Filter Results:
(477)
Show Results For
- All HBS Web
(2,251)
- Faculty Publications (477)
Show Results For
- All HBS Web
(2,251)
- Faculty Publications (477)
- 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.)
- January 2021 (Revised August 2021)
- Case
ByteDance: TikTok and the Trials of Going Viral
By: William C. Kirby and John P. McHugh
In 2020, TikTok became the most valuable start-up ever. The short-form, video-sharing social media platform emerged as the crown jewel of the Chinese technology firm ByteDance, realizing 850 million monthly users and an estimated worth of $180 billion. However, a... View Details
Keywords: China; Technology; Startup; Start-up; International Strategy; Global Strategy And Leadership; Innovation; Political Risk; Regulations; Trump; Foreign Policy; Foreign Investment; Chinese Internet Market; Global Strategy; Crisis Management; Risk and Uncertainty; Entrepreneurship; Globalized Economies and Regions; Government Legislation; Innovation and Management; Governing Rules, Regulations, and Reforms; Internet and the Web; Social Media; Technology Industry; China; United States
Kirby, William C., and John P. McHugh. "ByteDance: TikTok and the Trials of Going Viral." Harvard Business School Case 321-110, January 2021. (Revised August 2021.)
- January 2021 (Revised March 2022)
- Case
Arçelik: From a Dealer Network to an Omnichannel Experience
By: Ayelet Israeli and Fares Khrais
Arçelik Turkey, the country’s market leader in household appliances, was at an omnichannel crossroads in January 2020. Arçelik was a B2B player utilizing a dealership network with an umbrella of brands and had one of the largest brick-and-mortar store networks in... View Details
Keywords: Digital Marketing; Bricks And Mortar; Franchise Management; Franchising; Dealer Network; Dealers; B2B; B2B2C; Tradition; Culture Change; Cultural Adaptation; Omnichannel; Omnichannel Retail; Omni-channel; Omnichannel Retailing; Sales Channels; Sales Channel Development; Channel Management; Channels Of Distribution; Marketplace; Platforms; Collaboration; Online Channel; Online Data; Online Sales; Online Shopping; Online; Retail; Retailing; Disruption; Transformation; Franchise Ownership; Change Management; Partners and Partnerships; Consumer Behavior; Sales; Internet and the Web; Marketing Strategy; Conflict and Resolution; Conflict Management; Organizational Culture; Distribution Channels; Digital Transformation; Digital Platforms; Electronics Industry; Retail Industry; Consumer Products Industry; Turkey
Israeli, Ayelet, and Fares Khrais. "Arçelik: From a Dealer Network to an Omnichannel Experience." Harvard Business School Case 521-067, January 2021. (Revised March 2022.)
- January–February 2021
- Article
Compensation Packages That Actually Drive Performance
By: Boris Groysberg, Sarah Abbott, Michael R. Marino and Metin Aksoy
By aligning executives’ financial incentives with company strategy, a firm can inspire its management to deliver superior results. But it can be hard to get pay packages right. In this article four experts break down the key elements of compensation and explain how to... View Details
Keywords: Executive Compensation; Compensation and Benefits; Motivation and Incentives; Strategy; Performance
Groysberg, Boris, Sarah Abbott, Michael R. Marino, and Metin Aksoy. "Compensation Packages That Actually Drive Performance." Harvard Business Review 99, no. 1 (January–February 2021): 102–111.
- June 2021
- Article
From Predictions to Prescriptions: A Data-driven Response to COVID-19
By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details
Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science
Bertsimas, Dimitris, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg, and Cynthia Zeng. "From Predictions to Prescriptions: A Data-driven Response to COVID-19." Health Care Management Science 24, no. 2 (June 2021): 253–272.
- January 2021
- Article
How Personality and Policy Predict Pandemic Behavior: Understanding Sheltering-in-Place in 55 Countries at the Onset of COVID-19
By: Friedrich M. Götz, Andrés Gvirtz, Adam D. Galinsky and Jon M. Jachimowicz
The spread of COVID-19 within any given country or community at the onset of the pandemic depended in part on the sheltering-in-place rate of its citizens. The pandemic led us to revisit one of psychology’s most fundamental and most basic questions in a high-stakes... View Details
Keywords: COVID; COVID-19; Pandemic; Shelter-in-place; Personality; Government; Interactionism; Health Pandemics; Behavior; Personal Characteristics; Policy; Governance Compliance
Götz, Friedrich M., Andrés Gvirtz, Adam D. Galinsky, and Jon M. Jachimowicz. "How Personality and Policy Predict Pandemic Behavior: Understanding Sheltering-in-Place in 55 Countries at the Onset of COVID-19." American Psychologist 76, no. 1 (January 2021): 39–49.
- November–December 2021
- Article
Does Gender Matter? The Effect of Management Responses on Reviewing Behavior
By: Davide Proserpio, Isamar Troncoso and Francesca Valsesia
We study the effect of management responses on the reviewing behavior of self-identified female and male reviewers. Using data from Tripadvisor, we show that after hotels begin to respond to reviews, the probability that a negative review comes from a self-identified... View Details
Keywords: Word Of Mouth; Online Reviews; Management Responses; E-commerce; Gender; Prejudice and Bias; Digital Platforms; Customers
Proserpio, Davide, Isamar Troncoso, and Francesca Valsesia. "Does Gender Matter? The Effect of Management Responses on Reviewing Behavior." Marketing Science 40, no. 6 (November–December 2021): 1199–1213.
- Article
Healthy Buildings in 2070
By: John D. Macomber and Joseph G. Allen
Fifty years seems a very long time in the future for most industries. Not so in buildings and real estate; built structures routinely last decades if not hundreds of years, as long as they are economically competitive. Any discussion of the 50-year future has to... View Details
Keywords: Health & Wellness; Real Estate; Architectural Innovation; Public Health; Health; Buildings and Facilities; Well-being
Macomber, John D., and Joseph G. Allen. "Healthy Buildings in 2070." The Bridge 50, no. S (Winter 2020): 11–14. (Special 50th Anniversary Issue edited by Ronald M. Latanision.)
- 2023
- Working Paper
The Market for Healthcare in Low Income Countries
By: Abhijit Banerjee, Abhijit Chowdhury, Jishnu Das, Jeffrey Hammer, Reshmaan Hussam and Aakash Mohpal
Patient trust is an important driver of the demand for healthcare. But it may also impact supply:
doctors who realize that patients may not trust them may adjust their behavior in response. We
assemble a large dataset that assesses clinical performance using... View Details
Banerjee, Abhijit, Abhijit Chowdhury, Jishnu Das, Jeffrey Hammer, Reshmaan Hussam, and Aakash Mohpal. "The Market for Healthcare in Low Income Countries." Working Paper, July 2023.
- Article
Value of New Performance Information in Healthcare: Evidence from Japan
By: Susanna Gallani, Takehisa Kajiwara and Ranjani Krishnan
Mandatory measurement and disclosure of outcome measures are commonly used policy tools in
healthcare. The effectiveness of such disclosures relies on the extent to which the new information produced by the mandatory system is internalized by the healthcare... View Details
Keywords: Value Of Information; Feedback; Patient Satisfaction; Healthcare; Health Care and Treatment; Satisfaction; Information; Measurement and Metrics; Performance Improvement
Gallani, Susanna, Takehisa Kajiwara, and Ranjani Krishnan. "Value of New Performance Information in Healthcare: Evidence from Japan." International Journal of Health Economics and Management 20, no. 4 (December 2020): 319–357.
- November 3, 2020
- Article
Gender Differences in COVID-19 Attitudes and Behavior: Panel Evidence from Eight Countries
By: Vincenzo Galasso, Vincent Pons, Paola Profeta, Michael Becher, Sylvain Brouard and Martial Foucault
Using original data from two waves of a survey conducted in March and April 2020 in eight OECD countries (N = 21,649), we show that women are more likely to see COVID-19 as a very serious health problem, to agree with restraining public policy measures adopted in... View Details
Galasso, Vincenzo, Vincent Pons, Paola Profeta, Michael Becher, Sylvain Brouard, and Martial Foucault. "Gender Differences in COVID-19 Attitudes and Behavior: Panel Evidence from Eight Countries." Proceedings of the National Academy of Sciences 117, no. 44 (November 3, 2020).
- Article
Cheating, Inequality Aversion, and Appealing to Social Norms
By: Clara Amato, Francesca Gino, Natalia Montinari and Pierluigi Sacco
We conduct a field experiment involving 143, 9-years old children in their classrooms. Children are requested to flip a coin in private and receive a big or a small prize depending on the outcome they report. Comparing the actual and theoretical distribution of... View Details
Keywords: Cheating; Inequality Aversion; Social Norms; Children; Experiment; Behavior; Equality and Inequality; Moral Sensibility
Amato, Clara, Francesca Gino, Natalia Montinari, and Pierluigi Sacco. "Cheating, Inequality Aversion, and Appealing to Social Norms." Journal of Economic Behavior & Organization 179 (November 2020): 767–778.
- 2020
- Working Paper
Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation
By: Benjami Lockwood, Afras Y. Sial and Matthew C. Weinzierl
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
Lockwood, Benjami, Afras Y. Sial, and Matthew C. Weinzierl. "Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation." NBER Working Paper Series, No. 28098, November 2020.
- 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
Beshears, John, and Harry Kosowsky. "Nudging: Progress to Date and Future Directions." Organizational Behavior and Human Decision Processes 161, Supplement (November 2020): 3–19.
- September 2020 (Revised July 2022)
- Technical Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Retail Industry; Apparel and Accessories Industry; United States
Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
- September 2020 (Revised February 2024)
- Teaching Note
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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
- September 2020 (Revised July 2022)
- Exercise
Artea (B): Including Customer-Level Demographic Data
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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
- September 2020 (Revised July 2022)
- Exercise
Artea (C): Potential Discrimination through Algorithmic 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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
- 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
Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
- 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