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Show Results For
- All HBS Web
(8,881)
- People (24)
- News (2,314)
- Research (5,565)
- Events (19)
- Multimedia (253)
- Faculty Publications (4,096)
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- April 2024
- Article
Decision Authority and the Returns to Algorithms
By: Hyunjin Kim, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these... View Details
Keywords: Algorithmic Aversion; Algorithmic Decision Making; Algorithms; Public Entrepreneurship; Govenment; Local Government; Crowdsourcing; Crowdsourcing Contests; Inspection; Principal-agent Theory; Government Administration; Decision Making; Public Administration Industry; United States
Kim, Hyunjin, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Decision Authority and the Returns to Algorithms." Strategic Management Journal 45, no. 4 (April 2024): 619–648.
- 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.)
- 2018
- Working Paper
Algorithm Appreciation: People Prefer Algorithmic to Human Judgment
By: Jennifer M. Logg, Julia A. Minson and Don A. Moore
Even though computational algorithms often outperform human judgment, received wisdom suggests that people may be skeptical of relying on them (Dawes, 1979). Counter to this notion, results from six experiments show that lay people adhere more to advice when they think... View Details
Keywords: Algorithms; Accuracy; Advice Taking; Forecasting; Theory Of Machine; Mathematical Methods; Decision Making; Forecasting and Prediction; Trust
Logg, Jennifer M., Julia A. Minson, and Don A. Moore. "Algorithm Appreciation: People Prefer Algorithmic to Human Judgment." Harvard Business School Working Paper, No. 17-086, March 2017. (Revised April 2018.)
- Article
Corporate Stakeholders Management – An Empirical Study of Organisational Decision Making Criteria
By: Shashank Shah and Sudhir Bhaskar
Shah, Shashank, and Sudhir Bhaskar. "Corporate Stakeholders Management – An Empirical Study of Organisational Decision Making Criteria." International Journal of Indian Culture and Business Management 4, no. 2 (2011): 218–239.
- November 2022 (Revised February 2024)
- Exercise
Managing Customer Retention at Teleko
By: Eva Ascarza
This exercise aims to teach students about 1) Targeting Policies; and 2) Algorithmic decision making, and 3) Retention management. View Details
Ascarza, Eva. "Managing Customer Retention at Teleko." Harvard Business School Exercise 523-005, November 2022. (Revised February 2024.)
- 2023
- Working Paper
Algorithm Failures and Consumers' Response: Evidence from Zillow
By: Isamar Troncoso, Runshan Fu, Nikhil Malik and Davide Proserpio
In November 2021, Zillow announced the closure of its iBuyer business. Popular media largely attributed this to a failure of its proprietary forecasting algorithm. We study the response of consumers to Zillow’s iBuyer business closure. We show that after the iBuyer... View Details
Keywords: Algorithmic Pricing; Price; Forecasting and Prediction; Consumer Behavior; Real Estate Industry
Troncoso, Isamar, Runshan Fu, Nikhil Malik, and Davide Proserpio. "Algorithm Failures and Consumers' Response: Evidence from Zillow." Working Paper, July 2023.
- Research Summary
Decision making
Dr. Bos investigates how unconscious processes aid and improve performance. His work contests the common-sense notion that conscious deliberation always leads to the best outcomes. Dr. Bos and colleagues propose that, for complex decisions, the best outcomes result... View Details
- Article
Algorithms Need Managers, Too
By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details
Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science
Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
- 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.)
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption... View Details
Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 2017
- Working Paper
The 4 Minds of the Customer: A Framework for Understanding and Applying the Science of Decision Making
By: Ryan Hamilton and Uma R. Karmarkar
Scientists have spent decades creating powerful and detailed descriptions of how people make decisions. Unfortunately, many of these theories make contradictory predictions and are difficult to understand and implement. We introduce the 4 Minds framework as a practical... View Details
Keywords: Consumer Choice; Market Research; Decision Making Process; Decision; Marketing Research; Consumer Behavior; Decision Choices and Conditions; Marketing; Decision Making; Segmentation; Research
Hamilton, Ryan, and Uma R. Karmarkar. "The 4 Minds of the Customer: A Framework for Understanding and Applying the Science of Decision Making." Marketing Science Institute Report, No. 17-109, May 2017.
- Research Summary
Intra-Household Decision Making
Professor Ashraf's research in intra-household decision making examines how households make financial and health decisions, particularly in the presence of asymmetric information or benefits.
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- 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.)
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Arielle Anderer and Christian Kaps
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
Keywords: Learning Curve; Technology; Innovation; Batteries; Energy Storage; Sequential Decision Making; TELCO; Exploration; Exploitation
Anderer, Arielle, and Christian Kaps. "How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions." Working Paper, March 2025.
- September 1989
- Background Note
Introduction to Decision Making
By: Francis Aguilar
Describes the process of decision making (establish objectives, generate alternatives, and so on) emphasizing the human side of it (using rules of thumb, favoring one's own pet projects) yet demonstrating the role an analytic/quantitative contribution has to make. View Details
Aguilar, Francis. "Introduction to Decision Making." Harvard Business School Background Note 390-048, September 1989.
- 2025
- Working Paper
Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces
By: Santiago Gallino, Nil Karacaoglu and Antonio Moreno
Most online sales worldwide take place in marketplaces that connect sellers and buyers. The presence of numerous third-party sellers leads to a proliferation of listings for each product, making it difficult for customers to choose between the available options. Online... View Details
Keywords: Algorithms; E-commerce; Sales; Digital Marketing; Internet and the Web; Customer Satisfaction
Gallino, Santiago, Nil Karacaoglu, and Antonio Moreno. "Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces." Working Paper, 2025.
- 2013
- Book
Sidetracked: Why Our Decisions Get Derailed and How We Can Stick to the Plan
By: Francesca Gino
You may not realize it but simple, irrelevant factors can have profound consequences on your decisions and behavior, often diverting you from your original plans and desires. Sidetracked will help you identify and avoid these influences so the decisions you make do... View Details
Keywords: Decision Making; Decision-making; Judgment; Decisions; Strategy; Behavior; Ethics; Attitudes
Gino, Francesca. Sidetracked: Why Our Decisions Get Derailed and How We Can Stick to the Plan. Boston, MA: Harvard Business Review Press, 2013.
- October 2003 (Revised January 2005)
- Case
Shared Decision Making
By: Richard M.J. Bohmer, Karen Sepucha and Laura Feldman
The Foundation for Informed Medical Decision-Making has created an interactive videodisc system that provides patients with customized support regarding medical treatment or screening decisions when they face a choice between two equally effective courses of action.... View Details
Keywords: Decision Choices and Conditions; Borrowing and Debt; Health Care and Treatment; Innovation Strategy; Technological Innovation; Product Marketing; Distribution Channels; Production; Partners and Partnerships; Research and Development; Information Technology
Bohmer, Richard M.J., Karen Sepucha, and Laura Feldman. "Shared Decision Making." Harvard Business School Case 604-001, October 2003. (Revised January 2005.)
- February 2017
- Background Note
Decision Analysis
By: George Wu and Kathleen McGinn
Describes decision analysis, a systematic approach for analyzing decision problems. A running example illustrates problem structuring (decision trees), probability assessment, endpoint evaluation, “folding back the tree” as a method of analysis, and sensitivity... View Details
Wu, George, and Kathleen McGinn. "Decision Analysis." Harvard Business School Background Note 917-018, February 2017.
- Research Summary
Optimal Decision Making Under Uncertainty
Inventory control problems in supply chains. In this stream of theoretical research, Professor Goh has investigated how inventory should be optimally managed in supply chains. Specifically, he has studied how supply chains can make decisions to operate... View Details