Optimal Seller Strategies in Overlapping Auctions

Little research has been conducted on a common phenomenon in today’s online environment: the concurrent selling of identical products in online auctions. To fill this gap, the current research proposes a game-theoretical model to analyze the seller’s optimal strategy for selling two identical items in overlapping auctions. The overlap is modeled endogenously (as the seller’s decision), trading off multiple influences including the positive effect on the overlap from bidders’ forward-looking behavior and the seller’s time discounting, versus the negative impact from bidders’ learning and varied demand (i.e., bidder entry). The combined impact of these factors governs the conditions for which a simultaneous, sequential, or partially overlapping strategy is optimal. When the effect of bidders’ forward-looking behavior and/or the seller’s time discounting dominates, running simultaneous auctions is optimal; when bidders’ learning (and bidder entry) dominates, running sequential auctions is optimal. Partially overlapping auctions are optimal when neither effect dominates and the opposing effects are offsetting