirical generalization of a key finding on promotional response how elasticities decompose across brand choice purchase incidence and stockpiling and new insights into factors that explain variance in promotional response these findings are likely to be of interest to researchers who are concerned with theory development and the generalizability of marketing phenomena and to managers who plan promotion campaigns

creating win win trade promotions theory and empirical analysis of scan back trade deals manufacturer trade promotion spending is second only to cost of goods sold as a profit and loss item yet manufacturers often lose money on these deals as a result of forward buying by retailers the search for more effective forms of trade promotion and the availability of scanners at cash registers has led to the emergence of a new type of trade deal the scan back that gives retailers a discount on unitssoldduring the promotion rather than on unitsbought we develop a theory to compare retailer pricing decisions and profitability under scan back and traditional off invoice trade deals we show that when the terms of the trade deal are identical retailers prefer off invoice trade deals and manufacturers prefer scan backs manufacturers can however redesign the scan back to leave the retailer weakly better off and leave themselves strictly better off using proprietary data from the beverage category we conduct an empirical analysis and find that during the promotion period scan back trade deals relative to off invoice deals 1 do not cause excess ordering and 2 generate higher retail sales through lower retail prices implications for researchers and managers are discussed

game theory and empirical generalizations concerning competitive promotions this paper offers the generalization that competitive promotions are mixed strategies first an empirical regularity is established that promotions are independent across competitors this regularity is then elaborated on in the context of a promotion game the promotion game is linked to observable outcomes and a classification of possible situations is developed in particular the classification includes the prisoners dilemma battle of the sexes and marketing models of promotion competition the evidence for the generalization comes from a variety of product markets spanning trade promotions retail price reductions and retail promotions such as advertised specials the product markets include coffee baby diapers toilet tissue saltines dishwashing fluid ketchup and detergents among others the data in some cases were from cooperating grocery chains and in others from iri scanner panels the evidence from extant research and from new analyses is presented each situation is identified as be

promotion effect on endogenous consumption over the years researchers have found that promotion makes consumers switch brands and purchase earlier or more however it is unclear how promotion affects consumption especially for product categories that are perceived to be versatile and substitutable in this paper we propose a dynamic structural model with endogenous consumption under promotion uncertainty to analyze the promotion effect on consumption this model recognizes consumers as rational decision makers who form promotion expectations and plan their purchase and consumption decisions in light of promotion schedule applying the proposed model to packaged tuna and yogurt we find that endogenous consumption responds to promotion as a result of forward looking and stockpiling behavior this is the first empirical paper that recognizes consumption as an endogenous decision variable and proposes a structural model to offer behavioral explanations on whether how and why promotion encourages consumption for product categories with flexible consumption