Determining profit-optimizing return policies - a two-step approach on data from taobao.com

Selecting an optimal return policy requires taking into account two effects: the potential positive effect on sales and the potential negative effect of higher costs. We propose a two-step model, in which we first utilize a robust regression to explain purchase behavior, and then apply a zero-inflated negative binominal regression to model the return behavior. We apply this model to data from the most important online platform in China and obtain three main findings. First, the adoption of return policies results in increased sales, while reputation works as a moderator in this process. Second, good reputation and traditional customer friendly return policies (like the Seven-Day Return policy) can significantly increase the number of returns, while more guarantee credibility (enhanced by Guarantee Money) is related to fewer returns. Taken together, both the Seven-Day Return policy (profit increase of +0.29 %) and Guarantee Money (profit increase of +0.016 % per Yuan guarantee) ultimately increase firms' profit.