The area of inventory liquidation of consumer products has been revolutionized by retailers adopting direct-to-consumer approaches via the ecommerce stores and online auction sites (Bapna et al. 2009) enabled by advanced information technologies. For example, retailers such as Best Buy have...

Online retailers use product ratings to signal quality and help consumers identify products for purchase. These ratings commonly take the form of either non-personalized, aggregate product ratings (i.e., the average rating a product received from a number of consumers such as “the average...

Research studies have shown that recommender systems' predictions that are observed by users can cause biases in users' post-consumption preference ratings. Because users' preference ratings are typically fed back to the system as training data for future predictions, this process is likely to...

With the increasing use of recommender systems in various application domains, many algorithms have been proposed for improving the accuracy of recommendations. Among a number of other dimensions of recommender systems performance, long-tail (niche) recommendation performance remains an...

Initially popularized by Amazon.com, recommendation technologies have become widespread over the past several years. However, the types of recommendations available to the users in these recommender systems are typically determined by the vendor and therefore are not flexible. In this paper, we...

Prior IS research on technological change has focused primarily on organizational information systems and technology (IS&T) innovation; however, there is a growing need to understand the dynamics of supply-side forces in the introduction of new technologies. In this paper we investigate how the...