  We study the problem of bidding in uniform price auctions widely used in
practice. Although these auctions are non-truthful for bidders with quasilinear
utility functions, several empirical findings suggest that the auction format
induces truthful bidding from the bidders. We attribute this difference in
theory and practice to the assumption of the behavioral model of the bidders.
In this pursuit, we study uniform price auctions in a repeated setting from the
perspective of a value-maximizing buyer who aims to maximize their acquired
cumulative value across $T$ rounds, subject to per-round return-on-investment
(RoI) constraints. For a RoI-constrained, value-maximizing buyer, we study a
generalized version of the uniform bidding format, commonly used in practice,
which we term as $m$-uniform bidding. To characterize the optimal $m$-uniform
bid, we introduce and study the notion of universally feasible (UF) bidding
policies, which are robust, meaning that RoI feasibility is obtained regardless
of the competitors' bids. We show that the optimal class of UF bidding policies
is essentially a generalization of truthful bidding policies, which depends
only on the valuation curve of the bidder and target RoI. To measure the
performance of UF bidding policies against the optimal bidding policy that is
not necessarily UF, we introduce a metric called the Price of Universal
Feasibility (PoUF) and establish that PoUF is at most 2, irrespective of $m$
and the upper bound is tight. We further compare the generalized $m$-uniform
bidding interface against the classical uniform bidding format under which
$m=1$, showing the total value under $m$-uniform bidding increases at most by a
factor of $m$. Numerical simulations on semi-synthetic data demonstrate that UF
bidding policies perform significantly better than the derived theoretical
bounds.
