We investigate the moderating effect of product attributes and review ratings on {views, conversion|views (conversion conditional on views), final conversion} of a purchase-based collaborative filtering recommender system on an e-commerce site. We run a randomized field experiment on a top...

We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and Natural Language Processing algorithms. We use this dataset to study the...

We investigate the impact of collaborative filtering recommender algorithms (e.g., Amazon’s “Customers who bought this item also bought”) commonly used in e-commerce on sales diversity. We use data from a randomized field experiment run on the website of a top retailer in North America...

Recommender systems are becoming integral to how consumers discovermedia. The value that recommenders offer is personalization: inenvironments with many product choices, recommenders personalize thebrowsing and consumption experience to each user's taste. Popularapplications include product...

Recommender systems are becoming integral to how consumers discover media. The value that recommenders offer is personalization: in environments with many product choices, recommenders personalize the browsing and consumption experience to each userÕs taste. Popular applications include product...

Personalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a customer’s preferences and recommend content best suited to him (e.g., “Customers who liked this also liked…”). A debate has emerged as to whether personalization has...

The erosion of high-end fashion brands by fast fashion copycats (e.g., Zara, H&M) has provoked ongoing controversies and unceasing legal attempts to copyright fashion designs. Despite this tension around the enforcement of copyrights and the purported negative impact of copycats, the effect of...

We examine whether and how ride-sharing services influence the demand for home-sharing services. Our identification strategy hinges on a natural experiment where Uber/Lyft exited Austin in May 2016 in response to new regulations. On a 12-month longitudinal data spanning 11,423 Airbnb properties,...

Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to analyze rich media...

We theorize peer awards’ effects on the volume and novelty of creative user-generated content (UGC) produced at online platform communities. We then test our hypotheses via a randomized field experiment on Reddit, wherein we randomly and anonymously assigned Reddit’s Gold Award to 905...