Electron Markets (2010) 20:119–129 DOI 10.1007/s12525-010-0033-z

FOCUS THEME

Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel

Tuo Wang & Michael Y. Hu & Andy Wei Hao

Received: 25 August 2009 /Accepted: 23 February 2010 /Published online: 29 April 2010 # Institute of Information Management, University of St. Gallen 2010

Abstract This study examines the Name-Your-Own-Price is low (high expected consumer surplus from buying at list (NYOP) retailer’s information revelation strategy when price); (3) provide both the upper and lower bound of its competing with list-price channel. We propose an integrated threshold price when consumer surplus of buying at list economic framework focusing on the comparison of price is unknown. expected consumer surplus from at NYOP and guaranteed consumer surplus from buying at a list Keywords Name-Your-Own-Price (NYOP) . . price. We then conduct an empirical study to examine the E-tailing . Multi-channel selling effects of seller-supplied price information on NYOP bidding outcome (especially on expected winning proba- JEL D4 bility and the number of bidders). The results of our study strongly indicate the effects of seller-supplied information on expected winning probability (as well as the expected Introduction consumer surplus) in a NYOP auction. We also illustrate the strategic implications of seller-supplied price informa- With the advance of Internet and computer technologies, tion via a revenue simulation for the NYOP seller. Our many products and services are now offered in non- results suggest that NYOP seller may increase his expected traditional pricing formats. One of the most innovative revenue by (1) provide only the upper bound of its pricing mechanisms is Name-Your-Own-Price (NYOP) threshold price when list price is high (low expected exemplified by Priceline.com. This format is quite different consumer surplus from buying at list price); (2) provide from traditional pricing practices. Instead of the seller only the lower bound of its threshold price when list price setting the price so that buyers choose to buy or not buy at a list price, every buyer can now indicate a price (a bid) that Responsible editor: Martin Spann he/she is willing to pay so that the seller can choose to T. Wang (*) accept or reject this bid. There also exist significant Kent State University, differences among NYOP practices. One of them is the Room 532, BSA, allowed rounds of bidding. If the NYOP bidding can be Kent, OH 44242, USA repeated, it is multiple-bid NYOP (such as a German travel e-mail: [email protected] firm discussed in Spann and Tellis 2006); otherwise, it A. W. Hao becomes a single-bid NYOP (this is Priceline’s bidding University of Hartford, policy). In this paper, we focus on the single-bid mecha- 200 Bloomfield Avenue, nism which is adopted by Priceline.com. Although NYOP West Hartford, CT 06117, USA e-mail: [email protected] is similar to auction, differences are significant (Chernev 2003): (1) bidders do not compete directly among them- M. Y. Hu selves. All bids are compared to a certain threshold price Kent State University, known only to the seller; (2) the lack of a clearly defined Room 526, BSA, Kent, OH 44242, USA reference price (opening bid, appraised value, etc.): bidders e-mail: [email protected] name a price without an explicitly available reference point. 120 T. Wang et al.

On the other hand, the NYOP seller has the option to We look at the information revelation strategy (the provide any other reference price points, if doing so is choice of reference point format) of the NYOP seller under likely to increase his revenue. In fact, Chernev (2003) different scenarios. Specifically, we examine two issues: found that consumer preference for a NYOP method (1) The effects of seller-supplied price information on increases when a readily available reference price range is bidders’ expected winning probability and their provided (due to the easiness of decision). He also expected consumer surplus. suggested that NYOP seller can benefit from offering (2) The effects of list price (or guaranteed consumer reference price points by creating an easier NYOP process surplus) on the revenue of a NYOP seller and his for bidders. Although easiness of decision is a major information revelation strategy. concern for potential customers, we believe that the appeal of NYOP channel ultimately depends on the economic Our main focus of this paper is on the implications for a incentive when compared to list price channel. Extant NYOP seller when different information formats are literature is not consistent, however, on the economic presented to potential consumers. Unlike Ding et al. effects of seller-supplied reference price in an auction: (2005) and Wolk and Spann (2008) where bid propensity significant positive correlation between reference price and or purchase intention is measured, we induce the bid valuation/bids is reported by Kamins et al.(2004) under propensity by comparing respective consumer surpluses eBay style auction, Wolk and Spann (2008) find only under buying at list price and bidding at NYOP auction. limited influence on bidders’ value in an interactive NYOP With our understanding of these effects of seller-supplied auction. In addition, they find such effects are moderated by information, it is possible to evaluate information revelation the believability of seller-supplied reference price. Besides policies to enhance a NYOP seller’s revenue. the bid value submitted by consumers, the number of This paper is organized as follows. First, we construct a auction participants is another important factor for NYOP conceptual framework of the NYOP mechanism based on seller’s revenue. Contrary to traditional list price format, the basic economics of expected consumer surplus. Second, Kamins et al. (2004) and Wolk and Spann (2008) both we empirically investigate the effects of price information show that the presence of a seller-supplied reference price formats on consumers’ perceived value, bids and expected significantly decrease the number of participants in an eBay winning probability. Finally, we perform a revenue simu- style auction or the purchase intention in an NYOP style lation to illustrate the appropriate information revelation auction, respectively. It is believed that people with lower strategy for a NYOP seller. valuation no longer expect to win and will drop from the auction due to lower expected consumer surplus (Wolk and Spann 2008). Although Wolk and Spann (2008) found Literature review limited influence of seller-advertising reference prices, they also recognized that different forms of providing reference As a new pricing mechanism, NYOP is catching academic prices to bidders could help NYOP sellers to positively interest due to its uniqueness and its potential to be an influence consumers. important outlet for the service industry. Previous research Because a NYOP seller’s revenue is the sum of all on the NYOP model has focused on three separate issues: accepted bids, it is important to know the combined effects of seller-supplied reference price on the revenue of an (1) The optimal design of NYOP auction: whether to NYOP seller. Providing reference price makes economic allow repeat bidding (Fay 2004) and the estimation of sense to the seller only when revenue goes up with both the haggling cost for NYOP bidders (Hann and Terwiesch final bid value and number of bidders taken into consider- 2003); ation. Such a study requires a comprehensive economic (2) The rationality and emotion of bidders at the NYOP framework by explicitly investigate the expected consumer channel (Spann and Tellis 2006; Ding et al 2005). surplus in a NYOP auction when compared to that of Their findings also showed that as popular as NYOP buying at a list price. might be, it is relatively new and little is known about In this paper, we intend to answer the following its impact on the market; and questions for a NYOP seller: (3) The effect of reference price on NYOP bidding behaviours: Using experimental data, Chernev (2003) & Would the NYOP seller be better off by providing showed that by providing an external reference price reference price information to the bidders? range, consumers are more likely to favor naming a & If so, what form of reference price information should price than the condition under which reference price be provided to the bidders under different list price range is absent. He suggested that the NYOP seller levels to increase revenue for the NYOP seller? should make bidding easier by providing a readily Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel 121

available reference price range. Wolk and Spann list price or participating in NYOP auction, the comparison (2008) showed that doing so have only limited impact of consumer surplus between the two alternatives creates a on NYOP bidders, with the effects moderated by foundation for calculating their bid propensity at NYOP believability of reference price information. auction. Economics suggested that it was benefi- Pricing literature lends substantial support for the impact cial for the seller not to intentionally hide information from of both internal and external reference prices on consumers’ bidders (Milgrom and Weber 1982). As noted by Levin and buying behavior (see Monroe 2003) and bidding behavior Smith (1994), traditional auction theory assumes a fixed (i.e. Kamins et al. 2004). With final bid as the outcome of number of bidders when comparing expected revenue from eBay styled , it was found to be greatest different auction designs. The focus of these studies was on when only a high external reference price was presented, the bid price itself. When number of bidders (auction entry) lowest when only a low external reference price was is considered, Levin and Smith (1994) found that revealing presented, in the middle when the seller did not commu- seller’s minimum acceptable price discourage entry. Recent nicate any reference price. It should be noted that reference studies (i.e. Bajari and Hortacsu 2003) confirmed the prices have been operationalized in many different forms, importance of endogenous entry in understanding observed e.g. aspiration price, reserve price, minimum bid, buy-it- bidding behavior at eBay’s website. This information may now price, and list price. Thus their effects on the bidding be obtained through digital social network (Hinz and Spann outcome should vary. Since the NYOP auction usually do 2008), or provided intentionally by the seller. Our study not have minimum bid to start with (no repeat bidding focus on the latter and we assume that consumers have no allowed at Priceline.com) and list price is neither deter- other information available on the secret threshold price mined nor announced by a NYOP seller, we focus on from different sources. reserve price and buy-it-now price in this paper. Reserve price in traditional auction is defined as “a price that the final bid must meet or surpass for the deal to be Theoretical model of NYOP consummated” (Kamins et al. 2004, p.622). Therefore, it establishes a bidding level “below which the seller is Basic economics of NYOP auction unwilling to part with the item” (Budish and Takeyama 2001, p.326). For the NYOP auction, a similar term would Our basic problem setting is as follows: we have a group of be the lower bound of a secret threshold price, below which potential customers and a NYOP seller (offering airline the winning probability is 0%. Another important reference tickets). Each consumer is interested in one unit of the price is the “buy-it-now” price shown in many eBay product. Consumers have to first decide whether to buy at a auctions. This is a price announced by the seller and is public list price or to submit a bid to the NYOP seller. If the “functional opposite of a reserve price” or “a maximum they decide to bid, they need to decide how much to bid. bidding level at which the seller is willing to part with the Their bids are not in competition with each other. Instead, item immediately” (Budish and Takeyama 2001, p.326). each bid is compared to a secret threshold price known only For the NYOP auction, a similar term is the upper bound of to the NYOP seller. Although the threshold price is set by his threshold price, above which the winning probability is the service provider (Wang et al. 2009), the NYOP seller 100%. has a decision to make: how should the bidders be informed Our paper goes beyond the effects of external reference about the threshold price (the price at or above which a bid price on the consumer’s bids in an auction setting and will be accepted)? As the only one who knows the easiness of the price articulation task. With list price as an threshold price, the seller can choose either to reveal some alternative, we specifically investigate the effects of seller- information about what the threshold price range1 is or to supplied price information on bid uncertainty and NYOP tell nothing at all. If he decides to reveal some information, bidders’ expected consumer surplus. Consumer surplus in then he needs to know what type of price information he microeconomic theory is defined as a welfare measure that should reveal: the upper bound of acceptable price range is equal to the difference between willingness to pay (WTP) only, the lower bound of the acceptable price only, or both and the actual price paid by an individual consumer bounds together as a range. (Marshall 1920). Bapna et al. (2008) found that consumers In order to understand the potential strategy of a NYOP extract a median surplus of at least $4 per eBay auction. seller, it seems to us that the NYOP seller needs to consider Given the importance of consumer surplus in decision the consumer’s willingness-to-bid when buying directly is a making of a potential bidder, further research on the impact of expected consumer surplus in NYOP auction is 1 The threshold price range is similar to Ding et al (2005)’s product warranted. When consumers have the choice of buying at cost, which is assumed to be uniformly distributed over a range. 122 T. Wang et al.

Fig. 1 Economics of NYOP Consumers NYOP Seller auction (Bid or buy) (Deal or no deal)

Guaranteed Consumer GCS v -LP Surplus ( ) = i Threshold B ≥ P Buy at List Price P Price (LP) Deal

Expected Consumer Surplus with B If GCS ≥ ECS i Bids (B) B < P (ECS) Submitted No Deal − ≥ = (vi Bi ) Pr(Bi P)

If GCS < ECS real option. Their bidding intention is based on a We now discuss the bidding strategy of potential comparison of expected consumer surplus between buying consumers. at list price and bidding with NYOP seller. Following Hann and Terwiesch (2003) with the added Consumers’ optimal bidding strategy concept of consumer surplus, the economics of NYOP auction is demonstrated in Fig. 1. In order to maximize their expected consumer surplus, At any given time, there is only one consumer bidding consumers need to find an optimal bidding strategy. In this against a predetermined unknown threshold price. If the section, we assume that there is no bidding cost4 and bidder consumer wins, he/she pays the bidding price. Any i is trying to maximize her expected consumer surplus with » difference between the bid and the threshold price is submitted bidBi . According to the basic utility theory (Von pocketed by the NYOP seller. As noted by Wang et al. Neumann and Morgenstern 1944) and following the (2009) and industry reports, a major NYOP seller such as notation of Wang et al. (2009), each bidder i will try to Priceline.com does not set the threshold price of the maximize their expected consumer surplus as: services (airline tickets, hotel room rates, etc.) Instead, a Max ECS ¼ðvi BiÞ PrðBi PÞð1Þ NYOP seller simply collects the threshold price information Bi from service providers and bids from potential buyers. where v is the perceived value of bidder i, and PrðB PÞis Following their study, we assume that the threshold price is i i the probability of bid B being accepted by the NYOP exogenously determined by service providers instead of i seller. NYOP sellers. Therefore, the objective of a NYOP seller is Following the assumption of Ding et al (2005), a seller’s to maximize its revenue (given the fixed threshold price). threshold price P is expected to be uniformly distributed The NYOP seller, on the other hand, does have incentive to between P and P, increase the attractiveness of the bidding process versus buying at the list price. Like traditional auctions, the NYOP ð Þ¼Bi P ð Þ seller benefits from higher bids from each consumer. Pr Bi P 2 P P Figure 1 shows that the attractiveness of NYOP in the eyes of potential consumers depends on the comparison of The first order condition for surplus maximization of (1) 2 @ECS guaranteed consumer surplus (GCS ) from buying at the list gives us ¼ vi 2Bi þ P ¼ 0; or the optimal bid of @Bi price and expected consumer surplus (ECS3) from NYOP. bidder i equals to If GCS≥ECS, then she buys directly at the list price. þ Otherwise, she is better off submitting a bid to the NYOP » ¼ vi P » > ; » < : ð Þ Bi subject to Bi 0 Bi P 3 seller. 2

2 Guaranteed Consumer Surplus is the difference between consumer’s 4 The bidding cost was estimated to be somewhere between EUR 3.54 perceived value and the list price of the item, or GCS ¼ v LP. and 6.08 in Hann and Terwiesch (2003). Since this paper follows the 3 The expected consumer surplus of her optimal bid is the product of single-bid policy of Priceline.com, the effects of bidding cost for one winning probability of optimal bid and the difference between consumer’s bid on consumers’ surplus is assumed to be ignorable; especially for perceived value and the optimal bid, or ECS ¼ðvi BiÞ PrðBi PÞ, college students whose opportunity cost of bidding time is much lower where PrðBi PÞis the expected winning probability of bid Bi. than consumers with higher income or less spare time. Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel 123

This result is the same as Ding et al (2005) under the bility of their bids should be higher/lower when only the case of infinite value of bid propensity (since we require lower/upper bound is presented. every consumer to submit a bid). Although information Previous economics studies in traditional auctions about the upper bound and the lower bound helps to reduce suggest that the disclosure of the seller’s information not bid uncertainty, the lower bound is likely to be more useful only reduces uncertainty about the common value but also in constructing an optimal bid (to maximize expected raises expected surplus for the buyer (Goeree and Offerman utility). As we can see in Eq. 3, a consumer’s optimal bid 2003). They also predicted that “the positive effects of the depends on both her perceived value of the product and the seller’s information are stronger the more precise the lower bound of acceptable price range. Without information information is” (p. 600). As winning probability is expected about the lower bound, it would be more difficult for the to be positively related to expected consumer surplus, we bidders to construct their bids. Therefore, the lower bound predict that higher valued information provided by the information not only makes it easier for bidders to submit a seller helps to increase the expected surplus for the bidders. bid, but also plays a dominant role on reducing bid Figure 2 demonstrates the relationship between seller- uncertainty for consumers. supplied price information and consumers’ perceived value,6 actual bid, and the expected winning probability Effects of NYOP seller-supplied information on expected of the bid. These dependent variables determine the revenue winning probability and number of bidders of a NYOP seller. Previous research focused on the effects of high/low reference price cue on perceived value Unlike traditional English auction, NYOP seller’s revenue and submitted bid. When a high/low reference price cue is depends on the number of bidders, especially when the presented, it was consistently found that consumers tended service providers have unused capacity. The number of to value the item high/low and submit a high/low final bid bidders, when discussed in traditional auctions, acts as a (Kamins et al. 2004). We expect the same effects of high/ mediator affecting the bid outcome through the final price. low price cue on product valuation and submitted bids in In the NYOP auction, however, the number of bidders has a the NYOP context. On the other hand, our study focuses on direct effect on the NYOP seller’s revenue. To attract more the effects of number of bidders on NYOP revenue. We bidders, the NYOP seller needs to increase expected assume that potential customers enter the NYOP auction consumer surplus by increasing expected winning proba- only when the expected consumer surplus is higher than bility of their bids. Consistent with Chernev (2003) but for that of buying at a list price (endogenous entry). Our model a different reason, we expect that by providing reference supplements extant marketing literature’sframework price information, the NYOP auction should be more whereas only the final bid (valuation) is considered. attractive to potential bidders. We believe that increased Figure 2 also shows that when auction entry is attractiveness comes from increased expected consumer endogenous in a NYOP context, the number of bidders surplus, not task easiness (Chernev 2003). will be an important component in the NYOP seller’s Bidders’ expected winning probability will be higher if revenue. With the exception of Ding et al (2005), previous the bidding uncertainty can be reduced. In a NYOP auction, literature did not take bid propensity into consideration P; P is a seller-supplied acceptable price range that when buying directly is an option. We intend to demon- corresponds to a winning probability from 0% to 100% strate that seller-supplied information not only has impact based on historical frequencies.5 For NYOP bidders, this on perceived value and bid, it may also reduce the bidding range is also a measure of bid uncertainty. With more uncertainty and increase winning probability. Since higher information and reduced uncertainty, bidders are likely to expected winning probability leads to higher consumer construct a more accurate and narrower range for the threshold surplus at NYOP channel, more bidders will be attracted to price. Since lower value of denominator leads to a higher the NYOP auction and potentially increase the total revenue winning probability of submitted bid PrðÞ¼B P Bi P, of the seller. i PP ceteris paribus, we shall expect that providing this range In the next section, we describe a NYOP pricing study. information about threshold price is likely to increase the We show the effects of seller-supplied price information on winning probability. Although all information is helpful on both consumers’ perceived value and their bids. Specifical- reducing bidding uncertainty, a reference price point with ly, we investigate the effects of four different information higher informational value should play a more dominant role formats on winning probability and expected consumer in this process. Consequently, the expected winning proba-

6 Perceived value is defined as perceived monetary value of a product/ 5 A similar concept of price range mapped to probability can be found service and is equivalent to Willingness-to-pay in Simonson and from the buyer side when they are uncertainty about their own Drolet (2004). Simonson and Drolet found Willingness-to-pay of reservation price in Wang et al. (2007). consumer products were significantly influenced by arbitrary anchors. 124 T. Wang et al.

NYOP revenue We expect the effects of high reference price cue to lift the perceived value and consequently the bid. The low reference price cue will reduce the perceived value and Number of bidders Submitted bid (B) leads to a lower bid. In addition, consumer responses to the range information will provide credence to previous effects + + being discussed. A consumer is expected to integrate both Perceived value (V) Expected winning prob. of upper and lower bound price information in their responses + submitted bid Pr (B≥ P) + to bid, value and probability. Thus we included a third + (Bid uncertainty) + treatment—range of successful bids, as a validity check for + the earlier two treatments. These three treatments are Information usefulness for Reference price cue bid construction (High/Low) (High/Low) randomly assigned to 183 undergraduate students in a major Midwest public university. The treatment conditions are balanced with respect to the number of subjects, with a total of 61 in each condition. Lower bound P Upper bound P All subjects were presented with a hypothetical scenario in which they were asked to purchase a round trip ticket Fig. 2 Effects of seller-supplied price information on the NYOP from Cleveland, Ohio to Los Angeles, California in the U. revenue S. from a NYOP seller. The seller employs a single-bid mechanism similar to Priceline.com. Subjects were in- surplus. Using the study results, we simulate the expected formed that this seller has a threshold price and all bids revenue of the NYOP seller under each price information above or equal to this threshold will be accepted and all formats. bids below this threshold will be rejected. Subjects were asked to indicate one bid and one bid only for a round trip ticket from Cleveland to Los Angeles. After reading this NYOP Study description, subjects entered the first stage and were immediately asked to: (1) indicate the perceived value7 of This study examines the effects of seller-supplied informa- this flight to them; (2) name the price he/she is willing to tion on consumer bidding behavior in a NYOP auction. pay for this flight; and (3) estimate the winning probability Previous studies suggested that external information affect of this bid. both perceived value (e.g. Kamins et al. 2004) and NYOP Next, we randomly assigned the three conditions to bidding behavior (Chernev 2003). Since NYOP is an subjects. Group 1 was presented with information about the alternative channel of list price in our model, we add a lower bound P only (operationalized as “The lowest new dependent variable (expected winning probability of successful bidding price during the last 12 months is submitted bid) to investigate the tradeoff between buying at $200.00”). Group 2 was presented with information about list price and bidding at a NYOP seller. Thus we have three the upper boundP (operationalized as “The highest suc- dependent measures from each individual i in this study: cessful bidding price during the last 12 months is $550.00”) perceived value vi, actual bid bi, and expected winning and group 3 the range (operationalized as “The price range probability of the bid Pr(bi). We conduct the trade-off by for successful bids during the last 12 months is between comparing expected consumer surplus with guaranteed $200.00 and $550.00”). We again collected information on surplus from buying directly. the three dependent measures: perceived value of the flight, As indicated previously in Fig. 2, the key treatments to be bid, and expected winning probability of the bid. Also, each manipulated in this study are the upper and low bound was asked to evaluate the usefulness of the information information of the thresholdprice.Inthisstudy,we being provided in determining the submitted bid on a 1 (not operationalized the upper or lower bound information about useful) to 10 (useful) scale. Afterwards, the subjects were the threshold price as high and low limit of the historical debriefed and thanked for their participation. distribution of successful bids. A NYOP seller will not want to release the threshold price to buyers. Doing so will induce 7 ’ We used stated value instead of induced value. Although non- bidders to bid at that exact price, thus lowering the seller s incentive compatible stated value may contain hypothetical bias, such revenue. Information on the historical successful bids will a bias exists for all bidders in our study. Moreover, the focus of this show potential bidders that these are indeed reasonable bids study is not on optimal pricing, which requires more accurate previously submitted and accepted by the seller. In addition, measures of willingness-to-pay. Our primal interest is to investigate the information revelation strategy of a NYOP seller by incorporating this information will assist consumers to gauge the proba- bidder’s expected winning probability. Induced value will likely to bility of their bids being accepted by the seller. reduce some hypothetical bias but is unlikely to change our results. Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel 125

Results Table 2 Effects of NYOP seller supplied upper bound information on bidding

As shown in Tables 1, 2, 3 and 4, lower bound information N=61 Upper bound No Difference receives a usefulness rating of 7.25; upper bound 5.62 and revealed information range 7.59. The statistical significance of the differences among these three averages is given in Table 4, F-statistic= Perceived values $435.66 $364.51 71.15** 25.22; p-value < .01. Tukey’s pairwise comparison indi- Actual bids $329.18 $265.57 63.61** − ns cates significant difference between lower bound and upper Expected winning 49.64% 53.85% 4.21% probability bound condition. In addition, when the range is provided, Expected consumer $49.39 $50.57 −1.18ns participants find it to be more useful than either lower or surplus upper bound. Information Usefulness 5.62 N/A N/A The lower bound only format significantly lowers both (1:not useful;10: useful) the perceived value from $375.82 to $358.36 (t=2.24, **p < .01ns: not significant p<.05) and the bidding price from $271.64 to $237.62 (t=3.51, p<.01). The upper bound only format significantly increases both the perceived value of the service from probability are detected between lower and upper bound in $364.51 to $435.66 (t=4.04, p<.01) and the bidding price Tukey’s test. from $265.57 to $329.18 (t=4.41, p<.01). Recall that expected consumer surplus entails a combi- It should be noted these results are quite consistent with nation of value, bid and probability. Therefore, when that associated with the range (see Table 3): the combined compared to no information condition, even if the upper effects of upper and lower bound is skewed toward the bound information increases the perceived value and bid, lower bound. As average perceived value increases from lower consumers’ expected winning probability leads to $349.43 to $377.62 (p<.05), the average of $377.62 when lower expected surplus (from $50.57 to $49.39 yielding range is presented is closer to $358.36 than $435.66, average decrease of $1.18, although not significant). In signifying the larger impact of lower bound of threshold comparison, range format yields the highest increase of price. Similar pattern is detected for the average bid. It expected consumer surplus from $44.01 to $71.98 (an decreases from $266.31 to $259.10 (closer to $237.62 than increase of $27.97, p<.01). The lower bound only format $329.62). yields an significant increase from $55.13 to $71.96 (an Statistically significant differences (as shown in Table 4) increase of $16.83, p<.01). When compared to upper are detected among the three groups along perceived value bound condition, consumers expected significantly higher differences and bid differences (F=6.56, p<.01; F=20.73, in increase in surplus (a difference of $18.01=$16.83+ p<.01 respectively). $1.18) under the lower bound condition. Statistically Table 2 shows that the expected winning probability significant difference is detected between the two condi- decreases from 53.85% in the upper bound only condition tions using Tukey’s pairwise comparison as reported in to 49.64% when no information is revealed (although not Table 4. significant). Significant increases were observed in the In summary, consistent with previous studies on tradi- other two conditions (the lower bound and range condi- tional auctions, both the upper bound and the lower bound tion). Moreover, significant differences in expected winning only formats have impact on the perceived value and bidding price (Kamins et al. 2004). Moreover, the presence of lower bound increases the bidder’s perceived winning Table 1 Effects of NYOP seller supplied lower bound information on bidding Table 3 Effects of NYOP seller supplied range information on bidding N=61 Lower bound No Difference revealed information N=61 Range info. No Difference revealed information Perceived values $358.36 $375.82 −17.46* Actual bids $237.62 $271.64 −34.02** Perceived values $377.62 $349.43 28.20* Expected winning 60.74% 53.20% 7.54%** Actual bids $259.10 $266.31 −7.21ns probability Expected winning probability 59.75% 54.10% 5.66%* Expected consumer $71.96 $55.13 16.83** surplus Expected consumer surplus $71.98 $44.01 27.97** Information usefulness 7.25 N/A N/A Information usefulness 7.59 N/A N/A (1:not useful;10: useful) (1:not useful;10: useful)

* p < .05 ** p < .01 *p <.05 ** p <.01ns: not significant 126 T. Wang et al.

Table 4 Effects of NYOP seller supplied information on bidding Note that these bidders participate in the NYOP auction (One-way ANOVA) only because they expect higher surplus than buying F-value p-value Tukey’s comparison directly at a list price. If the expected winning probability (significant at 5%) is low, the expected consumer surplus from bidding can decrease to a level too low to attract enough bidders. Some Perceived values 6.56 .002 (lower, upper) potential bidders may choose to buy at a list price. The (upper, range) number of bidders depends on the comparison of ECS Actual bids 20.73 .001 (lower, upper) (upper, range) (determined by the expected winning probability of their Expected winning 5.87 .003 (lower, upper) optimal bids) and GCS (determined by the list price probability (upper, range) available readily to the consumers). Expected consumer surplus 3.47 .03 (lower, upper), In order for the NYOP seller to maximize his revenue, (upper, range) the information revelation strategy has to achieve two Information usefulness 25.22 .001 (lower, upper), objectives simultaneously: (1:not useful;10: useful) (upper, range) (1) To attract more bidders by increasing consumers’ expected winning probability of their bids with a low probability by helping them construct the bid with higher reference price point. level of confidence. We found that revealing lower bound (2) To raise the bidding prices by increasing the perceived increases the expected consumer surplus and the attractive- value of the product with a high reference price point. ness of NYOP format. Our data also confirm the prediction The two objectives create an interesting dilemma on of economists in traditional auction (Milgrom and Weber whether an upper bound only format or a lower bound only 1982) that information disclosure from the seller raises the format or a range format or no information should be expected winning probability and expected consumer provided. This creates a unique situation for the NYOP surplus. Information revelation significantly increases the seller, unlike traditional auctions. Depending on the number attractiveness of NYOP as measured by expected surplus. of items available and the level of guaranteed surplus, different information revelation formats may be appropriate for the NYOP seller. Revenue simulation with endogenous entry Bajari and Hortacsu (2003) simulated seller revenue under different reserve price at eBay auction. In this section Since NYOP is a different bidding mechanism from tradition- we report the comparison of revenue obtained by a NYOP al auctions, particularly on the available volume of product/ seller when different level of guaranteed surplus is available service, maximizing bidding price may not be the only to consumers. objective for the NYOP seller. According to the above Four information formats were used: “no information,” discussion, the NYOP seller needs to maximize the summa- “lower-bound only,”“upper-bound only,” and “range”. tion of all successful bids, as not every consumer is willing to As the guaranteed surplus (GCS) level depends on both participate in the NYOP auction. In Fig. 1, the number of the list price and the perceived value, GCS will change participating bidders is determined by their expected surplus accordingly with the change of list price (i.e. a $50 decrease of participating in the NYOP auction compared to guaran- of the list price will likely increase the GCS by $50, and teed surplus of buying at a list price. Therefore, the objective thus increase the attractiveness of list price channel when of a NYOP seller is to maximize his revenue: compared to NYOP channel, assuming fixed perceived XN value). Given the knowledge of both the list price and the Max p ¼ Bi where Bi > P; and ECSi > GCSi perceived value, GCS is usually available to consumers 1 before they decide to participate in the NYOP auction. The

Table 5 Revenues of NYOP seller under four different Information Format (n=61) Alt. consumer surplus (GCS) of buying at list price information formats GCS=$25 GCS=$50 GCS=$75 Average

No information $12,490 $7,055 $4,023 $7,856 Lower bound only $12,000 $8,720 $6,005 $8,908 Upper bound only $13,270 $9,650 $3,780 $8,900 Range $12,475 $9,630 $5,850 $9,318 Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel 127

Table 6 Percentage of partici- pating bidders at NYOP Information format (n=61) Alt. consumer surplus (GCS) of buying at list price auction under four different information formats GCS=$25 GCS=$50 GCS=$75 Average

No information 74% 41% 39% 51% Lower bound only 80% 56% 39% 58% Upper bound only 62% 44% 18% 41% Range 77% 59% 36% 57%

revenue of a NYOP seller was obtained by specifying a participate when GCS is $50 and only 34% would participate GCS of $25, $50, or $75. We believe that $25 as when GCS is as high as $75.) In this situation, the NYOP approximately 10% of the average bid represents a small seller could benefit from revealing the lower bound of the surplus. In contrast, $75 which is about 30% of the average acceptable price. In fact, the NYOP seller achieves the bid represents a large surplus to consumers. highest revenue under conditions of high guaranteed surplus The expected revenues of NYOP seller for four ($75). Doing so is likely to increase expected consumer informational formats under different GCS levels are shown surplus by reducing uncertainty of the bid acceptance. We in Table 5 and the percentage of participating bidders are find the support of more auction entry with lower bound presented in Table 6. only at Table 6: lower bound only format attracts the highest From Table 5, we can see that if consumers have a low percentage on average across conditions (58%). Moreover, surplus from buying directly at a list price (for example, we find that by informing potential bidders the range, the high list price), the NYOP seller is better off in revenue by NYOP seller achieves the highest average revenue across all providing the upper bound of acceptable price range only. conditions ($9,318). When the list price is relatively high, buying directly at list Figure 3 demonstrates a comparison of revenue gener- price becomes less attractive; we expect more consumers to ated from three different information formats. Since the participate in the NYOP auction (on average, 74% would default format is “no information”, revenue calculated from participate in the auction when GCS is $25; 51% would each information format (lower bound only, upper bound

Fig. 3 Comparison of NYOP $3,000 revenues with three price infor- High Range mation format under different NYOP Revenue (w/ information) GCS levels - NYOP Revenue (no information) $2,500

Low Range $2,000 Low

$1,500

$1,000 High

$500

Range High Low $0

-$500 GCS = $25 GCS = $50 GCS = $75

Levels of Guranteed Consumer Surplus -$1,000 Low: provide lower bound only High: provide upper bound only Range: provide range of threshold price 128 T. Wang et al. only, and range) is deducted from the revenue from “no From the NYOP seller’s perspective, he has to consider information”. From Fig. 3 we can tell that: various information revelation strategies as they can either increase the bid price or increase number of bidders. The (1) “lower bound only” and “range” format are both tradeoff between the two outcomes needs to be weighted to worse off than “no information” when GCS is find an optimal information revelation strategy. Therefore, a relatively low ($25, possibly due to a high list price); NYOP seller may want to reveal different price information Under this condition, the rule of thumb is to report to the potential bidders depending on the level of consumer only the “upper bound” or nothing at all. surplus at primary list price channel. Specifically, when (2) “upper bound only” is worse off than “no information” consumers do not have high surplus from buying directly at when GCS is relatively high ($75, possibly due to a low the list price, the NYOP seller can increase the number of list price); This is the condition when number of bidders bids by revealing the upper end of acceptable price range is critical to the expected revenue, “lower bound only” (which leads to high level of perceived value and bid). On is the best choice to encourage auction entry, and the other hand, when consumers have high surplus from (3) “Upper bound only” and “range” formats are both buying at the list price, the NYOP seller can raise the doing well when GCS is medium ($50). attractiveness of bidding by revealing both ends of the Therefore, it is clear that no single format is good for all acceptable price range (which leads to high level of situations. When list price is relatively low and guaranteed expected surplus). Also, we demonstrate the revenue consumer surplus (GCS) is high, the NYOP seller is better implications for the NYOP seller under the three price off reducing bidding uncertainty to increase expected revelation via a revenue simulation. consumer surplus and thus the number of bidders. When Some limitations of this study are listed below. First, list price is relatively high and GCS is low, the NYOP seller hypothetical buying scenarios in our study will create is better off with a high reference price and thus induces overbidding bias for value elicitation (List and Shogren high bidding price from consumers. 1998). This will happen in all experimental conditions and As a side note, this study illustrates how the optimal should not fundamentally change the results of our study. reference price is to be estimated. It should now be obvious Second, we only study travelling services which dominant that there is a trade-off between average bidding price and the offering of Priceline.com, other commercial NYOP number of bidders. Both factors are subject to the influence of sellers may attend to different markets. Third, we studied reference price. As reference price increases, average bidding seller’s provided reference price only, where other sources price increases and number of bidders goes down. Given this of reference price also play roles in consumers’ decision trade-off, the ‘optimal’ reference price corresponds to the making process (Wolk and Spann 2008). Additional works point where total revenue reaches the highest point. on bidder’s decision making process may provide a better guidance for future studies. Fourth, we used revenue of NYOP sellers as dependent variable instead of profit based Discussion on assumption of exogenously determined threshold price. This assumption, however, may be a strong one if costs or This study proposes an integrative framework to examine adaptive threshold price (Hinz et al. 2010) is considered by the effects of reference price information on both the NYOP sellers. Finally, our study is based on induced bidders and bid-takers. From consumers’ perspective, bidding propensity. Similar to induced willingness-to-pay NYOP auction is almost always secondary to the list price (i.e., conjoint analysis), this approach is likely to have channel. Potential NYOP bidders are looking for better deal certain advantage (less bias) and disadvantage (higher than that at buying at list price. In this study, we focus on sensitivity) when compared to measured bidding propensi- the economic foundation of a NYOP channel: comparison ty. The implications of this choice, however, require future of surplus between buying at list price and bidding at the comparative research. NYOP seller. 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