Filter Results
:
(423)
Show Results For
-
All HBS Web
(1,519)
- Faculty Publications (423)
Show Results For
-
All HBS Web
(1,519)
- Faculty Publications (423)
- May 8, 2020
- Article
Which Covid-19 Data Can You Trust?
By: Satchit Balsari, Caroline Buckee and Tarun Khanna
The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad...
View Details
Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
- 2020
- Article
Public Sentiment and the Price of Corporate Sustainability
By: George Serafeim
Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong...
View Details
Keywords:
Sustainability;
ESG;
ESG (Environmental, Social, Governance) Performance;
Investment Management;
Investment Strategy;
Big Data;
Machine Learning;
Environment;
Environmental Sustainability;
Corporate Governance;
Performance;
Asset Pricing;
Investment;
Management;
Strategy;
Human Capital;
Public Opinion;
Value;
Analytics and Data Science
Serafeim, George. "Public Sentiment and the Price of Corporate Sustainability." Financial Analysts Journal 76, no. 2 (2020): 26–46.
- March 2020 (Revised June 2022)
- Case
GreenLight Fund
By: Brian Trelstad, Julia Kelley and Mel Martin
As Tara Noland, the Executive Director (ED) of GreenLight Cincinnati, reflected on her first few years on the job. Noland had delivered on what she had been hired to do in the city: work with leading philanthropists and nonprofit executives to use data and evidence to...
View Details
Keywords:
Philanthropy;
Venture Philanthropy;
Replication;
Philanthropy and Charitable Giving;
Venture Capital;
Social Issues;
Decision Making;
Analytics and Data Science;
Cincinnati
Trelstad, Brian, Julia Kelley, and Mel Martin. "GreenLight Fund." Harvard Business School Case 320-053, March 2020. (Revised June 2022.)
- March 2020
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data.
View Details
Keywords:
Analytics;
Human Resource Management;
Data;
Workforce;
Hiring;
Talent Management;
Forecasting;
Predictive Analytics;
Organizational Behavior;
Recruiting;
Analytics and Data Science;
Forecasting and Prediction;
Recruitment;
Selection and Staffing;
Talent and Talent Management
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
- 2021
- Working Paper
Corporate Environmental Impact: Measurement, Data and Information
By: David Freiberg, DG Park, George Serafeim and T. Robert Zochowski
As an organization’s environmental impact has become a central societal consideration, thereby affecting industry and organizational competitiveness, interest in measuring and analyzing environmental impact has increased. We develop a methodology to derive comparable...
View Details
Keywords:
Environment;
Impact;
Measurement;
Environmental Ratings;
Corporate Valuation;
Financial Materiality;
Sustainability;
Environmental Impact;
Environmental Strategy;
Impact-Weighted Accounts;
IWAI;
Environmental Sustainability;
Corporate Social Responsibility and Impact;
Measurement and Metrics;
Valuation
Freiberg, David, DG Park, George Serafeim, and T. Robert Zochowski. "Corporate Environmental Impact: Measurement, Data and Information." Harvard Business School Working Paper, No. 20-098, March 2020. (Revised February 2021.)
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first...
View Details
Keywords:
Missing Data;
Diagnostic Tools;
Sensitivity Analysis;
Hypothesis Testing;
Missing At Random;
Row Exchangeability;
Analytics and Data Science;
Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- 2020
- Book
The Power of Experiments: Decision-Making in a Data-Driven World
By: Michael Luca and Max H. Bazerman
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...
View Details
Keywords:
Experiments;
Randomized Controlled Trials;
Organizations;
Decision Making;
Analytics and Data Science;
Management Analysis, Tools, and Techniques
Luca, Michael, and Max H. Bazerman. The Power of Experiments: Decision-Making in a Data-Driven World. Cambridge, MA: MIT Press, 2020.
- 2020
- Working Paper
A General Theory of Identification
By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree
on a definition in the context of parametric statistical models — roughly, a parameter θ in a model
P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective....
View Details
Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
- February 2020 (Revised April 2021)
- Case
StockX: The Stock Market of Things
By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust...
View Details
Keywords:
Markets;
Auctions;
Bids and Bidding;
Demand and Consumers;
Consumer Behavior;
Analytics and Data Science;
Market Design;
Digital Platforms;
Market Transactions;
Marketplace Matching;
Supply and Industry;
Analysis;
Price;
Product Marketing;
Product Launch;
Apparel and Accessories Industry;
Fashion Industry;
North and Central America;
United States;
Michigan;
Detroit
Farronato, Chiara, John J. Horton, Annelena Lobb, and Julia Kelley. "StockX: The Stock Market of Things." Harvard Business School Case 620-062, February 2020. (Revised April 2021.)
- 2020
- Book
Experimentation Works: The Surprising Power of Business Experiments
By: Stefan Thomke
Don’t fly blind. See how the power of experiments works for you. When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition,...
View Details
Keywords:
Experimentation;
Experiments;
Market Research;
Innovation and Invention;
Innovation and Management;
Customers;
Research
Thomke, Stefan. Experimentation Works: The Surprising Power of Business Experiments. Boston, MA: Harvard Business Review Press, 2020.
- January 2020
- Case
Kaggle 2019 Data Science Survey
By: Yael Grushka-Cockayne, Michael Parzen, Paul Hamilton and Steven Randazzo
Grushka-Cockayne, Yael, Michael Parzen, Paul Hamilton, and Steven Randazzo. "Kaggle 2019 Data Science Survey." Harvard Business School Case 620-091, January 2020.
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving...
View Details
Keywords:
Autoencoder Networks;
Pattern Detection;
Subset Scanning;
Computer Vision;
Statistical Methods And Machine Learning;
Machine Learning;
Deep Learning;
Data Mining;
Big Data;
Large-scale Systems;
Mathematical Methods;
Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting...
View Details
Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
- November 2019
- Supplement
Innovation at Uber: The Launch of Express POOL
By: Chiara Farronato, Alan MacCormack and Sarah Mehta
This multimedia supplement accompanies the case “Innovation at Uber: the Launch of Express POOL” (case no. 619-003). Set in March 2018, the case follows ride-sharing company Uber as it develops and launches a new product called Express POOL. This multimedia supplement...
View Details
Keywords:
Innovation and Management;
Innovation Leadership;
Innovation Strategy;
Technological Innovation;
Information Technology;
Mobile and Wireless Technology;
Applications and Software;
Digital Platforms;
Technology Industry;
California;
San Francisco
Farronato, Chiara, Alan MacCormack, and Sarah Mehta. "Innovation at Uber: The Launch of Express POOL." Harvard Business School Multimedia/Video Supplement 620-702, November 2019.
- November 2019 (Revised January 2020)
- Case
Bayer Crop Science
By: David E. Bell, Damien McLoughlin, Natalie Kindred and James Barnett
In mid-2019, a year after German conglomerate Bayer Group closed its acquisition of U.S.-based seeds giant Monsanto, the leadership of Bayer’s Crop Science division (which absorbed Monsanto) is reflecting on the opportunities ahead. Some observers have questioned...
View Details
Keywords:
Agribusiness;
Research and Development;
Innovation and Invention;
Innovation Strategy;
Mergers and Acquisitions;
Consolidation;
Customer Value and Value Chain;
Change Management;
Agriculture and Agribusiness Industry;
Technology Industry;
United States;
Germany
Bell, David E., Damien McLoughlin, Natalie Kindred, and James Barnett. "Bayer Crop Science." Harvard Business School Case 520-055, November 2019. (Revised January 2020.)
- September 2019 (Revised August 2020)
- Case
Engineering an Inclusive Bioeconomy
By: Tarun Khanna, Raffaella Sadun and Susie L. Ma
In 2019, entrepreneur Juan Carlos Castilla-Rubio was developing a project he hoped could generate and share wealth from the natural resources of the Amazon without destroying those resources. His idea, called Earth Bank of Codes (EBC), would create a library of the...
View Details
Keywords:
Decision Making;
Development Economics;
Entrepreneurship;
Innovation and Invention;
Intellectual Property;
Emerging Markets;
Market Design;
Marketplace Matching;
Science;
Genetics;
Natural Environment;
Environmental Sustainability;
Climate Change;
Social Enterprise;
Strategy;
Strategic Planning;
Information Technology;
Ownership;
Social Psychology;
Trust;
Society;
Biotechnology Industry;
South America;
Amazon Basin
Khanna, Tarun, Raffaella Sadun, and Susie L. Ma. "Engineering an Inclusive Bioeconomy." Harvard Business School Case 720-356, September 2019. (Revised August 2020.)
- Article
Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions
By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani
Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant...
View Details
Keywords:
Computational Biology;
Bioinformatics;
Innovation Competitions;
Research;
Collaborative Innovation and Invention
Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." PLoS ONE 14, no. 9 (September 2019).
- August 2019 (Revised February 2020)
- Teaching Note
Sidewalk Labs: Privacy in a City Built from the Internet Up
By: Leslie John and Mitch Weiss
Email mking@hbs.edu for a courtesy copy.
The case serves as a microcosm of issues of digital privacy: the availability of data – personal data in particular – has tremendous potential to improve people’s lives... View Details
The case serves as a microcosm of issues of digital privacy: the availability of data – personal data in particular – has tremendous potential to improve people’s lives... View Details
Keywords:
Privacy;
Privacy By Design;
Privacy Regulation;
Platforms;
Data;
Data Security;
Behavioral Science;
Analytics and Data Science;
Safety;
Entrepreneurship;
Business and Government Relations;
Consumer Behavior;
Digital Platforms
John, Leslie, and Mitch Weiss. "Sidewalk Labs: Privacy in a City Built from the Internet Up." Harvard Business School Teaching Note 820-023, August 2019. (Revised February 2020.) (Email mking@hbs.edu for a courtesy copy.)
- 2019
- Working Paper
The Impact of Professionals' Contributions to Online Knowledge Communities on Their Workplace Knowledge Work
By: Hila Lifshitz - Assaf and Frank Nagle
Knowledge work is becoming increasingly challenging as pace of change in the knowledge frontier is increasing. Organizations have created multiple mechanisms to minimize knowledge gaps and increase learning such internal training, mentorship programs as well as...
View Details
Keywords:
Open Source;
Future Of Work;
Software Development;
Knowledge Work;
Online Community;
Learning;
Knowledge Sharing;
Applications and Software;
Open Source Distribution;
Performance Productivity
Lifshitz - Assaf, Hila, and Frank Nagle. "The Impact of Professionals' Contributions to Online Knowledge Communities on Their Workplace Knowledge Work." Working Paper, April 2019.
- 2019
- Article
History, Micro Data, and Endogenous Growth
By: Ufuk Akcigit and Tom Nicholas
The study of economic growth is concerned with long-run changes, and therefore, historical data should be especially influential in informing the development of new theories. In this review, we draw on the recent literature to highlight areas in which study of history...
View Details
Keywords:
Economic Development;
Growth;
Innovation;
Economic Growth;
History;
Analytics and Data Science;
Innovation and Invention
Akcigit, Ufuk, and Tom Nicholas. "History, Micro Data, and Endogenous Growth." Annual Review of Economics 11 (2019): 615–633.