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  • All HBS Web  (1,486)
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Show Results For

  • All HBS Web  (1,486)
    • News  (192)
    • Research  (1,057)
    • Events  (20)
    • Multimedia  (8)
  • Faculty Publications  (655)
← Page 11 of 1,486 Results →
  • May 2018
  • Case

The Multiple Myeloma Research Foundation's Answer Fund

By: Richard G. Hamermesh and Matthew G. Preble
Keywords: Data Analytics; Customer Focus and Relationships; Customer Relationship Management; Cost vs Benefits; Investment Return; Health Care and Treatment; Innovation Leadership; Intellectual Property; Knowledge Sharing; Knowledge Dissemination; Leadership; Leading Change; Resource Allocation; Goals and Objectives; Marketing Communications; Performance; Programs; Projects; Business and Community Relations; Business and Stakeholder Relations; Networks; Partners and Partnerships; Research and Development; Genetics; Behavior; Motivation and Incentives; Social and Collaborative Networks; Nonprofit Organizations; Strategy; Health Industry; Pharmaceutical Industry; Biotechnology Industry; United States
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Hamermesh, Richard G., and Matthew G. Preble. "The Multiple Myeloma Research Foundation's Answer Fund." Harvard Business School Case 818-045, May 2018.
  • February 2013
  • Case

Recorded Future: Analyzing Internet Ideas About What Comes Next

Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The... View Details
Keywords: Big Data; Analytics; Internet; Analytics and Data Science; Internet and the Web; Entrepreneurship; Forecasting and Prediction; Business Startups; Information Technology Industry
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Davenport, Thomas H. "Recorded Future: Analyzing Internet Ideas About What Comes Next." Harvard Business School Case 613-083, February 2013.
  • February 2006
  • Article

Do Stronger Intellectual Property Rights Increase International Technology Transfer? Empirical Evidence from U.S. Firm-Level Panel Data

By: Lee G. Branstetter, Raymond Fisman and C. Fritz Foley
Keywords: Intellectual Property; Rights; Information Technology; Information; Analytics and Data Science; United States
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Branstetter, Lee G., Raymond Fisman, and C. Fritz Foley. "Do Stronger Intellectual Property Rights Increase International Technology Transfer? Empirical Evidence from U.S. Firm-Level Panel Data." Quarterly Journal of Economics 121, no. 1 (February 2006): 321–349.
  • November 5, 2021
  • Article

Leaders: Stop Confusing Correlation with Causation

By: Michael Luca
We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide... View Details
Keywords: Behavioral Economics; Data Analysis; Organizations; Decision Making; Analytics and Data Science; Analysis; Learning
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Luca, Michael. "Leaders: Stop Confusing Correlation with Causation." Harvard Business Review Digital Articles (November 5, 2021).
  • January 2025 (Revised March 2025)
  • Case

Thomas Müller: Mr. Bayern Munich

By: Boris Groysberg, Sascha L. Schmidt, Alexander Liebhart and Sarah Abbott
In 2024, FC Bayern Munich superstar Thomas Müller announced his retirement from German national football. His contract with Bayern Munich runs through the end of the 2024-25 season. In 2025, Müller reflects on his long career in football, on the skills that have driven... View Details
Keywords: Soccer; Football; Data Science And Analytics Management; Bundesliga; Sports Data; "Sports Organizations,; Career Changes And Transitions; Career Management; Retirement Transition; Skills Development; Analysis; Competency and Skills; Decision Making; Performance; Personal Development and Career; Retirement; Transition; Sports Industry; Germany
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Groysberg, Boris, Sascha L. Schmidt, Alexander Liebhart, and Sarah Abbott. "Thomas Müller: Mr. Bayern Munich." Harvard Business School Case 425-031, January 2025. (Revised March 2025.)
  • October 2017 (Revised November 2017)
  • Case

NYC311

By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded... View Details
Keywords: New York City; NYC; 311; NYC311; Big Data; Equal Access; Bias; Data Analysis; Public Entrepreneurship; Urban Informatics; Predictive Analytics; Chief Data Officer; Data Analytics; Cities; City Leadership; Analytics and Data Science; Analysis; Prejudice and Bias; Entrepreneurship; Public Sector; City; Public Administration Industry; New York (city, NY)
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Kontokosta, Constantine E., Mitchell Weiss, Christine Snively, and Sarah Gulick. "NYC311." Harvard Business School Case 818-056, October 2017. (Revised November 2017.)
  • February 2021
  • Tutorial

T-tests: Theory and Practice

By: Michael Parzen, Natalie Epstein, Chiara Farronato and Michael Toffel
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details
Keywords: Data Analysis; Data Analytics; Experiment Design; Experimentation; Analytics and Data Science; Analysis
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Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021.
  • September 2020 (Revised June 2023)
  • Supplement

Spreadsheet Supplement to Artea Teaching Note

By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to Artea Teaching Note 521-041. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details
Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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Ascarza, Eva, and Ayelet Israeli. "Spreadsheet Supplement to Artea Teaching Note." Harvard Business School Spreadsheet Supplement 521-705, September 2020. (Revised June 2023.)
  • August 2020
  • Technical Note

Comparing Two Groups: Sampling and t-Testing

By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
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Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
  • April 2015
  • Case

Carolinas HealthCare System: Consumer Analytics

By: John A. Quelch and Margaret L. Rodriguez
In 2014, Dr. Michael Dulin, chief clinical officer for analytics and outcomes research and head of the Dickson Advanced Analytics (DA2) group at Carolinas HealthCare System (CHS), successfully unified all analytics talent and resources into one group over a three year... View Details
Keywords: Consumer Segmentation; Big Data; Management Information Systems; Hospital Management; Health Care and Treatment; Marketing; Segmentation; Analytics and Data Science; Information Management; Information Technology; Health; Health Industry; United States
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Quelch, John A., and Margaret L. Rodriguez. "Carolinas HealthCare System: Consumer Analytics." Harvard Business School Case 515-060, April 2015.
  • 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... View Details
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
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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.)
  • Spring 2016
  • Article

The Billion Prices Project: Using Online Prices for Inflation Measurement and Research

By: Alberto Cavallo and Roberto Rigobon
New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both... View Details
Keywords: Billion Prices Project; Online Scraped Data; Online Price Index; Economics; Research; Price; Analytics and Data Science
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Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Inflation Measurement and Research." Journal of Economic Perspectives 30, no. 2 (Spring 2016): 151–178.
  • Article

Nudging: Progress to Date and Future Directions

By: John Beshears and Harry Kosowsky
Nudges influence behavior by changing the environment in which decisions are made, without restricting the menu of options and without altering financial incentives. This paper assesses past empirical research on nudging and provides recommendations for future work in... View Details
Keywords: Nudge; Choice Architecture; Behavioral Economics; Behavioral Science; Behavior; Change; Situation or Environment; Decision Choices and Conditions; Decision Making
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Beshears, John, and Harry Kosowsky. "Nudging: Progress to Date and Future Directions." Organizational Behavior and Human Decision Processes 161, Supplement (November 2020): 3–19.
  • January 2014 (Revised December 2014)
  • Case

GenapSys: Business Models for the Genome

By: Richard G. Hamermesh, Joseph B. Fuller and Matthew Preble

GenapSys, a California-based startup, was soon to release a new DNA sequencer that the company's founder, Hesaam Esfandyarpour, believed was truly revolutionary. The sequencer would be substantially less expensive—potentially costing just a few thousand dollars—and... View Details

Keywords: DNA Sequencing; Life Sciences; Business Model; Innovation & Entrepreneurship; Health Care and Treatment; Genetics; Business Strategy; Biotechnology Industry; Pharmaceutical Industry; Technology Industry; Health Industry; Medical Devices and Supplies Industry; United States
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Hamermesh, Richard G., Joseph B. Fuller, and Matthew Preble. "GenapSys: Business Models for the Genome." Harvard Business School Case 814-050, January 2014. (Revised December 2014.)
  • February 2014
  • Case

BGI: Data-driven Research

By: Willy Shih and Sen Chai
BGI has the largest installed gene-sequencing capacity in the world, and to Zhang Gengyun, general manager of the Life Sciences Division, this represented an opportunity to apply his training as a plant breeder and his early career work as a biochemist to improving... View Details
Keywords: Genomics; Gene Sequencing; Life Sciences; Plant Breeding; Human Genome Program; Beijing Genomics Institute; BGI; Rice Genome; Technological Innovation; Innovation Strategy; Research; Research and Development; Science; Genetics; Science-Based Business; Strategy; Commercialization; Corporate Strategy; Information Technology; Applications and Software; Agriculture and Agribusiness Industry; Biotechnology Industry; Food and Beverage Industry; China; United States
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Shih, Willy, and Sen Chai. "BGI: Data-driven Research." Harvard Business School Case 614-056, February 2014.
  • March–April 2017
  • Article

Advancing Conservation by Understanding and Influencing Human Behavior

By: Sheila M. Reddy, Jensen Montambault, Yuta J. Masuda, Ayelet Gneezy, Elizabeth Keenan, William Butler, Jonathan R. Fisher and Stanley T. Asah
Behavioral sciences can advance conservation by systematically identifying behavioral barriers to conservation and how to best overcome them. Behavioral sciences have informed policy in many other realms (e.g., health, savings), but they are a largely untapped resource... View Details
Keywords: Adaptive Management; Awareness; Behavioral Economics; Behavioral Science; Conservation Intervention; Conservation Planning; Decision-making; Incentives; Nudge; Management; Motivation and Incentives; Behavior; Marketing; Decision Making; Environmental Sustainability; Economics
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Reddy, Sheila M., Jensen Montambault, Yuta J. Masuda, Ayelet Gneezy, Elizabeth Keenan, William Butler, Jonathan R. Fisher, and Stanley T. Asah. "Advancing Conservation by Understanding and Influencing Human Behavior." Conservation Letters 10, no. 2 (March–April 2017): 248–256. (doi:10.1111/conl.12252.)
  • July 2023 (Revised July 2023)
  • Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
  • January 2022
  • Article

Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems

By: David R. Clough and Andy Wu
Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of... View Details
Keywords: Artificial Intelligence; Data Strategy; Ecosystem; Value Capture; Digital Platforms; Analytics and Data Science; Strategy; Learning; Value Creation; AI and Machine Learning; Technology Industry; Information Technology Industry; Video Game Industry; Advertising Industry
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Clough, David R., and Andy Wu. "Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems." Academy of Management Review 47, no. 1 (January 2022): 184–189.
  • January 2021 (Revised March 2021)
  • Case

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
  • September 2020 (Revised July 2022)
  • Exercise

Artea (D): Discrimination through Algorithmic Bias in Targeting

By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
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