Abstract
We develop an optimization framework to trade short-term profits for reputation (i.e., reducing ramp-up time). We apply the stochastic bandits framework to design an online discounting mechanism which infers the optimal discount from a seller's historical transaction data. We conduct experiments on an eBay's dataset and show that our online discounting mechanism can trade 60% of the shortterm profits for reducing the ramp-up time by 40%.
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