Facing mounting criticism and evidence of widespread racial discrimination on the platform, apartment rental platform Airbnb needed to decide a path forward. For years, Airbnb had given hosts extensive discretion about whether to reject a guest after seeing little more than a name and a picture, believing this was the best way for the company to build trust. While Airbnb ran thousands of experiments per year looking at ways to grow the user base and short-run profit, they failed to track or account for the possibility of discrimination. Should they become more proactive about identifying discrimination on the platform? Should they change the design of the platform to reduce discrimination? If so, how would they decide whether the changes were successful?
Online reviews are transforming the way consumers choose products and services of all sorts. We turn to TripAdvisor to plan a vacation, Zocdoc to find a doctor, and Yelp to choose a new restaurant. Reviews can create value for buyers and sellers alike, but only if they attain a critical level of quantity and quality. The authors describe principles for setting the incentives, design choices, and rules that help review platforms thrive. To address a shortage of reviews, companies can seed them by hiring reviewers or drawing reviews from other platforms; offer incentives; or pool products. To address selection bias, they can require reviews, allow private comments, and design prompts carefully. To combat fraudulent and strategic reviews, they can set rules for reviewers and call in moderators--whether employees, the community, or algorithms.
Advertising Experiments at RestaurantGrades is an exercise in which students are asked to analyze and make a recommendation on the basis of simulated experimental data. The setting is a hypothetical restaurant review company called RestaurantGrades (RG), which shows advertisements above the organic search results when someone searches on the page. RG is trying to understand whether the current advertising package it sells to restaurants is effective at driving traffic-and whether an alternative advertising package might be better. To do this, RG has run an experiment with two treatment groups and a control group-with random assignment done at the restaurant level. Restaurants in the control group are provided with no advertising; restaurants in the first treatment group are given RG's current advertising package, and restaurants in the second treatment group are given an alternative advertising package. Students are provided with the resulting data-which includes an indicator for which arm a business was in, as well as outcomes at the monthly level for each business-and asked to assess which advertising package is more effective. The exercise provides students with an opportunity for experiential learning around the use of experiments to guide business decisions.
By providing free and open-access online courses at a large scale, Massive Open Online Course (MOOC) platforms seek to innovate the business models of the traditional higher education industry. In a little over a year, Coursera had grown at a rapid rate to emerge as a leader of the MOOCs in terms of the number of student enrollments, courses, and partners. The case examines two aspects of these developments in the industry: (1) What choices did Coursera make that enabled it to grow so quickly? (2) In what ways did Coursera's success impact the success of its competitors, Udacity and edX? Would one player naturally come to dominate the industry, and if so, what choices should Coursera make to retain its market positioning?