A Subject Experiment of an Approximate DGS Algorithm: Price Increment, Allocative Efficiency, and Seller’s Revenue

For multiple-item auctions with unitary demands, the approximate Demange-Gale-Sotomayor (DGS) algorithm has an easy-to-understand rule but it needs a considerably longer time to settle, as compared with the Vickrey-Clarke-Groves (VCG) mechanism. A possible way to make the time shorter is to raise asking prices in larger increments, but concerns about deterioration of allocative efficiency and the seller’s revenue arise when the increments are large. In a subject experiment, we observed under the approximate DGS algorithm that there was an appropriate increment in asking prices by which the seller’s revenue and allocative efficiency did not significantly differ from those in a smaller increment. The theoretical approximation boundaries of the winning prices were not necessarily satisfied because human subjects did not choose sincere bidding.