Business-to-consumer online auctions form an important element in the portfolio of mercantile processes that facilitate electronic commerce activity. Much of traditional auction theory has focused on analyzing single-item auctions in isolation from the market context in which they take place. We demonstrate the weakness of such approaches in online settings where a majority of auctions are multiunit in nature. Rather than pursuing a classical approach and assuming knowledge of the distribution of consumers' valuations, we emphasize the largely ignored discrete and sequential nature of such auctions. We derive a general expression that characterizes the multiple equilibria that can arise in such auctions and segregate these into desirable and undesirable categories. Our analytical and empirical results, obtained by tracking real-world online auctions, indicate that bid increment is an important factor amongst the control factors that online auctioneers can manipulate and control. We show that consumer bidding strategies in such auctions are not uniform and that the level of bid increment chosen influences them. With a motive of providing concrete strategic directions to online auctioneers, we derive an absolute upper bound for the bid increment. Based on the theoretical upper bound we propose a heuristic decision rule for setting the bid increment. Empirical evidence lends support to the hypothesis that setting a bid increment higher than that suggested by the heuristic decision rule has a negative impact on the auctioneer's revenue.