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III. Research Questions and Methodology
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III. Research Questions and Methodology In February through August of 2004, 126 observations were collected from completed eBay Motors auctions. Our data includes only auctions offering Honda Accords made between the years 1992 and 2003 with winning bid prices between $4000 and $20,000. Data were only collected on completed auctions in which the “reserve price” (minimum seller is willing to accept) was met and in which the automobile is described as being in good condition. Autos that had been damaged, salvaged, or customized were not considered. Using the data (model type, year, mileage, options, etc.,) from each auction listing, “blue book” values were collected for each vehicle using the Kelley Blue Book (2004) web site (kbb.com). If the necessary data was not included in the listing (model type, options, etc.) the observation was not included in the data set. See Figure 4 for an example of a Kelley Blue Book retail price listing.
Since our study involved vehicles with varying model types (e.g., DX, LX, EX), mileage, and options, the Price Ratio is the primary dependent variable of interest. This ratio serves as percentage of retail value that an auction listing achieved. For example, if an auction’s winning bid price was $7,000 and the automobile’s retail value (as determined by using the Kelly Blue Book price) was $10,000, the Price Ratio would be 70%. Based on the variables shown in Table 2, some interesting research questions emerge. Many of these research questions help to explore the role of risk in eBay Motors auctions. In some eBay markets, more expensive items could sell for a lower percentage of retail value. For example, Sena et al (2004) found that the retail value of DVDs was negatively correlated with the Price Ratio (percent of retail value). However, in the case of automobiles, given a fixed model type (Honda Accords), more expensive (or newer) models, may be considered less risky and thus may realize a higher Price Ratio. To examine these factors from different perspectives, we have focused on 9 specific research questions as shown in Table 3. Questions 1-3 focus on the relationship between price ratios and winning bid prices, retail values, and the age (model year) of the autos. Research question 4 focuses on the impact of automobile dealerships on bid prices. Beyond the perception that dealers may be less likely to commit fraud (perhaps because users have a name, address, etc.,) they may also have the ability to offer services, warranties, etc., that may entice buyers to offer higher bids. Research question 5 explores the relationship between the number of bids in an auction and the winning bid price while Research question 6 examines whether listings that include more pictures realize higher prices. This research question builds on a finding from Sena et al (2004) that higher quality descriptions (for designer watches and DVDs) resulted in higher bid prices. See Figure 3 for an example of a listing with 28 thumbnail photos. Prior research has indicated, with some exceptions, that seller feedback correlates positively with winning bid prices. As described in Table 2, two seller reputation variables were collected from eBay listings: seller percent positive, and seller feedback rating. The feedback rating serves as a measure of the seller’s experience, as estimated by the seller’s number of previous feedback responses. These variables are generally the only measures of seller reputation that eBay buyers observe as they are displayed on the main auction listing. Research questions 7 and 8 examine whether seller feedback ratings have an impact on winning bid prices. It is important to reiterate that our sample includes only completed auctions, excluding auctions where bid prices did not exceed the seller’s reserve value. Thus, it is possible that seller feedback plays an important role beyond what our study captures. For instance, the seller feedback (or lack thereof) may result in fewer or lower bids that fail to meet the seller’s minimum acceptable price. Finally, Research question 9, examines the role of feedback ratings for the buyer rather than the seller. The seller feedback is an estimate of buyer experience with eBay. From our anecdotal observations, it appears that many buyers purchase multiple vehicles on eBay Motors, presumably with the intention of re-selling. This variable, if significant, would likely be negatively related to price ratio, as one would expect more experienced users to recognize better deals (and thus lower price ratios). .
Statistical Analyses and Findings Descriptive Statistics To begin our analysis, we examine the descriptive results of our data set. As shown in Table 4, the mean winning bid price for the 126 automobiles in our sample was $8,765 while the mean retail value of these automobiles was $12,092, resulting in a mean price ratio of just over 72%. The authors collected data for listings with model years ranging from 1992 to 2003 with a mean year of 1998.75. Compared with other eBay marketplaces, buyers and sellers seem to have fewer feedback ratings. Buyers in our sample have an average of 17.83 feedback ratings while sellers have an average of 177.49. Like other eBay markets, feedback tends to be heavily positive with sellers in our sample having a mean positive feedback percentage of 97.43%. It is important to note that eBay combines all feedback into one rating regardless of whether the user was a buyer or seller and whether the item was sold on eBay Motors or another eBay listing. Thus, feedback scores and percent positive ratings can occasionally be misleading (e.g., a rating based on beanie baby purchases rather than auto sales). Given the limitations of using eBay Motors for such an important purchase, the auction listing plays an important role in marketing the auto and conveying the important information that potential buyers require. Thus, it is not surprising that sellers provide numerous digital images in most listings. In our sample, the mean number of pictures provided was 18.59. Automobiles offered by dealerships may be considered less risky by some eBay users. In our sample, 71% of the sellers were deemed to be automobile dealerships based on the item description. The number of bids on automobile auction may vary depending on the starting (minimum) bid price, the reserve price, and whether the seller offers a “buy it now” option. In our sample, auctions had a mean of 19.84 bids, with 13 auctions ending after just one bid.
1- excludes six observations with zero feedback ratings Research Questions 1 to 3 As shown in Table 5, the correlation between Price Ratio and the Winning Bid Price is very strong while the correlations between Price Ratio and Blue Book Value and Year are positive but insignificant in our sample. However, as shown in Table 6, a test of mean differences at selected values show that there may still be some relationship between these variables. This suggests that perhaps the relationships are not linear. For example, in the case of model year, perhaps buyers are willing to pay a higher percentage of retail for a recent (and presumably more trouble-free and less risky) car but the relationship fails to hold once cars reach a certain age.
*** significant at p<=.01; ** significant at p<=.05; * significant at p<=.10
*** significant at p<=.01; ** significant at p<=.05; * significant at p<=.10 Research Question 4 The results in Table 7 are somewhat surprising. While the sample data indicate that dealerships earn a moderately greater percentage of retail value than individual sellers (72.8 vs. 70.4%), the results are not statistically significant. Perhaps as dealers gain more experience in using eBay these differences will become greater. It may also be possible that buyers may have more confidence in private sellers and are willing to pay a higher price under certain circumstances.
Research Question 5 As shown in Table 8, there was absolutely zero correlation between the number of bids and the percentage of retail value earned in our sample. The data seems to indicate that perhaps auctions with a single bid (indicating the likelihood of a “buy it now” purchase), result in higher price ratios. However, given the small sample size, this difference in means is not statistically significant, leaving this as an item for future study.
Research Question 6 Table 9 reveals, in our opinion, the most interesting finding of this study. While the correlation between the number of pictures and price ratio is somewhat weak (with a p-value of .07), one would expect that this relationship would probably not follow a linear pattern. That is, if an auction includes very few pictures this may increase the perceived risk and result in a lower price. However, at some point, additional pictures probably do not return the same marginal benefit. In our sample, there were a large number of listing that included 12 pictures (perhaps from a template offered by eBay). These listings and those that included fewer pictures earned on average nearly 6% less of retail value compared with listings that include 13 or more pictures. It is very likely in the near future that multimedia presentations with video or panoramic images will become common on eBay Motors and other sites demonstrating used vehicles.
*** significant at p<=.01; ** significant at p<=.05; * significant at p<=.10 Research Questions 7 to 9 In our initial analysis, as shown in Table 10, it is somewhat surprising that feedback does not play a substantial role in determining price ratios. None of the correlations between feedback variables and price ratio were statistically significant. While Table 11 shows some moderate differences in mean price ratio among selected subsections of the data, these are also not statistically significant. Of course, feedback may still play an important role in a buyer’s decision to bid on a particular vehicle or on vehicles that fail to result in a sufficient bid price to meet the seller’s minimum (reserve) price. However, our data set fails to show substantial relationships between eBay’s feedback and winning bid prices (as compared with the respective retail value). In an attempt to further explore the role of seller feedback (in particular, the Percent Positive variable) we selected a subset of the data using only observation in which the seller had been rated at least 25 times. In sellers with very few feedback details, the Percent Positive is likely not as meaningful to prospective buyers. The results presented in Table 12 shows that perhaps when buyers observe an adequate number of feedback ratings, then the Percent Positive rating does play a role in the amount they are willing to bid for an automobile. Although the correlation is still not statistically significant in this subset, a comparison of means among subgroups with greater than 98% positive feedback ratings versus those with less than 98% positive feedback, shows a statistically significant difference in price ratio.
*** significant at p<=.01; ** significant at p<=.05; * significant at p<=.10 V. Conclusions The principal findings of our study may be of interest to both practitioners and scholars of various disciplines. Our results provide an empirical basis for future studies and reveal several research questions that can be probed in greater detail using additional methodologies and more extensive datasets. While numerous studies have analyzed eBay exchanges, this study has the potential to be among the most significant because of the importance of automobiles in our economy. While our dataset was limited, it captured over 1.1 million dollars worth of transactions. The results provide a starting point for academic assessment of this exciting and important market. The results of this analysis promote an understanding the factors that impact bid prices of automobiles in Internet auctions. For example, our findings reveal that the price of the automobile and the inclusion of numerous pictures may play an important role in predicting the percent of retail value that an auction listing will achieve. The study also adds to the growing body of literature focused on the impact of Internet-based reputation systems. While the relationships between feedback ratings and price ratios in our dataset were not statistically significant (contrary to some past studies), more studies are needed to further explore this relationship. Our analysis does point out that the relationships between the variables in our study may not follow a linear pattern. Thus, there is an opportunity for researchers to conduct more robust statistical analyses on datasets of this nature. Although the market for automobiles on the Internet, particularly on eBay Motors, has exploded in the past year, the marketplace is still in its infancy. Consumer habits are likely to adjust over time as sellers learn to use the medium more effectively and buyers become more comfortable with the marketplace. Similarly, advancements in technology and new business ventures will undoubtedly continue to play a role in these exchanges. This study provides a cursory analysis of the eBay Motors marketplace as it currently exists for the data we collected. Clearly, further research focused on eBay Motors and other Internet-based automobile marketplaces is needed to clarify the relationships examined in this research. VI. References AutoByTel (2004) http://www.autobytel.com last accessed Aug. 15, 2004. AutoTrader (2004) http://www.autotrader.com last accessed Aug. 15, 2004. Ba S. and P.A. Pavlou (2002). “Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior,” MIS Quarterly. 26(3). Bajari P. and A. Hortescu (2003). “Winner’s Curse, Reserve Prices and Endogenous Entry: Empirical Insights from eBay Auctions,” Rand Journal of Economics. 34(2). Cabral, L. M B and A.Hortacsu (2003). “The Dynamics of Seller Reputation: Theory and Evidence from eBay.” Working Paper. Stern School of Business. New York University. http://pages.stern.nyu.edu/~lcabral/papers/ebay.pdf. Cars.com (2004) http://www.cars.com last accessed Aug. 15, 2004. CarsDirect (2004) http://www.carsdirect.com last accessed Aug. 15, 2004. Cuneo, A. Z.(2003a). “eBay bids to remake $372B used-car biz; Ads pitch service that ‘nationalizes’ local industry.” Advertising Age, 74(19), p. l. Cuneo, A. Z.(2003b). “eBay unleashes used-car campaign.” Automotive News, 77. 16. Dellarocas, C. (2003). “The Digitization of Word-of-Mouth: Promises and Challenges of Online Feedback Mechanisms.” Management Science. 49(10). Dewan S. and V. Hsu (2002). “Price Discovery in Generalist Versus Specialty Online Auctions”, Working Paper, Graduate School of Management, University of California, Irvine. http://databases.si.umich.edu/reputations/bib/papers/Dewan&Hsu.doc. Eaton, D. H. (2002). “Valuing Information: Evidence from Guitar Auctions on eBay.” Working Paper, Murray State University. http://campus.murraystate.edu/academic/faculty/david.eaton/workpaper0201.pdf eBay Feedback FAQs (2004) http://pages.eBay.com/help/new/feedback_faqs.html last accessed Aug. 15, 2004. eBay Feedback Forum (2004) http://pages.eBay.com/services/forum/feedback.html last accessed Aug. 15, 2004. eBay Motors (2004) http://www.motors.ebay.com last accessed Aug 15, 2004. Houser, D. and J. Wooder (2003), “Reputation in Auctions: Theory, and Evidence from eBay,” with Dan Houser. Under review at Journal of Economics and Management Science. http://w3.arizona.edu/~econ/working_papers /Internet_Auctions.pdf. Kalyanam K. and S. McIntyre (2001). “Returns to Reputation in Online Auction Markets,” Working Paper W-RW01-02, Santa Clara University. http://business.scu.edu/faculty/research/working_papers/pdf/ kalyanam_mcintyre_wp10.pdf.
Sandeep Krishnamurthy, editor. Idea Group. Standifird, S (2001), Reputation and E-commerce: eBay Auctions and the Asymmetrical Impact of Positive and Negative Ratings, Journal of Management, 2001, 27. Verma, M. (2003). “Click-drive: EBay motors zooms, zooms, zooms. Local dealers in first gear”. Greater Baton Route Business Report, 21(26) p. 36(3). Wingfield, N. and K. Lundegaard (2003). “Improbably, EBay Emerges As a Giant in Used-Car Sales,” The Wall Street Journal Online. Feb. 7, 1-5. Figure 3: Example of “thumbnail” photos in eBay Motors listing. 
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