Michael Luca is the Lee J. Styslinger III Associate Professor of Business Administration at Harvard Business School. Professor Luca teaches From Data to Decisions: The Role of Experiments, an elective course about the rise of experiments in organizations, and the role that they play in decision making. He also teaches an elective course in which student teams develop interventions based in behavioral economics for government and company clients, called Behavioral Insights.
Professor Luca's current research and advisory work focuses on the design of online platforms, and on the ways in which data from platforms can inform managerial and policy decisions. His work has been published in academic journals including Management Science, the Proceedings of the National Academy of Sciences, American Economic Review: Papers and Proceeding, the American Economic Journal: Applied Economics, and the American Economic Journal: Microeconomics. He has also written about behavioral economics and online platforms for media outlets including The Wall Street Journal, The Atlantic, and Slate.
His research has been written about in a variety of media outlets including The Wall Street Journal, New York Times, New Yorker, Atlantic, Economist, Washington Post, Financial Times, Guardian, Huffington Post, Harvard Business Review, Time, USA Today, Boston Globe, LA Times, San Francisco Chronicle, Fortune, Mashable, GQ, Wired, and Vox.
Professor Luca serves on the board of directors at the National Association of Business Economics, the academic advisory board of the Behavioural Insights Team, and the advisory board of the CNBC Technology Executive Council, and is a faculty research fellow at the National Bureau of Economic Research.
Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of changes to an experience or product. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream – and is becoming an important part of the managerial toolkit.
In The Power of Experiments: Decision-Making in a Data Driven World, Michael Luca and Max Bazerman explore the value of experiments, and the ways in which they can improve organizational decisions. Drawing on real world experiments and case studies, Luca and Bazerman show that going by gut is no longer enough—successful leaders need frameworks for moving between data and decisions.Experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget without losing customers. Experiments can also bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts.
The Power of Experiments introduces readers to the topic of experimentation and the managerial challenges that surround them. Looking at experiments in the tech sector and beyond, this book offers lessons and best practices for making the most of experiments.
As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies-tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems.
State waiting periods for handgun purchases prevent about 750 gun deaths each year in the United States, new research has found.
An estimated 910 gun deaths could also be avoided if those policies were adopted nationwide, according to the study, published Monday in the Proceedings of the National Academy of Sciences.
Abstract: We study the impact of the minimum wage on firm exit in the restaurant industry, exploiting recent changes in the minimum wage at the city level. The evidence suggests that higher minimum wages increase overall exit rates for restaurants. However, lower quality restaurants, which are already closer to the margin of exit, are disproportionately impacted by increases to the minimum wage. Our point estimates suggest that a one dollar increase in the minimum wage leads to a 14 percent increase in the likelihood of exit for a 3.5-star restaurant (which is the median rating), but has no discernible impact for a 5-star restaurant (on a 1 to 5 star scale).
Some restaurants owners have argued that raising the minimum wage may force them to close, or cut staff. Now a new study suggests that this only really happens to restaurants with lower customer satisfaction ratings as measured by Yelp.
Abstract: In an experiment on Airbnb, we find that applications from guests with distinctively African American names are 16 percent less likely to be accepted relative to identical guests with distinctively white names. Discrimination occurs among landlords of all sizes, including small landlords sharing the property and larger landlords with multiple properties. It is most pronounced among hosts who have never had an African American guest, suggesting only a subset of hosts discriminate. While rental markets have achieved significant reductions in discrimination in recent decades, our results suggest that Airbnb's current design choices facilitate discrimination and raise the possibility of erasing some of these civil rights gains.
In the sharing economy, the goal to personalize the exchange can have some unintended consequences. The Hidden Brain podcast explores how discrimination plays out on AirBnB.
The company announced plans to combat discrimination on its platform. It’s still falling short.
Not that long ago, online commerce promised not only to make markets more efficient but also more inclusive and less prone to discrimination. The rationale was simple: On the internet, no one knows whether you’re black or white, male or female, making it more difficult for discrimination to occur. Those early ideals have long since withered, as Airbnb and other online platforms have increasingly asked buyers and sellers to provide pictures and other racially identifying information to counterparties. Even worse, the emergence of discrimination in online markets is undoing gains that occurred in offline markets through decades of regulation and enforcement.
In the late 1980s, law professors Ian Ayres and Peter Siegelman set out to learn whether blacks and women got the same deals as white men when buying a new car. They trained 38 people—some white and some black, some male and some female—to negotiate a purchase using a fixed script, and uncovered disturbing differences: Across 153 dealerships, black and female buyers paid more for the same cars than white men did, with black women paying the most—on average, nearly $900 more than white men. Although the findings weren’t a surprise to most people, least of all to blacks and women, they were a compelling demonstration of just how discriminatory markets can be.
Most managers’ jobs involve making predictions. When HR specialists decide whom to hire, they’re predicting who will be most effective. When marketers choose which distribution channels to use, they’re predicting where a product will sell best. When VCs determine whether to fund a start-up, they’re predicting whether it will succeed. To make these and myriad other business predictions, companies today are turning more and more to computer algorithms, which perform step-by-step analytical operations at incredible speed and scale.
The Digital Initiative is a cross-unit venture that unites scholars and practitioners to explore and impact the transformation of business in today’s digital, networked, and media-rich environment.
