Prior research with consumable goods has consistently found that consumers have a preference for greater variety when selecting items simultaneously as a bundle, rather than as a sequential series of individual decisions. However, digital information goods have a number of important differences from consumable goods that may impact variety-seeking behavior. In three experiments, we address two general research questions. First, as a precursor to studying digital goods, we disentangle the role of bundle cohesion (i.e., item relatedness) from the role of timing (simultaneous vs. sequential choice) as factors in variety seeking with consumable goods. Next, based on differences between digital and consumable goods, we theorize differences in the behavioral effects of bundle cohesion and timing on variety preferences for digital goods. The results show a reduction of influences upon variety-seeking behavior with digital goods, providing important implications for the sellers of such goods in contrast to what has been suggested for consumable goods. Therefore, a key takeaway is that, for digital goods such as music, the use of consumer-driven bundling variations does not suggest an advantage in terms of their ability to affect consumers' variety-seeking behavior. > >
Recommender systems are becoming a salient part of many e-commerce websites. Much research has focused on advancing recommendation technologies to improve accuracy of predictions, although behavioral aspects of using recommender systems are often overlooked. In our studies, we explore how consumer preferences at the time of consumption are impacted by predictions generated by recommender systems. We conducted three controlled laboratory experiments to explore the effects of system recommendations on preferences. Studies 1 and 2 investigated user preferences for television programs across a variety of conditions, which were surveyed immediately following program viewing. Study 3 investigated the granularity of the observed effects within individual participants. Results provide strong evidence that the rating presented by a recommender system serves as an anchor for the consumer's constructed preference. Viewers' preference ratings are malleable and can be significantly influenced by the recommendation received. The effect is sensitive to the perceived reliability of a recommender system and, thus, not a purely numerical or priming-based effect. Finally, the effect of anchoring is continuous and linear, operating over a range of perturbations of the system. These general findings have a number of important implications (e.g., on recommender systems performance metrics and design, preference bias, potential strategic behavior, and trust), which are discussed.
Advancements in information technology offer opportunities for designing and deploying innovative market mechanisms that can improve the allocation and procurement processes of businesses. For example, combinatorial auctions-in which bidders can bid on combinations of goods-have been shown to increase the economic efficiency of a trade when goods have complementarities. However, the lack of real-time decision support tools for bidders has prevented this mechanism from reaching its full potential. With the objective of facilitating bidder participation in combinatorial auctions, this study, using recent research in real-time bidder support metrics, discusses several novel feedback schemes that can aid bidders in formulating combinatorial bids in real-time. The feedback schemes allow us to conduct continuous combinatorial auctions, where bidder scan submit bids at any time. Using laboratory experiments with two different setups, we compare the economic performance of the continuous mechanism under three progressively advanced levels of feedback. Our findings indicate that information feedback plays a major role in influencing the economic outcomes of combinatorial auctions. We compare several important bid characteristics to explain the observed differences in aggregate measures. This study advances the ongoing research on combinatorial auctions by developing continuous auctions that differentiate themselves from earlier combinatorial auction mechanisms by facilitating free flowing participation of bidders and providing exact prices of bundles on demand in real time. For practitioners, the study provides insights on how the nature of feedback can influence the economic outcomes of a complex trading mechanism