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Show Results For
- All HBS Web
(954)
- People (1)
- News (156)
- Research (636)
- Events (13)
- Multimedia (3)
- Faculty Publications (542)
- June 2022
- Article
The Use and Misuse of Patent Data: Issues for Finance and Beyond
By: Josh Lerner and Amit Seru
Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing... View Details
Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Finance and Beyond." Review of Financial Studies 35, no. 6 (June 2022): 2667–2704.
- April 2023
- Case
Fizzy Fusion: When Data-Driven Decision Making Failed
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
This is a case about a fictional New York beverage company called Fizzy Fusion. The business is facing supply chain and inventory management challenges with its new product, SparklingSip. Despite seeking help from a data science consulting firm, the machine learning... View Details
Keywords: Supply Chain Management; Production; Risk and Uncertainty; Analytics and Data Science; Food and Beverage Industry
Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "Fizzy Fusion: When Data-Driven Decision Making Failed." Harvard Business School Case 623-071, April 2023.
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,... View Details
- April 2021 (Revised August 2021)
- Case
Borusan CAT: Monetizing Prediction in the Age of AI (A)
By: Navid Mojir and Gamze Yucaoglu
Borusan Cat is an international distributor of Caterpillar heavy machines. Esra Durgun (Director of Strategy, Digitization, and Innovation) and Ozgur Gunaydin (CEO) seem to have bet their careers on developing Muneccim, a new predictive technology that is designed to... View Details
Keywords: Monetization Strategy; Artificial Intelligence; AI; Forecasting and Prediction; Applications and Software; Technological Innovation; Marketing; Segmentation; AI and Machine Learning; Construction Industry; Turkey
Mojir, Navid, and Gamze Yucaoglu. "Borusan CAT: Monetizing Prediction in the Age of AI (A)." Harvard Business School Case 521-053, April 2021. (Revised August 2021.)
- March 2022
- Case
Unilever: Remote Work in Manufacturing
By: Prithwiraj Choudhury and Susie L. Ma
In December 2021, Unilever—one of the world’s largest producers of consumer goods—was in the midst of a pilot project to digitize its manufacturing facilities and enable remote work for factory employees. This was possible because of an earlier project to retrofit a... View Details
Keywords: Change; Globalization; Information Technology; Technology Adoption; Human Resources; Jobs and Positions; Operations; Education; Training; Manufacturing Industry
Choudhury, Prithwiraj, and Susie L. Ma. "Unilever: Remote Work in Manufacturing." Harvard Business School Case 622-030, March 2022.
- January–February 2023
- Article
Data-Driven COVID-19 Vaccine Development for Janssen
By: Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu and Najat Khan
The COVID-19 pandemic has spurred extensive vaccine research worldwide. One crucial part of vaccine development is the phase III clinical trial that assesses the vaccine for safety and efficacy in the prevention of COVID-19. In this work, we enumerate the first... View Details
Keywords: COVID-19; Health Testing and Trials; Forecasting and Prediction; AI and Machine Learning; Research; Pharmaceutical Industry
Bertsimas, Dimitris, Michael Lingzhi Li, Xinggang Liu, Jennings Xu, and Najat Khan. "Data-Driven COVID-19 Vaccine Development for Janssen." INFORMS Journal on Applied Analytics 53, no. 1 (January–February 2023): 70–84.
- 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
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.)
- 17 Oct 2016
- News
How to Hire with Algorithms
- April 2020
- Article
CEO Behavior and Firm Performance
By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun
We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level... View Details
Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun. "CEO Behavior and Firm Performance." Journal of Political Economy 128, no. 4 (April 2020): 1325–1369.
- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive... View Details
Keywords: Digital; Artificial Intelligence; Big Data; Digital Transformation; Technological Innovation; Transformation; Learning; Competency and Skills
Leonardi, Paul, and Tsedal Neeley. The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston, MA: Harvard Business Review Press, 2022.
- December 2022 (Revised January 2025)
- Case
Akooda: Charging Toward Operational Intelligence
By: Christopher Stanton and Mel Martin
The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google... View Details
Keywords: Data Mining; Productivity; Monitoring; Data Analysis; AI and Machine Learning; Knowledge Management; Operations; Problems and Challenges; Employee Relationship Management; Information Technology Industry; Technology Industry; Information Industry; Boston; Israel
Stanton, Christopher, and Mel Martin. "Akooda: Charging Toward Operational Intelligence." Harvard Business School Case 823-018, December 2022. (Revised January 2025.)
- October 2021 (Revised December 2021)
- Case
Customer-Centric Design with Artificial Intelligence: Commonwealth Bank
By: Karim R. Lakhani, Yael Grushka-Cockayne, Jin Hyun Paik and Steven Randazzo
As Commonwealth Bank (CommBank) CEO Matt Comyn delivered the full financial year results in August 2021 over videoconference, it took less than two minutes for him to make his first mention of the organization's Customer Engagement Engine (CEE), the AI-driven customer... View Details
Keywords: Artificial Intelligence; Customer-centricity; Banks and Banking; Customer Focus and Relationships; Technological Innovation; Transformation; Organizational Change and Adaptation; Performance; AI and Machine Learning; Financial Services Industry; Australia
Lakhani, Karim R., Yael Grushka-Cockayne, Jin Hyun Paik, and Steven Randazzo. "Customer-Centric Design with Artificial Intelligence: Commonwealth Bank." Harvard Business School Case 622-065, October 2021. (Revised December 2021.)
- Article
The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand
By: Marco Bertini and Oded Koenigsberg
More and more companies are relying on pricing algorithms to maximize profits. The use of artificial intelligence and machine learning enables real-time price adjustments based on supply and demand, competitors’ activities, delivery schedules, and so forth. But... View Details
Keywords: Algorithmic Pricing; Dynamic Pricing; Price; Change; Information Technology; Brands and Branding; Perception; Consumer Behavior
Bertini, Marco, and Oded Koenigsberg. "The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand." Harvard Business Review 99, no. 5 (September–October 2021): 74–83.
- 2022
- Working Paper
Communicating Corporate Culture in Labor Markets: Evidence from Job Postings
We examine how firms craft their job postings to convey information about their culture and
whether doing so helps attract employees. We utilize state-of-the-art machine learning methods to
develop a comprehensive dictionary of key corporate values across the near... View Details
Keywords: Corporate Culture Significance; Labor Markets; Disclosure; Organizational Culture; Recruitment; Talent and Talent Management
Pacelli, Joseph, Tianshuo Shi, and Yuan Zou. "Communicating Corporate Culture in Labor Markets: Evidence from Job Postings." Working Paper, October 2022.
- 2023
- Working Paper
The Optimal Stock Valuation Ratio
By: Sebastian Hillenbrand and Odhrain McCarthy
Trailing price ratios, such as the price-dividend and the price-earnings ratio, scale prices by trailing cash flow measures. They theoretically contain expected returns, yet, their performance in predicting stock market returns is poor. This is because of an omitted... View Details
Keywords: Price; Investment Return; AI and Machine Learning; Valuation; Cash Flow; Forecasting and Prediction
Hillenbrand, Sebastian, and Odhrain McCarthy. "The Optimal Stock Valuation Ratio." Working Paper, November 2023.
- October 14, 2019
- Article
How Artificial Intelligence Is Changing Health Care Delivery
By: Samantha F. Sanders, Mats Terwiesch, William J. Gordon and Ariel Dora Stern
The development of intelligent machines holds great promise for making health care delivery more accurate, efficient, and accessible, but challenges remain for incorporating AI into clinical and administrative settings. View Details
Keywords: Artificial Intelligence; Health Care and Treatment; Service Delivery; Technological Innovation; AI and Machine Learning
Sanders, Samantha F., Mats Terwiesch, William J. Gordon, and Ariel Dora Stern. "How Artificial Intelligence Is Changing Health Care Delivery." NEJM Catalyst (October 17, 2019).
- 2023
- Working Paper
Sending Signals: Strategic Displays of Warmth and Competence
By: Bushra S. Guenoun and Julian J. Zlatev
Using a combination of exploratory and confirmatory approaches, this research examines how
people signal important information about themselves to others. We first train machine learning
models to assess the use of warmth and competence impression management... View Details
Keywords: AI and Machine Learning; Personal Characteristics; Perception; Interpersonal Communication
Guenoun, Bushra S., and Julian J. Zlatev. "Sending Signals: Strategic Displays of Warmth and Competence." Harvard Business School Working Paper, No. 23-051, February 2023.
- 2020
- Working Paper
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a US Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Government Administration; Working Conditions; Safety; Quality; Production; Analysis; Resource Allocation; Manufacturing Industry; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." Harvard Business School Working Paper, No. 20-019, August 2019. (Revised February 2020.)
- 04 Dec 2024
- HBS Seminar