Many technology products and platform markets are characterized by indirect network effects. These network effects arise when the benefit from using a product or a service increases with the use of a complementary product or service.…Read More
We investigate the impact of several different recommender algorithms (e.g., Amazon.com’s “Consumers who bought this item also bought”), commonly used in ecommerce and online services, on sales volume and diversity, using field experiment data on movie sales from a top retailer in North America. …Read More
Randomized controlled trials—often called A/B tests in industrial settings—are an increasingly important element in the management many organizations. Such experiments are meant to bring the benefits of scientific rigor and statistical measurement to the domain of managerial decision making. …Read More
In this project, we attempt to provide a rigorous, empirical study of e-commerce A/B testing strategies. We perform a meta-analysis on 2,732 A/B tests conducted by 252 ecommerce companies across seven industries over the course of three years.…Read More
Traditional online platforms (e.g., Amazon Marketplace) use Unilateral Rating System (URS), where customers rate sellers. However, sharing economy platforms (e.g., Uber, Airbnb) have adopted Bilateral Rating System (BRS) that also allows service providers to rate customers, and even selects customers based on their ratings.…Read More
Wharton professor Kartik Hosanagar, author of “A Human’s Guide to Machine Intelligence,” walks through the evolution of artificial intelligence and points to the developments that lie ahead.…Read More
One of the most important trends in business in recent years has been the growth of Big Data and predictive analytics. The trend started with traditional analytics and the emergence of decision support systems. With advances in machine learning (ML), systems can now take in large amounts of data, learn how human decision-makers have made decisions in the past, and make decisions autonomously (achieving human-level or superhuman performance in many activities). …Read More
In this project, we seek to update the statistical paradigm for conducting A/B tests in the 21st century. In particular, we plan to develop a statistical framework that takes the guesswork out of deciding when to stop an experiment and to calibrate a firm’s decision thresholds based on their own historical data.…Read More
A well-known maxim in management is that “your people are your greatest asset”. Recruitment strategies in particular have been linked to firms’ innovative capacity, emphasizing the importance of maintaining competitive advantages in HR as a key goal of effective innovation management. …Read More
We study the impact of network overlap — the overlap in network connections between two users — on content sharing in directed social media platforms. We propose a hazards model that flexibly captures the impact of three different measures of network overlap (i.e., common followees, common followers and common mutual followers) on content sharing.…Read More
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.…Read More
In recent years, digital innovations have fundamentally changed how many services and resources are put together and deployed. These include marketplaces like Uber and Airbnb that help match decentralized supply with demand. …Read More
More than ever before, companies have at their disposal immense streams of customer data. Professor Kartik Hosanagar highlights how companies can make use of this data to attract customers online.…Read More
We study the impact of changes in the position of competing listings in organic search results on the performance of sponsored search advertisements. Using data for several keywords from an online retailer’s ad campaign, we measure the impact of organic competition on both click-through rate and conversion rate of sponsored search ads for these keywords.…Read More
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 drawbacks.…Read More
