How much do online consumers really value free product returns? Evidence from eBay

Consumer return rates have been steadily rising in recent years, resulting in growing costs for retailers who must manage the returns process and the disposition of returned products. This cost pressure is driven in part by extremely generous return policies, such as giving consumers a full refund upon return. Interestingly, this common retail practice of full refunds is inconsistent with the recommendations of many analytical models of returns, which nearly always show that a partial refund is optimal. Such inconsistencies between theory and practice might arise when the decision drivers included in the analytical models do not match the decision drivers in practice. It might also be the case that retailers are overly optimistic about the value that consumers assign to a full refund, and thus assume that the value of such a policy outweighs its costs. In this paper, we use data collected from eBay, where identical products are sold with different return policies, to investigate these open questions in the literature. We analyze both the return policy drivers from the retailer's perspective and the return policy value from the consumer's perspective. Our results suggest that the value of a full refund policy to consumers may not be as large as one might expect, and it also exhibits a large heterogeneity across buyers with different levels of online purchase experience. In addition, we provide empirical evidence for what has long been suspected by online retailers – that a non-refundable forward shipping charge quickly erodes any value that consumers assign to return policies. The generality of our results is limited by the fact that eBay differs from traditional retail contexts in many respects, including the fact that eBay buyers may not be representative of the general buyer population. However, our study of how eBay consumers value free returns provides new insights into an understudied area, and it can serve as a starting point for future studies of the value of return policies in other retail contexts.     

Estimating demand from eBay prices

This paper presents results for identification and estimation of the value distribution from eBay auction prices. The paper presents results for eBay type auctions with independent private values and unobserved participation. It is first shown that the distribution of values is identified from observing the distribution of prices and knowing the distribution of potential bidders. The main identification result presents conditions for which the distribution of values and the distribution of potential bidders are simultaneously identified. Not surprisingly, the intuition is similar to the standard results for identifying demand from observed equilibrium prices. The estimation method suggested by the identification results is used to estimate the value distribution for the “C5” Chevrolet Corvette sold on eBay. The results suggest that a simple OLS model on prices will over estimate the mean value of the item. The estimation results are then used to calculate the optimal reserve price for these cars. The estimated optimal reserves are compared to the actual reserves. Actual hidden reserves are set much higher than actual non-hidden reserves. The evidence suggests sellers set Buy-It-Nows and hidden reserves optimally to account for re-listing opportunities.     

The value of reputation on eBay: A controlled experiment

We conducted the first randomized controlled field experiment of an Internet reputation mechanism. A high-reputation, established eBay dealer sold matched pairs of lots—batches of vintage postcards—under his regular identity and under new seller identities (also operated by him). As predicted, the established identity fared better. The difference in buyers’ willingness-to-pay was 8.1% of the selling price. A subsidiary experiment followed the same format, but compared sales by relatively new sellers with and without negative feedback. Surprisingly, one or two negative feedbacks for our new sellers did not affect buyers’ willingness-to-pay. JEL Classification D82 · L14 · Z13     

Your Call: eBay and Demand for the iPhone 4☆

The iPhone 4 was introduced into the UK market on 24^th June 2010 to significant consumer interest. Demand revealed itself exceeding supply through conventional channels, since there was very extensive activity in terms of bidding on eBay auctions for the product. We monitored all UK eBay transactions on the iPhone 4 for six weeks from introduction, with total transactions amounting to around £1.5m. We analyse determinants of winning bids in terms of characteristics of the phone, the seller, and the buyer. Our most notable and novel finding relative to previous studies is a very significant premium over list price being paid in almost all cases, with positive uplift factors including whether the phone was unlocked and whether it could be sold overseas. Demand fell over time, as evidenced by lower achieved prices, but the fall in price was relatively modest. A significant premium of 32GB over 16GB versions is revealed.     

Successfully selling accommodation packages at online auctions – The case of eBay Austria

In this era of e-commerce online auctions have emerged as a valuable distribution channel (36 and 52). Displaying low entry and exit barriers but also vast coverage rates, online auctions may effectively augment the distribution potential of hotel businesses. This paper identifies those factors that positively affect the final price level obtained in online auctions for hotel room vouchers. Based on data gathered at eBay comprising 53,406 auctions, linear structural equation modelling (SEM) was conducted to identify significant relationships between auction characteristics and the obtained final price for hotel room vouchers. By drawing on these results and through an example of the Austrian eBay platform, selling strategies for successfully listing accommodation packages at online auctions are proposed.     

Snipers, Stalkers, and Nibblers: Online Auction Business Ethics

Spirited disagreement exists among online auction participants over the ethics of sniping: delaying one's bid until the closing seconds of an online auction. Through analysis of the structural features of online auctions and by deploying Rawls's (1955) distinction between justifying an action under a practice and justifying the practice itself, I argue that: (i) the disagreement is better conceived as one over the ethics of online auction hosting (and therefore, over business ethics) than over the ethics of online auction participation; (ii) so conceived, the argument against sniping is nonetheless implausible; and (iii) the disagreement remains interesting not on the merits, but for the curious fact that it is bidders who complain about sniping.     

Late and multiple bidding in second price Internet auctions: Theory and evidence concerning different rules for ending an auction

In second price Internet auctions with a fixed end time, such as those on eBay, many bidders submit their bids in the closing minutes or seconds of an auction. We propose an internet auction model, in which very late bids have a positive probability of not being successfully submitted, and show that late bidding in a fixed deadline auction can occur at equilibrium in auctions both with private values and with uncertain, dependent values. Late bidding may also arise out of equilibrium, as a best reply to incremental bidding. However, the strategic advantages of late bidding are severely attenuated in auctions that apply an automatic extension rule such as auctions conducted on Amazon. Field data show that there is more late bidding on eBay than on Amazon, and this difference grows with experience. We also study the incidence of multiple bidding, and its relation to late bidding.     

Empirical tests of information aggregation

This paper proposes tests to empirically examine whether auction prices aggregate information away from the limit. These tests are applied to a unique data set containing winning bids and measures of the value and dispersion of information signals in eBay auctions for computers. Results suggest that prices partially aggregate information but do not converge to the common value. Even away from the limit, more bidders and stronger information have a significant effect on the convergence of prices and information aggregation. Even partial information aggregation may represent a potential efficiency gain over one-to-one trade of used goods with uncertain common values.     

Effect of Buyer and Seller Experience on Buy It Now Pricing

ABSTRACT

Although auctions have been around for centuries, online auctions are still a relatively new phenomenon. This paper examines the phenomenon of online auctions, specifically on a pricing option known as “Buy It Now.” With this option, a buyer can purchase merchandise immediately at a stated price and truncate the auction process. Auction items sold with a Buy It Now price tend to be at a higher price than the high bid price for an identical item sold through an ascending-bid auction. In addition, Buy It Now prices tend to attract risk averse bidders while high bidders of ascending-bid auctions tend to be less risk averse or risk neutral bidders. On the other hand, we found more experienced sellers sell their items with a Buy It Now price while less experienced sellers sell their items through an ascending-bid process. Thus, experience and risk are factors in choosing a Buy It Now price for the seller and buyer.     

Auctions with a buy price

eBay and Yahoo allow sellers to list their auctions with a buy price at which a bidder may purchase the item immediately. On eBay, the buy-now option disappears once a bid is placed, while on Yahoo the buy-now option remains in effect throughout the auction. We show that when bidders are risk averse, both types of auctions raise seller revenue for a wide range of buy prices. The Yahoo format raises more revenue than the eBay format when bidders have either CARA or DARA. Bidders with DARA prefer the eBay auction, while bidders with CARA are indifferent between the two. Part of this work was completed while Reynolds was a visitor at Instituto de Analisys Economico in Barcelona and while Wooders was a visitor at Hong Kong University of Science and Technology. We are grateful to these institutions for their hospitality.