Date of Award

8-9-2014

Document Type

Open Access Dissertation

Department

Moore School of Business

First Advisor

Michael R. Galbreth

Abstract

Return policies (aka. money-back-guarantee policies) are frequently offered by retailers such that consumers can bring back the purchased products that do not fit their needs. On the benefit side, consumers perceive these policies as a risk-mitigation service and are willing to pay more for an otherwise identical product. All else being equal, being lenient in its return policy should allow a retailer to enjoy higher sales, which leads to increased revenue. On the cost side, a generous return policy will induce more returns and possibly also late returns. In 2007 alone, U.S. manufacturers and retailers paid more than $100 billion to process consumer returns. For electronic products, this cost is estimated at $16.7 billion per year, which represents 6% of an average electronics manufacturer’ revenue and 3% of an average retailer’s total sales. The return rate in the retail sector ranges from 10% to 20%. To effectively manage returns, a retailers should concurrently optimize its price and restocking fee so that it could enjoy the most benefit from offering a return policy. At the same time, it should also seek to better forecast the quantity of incoming returns and make efforts to reduces the number of futures returns.

Despite the magnitude of the returns management problem, academic research on this topic is still relatively scant. Through three separate studies, this dissertation delves into returns management from a multitude of perspectives. The first study explores a retailer’s optimal return policy when a fraction of the market is consist of opportunistic consumers, who might purchase with the explicit intention of returning. The second study demonstrates how retailers might use their point-of-sale data to better forecast future returns, uncover the duration of consumers’ product trial, and identify products that are more likely to be returned. The last study introduces a novel approach for retailers to quantify the incremental willingness-to-pay that consumers assign to money-back-guarantee policies in the on-line environment.

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