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Publications
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- All HBS Web
(1,176)
- Faculty Publications (180)
- March 2021
- Supplement
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Power Point Supplement to 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... View Details
Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
- March 2021
- Case
VideaHealth: Building the AI Factory
By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
- March 2021
- Article
Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment
By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman
This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the... View Details
- February 2021
- Tutorial
T-tests: Theory and Practice
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
- February 2021 (Revised June 2021)
- Case
Bairong and the Promise of Big Data
By: Lauren Cohen, Xiaoyan Zhang and Spencer C.N. Hagist
Bairong CEO Felix Zhang, in launching his credit scoring start-up that incorporates 74,000 variables per individual, found strong initial success. However, the shifting regulatory environment, growing breadth of competitors, difficulties in retaining top talent, and... View Details
- 2021
- Working Paper
The Effects of Temporal Distance on Intra-Firm Communication: Evidence from Daylight Savings Time
By: Jasmina Chauvin, Prithwiraj Choudhury and Tommy Pan Fang
Cross-border communication costs have plummeted and enabled the global distribution of work, but frictions attributable to distance persist. We estimate the causal effects of temporal distance, i.e., time zone separation between employees, on intra-firm communication,... View Details
- October 2020
- Article
Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance
By: Diwas S. KC, Bradley R. Staats, Maryam Kouchaki and Francesca Gino
How individuals manage, organize, and complete their tasks is central to operations management. Recent research in operations focuses on how under conditions of increasing workload individuals can decrease their service time, up to a point, in order to complete work... View Details
- 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
- 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
- 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
- September 2020 (Revised June 2023)
- Exercise
Artea: Designing Targeting Strategies
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: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- 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
- September 2020
- Article
Customer Supercharging in Experience-Centric Channels
By: David R. Bell, Santiago Gallino and Antonio Moreno
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and... View Details
- September 2020
- Article
How Multimedia Shape Crowdfunding Outcomes: The Overshadowing Effect of Images and Videos on Text in Campaign Information
By: J Yang, Y Li, Goran Calic and Anton Shevchenko
This study aims to explore the moderating effect of the number of images and videos on the relationship between text length in crowdfunding campaign descriptions and crowdfunding outcomes. We use data from 13,622 technology campaigns on the Kickstarter website to test... View Details
- September–October 2020
- Article
The Past, Present, and (Near) Future of Gene Therapy and Gene Editing
By: Julia Pian, Amitabh Chandra and Ariel Dora Stern
Emerging gene therapy and gene-editing technologies will have a growing impact on patient lives and health-care delivery. We analyzed a decade of data on clinical trials and venture capital investments to understand the likely trajectory of genetically focused... View Details
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- Article
The Impact of Penalties for Wrong Answers on the Gender Gap in Test Scores
By: Katherine B. Coffman and David Klinowski
Multiple-choice exams play a critical role in university admissions across the world. A key question is whether imposing penalties for wrong answers on these exams deters guessing from women more than men, disadvantaging female test-takers. We consider data from a... View Details
- 2021
- Working Paper
Changing Ingroup Boundaries: The Effect of Immigration on Race Relations in the U.S.
By: Vasiliki Fouka and Marco Tabellini
How do social group boundaries evolve? Does the appearance of a new outgroup change the ingroup's perceptions of other outgroups? We introduce a conceptual framework of context-dependent categorization, in which exposure to one minority leads to recategorization of... View Details
Keywords: In-group-out-group Relations; Immigration; Race; Attitudes; Boundaries; Prejudice and Bias
- 2021
- Working Paper
Hunting for Talent: Firm-Driven Labor Market Search in the United States
By: Ines Black, Sharique Hasan and Rembrand Koning
This article analyzes the phenomenon of firm-driven labor market search—or outbound recruiting—where recruiters are increasingly “hunting for talent” rather than passively relying on workers to search for and apply to job vacancies. Our research methodology leverages... View Details