Publications
Publications
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(5,459)
- Faculty Publications (895)
- November 2020
- Article
Disrupting the Disruptors or Enhancing Them? How Blockchain Re‐Shapes Two‐Sided Platforms
By: Daniel Trabucchi, Antonella Moretto, Tommaso Buganza and Alan MacCormack
The importance of platform‐based businesses in the modern economy is growing continuously and becoming increasingly relevant. Specifically, the deployment of digital technologies has enhanced the applicability of two‐sided business models, enabling companies to act not... View Details
- November–December 2020
- Article
Getting Serious About Diversity: Enough Already with the Business Case
By: Robin Ely and David A. Thomas
Leaders may mean well when they tout the economic payoffs of hiring more women and people of color, but there is no research support for the notion that diversifying the workforce automatically improves a company’s performance. This article critiques the popular... View Details
- October 2020 (Revised March 2024)
- Case
Experimentation at Yelp
By: Iavor Bojinov and Karim R. Lakhani
Over the last decade, experimentation has become integral to the research and development processes of technology companies—including Yelp—for understanding customer preferences and mitigating innovation risks. The case describes Yelp's journey with experimentation,... View Details
- October 2020 (Revised March 2022)
- Case
The What Works Centre: Using Behavioral Science to Improve Social Worker Well-being (A)
By: Ashley V. Whillans and Shibeal O'Flaherty
This case describes the experiences of Michael Sanders—the Chief Executive of the What Works Center for Children’s Social Care—as he led the design and implementation of a program of research aimed at improving the social care system in the United Kingdom (UK) at the... View Details
- October 2020 (Revised March 2022)
- Supplement
The What Works Centre: Using Behavioral Science to Improve Social Worker Well-being (B)
By: Ashley V. Whillans and Shibeal O'Flaherty
This case describes the experiences of Michael Sanders—the Chief Executive of the What Works Center for Children’s Social Care—as he led the design and implementation of a program of research aimed at improving the social care system in the United Kingdom (UK) at the... View Details
- Fall 2020
- Article
Christo and Jeanne‐Claude: The Negotiation of Art and Vice Versa
Over the past two decades the Program on Negotiation at Harvard Law School (PON) has named thirteen people as Great Negotiators. The project, directed by my colleague Jim Sebenius, has given us the opportunity to commend our honorees’ outstanding work and to learn from... View Details
- October 2020
- Article
Comparative Statics for Size-Dependent Discounts in Matching Markets
By: David Delacretaz, Scott Duke Kominers and Alexandru Nichifor
We prove a natural comparative static for many-to-many matching markets in which agents’ choice functions exhibit size-dependent discounts: reducing the extent to which some agent discounts additional partners leads to improved outcomes for the agents on the other side... View Details
- Oct 2020
- Conference Presentation
Optimal, Truthful, and Private Securities Lending
By: Emily Diana, Michael J. Kearns, Seth Neel and Aaron Leon Roth
We consider a fundamental dynamic allocation problem motivated by the problem of securities lending in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of identical copies of some scarce resource... View Details
- September 2020 (Revised July 2021)
- Case
Moderna (A)
By: Marco Iansiti, Karim R. Lakhani, Hannah Mayer and Kerry Herman
In summer 2020, Stephane Bancel, CEO of biotech firm Moderna, faces several challenges as his company races to develop a vaccine for COVID-19. The case explores how a company builds a digital organization, and leverages artificial intelligence and other digital... View Details
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details
Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio
- 2024
- Working Paper
Chimeric Antigen Receptor T-Cell Therapy—Living Drugs: Case Histories of Transformational Advances
By: Amar Bhidé and Srikant M. Datar
In 2017, the US Food and Drug Administration (FDA) approved an immunotherapeutic treatment, called CAR-T therapy, for two kinds of blood cancers—acute leukemia (ALL) and a lymphoma. We describe 1) how CAR-T works, 2) the foundational advances and discoveries, 3) the... View Details
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
- 2020
- Book
Dealmaking: The New Strategy of Negotiauctions
Based on broad research and detailed case studies, Dealmaking provides the jargon-free, empirically sound advice you need to close the deal.
Leading dealmaking scholar Guhan Subramanian specializes in understanding how deals work. As a Harvard Business... View Details
Leading dealmaking scholar Guhan Subramanian specializes in understanding how deals work. As a Harvard Business... View Details
- Article
Matching in Networks with Bilateral Contracts: Corrigendum
By: John William Hatfield, Ravi Jagadeesan and Scott Duke Kominers
Hatfield and Kominers (2012) introduced a model of matching in networks with bilateral contracts and showed that stable outcomes exist in supply chains when firms' preferences over contracts are fully substitutable. Hatfield and Kominers (2012) also asserted that in... View Details
- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments.... View Details
- July 2020
- Case
Mortgage Backed Securities and the Covid-19 Pandemic
By: Emil N. Siriwardane, Luis M. Viceira and Dean Xu
In April 2020, global financial markets were still reeling as the COVID-19 pandemic spread rapidly across the world. Global equity markets had initially fallen by 30% in response to the pandemic, and high-yield credit markets had dropped by nearly 20%. In contrast,... View Details
- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details
- Article
Active World Model Learning with Progress Curiosity
By: Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber and Daniel Yamins
World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal... View Details