Manufacturers adopt a variety of channels for the sale of their products in the attempt to deliver the highest possible value to end consumers. For instance, a manufacturers’ retail arm provides consumers with the instant gratification of product purchase and the benefit of in-store shopping assistance, whereas their online arm offers potential benefits by selling to market segments that value shopping convenience, product variety, availability, and customization. The main difference between these two channels is that consumers cannot “touch and feel” the product before they make an online purchase, whereas they can physically inspect and often even experience the product before making an in-store purchase. As a consequence, the online arm implies a higher degree of uncertainty about product fit than the retail arm. The ensuing possibility that consumers will return the product, due to product misfit, might impact the manufacturer's design of the channels of distribution. We show that product marginal value and salvage value for product returns determine whether the manufacturer will sell his product through “bricks” only, “bricks and clicks,” or “clicks” only. Our work highlights the pivotal role that online and retail channels play in the manufacturers’ sales strategies in a market characterized by returns, wherein the online channel reduces double price marginalization and the retail channel curtails the number of returns. In particular, we show that a “bricks and clicks” channel structure may be the most profitable option for the manufacturer, due to its flexibility in reducing returns without adhering to strict return policies that would hurt sales.

Additional Metadata
Keywords consumer returns, game theory, return policies, sales channels
Persistent URL dx.doi.org/10.1111/poms.12799, hdl.handle.net/1765/104656
Journal Production and Operations Management
Citation
Letizia, P, Pourakbar, M, & Harrison, T. (Terry). (2018). The Impact of Consumer Returns on the Multichannel Sales Strategies of Manufacturers. Production and Operations Management, 27(2), 323–349. doi:10.1111/poms.12799