Optimal Bidding Overtime Strategy for Online Art Auctions: Evidence from Chinese Auction Houses

The paper studies the impact of bidding overtime in online art auctions. We identify two contrasting overtime bidding mechanisms influencing the final winning price: the positive effect of valuation learning and the negative effect of attention cost. We define a theoretical auction model with bidding mechanisms that yield an optimum outcome through Monte Carlo simulation. By evaluating four bidding overtime durations at six Chinese art auction houses, we consistently observe a positive effect on final prices with longer overtime policies in all settings, from which we validate the bidding mechanisms and propose an optimal design of overtime duration at 3 minutes. The paper then discusses whether these effects apply to lower-value eBay auctions and physical auctions.