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All HBS Web
(1,525)
- News (199)
- Research (1,092)
- Events (13)
- Multimedia (1)
- Faculty Publications (622)
- June 2022 (Revised July 2022)
- Technical Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...
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Keywords:
Causal Inference;
Causality;
Experiment;
Experimental Design;
Data Science;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised July 2022.)
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea...
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Keywords:
Algorithm Bias;
Algorithmic Data;
Race And Ethnicity;
Experimentation;
Promotion;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Pricing Algorithms;
A/B Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
Marketing;
Race;
Gender;
Diversity;
Customer Relationship Management;
Marketing Communications;
Advertising;
Decision Making;
Ethics;
E-commerce;
Analytics and Data Science;
Apparel and Accessories Industry;
Apparel and Accessories Industry;
United States
- Research Summary
Overview
By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data...
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- October 2022
- Supplement
Single Earth: Science White Paper Supplement
By: Rembrand Koning and Emer Moloney
Science White Paper prepared by Single.Earth to give an overview of the models and solutions it has developed.
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Keywords:
Business Startups;
Entrepreneurship;
Climate Change;
Environmental Sustainability;
Green Technology;
Natural Resources;
Pollution;
Analytics and Data Science;
Marketing;
Product Marketing;
Product Launch;
Product Positioning;
Markets;
Market Timing;
Strategy;
Green Technology Industry;
Estonia
- August 1997
- Case
Orbital Sciences Corporation: ORBCOMM
By: Das Narayandas and John A. Quelch
In late 1993, Orbital Communications Corp. (OCC), a subsidiary of Orbital Sciences Corp., is developing a global two-way wireless data communications system, called "ORBCOMM," based on a 26-satellite constellation in low earth orbit. Service is scheduled to begin in...
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Keywords:
Business Subsidiaries;
Business Model;
Business Startups;
Price;
Global Strategy;
Marketing Strategy;
Demand and Consumers;
Partners and Partnerships;
Salesforce Management;
Telecommunications Industry
Narayandas, Das, and John A. Quelch. "Orbital Sciences Corporation: ORBCOMM." Harvard Business School Case 598-027, August 1997.
- April 2022
- Teaching Note
Banorte Móvil: Data-Driven Mobile Growth
By: Ayelet Israeli and Carla Larangeira
In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had...
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- January 2018
- Article
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
By: Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
New, "big" data sources allow measurement of city characteristics and outcome variables at higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for...
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Glaeser, Edward L., Scott Duke Kominers, Michael Luca, and Nikhil Naik. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life." Economic Inquiry 56, no. 1 (January 2018): 114–137.
- August 2022
- Supplement
Zalora: Data-Driven Pricing Recommendations
By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the...
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Keywords:
Pricing;
Pricing Algorithms;
Dynamic Pricing;
Ecommerce;
Pricing Strategy;
Pricing And Revenue Management;
Apparel;
Singapore;
Startup;
Demand Estimation;
Data Analysis;
Data Analytics;
Exercise;
Price;
Internet and the Web;
Apparel and Accessories Industry;
Apparel and Accessories Industry;
Apparel and Accessories Industry;
Singapore
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
- August 2015 (Revised January 2017)
- Technical Note
From Correlation to Causation
By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes...
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Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
- 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...
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Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing...
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Keywords:
Forecasting Models;
Simulation Methods;
Regional Economic Activity: Growth, Development, Environmental Issues, And Changes;
Geographic Location;
Local Range;
Transition;
Analytics and Data Science;
Measurement and Metrics;
Economic Growth;
Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
- October 2017
- Case
Quantopian: A New Model for Active Management
Keywords:
Big Data;
Hedge Fund;
Crowdsourcing;
Investment Fund;
Quantitative Hedge Fun;
Algorithmic Data;
Analytics and Data Science
Fleiss, Sara, Adi Sunderam, Luis M. Viceira, and Caitlin Carmichael. "Quantopian: A New Model for Active Management." Harvard Business School Case 218-046, October 2017.
- July 2022
- Case
Operation Overlord
By: Boris Groysberg, Greg Goullet, Katherine Connolly Baden and Sarah L. Abbott
On June 6, 1944, nearly 5,000 ships, 11,000 planes, and 160,000 infantrymen under an Allied joint-command of American, British, and Canadian leaders were sent across the English Channel, with hopes of re-establishing a foothold in Nazi-occupied France. Known as D-Day,...
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Keywords:
Execution;
Data Analytics;
Leadership;
Planning;
Operations;
Crisis Management;
War;
Organizational Structure;
Decision Choices and Conditions;
Information Management;
France;
England
Groysberg, Boris, Greg Goullet, Katherine Connolly Baden, and Sarah L. Abbott. "Operation Overlord." Harvard Business School Case 422-098, July 2022.
- February 2017 (Revised August 2018)
- Case
Sarah Powers at Automated Precision Products
By: Jeffrey T. Polzer, Michael Norris, Julia Kelley and Kristina Tobio
In 2017, Sarah Powers, VP of Sales at an automation hardware firm, is trying to understand why some members of her sales team have been underperforming. She is tasked with analyzing her firm’s email and calendar data to try to find relationships between communications...
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Keywords:
People Analytics;
Sales Attainment;
Communication Networks;
Data;
Human Resources;
Business Processes;
Sales;
Communication;
Analytics and Data Science;
Analysis;
Industrial Products Industry;
Manufacturing Industry;
United States
Polzer, Jeffrey T., Michael Norris, Julia Kelley, and Kristina Tobio. "Sarah Powers at Automated Precision Products." Harvard Business School Case 417-072, February 2017. (Revised August 2018.)
- 01 Dec 2014
- News
Making Big Data Fashionable
get designs to consumers in as little as four weeks—and at an affordable price. In 2012, Moon—who has a background in fashion design, investment banking, corporate strategy, and social commerce startups—launched Trendalytics, a visual...
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- October 2016
- Article
Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science
By: Kevin J. Boudreau, Eva Guinan, Karim R. Lakhani and Christoph Riedl
Selecting among alternative innovative projects is a core management task in all innovating organizations. In this paper, we focus on the evaluation of frontier scientific research projects. We argue that the "intellectual distance" between the knowledge embodied in...
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Keywords:
Knowledge;
Innovation;
Novelty;
Evaluation;
Resource Allocation;
Decision Choices and Conditions;
Innovation and Management;
Science-Based Business;
Experience and Expertise
Boudreau, Kevin J., Eva Guinan, Karim R. Lakhani, and Christoph Riedl. "Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science." Management Science 62, no. 10 (October 2016).
- 2016
- Working Paper
Innovating in Science and Engineering or 'Cashing In' on Wall Street? Evidence on Elite STEM Talent
By: Pian Shu
Using data on MIT bachelor's graduates from 1994 to 2012, this paper empirically examines the extent to which the inflow of elite talent into the financial industry affects the supply of innovators in science and engineering (S&E). I first show that finance does not...
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Shu, Pian. "Innovating in Science and Engineering or 'Cashing In' on Wall Street? Evidence on Elite STEM Talent." Harvard Business School Working Paper, No. 16-067, December 2015. (Revised November 2016.)
- May 2014
- Article
Incorporating Field Data into Archival Research
By: Eugene F. Soltes
I explore the use of field data in conjunction with archival evidence by examining Iliev, Miller, and Roth's (2014) analysis of an amendment to the Securities Exchange Act of 1934. This regulatory amendment allowed depositary banks to cross-list firms without the...
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Soltes, Eugene F. "Incorporating Field Data into Archival Research." Journal of Accounting Research 52, no. 2 (May 2014): 521–540.
- 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.)
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...
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Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 38th (2022): 1264–1274.