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Show Results For
- All HBS Web
(2,834)
- News (448)
- Research (2,171)
- Events (39)
- Multimedia (14)
- Faculty Publications (1,383)
- 23 Apr 2024
- In Practice
Getting to Net Zero: The Climate Standards and Ecosystem the World Needs Now
With each month clocking record-breaking temperatures across the planet, this Earth Day reflected the renewed urgency of regulators and businesses to find climate-change solutions. The US Securities and Exchange Commission recently adopted new rules that will mandate... View Details
Keywords: by Rachel Layne
- November 2020
- Case
Axis My India
By: Ananth Raman, Ann Winslow and Kairavi Dey
Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes AMI’s... View Details
Keywords: Market Research; Operations; Management; Infrastructure; Logistics; Service Operations; Political Elections; Forecasting and Prediction; Asia; India
Raman, Ananth, Ann Winslow, and Kairavi Dey. "Axis My India." Harvard Business School Case 621-075, November 2020.
- 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.
- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details
Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science
Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- October 2017 (Revised April 2018)
- Case
Improving Worker Safety in the Era of Machine Learning (A)
By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
- December 2011
- Article
Stock Price Fragility
By: Robin Greenwood and David Thesmar
We investigate the relationship between ownership structure of financial assets and non-fundamental risk. We define an asset to be fragile if it is susceptible to non-fundamental trading shocks. An asset can be fragile because of concentrated ownership or because its... View Details
Keywords: Stocks; Price; Ownership; Risk and Uncertainty; Assets; System Shocks; Financial Liquidity; Forecasting and Prediction; Investment Return; Volatility; Relationships; United States
Greenwood, Robin, and David Thesmar. "Stock Price Fragility." Journal of Financial Economics 102, no. 3 (December 2011): 471–490.
- 09 Dec 2019
- News
Identify Great Customers from Their First Purchase
- 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.
- 20 Mar 2017
- Working Paper Summaries
Bubbles for Fama
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
Keywords: Racial Disparity; Paycheck Protection Program; Measurement Error; AI and Machine Learning; Race; Measurement and Metrics; Equality and Inequality; Prejudice and Bias; Forecasting and Prediction; Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
- 23 Sep 2017
- Working Paper Summaries
Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale
- June 2023
- Case
Tractor Supply Co
By: David L. Ager and Michael A. Roberto
In February 2023, Hal Lawton, CEO of Tractor Supply Co, the largest farm and ranch retailer in the United States reflected on the company’s 70% growth between 2019 and 2022. Economists had begun to predict an economic downturn and experts were predicting softening... View Details
Keywords: COVID-19 Pandemic; Demand and Consumers; Economic Slowdown and Stagnation; Organizational Change and Adaptation; Retail Industry
Ager, David L., and Michael A. Roberto. "Tractor Supply Co." Harvard Business School Case 923-302, June 2023.
- 2008
- Article
Warmth and Competence As Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map
By: A. J.C. Cuddy, S. T. Fiske and P. Glick
The stereotype content model (SCM) defines two fundamental dimensions of social perception, warmth and competence, predicted respectively by perceived competition and status. Combinations of warmth and competence generate distinct emotions of admiration, contempt,... View Details
Keywords: Perception; Competency and Skills; Prejudice and Bias; Emotions; Business Model; Behavior; Research; Competition; Status and Position; Cognition and Thinking; Groups and Teams
Cuddy, A. J.C., S. T. Fiske, and P. Glick. "Warmth and Competence As Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map." Advances in Experimental Social Psychology 40 (2008): 61–149.
- April 2003 (Revised December 2006)
- Case
ZARA: Fast Fashion
By: Pankaj Ghemawat and Jose Luis Nueno
Focuses on Inditex, an apparel retailer from Spain, which has set up an extremely quick response system for its ZARA chain. Instead of predicting months before a season starts what women will want to wear, ZARA observes what's selling and what's not and continuously... View Details
Keywords: Organizational Change and Adaptation; Multinational Firms and Management; Competitive Advantage; Manufacturing Industry; Apparel and Accessories Industry; Retail Industry; Spain
Ghemawat, Pankaj, and Jose Luis Nueno. "ZARA: Fast Fashion." Harvard Business School Case 703-497, April 2003. (Revised December 2006.)
- 22 Dec 2015
- News
Algorithms Need Managers, Too
- February 2006 (Revised September 2007)
- Background Note
Winner-Take-All in Networked Markets
Discusses platform structure in new networked markets, that is, whether a market that exhibits network effects will be served by a single platform or by rival platforms. Defines "platforms" and "platform structure"; describes factors that influence the odds that a... View Details
Keywords: Forecasting and Prediction; Growth Management; Network Effects; Digital Platforms; Internet and the Web
Eisenmann, Thomas R. "Winner-Take-All in Networked Markets." Harvard Business School Background Note 806-131, February 2006. (Revised September 2007.)
- 09 Mar 2021
- Working Paper Summaries
Stock Price Reactions to ESG News: The Role of ESG Ratings and Disagreement
- 2018
- Working Paper
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
- February 2018 (Revised December 2020)
- Case
People Analytics at Teach For America (A)
By: Jeffrey T. Polzer and Julia Kelley
As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (A)." Harvard Business School Case 418-013, February 2018. (Revised December 2020.)