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Institutional dependencies in dynamic buyout price models for online auctions

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Abstract

There is disagreement in the auction literature on the question of whether dynamic Buy-It-Now (BIN) prices can increase the efficiency of online auctions, compared to static BIN price auctions. In a previous paper (Vragov et al. 2010), we reported experimental evidence that suggested, contrary to the current theoretical auction literature, that dynamic BIN pricing is indeed economically more efficient. The current paper presents a replication study of this research that interestingly fails to reproduce the earlier findings. It is based on the same general experimental design, but modifying the implementation of the specific trading institution by using a linearly declining BIN price (Online Linear Dutch Auction—OLDA) rather than the discrete one-time price change (Online One-time BIN-price Change Auction—OOBCA) that was used in the previous study. OLDA is more dynamic in nature than OOBCA, yet OOBCA outperforms a generalized static online auction design in the laboratory while the OLDA does not. We explain these different results, and thus resolve the ostensible contradiction between the two sets of experiments, by concluding that the specific implementation of the trading institution (i.e., the dynamic BIN pricing mechanism) has a significant effect on the overall market efficiency. In other words, our research finds that the efficiency of dynamic buyout price auctions is institution-dependent. This has important theoretical implications as most formal auction models assume that the auction outcome is institution-free. We also discuss some practical implications of our findings.

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Notes

  1. However, in a few categories of eBay items, the BIN option may continue to be available after the first bid for a limited time (http://pages.ebay.com/help/sell/fixed-price.html).

  2. Replication studies are are more than the mere repetition of previous experiment; they involve an important modification of the original design that allows the researcher to test the limits of generalizability of findings and the discovery of theoretical boundary conditions (cf Guala 2005, pp. 13–15).

  3. Undergraduate students have traditionally been used in experimental economics as the initial subject pool because of many practical considerations. Findings might or might not differ when the subject pool changes, but there have been indications of fairly strong consistencies in terms of findings even if the subject pool changes, for example, in experiments studying the properties of and behavior under continuous double auctions (see Smith 2003).

  4. In OLDA, once the auction starts, the system automatically updates the BIN price every second with the rate of change chosen by the seller in the beginning of the auction. Thus changing the price is costless for the sellers.

  5. For example if a seller with a time cost of $0.05 per second chose a BIN of $60 and that BIN was accepted after one second by a buyer then the seller will earn $60-0.05 = $59.95 for this round. At the same time if this buyer’s value was $84 and his time cost was $0.04 per second, then the buyer will earn $84-60-0.04 = $23.96 for this round.

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Correspondence to Richard D. Shang.

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Vragov, R., Shang, R.D. & Lang, K.R. Institutional dependencies in dynamic buyout price models for online auctions. Inf Syst E-Bus Manage 10, 351–366 (2012). https://doi.org/10.1007/s10257-011-0168-2

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