New auction model with contract design improves revenue by incentivizing bidder investment

Researchers Xiaolin Bu, Jiarong Jin, Junzhu Ke, Pinyan Lu, Biaoshuai Tao, Xiang Yan, Chunxue Yang, Haikuo Yang, and Zhihua Zhu have published a paper on arXiv titled 'Auctions with Contract Design' (arXiv:2607.13795). They address a fundamental problem in auction theory: bidders often make costly, quality-enhancing investments before winning the auction, creating a moral hazard where the risk of losing discourages effort. The authors propose integrating contracts into auctions—the auctioneer commits to a transfer rule that rewards the winner based on the ex-post quality of the transaction.

Studying both second-price and first-price auctions, they prove the existence of symmetric Bayes-Nash equilibria. For large numbers of bidders, they derive the optimal reward factor in linear contracts. Their main result shows this factor converges to the auctioneer's marginal benefit from quality, meaning the auctioneer optimally passes the full quality value to the winner. A revenue equivalence theorem holds across auction formats. Compared to standard auctions without quality rewards, the new framework effectively increases revenue by encouraging higher investments.