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- 2024
- Working Paper
What Is Newsworthy? Theory and Evidence
By: Luis Armona, Matthew Gentzkow, Emir Kamenica and Jesse M. Shapiro
We study newsworthiness in theory and practice. We focus on situations in which a news outlet observes the realization of a state of the world and must decide whether to report the realization to a consumer who pays an opportunity cost to consume the report. The... View Details
Armona, Luis, Matthew Gentzkow, Emir Kamenica, and Jesse M. Shapiro. "What Is Newsworthy? Theory and Evidence." NBER Working Paper Series, No. 32512, May 2024.
- April 3, 2024
- Article
How Automakers Can Address Resistance to Self-Driving Cars
By: Stuti Agarwal, Julian De Freitas and Carey K. Morewedge
Research involving multiple experiments found that consumers have biased views of their driving abilities relative to those of other drivers and automated vehicles. These findings have implications for the adoption of partly or fully automated vehicles, which one day... View Details
Keywords: Technology Adoption; Consumer Behavior; Government Legislation; Prejudice and Bias; Auto Industry; Technology Industry
Agarwal, Stuti, Julian De Freitas, and Carey K. Morewedge. "How Automakers Can Address Resistance to Self-Driving Cars." Harvard Business Review (website) (April 3, 2024).
- April 2024
- Article
Model-based Financial Regulations Impair the Transition to Net-zero Carbon Emissions
By: Matteo Gasparini, Matthew C. Ives, Ben Carr, Sophie Fry and Eric Beinhocker
Investments via the financial system are essential for fostering the green transition. However, the role of existing financial regulations in influencing investment decisions is understudied. Here we analyse data from the European Banking Authority to show that... View Details
Gasparini, Matteo, Matthew C. Ives, Ben Carr, Sophie Fry, and Eric Beinhocker. "Model-based Financial Regulations Impair the Transition to Net-zero Carbon Emissions." Nature Climate Change 14, no. 5 (April 2024): 434–435.
- 2024
- Working Paper
Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas
By: Jacqueline N. Lane, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
Evaluation of novel projects is essential for scientific and technological advancement. However,
evaluator bias toward a project’s potential can obscure its limitations. This study investigates
evaluation formats by contrasting combined assessments of novelty and... View Details
Lane, Jacqueline N., Tianxi Cai, Michael Menietti, Griffin Weber, and Eva C. Guinan. "Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas." Harvard Business School Working Paper, No. 24-064, March 2024.
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details
Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
- 2025
- Working Paper
Choosing and Using Information in Evaluation Decisions
By: Katherine Baldiga Coffman, Scott Kostyshak and Perihan O. Saygin
We use a controlled experiment to study how information acquisition impacts candidate evaluations. We provide evaluators with group-level information on performance and the opportunity to acquire additional, individual-level performance information before making a... View Details
- February 2024
- Module Note
Data-Driven Marketing in Retail Markets
By: Ayelet Israeli
This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details
Keywords: Data; Data Analytics; Retail; Retail Analytics; Data Science; Business Analytics; "Marketing Analytics"; Omnichannel; Omnichannel Retailing; Omnichannel Retail; DTC; Direct To Consumer Marketing; Ethical Decision Making; Algorithmic Bias; Privacy; A/B Testing; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Analytics and Data Science; E-commerce; Marketing Channels; Demand and Consumers; Marketing Strategy; Retail Industry
Israeli, Ayelet. "Data-Driven Marketing in Retail Markets." Harvard Business School Module Note 524-062, February 2024.
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- January 2024
- Case
Deion Sanders: The Prime Effect
By: Hise O. Gibson, Nicole Gilmore and Alicia Dadlani
In 2023, Deion Sanders, known as “Coach Prime,” became head football coach of the University of Colorado Boulder (CU). Sanders was tasked with leading CU’s struggling football program, which had only achieved one winning season in the last 15 years, back to glory. Many... View Details
Keywords: Leadership Style; Leading Change; Management Style; Race; Prejudice and Bias; Sports; Experience and Expertise; Sports Industry; United States; Colorado
Gibson, Hise O., Nicole Gilmore, and Alicia Dadlani. "Deion Sanders: The Prime Effect." Harvard Business School Case 624-001, January 2024.
- January 2024 (Revised May 2024)
- Case
Uncle Nearest: Creating a Legacy
By: Hise Gibson, Archie L. Jones, Nicole Gilmore and Ai-Ling Jamila Malone
Fawn Weaver, as a Black woman and industry outsider in a capital-intensive, highly regulated, competitive and male-dominated spirits industry, successfully overcame numerous obstacles to launch a premium American whiskey brand, Uncle Nearest in 2017, which became the... View Details
Keywords: Advertising; Business Startups; Customer Focus and Relationships; Decisions; Forecasting and Prediction; Age; Ethnicity; Gender; Entrepreneurship; Working Capital; Innovation Leadership; Innovation Strategy; Intellectual Property; Trademarks; Leadership Style; Growth and Development; Growth and Development Strategy; Product Marketing; Product Launch; Marketing Strategy; Mission and Purpose; Organizational Culture; Private Ownership; Performance Effectiveness; Strategic Planning; Problems and Challenges; Prejudice and Bias; Social Issues; Competition; Competitive Strategy; Expansion; Entrepreneurial Finance; Food and Beverage Industry; Tourism Industry; United States; Tennessee; France
Gibson, Hise, Archie L. Jones, Nicole Gilmore, and Ai-Ling Jamila Malone. "Uncle Nearest: Creating a Legacy." Harvard Business School Case 824-047, January 2024. (Revised May 2024.)
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which... View Details
Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- December 4, 2023
- Article
Stop Assuming Introverts Aren't Passionate About Work
By: Kai Krautter, Anabel Büchner and Jon M. Jachimowicz
Society often assumes that the only way to be passionate is to act extroverted, but that is simply not true. In their new research, the authors found that regardless of their actual level of passion, extroverted employees are perceived as more passionate than... View Details
Keywords: Passion; Personality; Extraversion; Scale Development; Personal Characteristics; Perception; Employees; Prejudice and Bias
Krautter, Kai, Anabel Büchner, and Jon M. Jachimowicz. "Stop Assuming Introverts Aren't Passionate About Work." Harvard Business Review Digital Articles (December 4, 2023).
- December 2023
- Article
Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting
By: Braiden Coleman, Michael Drake, Joseph Pacelli and Brady Twedt
In this study, we offer novel evidence on how the nature of brokerage-client relationships can influence the quality of equity research. We exploit a unique setting provided by the Protocol for Broker Recruiting to examine whether relaxed broker non-compete agreement... View Details
Keywords: Brokers; Analysts; Forecasts; Bias; Protocol; Investment; Research; Forecasting and Prediction
Coleman, Braiden, Michael Drake, Joseph Pacelli, and Brady Twedt. "Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting." Review of Accounting Studies 28, no. 4 (December 2023): 2075–2103.
- 2023
- Working Paper
Complexity and Hyperbolic Discounting
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
A large literature shows that people discount financial rewards hyperbolically instead of exponentially. While discounting of money has been questioned as a measure of time preferences, it continues to be highly relevant in empirical practice and predicts a wide range... View Details
Keywords: Hyperbolic Discounting; Present Bias; Bounded Rationality; Cognitive Uncertainty; Behavioral Finance
Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Complexity and Hyperbolic Discounting." Harvard Business School Working Paper, No. 24-048, February 2024.
- November 2023
- Article
Brokerage House Initial Public Offerings and Analyst Forecast Quality
By: Mark Bradshaw, Michael Drake, Joseph Pacelli and Brady Twedt
We examine how brokerage firm initial public offerings (IPOs) influence the research quality of sell-side analysts employed by the brokerage. Our main results focus on earnings forecast bias and absolute forecast errors as proxies for research quality. Using a... View Details
Keywords: IPOs; Research Analysts; "Brokerage Industry; Initial Public Offering; Employees; Behavior; Outcome or Result
Bradshaw, Mark, Michael Drake, Joseph Pacelli, and Brady Twedt. "Brokerage House Initial Public Offerings and Analyst Forecast Quality." Management Science 69, no. 11 (November 2023): 7079–7094.
- November–December 2023
- Article
Look the Part? The Role of Profile Pictures in Online Labor Markets
By: Isamar Troncoso and Lan Luo
Profile pictures are a key component of many freelancing platforms, a design choice that can impact hiring and matching outcomes. In this paper, we examine how appearance-based perceptions of a freelancer’s fit for the job (i.e., whether a freelancer "looks the part"... View Details
Keywords: Freelancers; Gig Workers; Demographics; Prejudice and Bias; Selection and Staffing; Jobs and Positions; Analytics and Data Science
Troncoso, Isamar, and Lan Luo. "Look the Part? The Role of Profile Pictures in Online Labor Markets." Marketing Science 42, no. 6 (November–December 2023): 1080–1100.
- October 2023
- Case
Making Progress at Progress Software (A)
By: Katherine Coffman, Hannah Riley Bowles and Alexis Lefort
In this case, the Human Capital team at Progress Software has identified that some employees have a hard time understanding how to advance within Progress. This realization leads the team to develop several major people-process innovations: the introduction of... View Details
Keywords: Leading Change; Organizational Culture; Performance Evaluation; Prejudice and Bias; Personal Development and Career; Human Capital; Employee Relationship Management; Technology Industry; Bulgaria
Coffman, Katherine, Hannah Riley Bowles, and Alexis Lefort. "Making Progress at Progress Software (A)." Harvard Business School Case 924-010, October 2023.
- October 2023
- Teaching Note
Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models
By: Tsedal Neeley and Tim Englehart
Teaching Note for HBS Case No. 422-085. Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that... View Details
- October 2023
- Supplement
Making Progress at Progress Software (B)
By: Katherine Coffman, Hannah Riley Bowles and Alexis Lefort
In this case, the Human Capital team at Progress Software has identified that some employees have a hard time understanding how to advance within Progress. This realization leads the team to develop several major people-process innovations: the introduction of... View Details
Keywords: Leading Change; Negotiation; Organizational Culture; Performance Evaluation; Prejudice and Bias; Talent and Talent Management; Employees; Technology Industry; United States; Bulgaria
Coffman, Katherine, Hannah Riley Bowles, and Alexis Lefort. "Making Progress at Progress Software (B)." Harvard Business School Supplement 924-011, October 2023.
- 2023
- Working Paper
Causal Interpretation of Structural IV Estimands
By: Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan and Jesse M. Shapiro
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning... View Details
Keywords: Mathematical Methods
Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper Series, No. 31799, October 2023.