J. of the Acad. Mark. Sei. (2008) 36:359-377

DOI 10.1007/s 11747-007-0076-7

The dual role of price: decomposing consumers'reactions to price

Franziska Völckner

Received: 5 February 2007/Accepted: 22 August 2007/Published online: 25 September 2007© Academy of Marketing Science 2007

Abstract Price plays two distinct roles in consumers'evaluations of product alternatives: as a measure ofsacrifice and as ati informational cue. This article mergestwo streams of empirical research into the effects of priceon consumers' product evaluations by combining statedpreferences, obtained from conjoint measurement., with dataon self-reported measures in the form of beliefs or attitudes.It thus offers new, substantive insights into the dual role ofprice. Specifically., it differentiates between the informa-tional and sacrifice effects of price using a choice-basedconjoint approach and differentiates further among differentsubcomponents of these two main effects by combiningchoice-based measures with self-reported measures thatpertain to potential sources of the dual role of price (priceresponse drivers) and underlying consumer characteristics.Thus, this article presents a general procedure to quantifythe impact of the dual role of price on choice shares forproduct alternatives within a market simulation. Thisprocedure enables managers to simulate the choice shareeffects of changes in price response drivers, as well asmodifications in segmentation and targeting strategies thatinvolve changes in the levels of the price response driversand thus the levels of the informational and sacrificecomponents of the price response of demand.

Keywords Dual role of price • Informational effect •Sacrifice effect

F. Völckner ( X )Department of Marketing and Brand Management,University of Cologne, Albertus-Magnus-Platz,50923 Cologne, Germanye-mail: franziska.voelckner@uni-koeln.de

Introduction

Setting prices for products represents one of the mostcritical decisions for managers (e.g., Gijsbrechts 1993;Monroe 2003). Developing and monitoring appropriatepricing strategies requires information about consumers'reactions to price and, specifically, quantification of theprice response of demand, which is driven by—amongothers—two opposing effects: the sacrifice and the infor-mational effects of price (Rao and Sattler 2003).

The sacrifice effect of price, which stems from classiceconomic theory, represents the consumer's evaluation ofthe amount of money he or she must sacrifice to satisfyhis or her consumption needs. In this respect, pricegenerates disutility and negatively affects purchaseprobabilities (Erickson and Johansson 1985). However,consumers do not always choose the lowest pricedproduct in a category., even when the products areotherwise similar. One explanation for this behavior,supported by empirical evidence (Brucks et al. 2000;Dodds et al. 1991; Kardes et al. 2004; Rao and Monroe1989), argues that consumers infer quality informationfi-om price, such that higher prices indicate higher qualityand thus increase perceived utility (and vice versa), whichresults in a positive price response of demand. Theinformational effect of price also may extend to favorableprice perceptions, because higher prices can convey theprominence and status of the purchaser to other people.Understanding the dual role that price plays in consum-ers' evaluations of product alternatives is fundamental tomanagerial decisions, because varying levels of thesacrifice and informational effects provide the rationalefor different pricing strategies.

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360 J. of the Acad. Mark. Sei. (2008) 36:359-377

Empirical research into the effects of price on consum-ers' product evaluations consists of two streams. First,some studies consider quantitative, demand-based priceeffects, such as analyses of econotiietric data (e.g., priceelasticities of demand), transactions data (e.g., scannerpanel data. Vickrey auctions, BDM-type procedures), orstated preferences obtained from conjoint measurement.These studies offer valuable insights into consumers' pricereactions on a quantitative level. For example, meta-analyses of price elasticities quantify the total effect ofprice on demand (Bijmolt et al. 2005; Tellis 1988), andscanner panel data (e.g., Erdem et al. 2005; Stiving andWiner 1997) reveal that the informational effect of priceinfluences sales. However, these studies either fail todecompose the total effect of price into its negative andpositive components (e.g., studies using stated preferences)or—if they do disentangle the two effects—do notdifferentiate ftirther among subcomponents such as prestigesensitivity, hedonistic effects, or transaction utility effects(e.g., studies using scanner panel data). However, it iscrucial to differentiate explicitly among these subcotnpo-nents to understand the reasons consumers respond posi-tively or negatively to price cues.

Second, other studies analyze self-reported measures inthe form of beliefs or attitudes to offer insights intopotential sources of the dual role of price by investigatingprice-related constructs (e.g., perceived allocative effects,price-quality schema, prestige sensitivity), consistent with anegative or positive perception of price, as well as byexploring consumer characteristics related to these negativeor positive perceptions (e.g., Ailawadi et al. 2001;Lichtenstein et al. 1993; Teas and Agarwal 2000). Howev-er, these studies also suffer a limitation; they fail to analyzethe impact of price-related constructs on quantitative,demand-based estimates, such as product choice and marketshare. Instead, they analyze the dual role of price and itspotential sources by relying exclusively on beliefs orattitudes that result from respondents' price perceptions.However, quantifying the dual role of price and its under-lying sources in terms of the effects on demand (e.g.,product choice, choice/market share) is crucial, becausevarying levels of these estimates coincide with varyinglevels of consumers' willingness to pay and thus varyingchoice/market shares. Beliefs and attitudes simply cannotcapture such effects.

Therefore, this article analyzes the effects of the dualrole of price and its sources on demand to extend existingliterature in two important ways. First, I merge the twoempirical research streams regarding the effects of price onconsumers' product evaluations by combining statedpreferences obtained from conjoint measurement with dataon self-reported measures in the form of beliefs or attitudes.

Using a choice-based conjoint approach, I differentiatebetween the informational and sacrifice effects of price in alab setting; then, using self-reported measures, I differen-tiate ftirther among different sources/subcomponents ofthese two main effects. I test the reliability and validityof this procedure and apply the proposed combination ofstated preferences with self-reported measures in anempirical setting to gain new, substantive insights into thedual role of price and demonstrate the advantages of thisproposed approach^particularly with regard to managerialinsights—compared with previous methods.

The derived conjoint utilities for the product attributes(including price) reflect their impact on consumers' productevaluations and choices, respectively, which enables calcu-lations of cboice shares for specific product alternativeswithin a market simulation; in other words, they are muchcloser to an economic measure of price effects than reportedbeliefs or attitudes and are directly comparable, unlike self-reported measures. 1 combine the proposed choice-basedmeasures of the sacrifice and informational effects withself-reported measures that indicate potential sources of thedual role of price (i.e., price response drivers). Thus, Iquantify the sources of the dual role of price and provideinsights into their relative importance for consumers'product choice decisions.

In comparison with previous approaches that considereither quantitative, demand-based price effects or self-reported measures, but not a combination of both, theproposed combination of stated preferences obtained fromconjoint measurement with self-reported measures providesnew insights into the dual role of price. Specifically, 1 canoffer a general procedure to quantify the impact of priceresponse drivers on choice shares for different productalternatives in a market setting. This procedure enablesmanagers to simulate the choice share effects of changes inthe price response drivers and consequently conduct "what-if ' analyses. I demonstrate an exemplary what-if analyiisby simulating choice share effects in the specific marketsetting of hotel offerings. Previous studies simply are notable to provide such infonnation to managers, because theydo not combine the aforementioned research streams.

Second, I examine associations between the identifiedprice response drivers and particular consumer character-istics, which gives marketers a means to design appropriatecommunication and pricing programs that account for thedivergent roles price plays in different consumers' productchoices. Although prior research addresses consumercharacteristics (as predictors of consumers' price percep-tions), this study offers a new and managerially relevantperspective on these characteristics. Specifically, theproposed procedure enables managers to simulate choiceshare effects when they modify segmentation and targeting

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J. of the Acad. Mark. Sei. (2008) 36:359-377 361

Strategies and thus alter the levels of the identified priceresponse drivers and the informational and sacrificecomponents of the price response of demand. Previousstudies cannot provide these insights because they do notcombine quantitative, demand-based price effects with self-reported measures pertaining to price response drivers andunderlying consumer characteristics.

The remainder of this article is organized as follows: Thefollowing section presents the conceptual framework. Next.1 describe the empirical study design, followed by thestudy's results. I conclude with a discussion of the findingsin terms of their managerial implications and present anoutline for nirther research.

Conceptual model

Figure 1 represents an overview of the conceptual model,which I analyze in two stages. First, I decomposeconsumers' price responses into informational and sacrificeeffects within a choice-based utility-formation framework.Second, I combine these demand-based measures with dataabout the potential sources of the dual role of price (priceresponse drivers) and provide insight into the associationsbetween price response drivers and consumer character-istics. I ftirthermore test the reliability and validity of thechoice-based conjoint methodology by addressing the test-retest reliability and predictive, face, and nomologicalvalidity. Finally, I present a general procedure thatquantifies the impact of (1) the sacrifice and informationalcomponents of consumers' price responses, (2) price

response drivers, and (3) their underlying consumercharacteristics on choice shares for different productalternatives in a market setting.

Informational and sacrifice components of priceresponse of demand

The sacrifice effect of price refers to price as a monetaryconstraint in purchase decisions. That is, price is the "give"component or sacrifice a person must make to obtain thebenefits generated by the bundle of attributes that con-stitutes the product; it limits how much the person hasavailable for spending on other products. The magnitude ofthe sacrifice effect therefore should relate inversely to theamount of budget the consumer retains after purchasing theproduct (Rao and Sattler 2003; Urbany et al. 1996) anddisappear if the product is free (e.g., sweepstakes prize, freesample in a sales promotion). But the informational effectof price remains the same, regardless of whether a personreceives the product for free (e.g., Mitgrom and Roberts1986), assuming that the consumer knows the market priceof the free product (which equals the price of the non-freeproduct).

According to this reasoning, Gautschi and Rao (1990)present a methodology to estimate the opposing effects ofprice separately in a conjoint analysis setting by collectingdata from two different scenarios. In the first scenario(budget constraints, full price to pay), respondents mustcomplete a conventional evaluation of product alternativesin regular purchase conditions ("Assume you have to paythe full price shown"). This scenario measures the total

Figure I Conceptual model. Consumer characteristics Sources of the dual role of price(price response drivers)

Consumers* price response(with ICPR > 0 and SCPR < 0)

Informational componentof the price response ofdemand (ICPR) [price-

specific conjoint utilities]

Sacrifice component of theprice response of demand

(SCPR) [price-specificconjoint utilities]

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362 J. ofthe Acad. Mark. Sei. (2008) 36:359-377

effect of price, because it does not distinguish betweensacrifice and informational effects. In the second scenario(without budget constraints, sweepstakes), the samerespondents view the same stimuli but are instructed thata third party will pay the shown price ("Assume you don'thave to pay for the product. You won the product in asweepstakes. Selling the prize or giving it away is notpossible"). Getting the product for free should eliminatethe sacrifice effect of price, so if price still exhibits a role,that role consists of informational effects that indicatequality or prestige.

Gautschi and Rao (1990) show that the sacrifice effect ofprice can be calculated at the individual level as the dif-ference between the total and infonnational effects of price.^^ ßh,Pricejotat denotes the individual price coefficient (i.e.,price-specific utility) obtained in the first scenario (budgetconstraints) and ßh.Prk-ejnf» is the price coefficient obtainedin the second scenario (no budget constraints), ßh.pncejotat~ßhj>ricejnfo equals the sacrifice effect {ßh,price_sacrifice), and

ßh,PHccjnfo reflects the informational effect of price.Studies by Gautschi and Rao (1990), Rao and Sattler

(2003), and Völckner and Sattler (2005) provide empiricalevidence that a conjoint-based approach can decompose theprice response of demand {i.e., price-specific conjointutility that measures the total effect of price on productchoices) into its positive and negative components, butnone ofthese studies investigates relationships between thesources of the dual role of price and the demand-basedestimates of the two opposing price effects. Nor do thesestudies offer a comprehensive test of the reliability andvalidity of the methodology.

I adopt this basic methodology and apply it to a choice-based conjoint setting that reveals preferences by examin-ing discrete choice behavior (Haaijer and Wedel 2003). Theestimated conjoint utilities for the product attributes(including price) reflect their impact on consumers' productchoice. Therefore, this methodology enables us to deter-mine quantitative, demand-based estimates of the twoopposing price effects.

Sources of infonnational and sacrifice components of priceresponse of demand (price response drivers)

According to cue utilization theory, consumers inferinfonnation from product-related attributes, and pricerepresents one of the most important marketplace cues(Gijsbrechts 1993; Rao and Monroe 1989; Richardson et al.1994). Research evidence in this context suggests threepotential sources of the informational component ofconsumers' price responses (e.g., Rao and Monroe 1989;Amaldoss and Jain 2005; Dubois and Laurent 1994): price-quality beliefs, prestige effects, and hedonistic effects. Inaddition, classic economic theory and Thaler's (1985)

transaction utility theory suggest that allocative effectsand transaction utility may provide two potential sources ofthe sacrifice component. ,

Price-quality beliefs The relationship between price andperceived quality has received significant attention in pricingresearch. Using price as a surrogate for product qualityusually occurs when the quality evaluation is uncertain,which makes the purchase risky. The use of a price cue toinfer product quality varies across situations and products(Erdem 1998; Urbany et ai. 1997), and some consumers aremore likely than others to use price as a general indicator ofquality across situations and products (Lichtenstein et al.1993). Because high price is perceived to indicate higherquality, it positively affects purchase probability.

Prestige effect.^ The purchase, use, display, and consump-tion of goods and services that bear high prices provide ameans to gain social status (Mason 1981). Therefore,consumers also may perceive price as a surrogate indicatorof prestige (e.g.. Lichtenstein et al. 1993), which againresults in a positive impact of price on purchase probability.For example, some consumers purchase an expensive carnot because of their quality perceptions per se but becauseof their perception that the purchase will signal a latentvariable, such as status or wealth, that others cannotobserve directly (Amaldoss and Jain 2005).

Hedonistic effects A positive impact of price on purchaseprobability also may derive from the feelings of pleasureand excitement associated with consuming higher pricedproducts (Dubois and Laurent 1994), as theorized byliterature on hedonistic consumption. Hedonistic consump-tion designates those facets of consumer behavior that relateto pursuing emotional responses associated with using aproduct, such as pleasure, excitement, arousal, good feel-ings, and fun (Hirschman and Hoibrook 1982). In tillscase, favorable perceptions of higher prices are based onwhat the price cue signals to the purchasers in terms of theirown thoughts and feelings associated with using theproduct. They prefer higher prices as a means of self-affirmation and to satisfy their egocentric desires to treatthemselves.

Allocative effects The classical model derived from theeconomic theory of consumer behavior postulates that aconsumer maximizes his or her utility by allocating alimited budget across alternative products (Nagle 1984).The higher the price for a particular product, the less moneybecomes available for spending on other products (Ericksonand Johansson 1985). The allocative effect thus becomes afiinction ofthe purchase price when the utility derived fromthe product remains constant. Consumers who are sensitive

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to the allocative role of price likely prefer low prices;higher prices are associated with strong allocative effectsand thus negatively affect purchase prohability among theseconsumers.

Tran.saction utility in addition to the allocative effect.Thaler's (1985) transaction utility theory suggests that thesacrifice component may be driven by the transaction utilityof the purchase. The concept of transaction utility capturesconsumers' reactions to the actual price relative to theirprice expectations and thus represents the incrementalutility associated with a "good deal," which can create asense of being a smart shopper who pays a low price for aparticular item and thus makes the consumer feel proud orcompetent (Schindler 1989). Thaler's transaction utilityeffect suggests that a notably low or high price (relative tothe expected price) affects willingness to buy beyond theinfluence of the allocative role of price (Lichtenstein et al.1990; Urbany et al. 1997). Empirical support for this effectindicates, for example, that a price discrepancy tenn thatcaptures the difference between the expected and actualprice contributes signiftcantly to brand choice predictions(Katyanaram and Winer 1995).

Interaction effects Brucks et al. (2000) note that themeaning of quality is multidimensional and that prestige,or how well the product communicates superiority to thepurchaser and his or her relevant social groups, representsan important quality dimension. Consumers use price andbrand name much more frequently when evaluatingprestige than when evaluating other quality dimensions(e.g., ease of use, durability). I therefore follow Bruckset al. (2000), consider prestige a quality dimension, andpostulate a positive interaction between price-qualitybeliefs and prestige effects. Analogously, hedonic productperformance might represent an important quality dimen-sion for some consumers, which suggests a positiveinteraction between price-quality beliefs and hedonisticeffects. Finally, the perceived emotional (hedonic) valueassociated with using a product might result from not onlypurchasers' egocentric desires to treat themselves but alsothe arousal associated with displaying wealth and status,which suggests a positive interaction between hedonisticand prestige effects.

On the basis of this reasoning, 1 offer the followinghypotheses:

Hi: Price-quality beliefs relate positively to the informa-tional component of the price response of detnand.

H2: Prestige effects relate positively to the informationalcomponent of the price response of demand.

H3: Hedonistic effects relate positively to the informa-tional component of the price response of demand.

H4: Allocative effects relate negatively to the sacrificecomponent of the price response of demand, such thatthe stronger the perceived allocative role of price, themore negative the sacrifice component of consumers'price response becomes.

H5; Transaction utility effects relate negatively to thesacrifice component of the price response of demand,such that consumers who attach greater value to thetransaction utility of a purchase exhibit a stronger(i.e., more negative) sacrifice component in theirprice response.

Hfii The positive effect of price-quality beliefs on theinformational component of the price response ofdemand increases as the level of prestige sensitivityincreases.

H7: The positive effect of price-quality beliefs on the in-formational component of the price response ofdemand increases as the level of hedonism increases.

Hg: The positive effect of prestige sensitivity on the infor-mational component of the price response of demandincreases as the level of hedonism increases.

The tests of the derived hypotheses regarding therelationships between the two price response componentsand the sources of this dual role offer particularlyinteresting results with regard to the nomological validityof the proposed choice-based conjoint methodology. Spe-cifically, a method has nomological validity if it behaves asexpected with respect to some other construct to which it istheoretically related (Churchill 1995).

The role of consumer characteristics

To gain insight into whether the five sources of informationaland sacrifice price components lead to distinct behaviorpatterns, and thereby infonn segmentation and targetingefforts, I examine the associations between the priceresponse drivers and consumer characteristics. The cost-benefits framework, derived from the concept of perceivedvalue, provides a theoretical framework for generatingparticular consumer characteristics for the empirical study,because consumers' perceptions of value represent fiinda-mental determinants of product choice (Agarwal and Teas2001). Perceived value refers to consumers' overall assess-ments of product utility, based on their perceptions of whatthey received and what they sacrificed, so value representsa trade-otT between the salient benefit and cost componentsassociated with purchasing a product.

The benefit components include product quality andother prominent, high-level abstractions, such as prestige/image enhancement and convenience. Cost componentsinclude monetary price and nonmonetary costs, such assearch, switching, and perceived enor costs (Gijsbrechts

364 J. of the Acad. Mark. Sei. (2008) 36:359-377

1993; Zeithaml 1988). I expect these benefits and costs tocreate associations between consumer characteristics andthe price response drivers. Because most of these relation-ships have been theoretically derived in prior literature(e.g.. Lichtenstein et al. 1993; Suri and Monroe 2003;Urbany et al. 1996; Teas and Agarwal 2000), I abstain froman explicit, a priori discussion of the potential relationships;rather, a detailed discussion of the statistically significantrelationships appears in "Results."

By defmition, product quality is important for consumerswho are quality conscious, and overall, it represents themost salient "get" component of a purchase transaction,because it reflects the consumer's judgment about aproduct's cumulative excellence. I conceptualize qualityconsciousness as the degree to which a consumer focuseson buying high-quality products (Ailawadi et al. 2001)

Prestige/image enhancement is relevant to consumerswho embody a high motivation to conform to peer expect-ations. Theoretical and empirical results support its inclu-sion in this study; for example. Vigneron and Johnson ( 1999)discuss the role of social approval and image enhancementin consumers' price perceptions, and Amaldoss and Jain(2005) highlight the effect of social needs, such as a desirefor uniqueness and confonriity, on demand pattems forconspicuous consumption goods.

Convenience relates to consumers' need for simplifica-tion of cognitive tasks, which allows for less extensiveinformation processing and greater reliance on easilyavailable diagnostic cues to simplify the buying process(Chatterjee and Suman 1998). Relying on the price cue pro-vides convenience and saves time by facilitating shoppingacross several categories.

The monetary price, which represents the amount ofeconomic outlay required by a given purchase transaction,is particularly relevant to consumers who are priceconscious and deal prone and who perceive themselves assubject to fmancial constraints or as price mavens. Priceconscious consumers generally want to pay low prices, aresensitive to price differences, and set internal limits on whatthey are willing to pay (O'Neill and Lambert 2001). Dealproneness refers to an increased propensity to respond to apurchase offer predominantly because it is in deal form(Lichtenstein et al. 1990). Deal-prone consumers seek topay reduced prices, and finding a lower price for a parti-cular item causes them to feel proud, smart, and competent.Financially constrained consumers focus on paying priceswithin their budget, and empirical and theoretical evidenceindicates that perceived budget constraints play importantroies in motivating consumers' search for low prices(Urbany et al. 1996). Finally,/;/7ce mavenism, an adaptationof the tenn "market mavenism" (Feick and Price 1987),reflects the desire to be informed about marketplace prices

and transmit that information to other people (Lichtensteinet al. 1993). Price mavens gather price infonnation, initiateshopping-related discussions, and respond to requests forinfonnation about marketplace prices and places to shop forthe lowest price.

With regard to costs, switching costs in particular arehigh for brand loyal consumers. Strong theoretical andempirical evidence supports the inclusion of brand loyaltyin this study; for example, Kirmani and Rao (2000) discussthe use of signals, such as brand name and price, to copewith imperfect product quality infonnation. Brucks et al.(2000) empirically find that consumers search for brandname and price infonnation much more fi^quently whenevaluating the prestige rather than the quality of thephysical attributes of products.

A major component of search costs refers to consumers'perceptions of the value of their time per unit of search efíbrt(Srinivasan and Ratchford 1991 ). Search costs thus relate totime pressure, such that consumers facing time constraintstend to use easily recognizable cues, including price, tofacilitate their shopping efforts (Suri and Monroe 2003).

Finally, risk is the consumer's subjective assessment ofthe financial, psychological, physical, functional, and/orsocial consequences of making an incorrect purchase(Murphy and Enis 1986). Evidence suggests that greaterrisk or consequences of product failure enhance pricereliance (Peterson and Wilson 1985; Zeithaml 1988). Itherefore include consumers' propensity to rely on the pricecue to cope with imperfect information (i.e., risk).

Previous research addresses these consumer character-istics. However, this research investigates these character-istics in a new and managerially relevant way. Specifically,I present a genera! procedure that can enable managers tosimulate choice share effects of modifications in segmen-tation and targeting strategies that involve changes in thelevels of the price response drivers and thus the levels ofthe informational and sacrifice components of the priceresponse of demand.

Data and research design

Sample

I collected data in a large Western European country using aconsumer survey of an online access panel that mirrors theoverall population. Respondents received an e-mail invita-tion to fill out an Internet questionnaire. In addition, allpanel participants are heads of households, are at least18 years of age, and have some experience in the productcategory investigated in this study. A total of 461 adultsparticipated in the survey.

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Choice-based conjoint tasks and multi-item measures

The questionnaire required respondents to participate inseveral discrete-choice tasks and answer rating-scaled ques-tions. Respondents completed ten choice tasks in the firstscenario (budget constraint) and ten choice tasks in thesecond scenario (no budget constraint), including tworeliability tasks, one in each scenario, that I use to test thereliability of respondents' answers. The cover story indicatedthat respondents planned a weekend trip to a major Europeancity, whose details had already been arranged, except that therespondents had to book a hotel room from a selection ofdifferent hotels. Each choice set contained three hotels (i.e.,conjoint stimuli), as well as a no-purchase option. The hotelswere middle-class hotels and differed in price (60.00, 90.00,and 120.00€), room size (regular, spacious), location (towncenter, near town center), and availability of health/fitnessarea (yes, no). All rooms had an en suite bathroom. A pretestwith 20 non-student subjects and a comprehensive review ofhotel offerings on www.hrs.com (an online hotel reservationservice) indicated the chosen attributes and attribute levelsare the most important items for product evaluation, as well

as distinguishing factors among products (Alpert 1971). Todetermine the levels of the attributes, I also draw on realmarket conditions. The creation of the stimuli (i.e., hotelaltematives) and conjoint choice sets employs a computer-generated design that accounts for the design principles oforthogonality, minimal overlap, and level balance (Huberand Zwerina 1996). Specifically, I use the Sawtooth designmodule to generate a randomized design that applies thecomplete enumeration option (Orme 1999). This option con-siders all possible stimuli and chooses each to produce themost nearly orthogonal design for each respondent. The stimuliwithin each task are as different as possible, and each attributelevel appears an approximately equal number of times.

In addition to the choice-based conjoint task, the surveyincludes multi-item scales for each price response driver andpsychographic correlate, measured on seven-point scalesfrom "strongly disagree" to "strongly agree," such thathigher scores indicate higher construct levels. Appendix 1provides the items associated with all the constructs usedin the study, many of which come directly or in modifiedform from prior studies (for details, see Table 1). 1 pretestall the scales with 25 respondents.

Table 1 Constructs and reliability statistics

Construct

Price response drivers''

Price-quahty beliefs

Prestige effectsHedonistic effectsAllocalive effects

Transaction utility

Consumer characteristics'^Quality consciousnessMotivation to conformNeed for simplitlcation

of cognitive tasks

Price consciousness

Deal proneness

Financial constraintsPrice mavenism

Brand loyalty

Time pressure

Price reliance

Cronbach's

alpha

Ü.7590.811

0.9160.878

0.719

0.804

0.8550.700

0.846

0.782

0.8870.898

0.914

0.7800.921

Construct

reliability

0.629

0.682

0.7780.710

0.719

0.717

0.6950.676

0.741

0.637

0.7210.831

0.764

0.532

0.803

Number

of items

3

343

3

343

2

3

33

3

2

3

Factor

0.688

0.7130.9270.9560.739

0.824

0.7880.624

0.824

0.6850.74]0.902

0.856

0.7200.836

loadings*

0.7780.689

0.9240.742

0.663

0.817

0.7560.842

0.891

0.9020.8460.861

0.907

0.8900.891

0.685

0.9360.6730.823

0.662

0.658

0.7530.559

0.6700.9840.961

0.886

0.949

0.919

0.802

Literature for

scale items

Peterson and Wilson (1985)

Lichtenstein el ai. (1993)--

Urbany et al. (1997),Grewal et al. (1998)

Ailawadi et al. (200!)

Bearden étal. (1989)-

Darden and PerTeault (1976).Slool et al. (2005)

Lichlenstein et al. (1993)

Urbany et al. (1996)Feick and Priée (1987),

Lichtenstein et al. (1993)Ailawadi et al. (2001).

Wood (2004)Hawes and Lumpkin (1984)

-

CFI Confinnatory fit index; TU Tucker-Lewis index, RMSEA root mean squared error of approximation" Chi-square/i//= 1.280, CFI-0.960, TLI-.95O. RMSEA (tesi of close m)=0.026 (p=1.000)^Chi-square/íí/=1.621. CFI=0.969. TLI=0.962, RMSEA (lest of close fit)=0.039 (;;-0.999)*All factor loadings significant at/)<O.OI

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Results

From the collected choice data, I obtain individual-levelestimates of the two components of consumers* priceresponses with a hierarchical Bayes model (Arora and

Huber 2001) that contains two levels. At the higher level, amultivariate normal distribution describes respondents'partworths. At the lower (i.e., individual) level, given arespondent's partworth, I derive individual choice proba-bilities in standard logit form (AUenby and Lenk 1994):

Plu =

ßNP.h • XNP,i + (1 ~ XNP.i) • ( E E ßhj,\jJM

(1)

h,i'-

where

ßhj.m'- parameter (partworth) for the mth level of theyth attribute for consumer /i,parameter (partworth) for the effect of pricelevel m for consumer A,'value of the mth level of the yth attribute ofproduct Í,

price level m of product i,choice probability of product Í forconsumer A,parameter (panworth) for the no-purchaseoption for consumer /i,binary variable indicating if selectedalternative / is the no-purchase option,

1, if i = no — purchase option.0 else.

index set of products in choice set a,index set of consumers,index set of products,index set of attributes without price, and

Mj'. index set of levels for theyth attribute.

The hierarchical Bayes estimation method proceeds in aniterative manner and recursively generates draws of themodel parameters, I therefore must ensure that theprocedure is stationary prior to retrieving estimates. Time-series plots of the root-likelihood values show that theprocess converges after a few thousand iterations, but I usea total of 10,000 preliminary iterations and 5,000 subse-quent iterations to generate parameter estimates.

I:

Depending on whether the estimation process uses choice data of thebudget constraint or unconstrained scenario, it reveals the total effectof price or the informational cotnponent of consumers' priceresponses, respectively.

The derived partworth utilities retlect influences onconsumers' product choices. Using the choice data of thebudget constraint scenario in the estimation process gen-erates estimates for the total effect of price on demand,whereas the choice data from the unconstrained budgetscenario yield partworths that reveal the informationalcomponent of the price response of demand (ICPR). Thedifferences between the individual price partworthsobtained in each scenario provide the sacrifice componentof the price response of demand (SCPR).

Reliability and validity of the choice-basedconjoint approach

In this section, I elaborate on the test-retest reliability,predictive validity, and face validity of the applied choice-based conjoint methodology. However, because testing fornomological validity requires estimating a structural modelthat represents the hypothesized relationships, which isclosely interwoven with the analysis of the price responsedrivers and consumer characteristics, I present the resultsregarding nomological validity in the subsequent section.

Test-retest reliability To measure reliability, I consider theagreement between respondents' choices in the first andtenth choice tasks, because the latter is a replication of thefirst, and in the eleventh and twentieth choice task, becausethe latter is a replication of the eleventh task (Ghiselli et al.1981). I exclude those subjects who responded differentlyto both reliability tests to minimize bias by random choicebehavior within the parameter estimation. Therefore, Ieliminate 44 from the sample of 461 respondents. Thereliabilities for the remaining 417 respondents are 87.05%(priee-to-pay scenario) and 85.13% (sweepstakes scenario).Therefore, each scenario (i.e., with or without budgetconstraints) has available 3,753 choices (9 choice tasks x417 respondents) for estimation.

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J. ofthe Acad. Mark. Sei. (2008) 36:359-377 367

Total effect of price on demand(partworths)

147

10

60.00 90.00 120.00

Price (Euro)

Partworths"' StandardPrice (mean) deviation

Informational component ofconsumers' price responses

(partworths)

Sacrifice component ofconsumers' price responses

(partworths)

-2

-61

-10

• 1 - t .

60.00 90 00

Price (Euro)

120.00 60.00 90.00

Price (Euro)

120.00

Partworths*" StandardPrice (mean) deviation

Partworths^* StandardPrice (mean) deviation

60 Euro

90 Euro

120 Euro

Price range

60-90 Euro

90-120 Euro

60-120 Euro

5.31

1.49

-6.80

Slope

-0,13

-0.28

-0.20

2.75

0.68

2.88

Standarddeviation

0.09

0.11

0.09

60 Euro

90 Euro

120 Euro

Price range

60-90 Euro

90-120 Euro

60-120 Euro

-100

.49

.53

.96

Slope

0.07

0.02

0.04

1.62

0.47

1.49

Standarddeviation

0.06

0.05

0.05

60 Euro

90 Euro

120 Euro

Price range

60-90 Euro

90-120 Euro

60-120 Euro

6.

0.

-7

81

96

.77

Slope

-0,20

-0.29

-0.24

2.96

0.74

3.08

Standarddeviation

0.10

0.11

0.10

a) Within each attribute, the partworthsFigure 2 Box plots of the parameter estimates.

sum to zero because ofthe use of effects coding (Omiel999).

Predictive validity To measure predictive validity, I exam-ine the extent to which a model based on the conjointutilities estimated through specific subsamples of choicetasks correctly predicts observed choice behavior in aholdout task (i.e.. choice task not used for parameterestimation). I apply the first choice transformation rule topredict individual choices, fora total of 2x9 holdout choicetasks.^ The first choice rule assumes each respondentchooses the profile that exhibits the highest utility,independent ofthe relative strength of his or her preference

^Respondents completed nine choice tasks in the first scenario andanolher nine in the second scenario (excluding reliability tests). 1 omitone choice task from parameter estimation, calculate model parameterson the basis of the remaining eighl choice tasks, predict individualchoices for the holdout task, and compule the resulting hit rate for eachofthe two scenarios. Thus, I obtain nine hit rates forthe ftill-price-to-payscenario and anolher nine hit rates for the sweepstakes scenario.

within the choice set. I draw on the hit rates to verifywhether respondents' observed choices equal their pre-dicted choices (Huber et al. 1993) and find that the mean hitrates are satisfactory: 85.47% for the full-price-to-payscenario and 81.25% for the sweepstakes scenario.

Face validity! For this measure, I examine the results ofthemanipulation check, which consists of respondents' self-reported perceptions ofthe sacrifice effect of price when theydo not face a budget constraint (sweepstakes scenario):"Even if I win my hotel accommodation forthe weekend tripin a sweepstakes, I perceive price as a measure of economicoutlay that must be sacrificed in order to utilize theaccommodation" (seven-point scale, l=strongly disagree,7^strongly agree). In total, 91.9% of respondents rated theitem 3 or lower, and 95.2% rated it 4 or lower (mean rating:1.31). The manipulation check thus indicates that thescenario successfully eliminates the sacrifice effect of price.

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368 J. of the Acad. Mark. Sei. (2008) 36:359-377

Furthermore, I examine whether the signs of the estimatedparameters for the informational and sacrifice components(i.e.. estimated conjoint utilities) are in the expecteddirection. Figure 2 summarizes the estimation results. Ailprice-level partworths (i.e., price-specific conjoint utilities)show the expected direction, because respondents' price-level partworths decrease as the price increases in the iull-price-to-pay scenario and increase as the price increases inthe sweepstakes scenario. In other words, the order of pricepreference changes from a preference for low prices in thefirst scenario (total effect of price) to a preference for highprices in the second, sweepstakes scenario (ICPR). The boxplot to the far right in Fig. 2 shows the resulting SCPR.which also exhibits the expected direction, in that the price-level partworths decrease as the price increases.

I also test whether the differences between the price-level partworths are significant by using paired Student'sMests. In all three settings—total effect of price, informa-tional component, and sacrifice component—the partworthsare significantly different (p<0.00\) for each price level.The same is true for the slopes in Fig. 2. I calculate theslopes between the three price-level partworths for eachrespondent to obtain appropriate measures of ICPR andSCPR, then use these measures in the subsequent analyses.

Figure 3 Estimated LISREL

framework.Consumer characteristics

• Qualiiy consciousnessMotivation to conformNeed for simplificationof cognitive tasksPrice consciousnessDeal pronenessFinancial constraintsPrice mavenismBrand loyaltyTime pressurePrice reliance

In summary, the tests suggest a high degree of reliability,predictive validity, and face validity of the choice-basedconjoint approach and estimates. :

Structural models for the infonnational and sacrificecomponents of price response

In this section, 1 investigate the relationships between thetwo price response components and their drivers, elaborateon the nomological validity of the choice-based conjointapproach, and provide insight into the associations betweenprice response drivers and consumer characteristics. I useLISREL software (Jöreskog 1982) to estimate the proposedmodels within a maximum likelihood estimation frame-work, which assumes the approximate normality of the datafor model estimation and testing. Multivariate tests ofnormality based on skewness and kurtosis of the observedvariables indicate the data are approximately normal (Chouand Bentler 1995). The estimated LISREL framework,depicted in Fig. 3, underscores the substantive insights ofthe proposed approach compared with previous methods.Previous work considers either quantitative, demand-basedprice effects (right-hand side of Fig. 3) or self-reported

Price response drivers Consumers' price response(with ICPR > 0 and SCPR < 0)

Results for measuremenl models of constructs (with allinterfactor covariances freely estimated): Table 1

Results for structural model: Table 2

Quality consciousnessMotivation to conformNeed for simplificationof cognitive tasksPrice consciousnessDeal pronenessFinancial constraintsPrice mavenismBnmd loyaltyTime pressurePrice reliance

^ ^Allocative

effects-^

^Transaction

utility- ^ ^ - ^ / j

111

SCPR

Results for measurement models of constructs (with allinlcrfactor covariances freely estimated): Tab!e I

( Results for structural model: Table 2

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J. of the Acad. Mark. Sei. (2008) 36:359-377 369

measures pertaining to potential sources of the dual role ofprice and consumer characteristics (left-hand side of Fig. 3).By combining both research streams, and thereby disen-tangling the dual rote of price into several subcomponents(i.e., price response drivers), this research enables analysesof the choice share effects of changes in the price responsedrivers, as well as of modifications in segmentation andtargeting strategies that alter the levels of the identifiedprice response drivers.

Measurement models of the price response drivers andconsumer characteristics I evaluate the measurement scalesof the latent constructs prior to estimating the structuralrelationships among the constructs and provide the reliabil-ity statistics in Table 1. Cronbach's alphas vary between0.80 and 0.92. Furthermore, I specify two confirmatoryfactor analysis models-one for the 16 items related to thefive price response drivers and another for the 29 itemsrelated to the ten psychographic correlates. I do not allowcross-loadings for either model, nor do I allow measure-ment errors to covary. All interfactor covariances are fi-eelyestimated. The fit of both models is very good, even ac-cording to the high standards of measurement qualityimposed by these conditions. The robust comparative fitindex is 0.960 for the measurement model of the five driversand 0.969 for the consumer characteristics measurementmodel. Similarly, the root mean squared error of approxi-mation is 0.026 for the former and 0.039 for the latter.

Loadings of all items on their factors are strong andsignificant. The magnitude of their i-statistics ranges fix)m8.25 to 31.82. On average, 75.78% of the variation in anitem is explained by its factor, and the magnitude ofinterfactor correlations ranges fi-om 0.011 to 0.417 (seeAppendix 2 for details). Finally, I conduct a test for con-struct discriminant validity using Fomell and Larcker's(1981) procedure, which suggests that a construct possessesdiscriminant validity if the average variance extracted by itis greater than the shared variance (i.e., squared interfactorcorrelation) with other latent constructs. Each constnictsatisfies this condition, which provides evidence of dis-criminant validity among all constructs.

Results for informational and sacrifice components of priceresponse of demand (ICPR and SCPR) Tables 2 and 3present the standardized parameter estimates., model R^,and fit statistics for the ICPR and SCPR models. All fitindicators fall within a satisfactory range, which indicatesthat the models fit well with the data (Byme 2001).

The price response drivers are statistically significant andhave the expected sign, in support of H| 5. as well as thenomological validity of the applied choice-based conjointmethod. The price response drivers explain 21.5% of thevariation in the ICPR and 28,7% of the SCPR variation. Inote that the explanatory variables are self-reported measuresof the three drivers, whereas ICPR and SCPR are tneasuredon the basis of observed choice behavior within a choice-based conjoint setting; the /?" is notably good comparedwith findings in other studies that attempt to explainobserved behavior on the basis of self-reported measures(e.g.. De Wulf et al. 2003; Pennings and Smidts 2000).

Price-quality beliefs are the most important source ofICPR, followed by the prestige value of high-pricedproducts and hedonistic effects. The strong effects ofprice-quality beliefs should be common in markets inwhich quality is difficult to evaluate (e.g., hotel accom-modations, which consist of experience and credenceattributes), whereas prestige effects should be particularlystrong for products and services purchased or consumed inpublic, highly visible contexts (e.g., again, hotel accom-modations). Finally, hedonistic effects depend on theindividual consumer and likely drive consumers* priceresponses in a broad variety of markets.

Transaction utility plays a stronger role than theallocative effect in explaining the SCPR, which might bea partial function of the relatively expensive productcategory investigated in this study. That is, paying a lowerprice than expected likely is particularly relevant for big-ticket items but less relevant for inexpensive products.

I also apply a single-indicator technique (Ping 1995) toincorporate the hypothesized moderating effects but find nostatistically significant (p>OAO) effects for the threeinteraction terms. Both a step-by-step procedure and asimultaneous estimation of all three interaction effects

Table 2 Results for the infonnational and sacrifice componetits of price response of demand

Dependent Variable Standardized paratnetcr estimates R-

Informational component of price response

of demandSacrifice compotietit of price response of demand

0.259*** price-quality beliefs + 0.189*** prestige effects+0.130** 0.215hedonistic effects

-0.174*** allocative effects-0.203*** transaction utility 0.287

Slope between the price-level partworlhs obtained iti the setting without budget constraitit, slope>0**p<0.05 I••*;7<0.0l

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370 J. of the Acad. Mark. Sei. (2008) 36:359-377

Table 3 Effects of consumer characteristics (standardized parameter estimates)

Quality consciousnessMotivation to conformNeed for simplificationof cognitive tasks

Price consciousnessDeal pronenessFinancial constraintsPrice mavenismBrand loyaltyTime pressurePrice relianceIfChi-squaiddfTucker-Lewis indexConfirmatory fit indexRoot mean squared errorof approximation

[90% confidence interval]p value of test of close fit

Structural model for the ICPR

Dqiendent variables

Price-quality-beliefs

0.0450.185***0.138**

0.050-0.024

0.012-0.113*

0.030-0.005

0.368***0.237

Prestigeeffects

0.0900.183***

-0.050

0.066-0.073-0.067

0.0290.214***

-0.0100.397***0.3791.4430.9600.9660.033

Hedonisticeffects

0.118**-0.002

0.100**

-0.134***-0.135***

0.0080.0510.0670.0080.546***0.533

[0.028, 0.037]0.999

X^ Statistic"

12 dß

1.7527.996**7.183**

9.790***5.413*1.1016.761**7.390**0.433

37.995***

Structural model for the SCPR

Dependent variables

Allocativeeffects

-0.086*0.044

-0.063

0.471***-0.014

0.187***0.050

-0.051-0.066

0.067

1.5060.9570.9640.035

Transactionutility

0.131**0.0640.097

0.220***0.488***0.035

-0.024-0.183***

0.0170.096

[0.030, 0.039]0.999

X^ Statistic"i2dß

5.681**0.0231.069

32.761***8.294***7.863***1.4570.0621.4610.202

" Statistic for testing equality of coefficients across the three equations*p<OAO**p<0.05***/i<o.ni

reveal statistically insignificant effects. Furthermore, Iconduct a subgroup analysis to test the three moderatingeffects, in which I divide the sample into two groups on thebasis of their levels of price-quality beliefs (low and high),prestige sensitivity (low and high), and hedonistic tenden-cies (low and high) using median and mean splits. Iestimate the model for each subgroup while imposing theconstraint that the structural relationships are invariantacross the two groups. Next, I estimate the model for eachsubgroup without coefficient equality constraints. A chi-square difference test indicates the tenability of invarianceconstraints, such that a statistically significant decrease inthe chi-square for the model without equality constraintswould indicate the grouping variable moderates the struc-tural relationships. I find no statistically significant {p>0.10) chi-square differences in any subgroup analysis andtherefore cannot confirm Hg, H7, or Hg.

Consumer characteristics explain between 23.7% (price-quality beliefs) and 53.3% (hedonistic effects) of the varia-tion in each price response driver. This level of explanatorypower compares favorably with other studies of shoppingbehavior that use self-reported variables. Table 3 also

reports the x^ statistics for each consumer characteristic,which indicate whether the coefficient of that variable isequal for each of the drivers of ICPR and SCPR. For ICPR.seven of the ten x^ values are significant; for SCPR, four ofthe ten x^ values are significant. That is, most consumercharacteristics have significantly different associations withthe five price response drivers, which offers a strong basisfor segmentation and targeting.

The first column of coefficients in Table 3 shows thatconsumers who perceive high prices favorably because oftheir price-quality beliefs want to simplify their cognitivetasks and rely on the price cue to cope with imperfectinformation (i.e., risk). This result is consistent with thenotion that price cues serve as heuristic techniques to assessproduct quahty when consumers want to reduce perceivedpurchase risk (Dawar and Parker 1994) or are notmotivated to process attribute information (Suri andMonroe 2003). However, the relationship between pricemavenism and price-quality beliefs emerges as significant-ly negative, which suggests consumers pay attention toprice cues consistently. That is, they are sensitive to eitherhigh prices because of their price-quality inferences or low

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prices because they want to transmit information to others.Price mavens furthermore are less likely to believe they willreceive product quality compensation in return for higherprices, which prompts a negative relationship between pricemavenism and price-quality beliefs. Finally, the positiverelationship of motivation to conform with price-qualitybeliefs demonstrates the role of social recognition in price-quality inferences, such that peers may look down on thepurchase of products of medium or low quality.

Consumers who choose high-priced products because ofprestige effects are brand loyal, fee! motivated to conformto the expectations of others, and use the price cue to copewith perceived risk. The strong positive effect of brandloyalty indicates that the effect of price on product choicebecomes more pronounced when a positive price cueappears with a positive second cue, such as a strong brand(Miyazaki et al. 2005). Prestige-sensitive consumers mayperceive the combination of high price and strong brandname as an even better signal of status or wealth than priceor brand name alone. Therefore, they buy high-pricedbrands and tend to be loyal to favored brand(s) that meettheir requirements. The positive coefficient of consumers'motivation to conform to peer expectations also shows that

consumers seek social approval by purchasing expensiveproducts.

The negative associations between price consciousnessor deal proneness and hedonistic effects support the notionthat hedonist consumers buy expensive products primarilyfor their pleasure and want to reward themselves (Duboisand Laurent 1994), which means they place less emphasison paying low priées. Rather, hedonist consumers arewilling to pay high prices for products that are clearlydistinguished by quality, as the significantly positivecoefficient of quality consciousness reveals. The resultsfurther suggest that hedonist consumers use the price eue tocope with the perceived risk that product performance(functional and hedonic) will not meet their requirements.Finally, consumers who are not motivated to processinformation extensively are more receptive to hedonicconsumption experiences.

Consumers who are sensitive to the allocative effect ofprice are not quality conscious but are highly priceconscious and fmancially constrained. They pereeive higherprices as a costly resource outlay and are willing to sacrificeproduct quality for low prices, as the significantly negativecoefficient of quality consciousness shows. In contrast.

Table 4 Simulation of choice share effects (illustrative case)

Price {€)Room size

Location

Health/fitness area

Choice shares (%)Base scenario

Increase of one unit'' inPrice-quality beliefsPrestige efFects

Hedonistic effectsAllocative effectsTransaction utility

Quality consciousnessMotivation to conformNeed for simplification

of cognitive tasksPrice consciousness

Deal pronenessFinancial constraintsPrice mavenism

Brand loyaltyPrice reliance

Hotel 1

60

Regular

Near towncenter

No

30.40

24.5926.13

27.4434.5635.2830.3128.4929.27

33.8333.20

31.1831.1128.57

25.01

Hotel 2

90

RegularNear town

centerNo

0.44

0.510.49

0.480.390.38

0.440.460.46

0.400.410.430.430.46

0.50

Hotel 3

90Regular

Near town

centerYes

5.73

5.89

5.875.84

5.515.46

5.745.815.79

5.555.59

5.705.705.80

5.89

Hotel 4

90

RegularTown center

No

7.58

7.91

7.841.11

7,237.16

7.597.717.66

7.307.357.52

7.537.71

7.89

Hotel 5

90Regular

Town center

Yes

41.29

42.3142.1741.9739.8239.5141.3241.7741.59

40.1240.3641.0641.0841.7542.28

Hotel 6

120

RegularTown center

No

0.68

1.03

0.920.840.52

0.490.690.78

0.74

0.540.57

0.650.650.77

1.00

Hotel 7

120SpaciousTown center

Yes

10.71

15.44

14.0612.958.14

7.7610.7712.1111.52

8.558.91

10.1810.2312.0615.06

None-option

3.16

2.31

2.522.713.84

3.963.142.872.98

3.713.613.283.272.882.37

° One point on the seven-point rating scale

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372 J. ofthe Acad. Mark. Sei. (2008) 36:359-377

those consumers who are receptive to the perceivedtransaction utility of a purchase are highly conscious ofboth price and quality. They are deal prone and not brandloyal. In addition, the significant and positive coefficientof quality consciousness suggests that transaction utilityeffects attract those smart shoppers who seek to pay lowprices but want a good quality product. Finding a pricefor a particular item that is lower than expected enhancestheir perception of themselves as good shoppers. Further-more, the statistically significant, negative coefficient ofbrand loyalty is consistent with the notion that switchingcosts are higher for brand-loyal consumers, so thenegative coefficient of brand loyalty is plausible becauseprice deals often require the consumer to switch brands(Bawa and Shoemaker 1987).

Deal proneness relates exclusively to transaction utilityeffects, whereas financial constraints are associated onlywith allocative effects. This finding is consistent with theconceptualization of the allocative effect of price, in thatprice limits the resources available for spending on othergoods. This effect should be particularly pronounced whenconsumers perceive themselves as financially constrained. Inaddition, transaction utility captures consumers' reactions

to actual prices relative to their expected prices and thusrepresents the incremental utility associated with a good deal,which should result in a positive relationship between dealproneness and transaction utility.

Simulation of choice share effects

In this section, I outline a general procedure to simulate thechoice/market share effects of changes in the levels of theprice response drivers or modifications in segmentation andtargeting strategies. Changes in the levels of price responsedrivers may result from communication programs that, forexample, enhance consumers' price-quality beliefs orelevate hedonistic tendencies. The proposed procedureoffers an intuitive tool managers may use to conductwhat-if analyses that explore the effects of the dual roleof price and price response drivers in terms of marketchoices; specifically, they can predict buyer behavior forspecific market situations and different levels of ICPR andSCPR. I model choice shares for a given set of productalternatives with a multinomial logit model (e.g., Arora andHuber 2001):

Share, ^

¿1 \ßNP.h+

( f-̂ Z-, ylij.m ' ^i-J-m "T" [Ph.Price-inJo '~ Ph. Price sacrifice) ' ^i.Price I

• ' " ^ ' /

; S ' iP I 2_^ ¿^ ßh.j.m '^i'J.m + {ßh,Pnce.-n,fo'^ ßh,Price..wcj-i.fice) ' ^j-,Pric

(2)

in which Share, is the choice share for product / in a set of1^1, ..., 1 product alternatives, including an option not tobuy any of the products offered. The set of productalternatives reflects a current (or fijture) market scenario: afirm's product versus the relevant competition. For theillustrative case, I consider a market scenario of sevenhotels (see Table 4) that reflect middle-class alternativesavailable in the market, according to www.hrs.com. Usingthe estimated individual-level partworth utilities, I examinethe choice shares of each product in this base scenario.Next, 1 investigate modifications ofthe base scenario; speci-fically, I consider the choice share effects of changes inthe informational ißh.pricejnfo) or sacrifice (ßh,price_,acrißce)components of the price response of demand. The marketsimulation thus is straightforward, because it involvessimply altering the price coefficients in the logit modeland rerunning the analysis.

In addition, managers might be interested in the choiceshare effects of (1) changes in the levels of the price

response drivers and (2) modifications in segmentationand targeting strategies that involve changes in the levelsof the price response drivers. In the former case, theyneed to know the effects of a particular price responsedriver on the infonnational {ßh.price_mfo) and sacrifice(ßhj'rice^sacrifice) components, whereas in the latter, theyrequire infonnation about the association between particularconsumer characteristics and the two components ofconsumers" price responses. The structural model analysis(Tables 2 and 3) provides both. For example, a one-unitincrease in the level of price-quality beliefs increasesthe ICPR of demand by 0.259 units. Similarly, I canexplore the impact of changes in particular consiunercharacteristics (resulting from segmentation and targetingstrategy modifications). For example, a one-unit increasein price consciousness results in an increase of thesacrifice component (i.e., SCPR becomes more negative)by -0.127 units [=0.471 x(-0.174)+0.220x(-0.203); seeTables 2 and 3] and a decrease of the informational

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J. of the Acad. Mark. Sei. (2008) 36:359-377 373

component by -0.017 units (—0.134x0.130, see Tables 2and 3).

Table 4 shows the choice share effects in the illustrativemarket simulation. I find notable choice share differences,particularly for hotels offered at the lower or upper levelsof the price range. An increase in the price responsedrivers by one unit leads to choice share differences of upto 5.8 percentage points. On average, I fmd choice sharedifferences of two percentage points, a notable and eco-nomically substantial result.

Furthermore, simulating modifications in the segmenta-tion and targeting strategies by means of one-unit changesin consumer characteristics yield choice share differences ofup to 5.7 percentage points, which again suggests a notableand economically substantial result.

Discussion

Unlike previous research into the effects of price onconsumers' product evaluations, this study merges twoempirical research streams by combining stated preferencesobtained from a choice-based conjoint approach with self-reported measures pertaining to price response drivers andunderlying consumer characteristics to provide new insightsinto the dual role of price. Specifically, this article differ-entiates between the informational and sacrifice effects ofprice using a choice-based conjoint approach, differentiatesfurther among several subcomponents (price responsedrivers) of these two main effects, examines underlyingconsumer characteristics, and evaluates the reliability andvalidity of the proposed approach. Finally, I introduce aprocedure to simulate the choice share effects of changes inprice response drivers and modifications in segmentationand targeting strategies.

The results suggest that the proposed procedure has ahigh degree of reliability, predictive validity, face validity,and nomological validity. The structural model analysesthat allow further differentiation among the subcomponentsof the dual role of price also reveal that price-qualitybeliefs, the prestige value of high-priced products, andhedonistic effects significantly infiuence the ICPR. Iflirthermore find that these three price response driversattract consumers with unique profiles. Whereas hedonisticeffects relate to quality consciousness, low price conscious-ness, and low deal proneness, price-quality beliefs aredriven by a need to simplify cognitive tasks, pressure toconform to the expectations of others, and low pricemavenism. Finally, prestige effects are particularly associ-ated with brand loyalty and motivation to conform to peerexpectations. The SCPR is strongly associated with pure

allocative effects and transaction utility; these two sourcesalso indicate distinct behavior patterns. Perceived allocativeeffects relate particularly to price consciousness andperceived budget constraints, in that financially constrainedconsumers transfer their price consciousness to monetarysavings, even at the expense of quality. In contrast,consumers who are receptive to the transaction utility ofa purchase are quality conscious, deal prone, and lessbrand loyal.

The estimated structural models form a basis forsimulating choice share effects that result from changes inprice response drivers, as well as from modifications insegmentation and targeting strategies. The illustrativemarket simulation reveals remarkable choice share differ-ences of up to 5.8 percentage points. '

Implications for managers

The analyses suggest several key implications tor manag-ers. In particular, price plays two distinct roles—sacrificeand informational—in consumers* utility functions andtherefore in consumers' price responses and choice behav-ior. The latter is fundamental to managerial decisions,because varying levels of sacrifice and informationalcomponents connect to variations in consumers' willing-ness to pay, which means they also provide the rationale fordifferent pricing strategies. If managers understand theimpact of the two price response components, the priceresponse drivers, and the underlying consumer character-istics on product choice, they can exploit the informationaleffect of price and influence, at least to a certain extent,consumers' willingness to pay. ! also provide managerswith an easy-to-implement approach for simulating thechoice share effects of changes in price response drivers aswell as segmentation and targeting strategies. Previousmethods cannot provide managers with such infonnationbecause they consider quantitative, demand-based priceeffects or self-reported measures, but not a combinationof both.

Also important from a managerial viewpoint are theimplications regarding the appropriateness of differentpricing strategies. For example, to access consumers whoare highly price conscious and perceive themselves assubject to financial constraints, managers should prime theperceived allocative effect of price by embracing aneveryday low price (EDLP) strategy. In contrast, managersshould not use an EDLP strategy if they want to accesssmart shoppers who are receptive to the transaction utilityof a purchase, because these consumers are both price andquality conscious and likely assume that any brand thatalways appears on sale cannot be a high-quality product.

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374 J. of the Acad. Mark. Sei. (2008) 36:359-377

In such circumstances, a Hi-LO pricing strategy might bebetter. The proposed simulation procedure allows manag-ers to compare different pricing strategies (to attractdifferent consumer segments) in terms of choice shareeffects.

Furthermore, managers may want to assess communica-tion programs that enhance or decrease particular priceresponse drivers (e.g., hedonistic tendencies, prestige sen-sitivity). The proposed market simulation-based procedureoffers an intuitive tool managers may use to conduct what-if analyses that explore the effects of changing specificprice response drivers in terms of market choices.

Finally, managers must be aware that setting a lowselling price or lowering the price with a discount offer notonly attracts customers (by addressing SCPR) but alsothreatens to lower perceptions of product quality, prestigevalue, and hedonistic value because of the negativesignaling effects related to lower selling prices. These lattereffects may deter purchase by customers whose priceresponse contains a strong informational component. Forexample, negative price-quality inferences occur mostoften when the brand name or retailer are poorly knownor intrinsic product quality cues are ambiguous or unavail-able. In these cases, price-quality beliefs likely induce astrong informational effect of price on demand that mayeven dominate the sacrifice component. This scenario couldexplain the fmdings in various empirical studies that priceelasticities reach values that are significantly greater thanzero (Tellis 1988).

Further research

This study has several implications for researchers that mayprovide interesting opportunities for further research aswell. The first implication relates to the generalizability ofprice effects across product categories. Differences in themagnitude of ICPR and SCPR certainly exist acrosscategories and merit additional research. However, thisstudy's success in characterizing the identified priceresponse drivers according to consumer characteristicsreveals that consumers tend to have overarching reactionsto price cues that may generalize across product categories.

The second implication relates to the consequences ofthe dual role of price for modeling demand functions andsetting optimal prices, which likewise merits additionalattention. Managers may be particularly interested inmodels that can relate ICPR and SCPR to marketing mixdecisions about price, sales promotions, distribution, andadvertising. For example, a profit-maximizing price dis-crimination strategy likely differs when the infonnationaleffect of price joins the brand choice model and consumers'utility functions.

Appendix 1: Survey items

I. Price response driversPrice-quality beliefs

Prestige effects

Hedonistic effects

Allocative effects

Transaction utility

2. Consumer characteristicsPrice consciousness

Deal proneness

Financial constraints

The higher the price of a product,the higher the quality

The old saying "you get what you

pay for" is generally trueYou always have to pay more for the bestIt says something to people when you

buy the high priced version of a productI have purchased an expensive

product just because I knew other

people would noticeI like to purchase an expensive

product merely because many others

cannot afFord such an expensive productI sometimes purchase an expensive

product primary for my own pleasureI spoil myself from time to time with an

expensive product because I am worth itBuying a high priced product makes me

feel good about myselfIf I want to give myself a treat,

I sometimes buy an expensive productThe higher the price of a product the

more I get the feeling to do without

some other products I would like topurchase

I perceive the price of a product in a

negative role because it indicates theamount of money that must be given upin order to obtain the product

Before making a purchase I consider the

amount of money available for spending

on other products I would like topurchase

Taking advantage of a reduced price

gives me a sense of joyI am willing to go to extra efFort to fmd a

lower price compared to the price 1initially have expected

I am annoyed, if I have to spend more

money than expected for a product

I am very concerned about low prices

when I buy productsIt is important for me to get the best price

for the products I buyI often search consciously for special

offers such as "two for one" or "allinclusive"

I am more likely to buy brands that are onspecial

It is worth the effort to search for

products that are on saleI have to hold on to my moneyBy the end of the month my accotmt is

often relatively emptyMy household budget is always tight

pringer

J. of the Acad. Mark. Sei. (2008) 36:359-377 375

Quality consciousness

Motivation to conform

Price mavenism

Brand loyalty

Time pressure

Need for simplification

of cognitive tasks

Price reliance

1 search for as much information as

possible on the quality of the productsbefore I choose one

It is important for me to know exactly the

quality of a product before 1 buy itIt is important for me to buy high-quality

productsIt is important for me what people think

about meIt bothers me if other people disapprove

my choicesIt is important for me to fit inMy behavior ofïen depends on how 1 feel

others wish me to behave1 am considered somewhat of an expert

when it comes to knowing the prices ofproducts

People ask me for price infonnationMy friends think of me as a good source

of information on places to shop for the

lowest price1 prefer one brand of most products I buyI am willing to make an effort to search

for my favorite brandI am willing to pay a bit more for my

favorite brandI wish I would have more time to relaxI always seem to be in a hurryI do not like tasks that require much

thinkingIt is important for me that my purchase

decision making is fast anduncomplicated

In purchase decision making, I often rely

on easily available attribute infonnationA higher price gives me the feeling that I

have not saved the wrong way if myexpectations are not met

! sometimes purchase an expensive

product in order not to have to reproachmyself if my expectations are not met

I sometimes purchase an expensive

product because this gives me thefeeling to make nothing wrong

Respondents were instructed as follows; Please think ofa weekend trip to a major European city. The joumey andother details have already been arranged. You only have tobook a hotel room (hereinafter referred to as "product") forthe weekend.

Appendix 2: Interfactor correlations

Tables 5 and 6

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Table 6

Price-quality beliefs Prestige effects Hedonistic effects

J. of the Acad

Allocative

. Mark.

effects

Sei. (2008) 36:359-377

Transaction utility

Pnce-quality beliefsPrestige effects

Hedonistic effectsAllocative effectsTransaction utility

1.0000.273***

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0.028 ns

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1.000-0.148**'-0.126**

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Each construct satisfies Fomell and Larcker's (1981) condition of discriminant validity* / K O . 1 O

**p<0.05

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