John J. Han is a PhD candidate in marketing at McGill University. His research straddles quantitative modeling, consumer behavior, and behavioral economics, with emphasis on multi-party strategic interactions. He studies market design and market inefficiencies in the B2B and P2P spheres, including auctions and bargaining. In a recent study, John explored how successive concessions and strategic delays can benefit all parties involved in B2B bargaining. His econometric models provide insights on the optimal distribution of concessions at each stage of negotiation and on optimal prices that allow sellers to maximize profits while avoiding unsuccessful and unnecessarily lengthy negotiations. Another area of John’s research is on the decision-making of an arbiter in resolving disputes between two parties that lay proportional claims on an asset. He designed two bargaining allocation problems to investigate this issue and found that the arbiter’s off-equilibrium beliefs influenced her decision, despite the known equilibria. More specifically, incentivizing the arbiter with the payoff to the lowest-paid disputant resulted in low incidence of impasse and egalitarian claims to each party. These findings provide implications for franchise property rights and shelf space allocation. In other works, John explores consumer learning with incomplete information and behavioral norms in virtual market settings.