228Journal of Marketing ResearchVol. XXXIX (MAY 2002), 228–241

KLAUS WERTENBROCH and BERND SKIERA*

Economists, psychologists, and marketing researchers rely on meas-ures of consumers’ willingness to pay (WTP) in estimating demand for pri-vate and public goods and in designing optimal price schedules. Existingmarket research techniques for measuring WTP differ in whether theyprovide an incentive to consumers to reveal their true WTP and inwhether they simulate actual point-of-purchase contexts. The authorspresent an empirical comparison of several procedures for eliciting WTPthat are applicable directly at the point of purchase. In particular, theauthors test the applicability of Becker, DeGroot, and Marschak’s (1964)well-known incentive-compatible procedure for assessing the utility of lot-teries to measuring consumers’ WTP. In three studies, the authorsexplore the reliability, validity, and feasibility of the procedure and showthat it yields lower WTP estimates than do non–incentive-compatiblemethods such as open-ended and double-bounded contingent valuation.They show experimentally that differences in WTP estimates arise fromthe incentive constraint rather than the cognitive effort required in

responding. They also control for strategic response behavior.

Measuring Consumers’ Willingness to Pay atthe Point of Purchase

*Klaus Wertenbroch is Associate Professor of Marketing, INSEAD (e-mail: klaus.wertenbroch@insead.edu). Bernd Skiera is Professor of Elec-tronic Commerce, Johann Wolfgang von Goethe-Universität (e-mail:skiera@skiera.de). The authors are grateful to Sönke Albers, Karen Gedenk,Jordan Louviere, Subrata Sen, Dick Wittink, and the three anonymous JMRreviewers for helpful comments on previous versions and presentations of thisarticle; the authors thank Birga Schweiger and Hristo Giochev for their help withthe data collection.

I am inclined to offer Mr. Vieweg from Berlin an epicpoem, Herrmann and Dorothea, which will haveapproximately 2,000 hexameters…. Concerning theroyalty we will proceed as follows: I will hand over toMr. Counsel Böttiger a sealed note which contains mydemand, and I wait for what Mr. Vieweg will suggest tooffer for my work. If his offer is lower than my demand,then I take my note back, unopened, and the negotiationis broken. If, however, his offer is higher, then I will notask for more than what is written in the note to beopened by Mr. Böttiger.

—Johann Wolfgang von Goethe in a letter on January16, 1797, cited by Moldovanu and Tietzel (1998)

Goethe’s scheme to elicit a price from Vieweg for his manu-script is perhaps the earliest documented example of enticing abuyer in an incentive-compatible format to truthfully reveal hiswillingness to pay (WTP), or reservation price, presagingNobel laureate William Vickrey’s (1961) analysis of the prob-lem by a century and a half. To Vieweg, Goethe’s sealed pricerepresents a random variable that is distributed independentlyof his own WTP (Moldovanu and Tietzel 1998). Therefore,Vieweg’s dominant response strategy is to bid exactly his WTP.The WTP denotes the maximum price a buyer is willing to payfor a given quantity of a good. It is a ratio-scaled measure of thesubjective value the buyer assigns to that quantity. He or shebuys that item from a set of alternatives, for which his or herWTP exceeds purchase price the most. As in the precedingexample, knowledge of consumers’ WTP is crucial in estimat-ing demand and designing optimal pricing schedules. Existingmarket research elicitation techniques differ in whether theyprovide an incentive to consumers to reveal their true WTP andin whether they simulate actual point-of-purchase contexts.

We present an empirical comparison of several such proce-dures for eliciting WTP at the point of purchase. In particular,we test the applicability of Becker, DeGroot, and Marschak’s

RESEARCH NOTESAND COMMUNICATIONS

Point-of-Purchase Willingness to Pay 229

(1964) well-known procedure (hereafter BDM) for assessingthe utility of lotteries to measuring consumers’ WTP in marketresearch. The BDM procedure enables us to combine incentivecompatibility with WTP elicitation in relevant point-of-purchase contexts. We begin with a brief discussion of existingapproaches to WTP measurement in market research. Next, wedevelop the theoretical and methodological properties of BDMfor use in market research. We then describe two point-of-purchase field studies that apply the procedure to inexpensivegrocery items. The studies demonstrate BDM’s feasibility, reli-ability, and validity and show its superior performance com-pared with a conventional method based on survey responses.A follow-up experiment compares BDM with a typical hypo-thetical choice–based approach. The experiment shows the fea-sibility of BDM across domains, applying it to an inexpensivedurable. It suggests that BDM yields lower WTP estimates thanhypothetical methods do because of the incentive constraintrather than the cognitive effort it requires from respondents.The experiment also controls for strategic response behavior.Our closing discussion focuses on the limitations of applyingBDM in market research.

DETERMINING WTP IN MARKET RESEARCH

Transactions Data

Market researchers estimate WTP either from actual markettransactions (revealed preferences, e.g., from scanner data) orfrom survey data (stated preferences). Transactions data such asscanner and simulated test market data (e.g., Silk and Urban1978) are incentive compatible and have high external validitybecause actual purchases are observed under realisticmarketing-mix conditions. For example, test market simula-tions such as ACNielsen’s BASES system (www.bases.com)provide consumers with opportunities to buy real products fromcompetitive choice sets at experimentally manipulated pricepoints. Participants receive a participation fee that they caneither keep or spend on the available products at the postedprices. Therefore, demand estimates cannot be biased down-ward simply because of possible liquidity constraints. How-ever, posted prices in real or simulated markets typically varyonly within limited ranges (Ben-Akiva et al. 1994). Thus, trans-actions data reveal only that a buyer’s WTP is at least as highas the posted price and that a nonbuyer’s WTP is lower than thatprice. A consumer’s true WTP remains unknown, which pre-vents marketers from extracting maximum consumer surplus.Moreover, except for test market simulations, transactions dataare unavailable for new products that have not yet been soldunder market conditions.

Survey Data

In contrast, the key advantage of survey data is that theycan be elicited in concept testing and new product develop-ment or in evaluations of nonmarket public goods (e.g.,Cameron and James 1987). The most successful methodol-ogy in market research is conjoint analysis (Green and Srini-vasan 1990), but survey data can also come from contingentvaluation (Mitchell and Carson 1989). Conjoint analysis isdesigned to determine trade-offs among product features orattributes (including price), and differences in utilities(WTP) are either inferred from subjects’ rankings or ratingsof alternatives or elicited as a dependent variable as the sumof money that would make subjects indifferent between abundle of attributes and the money (e.g., Kalish and Nelson

1Conjoint analysis is best described as incentive-neutral, because respon-dents have no incentive to be inaccurate in indicating their preferences forprice–quality bundles. We thank a reviewer for this suggestion.

1991; Rao and Soni 1994). Contingent valuation and relatedapproaches (e.g., Jones 1975; Kalish and Nelson 1991)require respondents to state their WTP for entire goods orfor attribute-level changes directly (open-ended contingentvaluation) or to make single or repeated choices of whetherthey would buy a good at a given price (closed-ended con-tingent valuation). On the downside, the external validity ofthese approaches may be limited: They provide little incen-tive to consumers to truthfully reveal their WTP, becauseresponses are hypothetical (Hoffman et al. 1993).1 Responseincentive effects can occur in contingent valuation when thesurvey itself prompts respondents to make inferences aboutthe value of the good (Alberini, Kanninen, and Carson 1997;Carson, Groves, and Machina 1999). Finally, Hoffman andcolleagues (1993) suggest that consumers’ revealed prefer-ences (i.e., choice reactions to posted prices) may arise fromdifferent reference frames than their stated preferences (i.e.,stated reservation prices). So the demand revealed underthese two approaches may differ systematically, arguing forthe application of a variety of WTP measurement proce-dures for cross-validation purposes.

Vickrey Auctions

Market researchers need methods that both are applicable atthe point of purchase and provide incentive-compatible esti-mates of WTP derived from real transactions. To address thelatter goal, Hoffman and colleagues (1993) advocate the use ofexperimental Vickrey auctions. Vickrey (1961) suggests thatincentive compatibility is ensured if a given bid determinesonly whether the bidder has the right to buy the good that isauctioned off. In a sealed-bid auction, the purchase price isdetermined solely by the other participants’ bids. The n highestbidders in a Vickrey auction (also called [n + 1]th-price, sealed-bid auction) win the good at the price of the (n + 1)th-highestbid. Bidders’ dominant strategy is to bid exactly their WTP(Kagel 1995; Vickrey 1961). Unlike methods based on statedpreference data, Vickrey auctions provide bidders with anincentive to reveal their WTP truthfully, because they must buythe good in a real transaction if their bid wins the auction.

Despite these theoretical advantages, Vickrey auctionsexhibit practical and empirical limitations. First, auctions maypose operational problems, because consumers/bidders mustmeet in a research facility, typically at a substantial set-up cost.Second, auction bidding processes do not naturally mimic con-sumer point-of-purchase decision-making processes in normalretail settings (Hoffman et al. 1993). In contrast to the practi-cally unrestricted supply of goods in retail settings, bidderscompete with one another for a limited stock. In practice, thedecision of how much to bid is thus not only a question of thebidder’s true valuation of the good but also of ensuring that heor she places the winning bid. Thus, participants in Vickreyauctions of objects with private values tend to violate the incen-tive constraint by bidding more than the objects are worth (e.g.,Kagel 1995; Kagel, Harstad, and Levin 1987). These empiricalviolations of incentive compatibility may limit the externalvalidity and usefulness of Vickrey auctions in marketingresearch. Hoffman and colleagues (1993, p. 334) acknowledgethe challenge of designing “learning trials, task frames andinstructions that explain incentive-compatible auctions so as to

230 JOURNAL OF MARKETING RESEARCH, MAY 2002

Figure 1FLOW CHART OF BDM PROCEDURE

Instructions

Initial Price Offer

Possibility to Revise Initial Price Offer

Final Price Offer (s)

Random Determination of Buying Price (p)

Buying Price ≤ Final Price Offer Buying Price > Final Price Offer

Buying Obligation No Buying Opportunity

minimize both the incidence and impact of such strategicbehavior.”

BDM

To address simultaneously some of the theoretical, empir-ical, and practical limitations of conventional transaction-and survey-based methods, we apply BDM to the elicitationof WTP at the point of purchase. This application isdesigned to be theoretically incentive compatible, realistic,transparent to respondents, and operationally efficient.Unlike Vickrey auctions, it enables researchers to determineindividual consumers’ WTP in relevant and typical purchasesettings in the field. In the original BDM procedure, the util-ity of lotteries was measured by eliciting minimum sellingprices (willingness to accept) for gambles by determiningactual transaction prices randomly (i.e., by drawing a ballmarked with a price from an urn). Thus, the distribution ofBDM transaction prices is exogenous to respondents’WTPs, just like in Vickrey auctions, which ensures thatBDM is theoretically incentive compatible (Kagel 1995).Experimental researchers in behavioral decision theory havewidely used BDM-type random preference elicitation pro-cedures with consumer goods as stimuli (e.g., Kahneman,Knetsch, and Thaler 1990; Prelec and Simester 2001;Wertenbroch 1998), but market research practitioners havenot relied on this approach.

Incentive Compatibility and Respondent Beliefs

Before proceeding with our discussion of BDM, we notethat incentive compatibility in practice requires unambigu-ous fit between sellers’ and buyers’ goals. More generally,all field-based methods for measuring WTP, includingBDM, are subject to possible uncontrollable belief-basedstrategic misrepresentation and may not be truth revealing ifsubjects consider their responses consequential beyond theimmediate survey context (Carson, Groves, and Machina1999). If subjects believe that their responses will be used toset long-term market prices, they have an incentive to under-state their WTP. If they believe that their responses willdetermine the introduction of a desirable new product, theymay perceive reasons to overstate their WTP.

INCENTIVE-COMPATIBLE ELICITATION AT THEPOINT OF PURCHASE

A key benefit of applying BDM is that it enables marketresearchers to create opportunities for transactions at real pointsof purchase under the marketing-mix conditions the marketerdesires. We sample target consumers and tell them that theyhave a chance to buy the product without spending more moneyon the purchase than they want to. They learn that the buyingprice p for the product is not yet set and will be determined ran-domly. Next, we explain and then apply the following proce-dure: We ask them to offer a price s for the product, whichshould equal the highest price they are willing to pay for theproduct. Then, we randomly determine p from a prespecifieddistribution (which is unknown to respondents). Allowing con-sumers to draw a ticket marked with a price from an urn shouldincrease their confidence in the randomness of the price-settingmechanism and underscore the futility of misrepresentation. Ifthe drawn price p is less than or equal to their offer s, they arerequired to buy the product at price p. If p exceeds their offer,they are not allowed to buy the product. Figure 1 illustrates theprocedure; sample instructions are in the Appendix. Con-

sumers’ dominant strategy is to offer their true WTP, becausefor any distribution of buying prices,

1. understating one’s true WTP (s < WTP) reduces the chance ofbuying at a gain (where the forgone gain is WTP – p > 0 forall s < p < WTP), without increasing the actual gain if the con-sumer must buy (if p ≤ s), because understating cannot affectthe buying price p, and

2. overstating one’s true WTP (WTP < s) increases the chanceof buying at a loss (where the incurred loss is WTP – p < 0 forall WTP < p ≤ s).

Realistic Purchase Settings

Compared with existing methods, BDM has both strengthsand weaknesses. The WTP can be elicited right at the point ofpurchase, so it can vary as a function of the purchasing contextand competitive set, which should enhance external validity.This also makes BDM easier to administer and should mitigatethe overbidding found in Vickrey auctions (e.g., Kagel 1995),in which consumers convene in an artificial format that isunrepresentative of the actual purchase context and that maytrigger unrepresentative competitive bidding behavior. Therealism in the elicitation context that BDM affords is crucial.Thaler (1985) finds that (hypothetically) incentive-compatibleWTPs differ dramatically for identical items (cold beer)depending on the point of purchase (a fancy resort hotel or arun-down grocery store), as the transaction context itselfinduces different levels of utility and WTP. Experimentalchoice researchers have long argued that choice tasks must bedesigned realistically, approximating as closely as possible theactual purchase context (Carson et al. 1994), because con-sumers often construct their preferences in response to thechoice context rather than retrieve a previously formed value(Bettman, Luce, and Payne 1998).

Out-of-Pocket Transactions

As an additional incentive for respondents to consider theirprice offers carefully, we suggest not giving them any compen-sation for their participation, so they need to have enough cashto pay out of their own pockets. This out-of-pocket obligationforces respondents to consider their real readiness to buy andminimizes possible distortions caused by the windfall characterof any extra compensation. Thaler and Johnson (1990) haveshown that propensity to spend varies with whether the fundsstem from such windfall gains. Therefore, prices that areelicited with existing procedures may overestimate WTP in

Point-of-Purchase Willingness to Pay 231

everyday market transactions because subjects receive a partic-ipation fee so that they never leave the lab with less money thanthey entered it with. Under BDM, however, respondents neednot be compensated for coming to a research facility (see Hoff-man et al. 1993), because they are intercepted at real points ofpurchase. Making respondents pay out-of-pocket renders BDMparticularly suitable for determining WTP for unplanned, low-cost purchases of consumer packaged goods. For these, any liq-uidity effects should be small or negligible.

The Distribution of Prices

Valid WTP estimation requires that respondents trust theinterviewer and expect to participate in a fair transaction.Therefore, the distribution from which buying prices are drawnmust have a range within which all prices appear fair. If the dis-tribution is skewed toward high prices, consumers may inferthat they are “cheated,” similar to bidders’fears of experimentermisrepresentation in Vickrey auctions (Rothkopf and Harstad1995). Subjects should not be told about the range andmoments of the distribution to avoid anchoring, which affectsselling price bids in BDM (Bohm, Lindén, and Sonnegård1997). The choice of distribution type and moments is flexible.It depends on the researcher’s budget and objectives, becausethe distribution affects the researcher’s expected revenue. Thedistribution itself cannot influence WTP responses. However, itis possible that the lottery nature of the task may bias responses.For example, for existing products, respondents might cap theirbids at the remembered market price if they perceive the task asan opportunity to “win” the item at a price below market. Thepossibility of such underbidding marks all incentive-compatible procedures; we return to the issue of strategicresponse biases subsequently.

In summary, BDM permits the elicitation of incentive-compatible WTP without convening consumers in groups in alaboratory. Respondents do not compete with others for thesame product. They pay out-of-pocket in real purchase loca-tions such as malls or stores, subject to the intended purchaseconditions and realistic purchasing motives. This keeps thecosts of BDM low compared with laboratory-based marketresearch, unless BDM buying prices happen to be much lowerthan the cost of goods sold. We now turn to an empirical assess-ment of BDM compared with other elicitation procedures.

STUDIES 1 AND 2: TESTING BDM IN THE FIELD

In two independent studies, we tested the feasibility, reliabil-ity, and validity of applying BDM at the point of purchase.Study 1 elicited WTP for a can of Coca-Cola on a public beachin Kiel, Germany. Study 2 elicited WTP for a piece of poundcake on a commuter ferry in Kiel. No substitutes were availablein either location. Our WTP distributions are specific to thesemonopolistic contexts. This point-of-purchase specificity is akey feature of WTP, as WTP distributions cannot be general-ized across choices from different competitive sets. But for anygiven point of purchase (including monopoly settings), we cancompare the performance of BDM with that of other methodsfor measuring WTP.

As a benchmark for methods based on stated preferences, weasked consumers to state their WTP hypothetically (e.g., Car-mon and Ariely 2000; Gabor and Granger 1966; Jones 1975;Kalish and Nelson 1991). According to Carson, Groves, andMachina (1999), this continuous response format is a specialtype of open-ended contingent valuation that corresponds toprice matching in the decision-making literature (e.g., Tversky,

2Closed-ended contingent valuation does not provide a measure of WTPat the level of individual respondents (see Cameron and James 1987),which we require for our reliability and validity analysis.

Slovic, and Kahneman 1990).2 Except for the lack of incentivecompatibility, we elicited these matching prices under the sameconditions as WTP under BDM, that is, in the actual purchasecontexts.

Method

Subjects, design, and procedure. Four hundred randomlyselected consumers participated in the studies—200 beachvisitors in the first and 200 ferry passengers in the second.Within each study, 100 consumers’ WTP was elicitedthrough price matching (control group), and the other 100consumers’ WTP through BDM (test group) in a two-levelbetween-subjects design, in which subjects were randomlyassigned to conditions. To control for environmental condi-tions that might affect demand for the products, we ran eachstudy under equal weather conditions across four consecu-tive days. The same interviewer conducted all interviews,and an equal number of consumers in both groups was inter-viewed every day during the same time interval to ensurecomparability of conditions further.

The interviewer approached subjects individually and intro-duced herself as an academic marketing researcher from thelocal university. Subjects in the control groups (price matching)were shown a can of classic Coca-Cola or a piece of poundcake and were asked for the maximum price they would bewilling to pay for it if it were for sale. In the test groups, weapplied the BDM procedure outlined previously (Figure 1).Thus, each test subject was offered a can of Coke or a piece ofcake for purchase. The specific instructions read to subjects bythe interviewer are listed in the Appendix, including instruc-tions on revising their offers. When respondents had deter-mined their final price offer, they drew a ball from the urn todetermine the purchase price.

In both studies, the distribution of potential purchase pricesin the urn was uniform. Coke prices ranged from DM .50 toDM 2.50, in increments of DM .10 (DM 1.00 approximatelyequaled US$.55). Cake prices ranged from DM .80 to DM2.00, in increments of DM .10. These ranges were wide enoughto include the soft drink and pound cake prices we had found ina survey of different local retail outlets. None of the character-istics of the price distributions in the urn were reported to sub-jects, even if they asked, to avoid anchoring their responses (seeBohm, Lindén, and Sonnegård 1997).

Measures. We recorded the final price offer (s), the ran-domly determined purchase price (p), and whether subjectscomplied with their purchase obligations. We also examinedvarious transparency and acceptability measures of BDM(Table 1), and subjects rated how thirsty (hungry) they were,how much they liked the items, how much they were crav-ing them, and what price they normally paid for them (Table2). Finally, BDM subjects who had to buy rated on five-point Likert scales how much value and satisfaction theyderived from their purchase, whereas BDM subjects whoseprice offers were less than the purchase price stated whetherthey regretted not having offered a higher price and whetherthey would have bought at a higher price.

Results

Table 1 shows that respondents perceived BDM as highlytransparent and acceptable. The procedure was not confusing,

232 JOURNAL OF MARKETING RESEARCH, MAY 2002

Table 1MEAN WTP AND TRANSPARENCY AND ACCEPTABILITY RATINGS PER CONDITION, N = 100 PER CONDITION (STANDARD

DEVIATIONS ARE IN PARENTHESES, MINIMUM WTP = 0 IN ALL CONDITIONS) IN STUDIES 1 AND 2

Coke Cake

BDM Price Matching BDM Price Matching

Mean WTP (across four subsamples in each of the four conditions)a DM 1.06b DM 1.35b DM 1.12c DM 1.68c

(.66) (.81) (.56) (.82)

Has this procedure been confusing for you? (reverse scored: 1 = “very 4.81 n.a. 4.95 n.a.much so,” 5 = “not at all”)d (.51) (.22)

Is it clear why it is in your best interest to state exactly the price you are 4.21 n.a. 4.14 n.a.willing to pay?d (.78) (.69)

Would you participate in a survey like this again? (% “yes” responses) 99.0% n.a. 95.0% n.a.

aWTP is either the final price offer (BDM) or the stated price (price matching).bValues with same superscripts differ (at p < .01 in a t-test with unequal variances).cValues with same superscripts differ (at p < .0001 in a t-test with unequal variances).dResponses were given on a five-point-scale (1 = “not at all,” 5 = “very much so”).Notes: n.a. = not applicable.

Table 2CORRELATION OF WTP WITH MEASURES OF FACE VALIDITY IN STUDIES 1 AND 2

Coke Cake

BDM Price Matching BDM Price Matching

How thirsty/hungry are you right now? .2708*** .0809** .2749*** .0079***(N = 100) (N = 100) (N = 100) (N = 100)

How much do you like Coca-Cola/cake? .3641*** .3005** .5915*** .2270***(N = 100) (N = 100) (N = 100) (N = 100)

How much do you normally pay for a can of Coca-Cola/a piece of cake? .2566*** .3111** .0337*** .4543***(in DM) (N = 87) (N = 75) (N = 92) (N = 94)

How much did you crave the Coca-Cola/the piece of cake? .4679*** n.a. .6478*** n.a.(N = 100) (N = 100)

*p < .05 that r = 0.**p < .01 that r = 0.***p < .0001 that r = 0.Notes: Responses were given on a five-point-scale for thirst/hunger, liking, and craving (1 = “not much,” 5 = “a lot”). n.a. = not applicable.

nor was it difficult for respondents to understand why it wasoptimal to state exactly their WTP. Hardly anyone approachedrefused to participate in the studies. Those who did, did not careat all for Coke or pound cake. All who agreed to participate didso without hesitation and visibly enjoyed drawing the purchaseprices themselves to learn whether they were eligible to buy aCoke or a piece of cake. Some respondents asked about therange of the possible purchase prices but were content whentold that the distribution was “reasonable, with prices neithertoo high nor too low.”

Distribution of WTP. The cumulative distributions ofWTPs in Figure 2 show that consumers stick to major pricepoints when asked only hypothetically under price matching(observed demand is measured as the number of respon-dents who say they would buy at price p ≤ WTP). In con-trast, WTPs elicited under BDM are distributed moresmoothly and are more differentiated, which suggestsgreater accuracy. Table 1 shows that mean WTPs underBDM are lower than mean matching prices (∆ = DM –.29,t = –2.65, p < .01 for Coke; ∆ = DM –.56, t = –5.70, p <.0001 for cake). For Coke, the mean final price offer is more

than 20% below the mean matching price; for cake, it is 33%less.

Reliability. We determined the reliability of the WTPmeasures by comparing mean WTPs across the four dailyrespondent subsamples within each condition (see Green,Tull, and Albaum 1988, p. 253). Analyses of variance ofnonzero WTPs failed to reveal any differences between thesubsamples under BDM for Coke (F(3, 82) = .80, p < 1) andcake (F(3, 96) = 1.14, p < 1). This suggests that BDM is reli-able when point-of-purchase characteristics remain stable.In contrast, our data suggest that WTPs elicited under pricematching may be less reliable. They appeared comparableacross subsamples for Coke (F(3, 96) = .13, p < 1) but werenot equal for cake (F(3, 96) = 2.63, p < .10).

Face validity of both methods. We determined the facevalidity of WTPs by correlating the final BDM price offersand the matching prices with the respondent characteristicsshown in Table 2. All correlation coefficients have theexpected (positive) signs. We transformed the individualcoefficients into Fisher Z scores (see, e.g., Glass and Stan-ley 1970) to test whether the correlations differed across test

Point-of-Purchase Willingness to Pay 233

Figure 2OBSERVED AND PREDICTED DEMAND IN STUDIES 1 AND 2

BDM-Cake (21 final price points)Quantity

.0 .40 .80 1.20 1.60 2.0 2.40 2.80 3.20

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and control groups. Subjects’ WTPs for Coca-Cola corre-lated significantly with how thirsty they were under BDM(ZBDM = .27) but not under price matching (Zmatch = .08; z =1.37, p < .10 for the difference in the two Z-coefficients).Subjects’ liking for Coca-Cola showed a directionally simi-lar pattern, but the difference in correlation coefficientsfailed to reach significance. Subjects’ WTPs for cake corre-lated with how hungry they felt under BDM (ZBDM = .28)but not under price matching (Zmatch = .01; z = 1.91, p <.05). Similarly, the correlation between WTPs and howmuch they liked cake was stronger under BDM (ZBDM =.68) than under price matching (Zmatch = .23; z = 3.13, p <.01), and BDM responses in both studies correlated withsubjects’ craving for the items. As predicted, these resultssuggest that WTPs from BDM provide a more valid meas-ure of subjects’ preferences than do WTPs from pricematching. How much subjects normally paid for Coca-Colaand cake tended to be less strongly correlated with WTPunder BDM than under price matching (Coke: ZBDM = .26versus Zmatch = .32; z = –.37, p < 1; cake: ZBDM = .03 ver-sus Zmatch = .49; z = –3.06, p < .01). This may imply thatprice-matching subjects anchor their responses on a refer-ence price instead of carefully determining their situation-and context-specific true WTP. Recall that matching priceswere distributed less smoothly than BDM WTPs, which also

suggests a simple anchoring or rounding process to deter-mine responses (Figure 2). In contrast, responses underBDM seem to reflect more closely subjects’ situation-specific individual demand.

Internal validity of both methods. Logit analyses of pur-chase probabilities Pr(buy|p) = ea + b × p/(1 + ea + b × p) indi-cated downward sloping demand with a = 3.94 (p < .0001)and b = –3.44 (p < .0001) in BDM-Coke, a = 4.32 (p <.0001) and b = –2.52 (p < .0001) in price matching-Coke,a = 4.58 (p < .0001) and b = –3.72 (p < .0001) in BDM-cake,and a = 6.42 (p < .0001) and b = –3.48 (p < .0001) in pricematching-cake. Figure 2 shows that predicted demand(measured as the expected number of respondents who buyat price p ≤ WTP) tracks observed demand much betterunder BDM than under price matching. This was confirmedby an analysis of the Fisher Z–transformed correlationsbetween observed and expected demand, which showed bet-ter fit under BDM than under price matching (Coke: rBDM =.9952, rmatch = .9881, ZBDM = 3.02 > Zmatch = 2.56; z = 1.60,p < .10; cake: rBDM = .9981, rmatch = .9876, ZBDM = 3.48 >Zmatch = 2.54; z = 3.09, p < .01). These results suggest thatBDM provides a highly internally valid measure of WTPand outperforms price matching in modeling demand.

Criterion validity of BDM. In addition, BDM has high cri-terion validity, measured as the percentage of consumers

234 JOURNAL OF MARKETING RESEARCH, MAY 2002

3Continuous response formats (e.g., Vickrey auctions, BDM) assume thatpreferences adhere to expected utility theory. They lose their truth-revealingproperties under violations of the independence axiom (e.g., Holt 1986).None of the reasons for misrepresentation implies a theoretical flaw inBDM but merely possible empirical challenges, as was pointed out by onereviewer.

that followed through with their purchase obligation (if p ≤WTP). Only 2.5% (1 of 41) refused to comply with theirpurchase obligation in the Coke study, and 7.5% (3 of 40)refused to buy in the cake study. Buyers’ ratings of how sat-isfied they were with their purchases were high (M = 4.17,s = .83 for Coke, M = 4.03, s = .73 for cake on a five-pointscale). The large majority of nonbuyers (if p > WTP) did notregret that they had not made a higher price offer and reaf-firmed their preference for not buying. This argues againstthe possibility of significant strategic underbidding. Only3.4% (2 of 59) in the Coke study and 6.7% (4 of 60) in thecake study said they should have offered a higher price. Ofthese six, five subjects said that they would have liked to buyat the purchase price they had randomly drawn. Finally, weasked for ratings of how much value the purchase providedto those who bought (if p ≤ WTP) or would have providedat the drawn price to those who did not buy (if p > WTP).The overall means were M = 2.91 (s = 1.22) for Coke andM = 3.23 (s = 1.07) for cake (on a five-point scale). Thesevalue ratings are significantly correlated with a measure ofconsumer surplus (WTP – p), r = .66 (p < .0001) for Cokeand r = .59 (p < .0001) for cake. Overall, the high purchaseobligation compliance rates and satisfaction ratings, the lowincidence of regret by nonbuyers, and the strong correlationbetween consumer surplus and transaction evaluations attestto the high criterion validity of BDM.

Discussion of Studies 1 and 2

Studies 1 and 2 suggest that BDM is a reliable and validmethod to determine consumer WTP. It outperforms pricematching, a conventional open-ended contingent valuationapproach, on measures of reliability and face, internal, and cri-terion validity. Yet several questions remain.

Incentive compatibility and strategic behavior. First, isBDM truly incentive compatible (i.e., the dominantresponse strategy is to bid one’s true WTP)? It is based onVickrey’s (1961) principle of making the distribution of pur-chase prices exogenous to respondents’ valuations, and itmirrors BDM’s (1964) original procedure for eliciting will-ingness to accept. Yet, as noted previously, respondents inVickrey auctions often bid above their WTP. Is it similarlypossible that BDM respondents misrepresent their WTP?There are at least three possible reasons for this conjecture.3

First, BDM may not be truth revealing if subjects’ normativeresponse goals extend beyond the immediate survey context.But the belief-based strategic misrepresentation we noted pre-viously may occur under all response formats (Carson, Groves,and Machina 1999), whether they are theoretically incentivecompatible (including Vickrey auctions and BDM) or not. Theargument holds for all marketing research methods and doesnot predict a difference in WTP between BDM and pricematching, in contrast to our findings in Studies 1 and 2.

Second, if respondents are uncertain about their valuations orwant to maintain control over whether to buy, rather than havethe transaction imposed on them, they may overstate their WTPto maximize their chances of becoming eligible to buy at thenext stage. After all, if they then believe that the price drawn

from the urn is too high, they may simply walk away from theirpurchase obligation. Note that this argument, too, applies toVickrey auctions (Hoffman et al. 1993). But only a small frac-tion of our respondents in the two studies (4 of 91) reneged ontheir purchase obligations. More important, Casey and Delquié(1995) find such strategic behavior in choice-based elicitationof WTP only when costs are explicitly framed as losses ofmoney but not when they are framed as payments in a transac-tion (as under BDM), which argues against this notion of strate-gic rule violations.

A third possible reason for strategically overstating trueWTP is that subjects may want to ensure that they do not walkaway empty-handed after they are engaged in the elicitationprocess, a form of escalation of commitment. Similarly, Kagel,Harstad, and Levin (1987) suggest that respondents in Vickreyauctions strategically overbid to increase their chances of win-ning. The expected cost of such overstating is negligible (onlypennies more), as respondents may well pay less than theirstated prices (Kagel 1995). Study 3 is a laboratory experimentdesigned to test this argument.

Differential attention. A second open question is whetherBDM outperforms price matching and produces lowerWTPs because it imposes an incentive constraint on respon-dents or simply because it induces more careful considera-tion of the value they place on an object. The preferencereversal literature (e.g., Carmon and Simonson 1998) sug-gests that price matching induces greater price sensitivitythan choice tasks do, because directly asking respondentsfor their WTP makes price, as an attribute, more salient thanit would be in a usual market setting. Might BDM exacer-bate the price sensitivity found in price matching tasks? Todetermine the role of the incentive constraint versus thesalience of price, Study 3 compares BDM with a choice-based elicitation procedure that is not incentive compatibleeither but that forces subjects to consider their responsescarefully and thus makes price equally salient.

Domain of applicability. A third open question involvesthe domain of applicability of BDM. The method isdesigned for products that can be made available at the siteof the survey, at the point of purchase. Thus, Studies 1 and2 show that BDM performs well for inexpensive food prod-ucts that are characterized by instantaneous demand. As ameasure of face validity, note that “craving” is a better pre-dictor of WTP for the two food and beverage items than“liking,” consistent with the idea that demand for such itemsis subject to “visceral” factors whose intensity fluctuateswith subjects’ hunger and thirst (Loewenstein 1996). Thisresult confirms that BDM is well suited for point-of-purchase contexts, in which consumers are interested inmaking an immediate purchase of a single item. However,applying it to big-ticket durables would require greater liq-uidity from respondents (e.g., carrying checks or creditcards) as well as a more complex survey context, in whichthe researcher can enforce purchase obligations and deliverproducts immediately. Short of these more complex condi-tions, can we apply BDM to nonfood items such as inex-pensive durables, for which demand is affected by currentinventory? Study 3 examines this question as well.

STUDY 3: STRATEGIC BEHAVIOR, INCENTIVECONSTRAINT, AND APPLICABLE DOMAIN

A laboratory experiment addresses these three issues. First,although there is no gold standard for measuring WTP because

Point-of-Purchase Willingness to Pay 235

it is impossible to know subjects’ unobservable true WTP, wecan test for strategic overbidding due to an escalation of com-mitment by varying the conditions for such an escalation ofcommitment. Thus, we manipulate whether subjects receivecompensation for their participation in BDM independently oftheir bids, enabling those who receive compensation not towalk away empty-handed even if they do not transact. We alsoexamine whether BDM responses reflect a desire to maintaincontrol over the purchase decision as another possible reasonfor strategic behavior.

Second, we compare BDM with a repeated choice–basedprocedure that imposes comparable demands on respondents’efforts and attention. This enables us to isolate the effect of theincentive constraint (i.e., of the immediate behavioral conse-quences) on WTP from possible effects (1) of insufficient cog-nitive resources being devoted to the task and (2) of lowersalience of price in the price-matching tasks in Studies 1 and 2.Specifically, we use a variant of Gabor and Granger’s (1966)price list procedure, in which subjects state whether they wouldwant to buy an item at each of several price points. Many vari-ants of this technique have appeared in the literature. In closed-ended or binary discrete choice contingent valuation, each sub-ject states for only one price whether he or she would buy atthat price (e.g., Cameron and James 1987). A more efficientvariant, double-bounded discrete choice, is also often used incontingent valuation surveys. Subjects state two purchase deci-sions. Conditional on their response to an initial price, subjectsare given a follow-up price that is either higher or lower thanthe initial one. The underlying WTP distribution as a functionof a set of independent variables (e.g., product attributes,respondent characteristics) is estimated from the choice proba-bilities with maximum-likelihood techniques (Alberini, Kanni-nen, and Carson 1997; Hanemann, Loomis, and Kanninen1991). We use this double-bounded approach and narrow downthe range within which a subject’s WTP lies even further, fol-lowing a choice bracketing technique reported by Casey andDelquié (1995).

The third purpose of Study 3 is to examine if BDM can alsobe applied to inexpensive durable goods. We elicit WTP for aballpoint pen in a laboratory context in which subjects cannotbe assumed to be in the market for a pen. This departure froma typical point-of-purchase use of BDM enables us to test howsensitive the method is to variations in subjects’ readiness tobuy.

Method

Subjects and stimuli. At a private northeastern university,255 undergraduate students were recruited to participate inthis experiment. When they arrived at the experimentalroom, they were told that the experimenter was interested indetermining their WTP at that moment (in the lab) for anewly designed ballpoint pen with an ergonomic cushiongrip. The experimenter then showed them this focal pen,along with two other pens for comparison purposes, and letthem examine and try out each of the pens. The focal pencost $5.49 at retail, and the other two pens cost $9.99 and$.20. Subjects were told only the last two prices.

Design and procedure. After this introduction, subjectswere randomly allocated to one of three conditions. Subjectsin the first two conditions were offered an opportunity topurchase the focal pen from the experimenter in the labora-tory under BDM. The distribution of prices in the urn wasuniform, ranging from $.00 to $10.00 in increments of $.25,

4We also applied the same transparency, acceptability, compliance, satis-faction, and regret measures as in Studies 1 and 2. The results were similar,so we do not report them here.

in line with retail prices of the reference pens. We did notreveal this distribution to the subjects. The specific instruc-tions and procedure followed those for Studies 1 and 2 (seethe Appendix). In one of these conditions (BDM-M&Ms),we gave subjects a bag of chocolate candy before theystarted the procedure. In the other condition (BDM-noM&Ms), they did not get any compensation. This manipula-tion was meant to test whether the possibility of walkingaway from the procedure empty-handed affected WTP.

Subjects in the third condition (BRACKETS) were given abag of candy as compensation for their participation but werenot offered an opportunity to purchase the pen. Instead, theywere asked to make a series of hypothetical buy/do not buychoices at different price points, imagining that the experi-menter was selling the pen in the laboratory. Figure 3 describesthe procedure. Specifically, subjects were asked whether theywould buy the pen for $5.00. If the response was “no” (“yes”),a follow-up price of $2.50 ($7.50) would be presented. Contin-gent on a subject’s response to that price, one of four lists ofnine or ten additional prices was then presented in steps of $.25.This narrowed down the price range to a small enough intervalso that the experimenter asked subjects directly how muchexactly they were willing to pay. The presentation order ofthese incremental prices (increasing or decreasing) was coun-terbalanced across subjects and had no effect on subjects’responses, so we pooled the data. Both BDM and BRACKETStook eight to ten minutes to administer.

Manipulation checks. Immediately after describing theprocedure, we presented subjects with checks of whethergiving them M&Ms reduced the conditions for an escalationof commitment that might cause strategic responses. Weasked them to rate on nine-point scales whether theybelieved they were obtaining something tangible for partici-pating and whether they believed they would walk awayfrom the experiment empty-handed if they did not transactunder BDM (for the questions, see Table 3).

Dependent measures. Dependent measures were subjects’WTP and their subjective estimates of how much they nor-mally paid for ballpoint pens. Subjects also rated howimportant it was to them to maintain control over whetherthey could buy, and they stated which of the three pens theywould most prefer to buy at the given prices, that is, theirstated WTP for the focal pen and the listed prices for the tworeference pens. Finally, we also asked them to rate on nine-point scales how much of a need they felt for the focal pen,how attractive and ergonomic they found it, and how impor-tant it was for them to write with an attractive andergonomic writing instrument (Table 3).4

Results and Discussion

Manipulation checks. The manipulation of the conditionsfor an escalation of commitment was successful (Table 3).Although there was no difference between subjects whoreceived a bag of M&Ms in BDM-M&Ms and in BRACK-ETS (t = –.14, p < .89), both believed more strongly thansubjects in BDM-no M&Ms that they were getting some-thing tangible for participating (t = 9.82, p < .0001 and t =

236 JOURNAL OF MARKETING RESEARCH, MAY 2002

Figure 3CHOICE BRACKETING PROCEDURE (BRACKETS CONDITION) IN STUDY 3

Would you pay?(circle “yes” or “no”)

$10.00 yes [___] no [___]. If no, how much exactly? $ [______]$9.75 yes [___] no [___]. If no, how much exactly? $ [______]$9.50 yes [___] no [___]. If no, how much exactly? $ [______]$9.25 yes [___] no [___]. If no, how much exactly? $ [______]$9.00 yes [___] no [___]. If no, how much exactly? $ [______]$8.75 yes [___] no [___]. If no, how much exactly? $ [______]$8.50 yes [___] no [___]. If no, how much exactly? $ [______]$8.25 yes [___] no [___]. If no, how much exactly? $ [______]

yes $8.00 yes [___] no [___]. If no, how much exactly? $ [______]$7.75 yes [___] no [___]. If no, how much exactly? $ [______]

$7.50$7.25 yes [___] no [___]. If no, how much exactly? $ [______]

yes no$5.25 yes [___] no [___]. If no, how much exactly? $ [______]

$5.00$4.75 yes [___] no [___]. If no, how much exactly? $ [______]

yesno $2.75 yes [___] no [___]. If no, how much exactly? $ [______]

$2.50$2.25 yes [___] no [___]. If no, how much exactly? $ [______]

no $0.00 yes [___] no [___]. If no, how much exactly? $ [______]

5All t-tests are based on unequal variances. Between-subjects analyses ofvariance with planned contrasts of all dependent measures revealed thesame effects.

9.78, p < .0001, respectively).5 Moreover, under BDM, sub-jects who received M&Ms believed more strongly thanthose who did not that they would get a fair deal rather thanwalk away empty-handed if they did not transact (t = 4.30,p < .0001).

Strategic behavior. This experiment had three purposes:First, we wanted to test for strategic overbidding due toescalation of commitment or to a desire to maintain controlover the purchase decision. As shown in Table 3, a t-testfailed to reveal a difference in mean WTP between the twoBDM conditions (t = –.50, p < .62), which we would haveexpected if BDM induced an escalation of commitment andled subjects to strategic overbidding so that they did notwalk away from the procedure empty-handed. Thus, reduc-ing the conditions for such an escalation of commitment bypaying subjects for their participation does not significantlydampen WTP under BDM. Also, if BDM encouraged over-bidding because subjects with uncertain preferences wantedto make it to the second stage of the procedure to ensure thatthey have the final choice of whether to buy or simply walkaway, subjects should display a desire to maintain controlover whether they can buy. But the negative mean ratings inTable 3 show that subjects in neither BDM conditionbelieved that it was important to maintain control over thepurchase situation (t = –3.68, p < .001 with M&Ms; t =–3.59, p < .001 without M&Ms).

The effect of the incentive constraint. The second purposeof this experiment was to examine whether differences inWTP estimates under BDM and price matching could be

due to the incentive constraint imposed under BDM or sub-jects simply devoting insufficient cognitive resources totheir price-matching responses. The BRACKETS conditionhad been designed to elicit comparable cognitive effort fromsubjects and make price equally salient so that any differ-ence in WTP between BDM and BRACKETS would derivefrom the incentive constraint under BDM. Logit analyses ofpurchase probabilities Pr(buy|p) = ea + b × p/(1+ ea + b × p)indicated downward sloping demand, with a = 2.72 (p <.0001) and b = –.89 (p < .0001) for BRACKETS, a = 2.20(p < .0001) and b = –1.84 (p < .0001) for BDM-M&Ms, anda = 1.96 (p < .0001) and b = –1.49 (p < .0001) for BDM-noM&Ms. Analyses of Fisher Z–transformed correlationsbetween observed and expected demand (Figure 4) showedno differences in model fit between BRACKETS (r = .992,Z = 2.74) and BDM (r = .989, Z = 2.61 with M&Ms [z =–.56, p < 1]; r = .988, Z = 2.56 without M&Ms [z = –.75, p <1]). This suggests that BDM has similar reliability and inter-nal validity to an elicitation method that requires subjects toconsider more carefully the value they place on an object.However, Table 3 shows that, as predicted, mean WTP washigher in BRACKETS than in either BDM condition (t =7.45, p < .0001 with M&Ms; t = 5.21, p < .0001 withoutM&Ms). Because BRACKETS was designed to make priceequally salient, this suggests that the incentive constraintalone can cause differences in WTP estimates betweenBDM and contingent-valuation approaches. This resultreplicates our findings in Studies 1 and 2, which showed thatWTPs under non–incentive-compatible price matching werehigher than under BDM.

Domain of applicability. The third purpose of the experi-ment was to examine the performance of BDM whenapplied not to food but to an inexpensive durable, for whichdemand depends on current inventory. Table 3 shows that a

Point-of-Purchase Willingness to Pay 237

Table 3MANIPULATION CHECKS, DISTRIBUTION OF WTP, AND MEANS OF RESPONDENT CHARACTERISTICS ACROSS CONDITIONS

(STANDARD DEVIATIONS IN PARENTHESES) IN STUDY 3

BDM- BDM-M&Ms no M&Ms BRACKETS

(n = 80) (n = 85) (n = 90)

Are you getting something tangible out of your participation in this survey?a 6.64e 3.22e, f 6.59f

(2.21) (2.26) (2.29)

Would not being able to buy feel more like “walking away empty-handed” 6.19e 4.34e n.a.( = 1) or more like “a fair deal” ( = 9)?a (2.52) (2.99)

Mean WTPb $1.24e $1.33f $3.04e, f

(.93) (1.21) (1.87)

How much do you normally pay for a ballpoint pen? (in $) $1.12 $1.34 $1.35(.86) (1.49) (1.18)

WTP minus normally paid price for pens $.12e $.15f $1.85e, f**(1.11) (2.45) (1.94)

How important was it to you to maintain control over whether or not you –.96* –.96*could buy?c (2.34) (2.48) n.a.

Which of the three pens at the given prices would you most prefer to buy? (share of focal alternative, χ2 = 22.8*) 85%e 81%f 56%e, f

How much do you feel you need this particular ballpoint pen?a 2.13g 2.44 2.69g

(1.46) (1.86) (1.93)

Weighted attractiveness of

•How attractive and ergonomic did you find the ballpoint pen I offered you? 3.93 4.13 4.27

•How important is it to you to write with an attractive and ergonomic writing instrument?a, d (1.68) (1.99) (1.70)

aResponses were given on a nine-point scale (1 = “not at all,” 9 = “very much”).bThe price is either the final price offer (BDM) or the stated price (BRACKETS).cResponses were given on a nine-point scale (1 = “not at all,” 9 = “very much”) rescaled from –4 to +4.dThe square root of product of attractiveness and importance ratings.e, fValues with the same superscripts differ at p < .0001 in a t-test with unequal variances.gValues with the same superscripts differ at p < .05 in a t-test with unequal variances.*p < .001 (different from 0).**p < .0001 (different from 0).Notes: The minimum prices in all conditions were zero; there is one missing value each in the BDM-no M&Ms and BRACKETS conditions. n.a. = not

applicable.

greater percentage of subjects preferred the focal pen (attheir stated WTP) over the comparison pens (at the givenprices) in either BDM condition than in BRACKETS (χ2 =22.8, p < .001). This suggests that even for nonfood items,for which demand is not driven by visceral consumptionimpulses, BDM enables subjects to derive their WTP in agiven purchase situation more accurately and with greatercertainty about their preferences.

To determine the causes of this superior performance, wecompared subjects’ WTPs with their estimates of the pricesthey normally paid for a ballpoint pen (Table 3). In BRACK-ETS, mean WTP exceeded the mean estimate of normally paidprices (t = 8.96, p < .0001), which was not the case in eitherBDM condition (t = .95, p < 1 with M&Ms; t = .56, p < 1 with-out M&Ms). We also regressed WTP on subjects’ ratings oftheir need for the focal pen, the square root of the product oftheir ratings of the pen’s attractiveness and their importanceweights, and their estimates of normally paid prices (Table 4).The only predictor of WTP in BRACKETS was subjects’ esti-mates of normally paid prices (b = .89, t = 5.23, p < .0001).Consistent with the findings in Studies 1 and 2, this suggeststhat WTP is driven by subjects’price memories rather than theirassessment of the value of the good in the current purchase con-text when it is elicited under a hypothetical response format. Itis as if subjects start with what they normally pay and then

adjust that estimate upward to derive their WTP. In contrast,WTP under BDM was predicted by the weighted attractivenessratings (b = .16, t = 2.30, p < .05 with M&Ms; b = .30, t = 2.51,p < .05 without M&Ms), which suggests, as predicted, thatBDM leads subjects to derive their WTP as a function of theperceived value of the good in the specific purchase situation.

OVERALL DISCUSSION AND CONCLUSIONS

Summary

Our studies demonstrate that BDM provides a feasible, reli-able, and valid market research procedure to elicit consumerWTP in specific point-of-purchase settings in fast-moving con-sumer goods markets. Relatively little cost, time, and effort areneeded to administer BDM. Studies 1 and 2 showed that face,internal, and criterion validities were high and compared favor-ably with a conventional open-ended contingent valuationapproach of hypothetically asking consumers to state theirWTP (price matching) for grocery items. Study 3 showed thatBDM is equally well suited for inexpensive durables, that theincentive constraint is key to its performance, and that there wasno evidence of overbidding, in contrast to empirical findings intests of Vickrey auctions (Kagel 1995).

A key result across all three studies is that consumersreported substantially lower WTP under BDM than under

238 JOURNAL OF MARKETING RESEARCH, MAY 2002

Figure 4OBSERVED AND PREDICTED DEMAND IN STUDY 3

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hypothetical response formats. This difference adds to similarfindings of hypothetical bias compared with other incentive-compatible formats across 39 studies reviewed by Harrison andRutström (2002), including the experimental results of Neilland colleagues (1994) for open-ended and Cummings, Harri-son, and Rutström (1995) for dichotomous choice contingentvaluation. For example, Neill and colleagues (1994) comparedWTP in continent valuation with WTP in hypothetical and(otherwise identical) real Vickrey auctions. They found thatWTP under the two hypothetical response formats exceededWTP in real Vickrey auctions by far, implying that the lack ofeconomic commitment rather than the absence of a structuredinstitution in contingent valuation causes the bias in hypotheti-cal WTP responses. This is also borne out in Study 3, in whichhigher WTP was found in the fairly structured BRACKETScondition than in BDM. Our findings suggest that stated-preference methods may lead managers to overprice comparedwith consumers’ true WTP, unless hypothetical surveyresponses can be recalibrated if the bias is known and stable(Harrison and Rutström 2002).

In addition, our results suggest that BDM provides a bettermeasure of consumers’ true point-of-purchase WTP, becauseconsumers in Studies 1 and 2 tended to round prices when

responses were only hypothetical, whereas BDM WTPs weremore differentiated. Study 3 showed that non–incentive-compatible responses depend on the prices consumers nor-mally pay in the category, whereas the incentive constraintunder BDM helps respondents determine their WTP on thebasis of the point-of-purchase context.

Limitations and Further Research

Our research has several limitations. First, because BDMrelies on actual transactions, it can be applied only to existingproducts (i.e., old products at new points of purchase or newproducts and prototypes). Unlike conjoint analysis, it cannot beused in concept design and new product development. Second,liquidity constraints may bias demand downward for higher-priced products and big-ticket items. Yet researchers may over-come these constraints by adapting the conditions under whichBDM is applied as much as possible to those consumers facewhen they buy big-ticket items. Respondents would not berequired to pay cash but could also be allowed to pay by checkor credit card or to take a loan from the market researcher (seeCummings, Harrison, and Rutström 1995). In addition, respon-dents may need extra time to think about their responses, aswell as additional information from trusted sources such as

Point-of-Purchase Willingness to Pay 239

Table 4MULTIPLE REGRESSION PREDICTORS OF WTP (STANDARD ERRORS IN PARENTHESES; TWO MISSING VALUES EACH IN BDM-

NO M&MS AND BRACKETS CONDITIONS) IN STUDY 3

BDM-BDM-M&Ms no M&Ms BRACKETS

Question (n = 80) (n = 83) (n = 88)

Intercept .19 .48 1.01(.25) (.32) (.50)

How much do you feel you need this particular ballpoint pen? .13 .00 .22(.08) (.08) (.12)

Weighted attractiveness of

•How attractive and ergonomic did you find the ballpoint pen I offered you? .16* .17* .18

•How important is it to you to write with an attractive and ergonomic writing instrument?a (.07) (.07) (.14)

How much do you normally pay for a ballpoint pen? ($) .15 .10 .53**(.11) (.09) (.17)

R2 .22*** .10* .25†

aSquare root of product of attractiveness and importance ratings.*p < .05.**p < .01.***p < .001.†p < .0001.Notes: Responses were given on a nine-point-scale (1 = “not at all,” 9 = “very much”).

Consumer Reports. To assure respondents of the legitimacy ofthe transaction, researchers may need to provide third-partyauthentication, for example, by a notary or other authenticationservice. More important, if BDM is applied at the targeted pointof purchase for big-ticket items, such as inside a departmentstore, the results should reflect how ready to buy consumers areunder real transaction conditions. Conceptually, BDM shouldthus be suited for products and services across all price ranges,given sufficient researcher credibility and trustworthiness.Nonetheless, further research should determine the relative per-formance and feasibility of BDM for big-ticket items. Finally,we tested BDM in monopolist purchase settings, as the specificpoint of purchase did not matter for our validation purposes.What happens when substitute products are available at thepoint of purchase? We predict that WTP varies inversely withthe surplus consumers can derive from these substitutes.

Conclusion

The BDM procedure enables researchers to elicit WTP in anincentive-compatible manner in specific point-of-purchase con-texts and under the controlled influence of marketing-mix vari-ables (e.g., WTP for candy bars on display at supermarketcheckout counters where a retailer may try to induce impulsebuying). As shown here, BDM can serve as a stand-alone (off-or online) procedure, or it can be combined with existing pref-erence elicitation techniques and pretest market research todevelop better insights into the factors that influence consumerchoice and product valuations (Huber et al. 1993).

In addition, BDM provides an alternative to auctions formarketers to price-discriminate in regular online transactions(using a transparent online random device). The surface fea-tures of BDM might resemble those of reverse auctions. Forexample, at Priceline.com, retail customers make binding bids,backed by a required credit card authorization. A participatingvendor can then reject or accept the bid, depending on thedesired margin. This enables vendors to generate incrementalrevenue and capacity utilization without disrupting their exist-

6For every purchase, the vendor forgoes and the bidder keeps WTP – swith Priceline and WTP – p with BDM. Therefore, vendors should preferBDM if E(pBDM) > E(sPriceline), which depends on the distribution of buy-ing prices (pBDM) the vendor chooses. Note that the lower bound of the dis-tribution would normally be given by the vendor’s marginal cost. Vendorsmay give customers information on the underlying price distribution to cre-ate anchoring effects (Bohm, Lindén, and Sonnegård 1997).

ing distribution channels or retail pricing structures. However,reverse auctions are not incentive compatible. Customers paywhat they bid (s), so they must bid less than their true WTP ifthey want to obtain surplus from the transaction. The BDM pro-cedure solves that problem. The random mechanism providesan incentive for customers to bid their true WTP. Thus, a ven-dor can better price-discriminate against successful bidders.6The vendor can also make follow-up offers to those who are notallowed to buy on the basis of their WTP. For example, onlineauctioneer Onsale successfully targeted nonwinning bidderswith tailor-made e-mail offers that were based on the bids it hadelicited from them previously (Moon 1999). Thus, BDM couldsell Goethe’s Hermann and Dorothea under incentive-compatible conditions again one day.

APPENDIXINSTRUCTIONS GIVEN BY THE INTERVIEWER

The BDM instructions the interviewer read to the subjects inStudies 1 and 2 are as follows:

Initial Instructions

Hello! I am a researcher from the University of Kiel and amconducting a marketing survey here on the beach (ferry). Thesurvey takes only a few minutes. I am wondering if you wouldlike to participate. You will need a small amount of money,because I will offer you an opportunity to buy a can of Coca-Cola (a piece of pound cake). You will not have to spend anymore for the Coke (cake) than you really want to. I’d like toknow how much money you are willing to spend for this can of

240 JOURNAL OF MARKETING RESEARCH, MAY 2002

Coke (piece of cake) here on the beach (ferry). The purchaseprice is not yet determined. Please tell me the highest price youwould be willing to pay. You may then draw a ball from thisurn. The balls are labeled with different prices. If you draw aprice that is less than or equal to the price you tell me, you willhave to buy the Coke (cake) for the price you drew from theurn. If the price you draw is greater than the price you tell me,you will not be able to buy the Coke (cake). This procedureensures that it is best for you to truthfully reveal the maximumprice you are willing to pay. If you tell me a price that is higher,you may actually have to pay that higher price. If you tell me aprice that is lower, you may be disappointed if you can’t buy ifyou draw a price that is higher than the price you tell me butlower than your “true” price. Note that you cannot influence thepurchase price with the price you tell me. Because you draw thepurchase price from the urn, it is completely random and inde-pendent of whatever you tell me. Do you have any questions?

Initial Price Offer

Now, what is the maximum amount you are willing to payfor this can of Coke (piece of cake)? [The subject states aprice.] If you now draw a price that is less than or equal to theprice you just stated, I will sell you the Coke (cake) at the priceyou drew from the urn. However, if you now draw a price thatexceeds the one you just stated, I will not sell you the Coke(cake).

Option to Revise

If you now drew a price that is DM .10 higher than the priceyou just stated, would you consider buying the Coke (cake)after all? If so, please tell me the true maximum price at whichyou would be willing to buy. [The subject continues to statehigher prices, until he or she would not consider a purchaseanymore at a price that is DM .10 higher than stated.]

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