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(1,093)
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Show Results For
- All HBS Web
(1,093)
- People (1)
- News (169)
- Research (616)
- Events (17)
- Multimedia (5)
- Faculty Publications (371)
- 2020
- Working Paper
Targeting for Long-Term Outcomes
By: Jeremy Yang, Dean Eckles, Paramveer Dhillon and Sinan Aral
Decision makers often want to target interventions so as to maximize an outcome that is observed only in the long term. This typically requires delaying decisions until the outcome is observed or relying on simple short-term proxies for the long-term outcome. Here we... View Details
Keywords: Targeted Marketing; Optimization; Churn Management; Marketing; Customer Relationship Management; Policy; Learning; Outcome or Result
Yang, Jeremy, Dean Eckles, Paramveer Dhillon, and Sinan Aral. "Targeting for Long-Term Outcomes." Working Paper, October 2020.
- 2020
- Working Paper
Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus
By: David Hao Zhang and Paul Willen
We use a new methodology to assess mortgage pricing discrimination by race. We make four main contributions. First, we show that existing estimates of mortgage pricing differences by race can be confounded by a "menu problem," which is the problem associated with... View Details
Keywords: Mortgages; Financing and Loans; Prejudice and Bias; Race; Measurement and Metrics; Banking Industry; United States
Zhang, David Hao, and Paul Willen. "Do Lenders Still Discriminate? A Robust Approach for Assessing Differences in Menus." Working Paper, September 2020.
- Research Summary
Efficient Consumer Response (ECR)
Seifert is conducting ongoing research on ECR success factor study. Identifying the relevant success factors for ECR-Implementation. Research includes analysis of supply chain mangement and category management implementiation. Statistical data is based on extensive... View Details
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- January 2019
- Article
Increasing the Electoral Participation of Immigrants: Experimental Evidence from France
By: Vincent Pons and Guillaume Liegey
Improving the political participation of immigrants could advance their interests and foster their integration into receiving countries. In this study, 23,800 citizens were randomly assigned to receive visits from political activists during the lead-up to the 2010... View Details
Pons, Vincent, and Guillaume Liegey. "Increasing the Electoral Participation of Immigrants: Experimental Evidence from France." Economic Journal 129, no. 617 (January 2019): 481–508. (Also Harvard Business School Working Paper, No. 16-094, February 2016.)
Entry into Platform-based Markets
This paper examines the relative importance of platform quality, indirect network effects, and consumer expectations on the success of entrants in platform-based markets. We develop a theoretical model and find that an entrant's success depends on the strength of... View Details
- 11 Mar 2008
- Working Paper Summaries
Finding Missing Markets (and a disturbing epilogue): Evidence from an Export Crop Adoption and Marketing Intervention in Kenya
- 2019
- Article
An Empirical Study of Rich Subgroup Fairness for Machine Learning
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.
- June 2010 (Revised September 2011)
- Background Note
An Overview of Project Finance and Infrastructure Finance--2009 Update
By: Benjamin C. Esty and Aldo Sesia
Provides an introduction to the fields of project finance and infrastructure finance and gives a statistical overview of project-financed investments over the years from 2005 to 2009. Examples of project-financed investments include the $1.4 billion Mozal aluminum... View Details
Esty, Benjamin C., and Aldo Sesia. "An Overview of Project Finance and Infrastructure Finance--2009 Update." Harvard Business School Background Note 210-061, June 2010. (Revised September 2011.)
- Research Summary
Clusters and Competition
Porter is conducting ongoing research on the theory of clusters, or geographic concentrations of interconnected companies and institutions in a particular field. This work includes further development of cluster theory and its implications for management and public... View Details
- 2015
- Working Paper
Lost in the Clouds: The Impact of Changing Property Rights on Investment in Cloud Computing Ventures
By: Josh Lerner and Greg Rafert
Our analysis seeks to understand the impact of changing allocations of property rights on investment in new firms. We focus on the Cartoon Network, et al. v. Cablevision decision in the U.S., which narrowed the protection enjoyed by content creators (e.g., movie... View Details
Keywords: Technological Innovation; Venture Capital; Internet and the Web; Entrepreneurship; Investment; Copyright
Lerner, Josh, and Greg Rafert. "Lost in the Clouds: The Impact of Changing Property Rights on Investment in Cloud Computing Ventures." Harvard Business School Working Paper, No. 15-082, April 2015.
- Article
Entry into Platform-based Markets
By: Feng Zhu and Marco Iansiti
This paper examines the relative importance of platform quality, indirect network effects, and consumer expectations on the success of entrants in platform-based markets. We develop a theoretical model and find that an entrant's success depends on the strength of... View Details
Keywords: Platform-based Markets; Winnter-take-all; First-mover Advantage; Indirect Network Effects; Video Game Industry; Quality; Network Effects; Market Entry and Exit; Digital Platforms; Motion Pictures and Video Industry
Zhu, Feng, and Marco Iansiti. "Entry into Platform-based Markets." Strategic Management Journal 33, no. 1 (January 2012): 88–106.
- May 2011
- Article
Race at the Top: How Companies Shape the Inclusion of African Americans on Their Boards in Response to Institutional Pressures
By: Clayton S. Rose and William T. Bielby
Drawing on institutionalist theory, we conceptualize the racial composition of the boards of directors of large American companies as shaped in response to social and political norms. We use new longitudinal and cross-sectional data to test hypotheses about factors... View Details
Keywords: Leadership; Governing and Advisory Boards; Race; Mathematical Methods; Government and Politics; Public Ownership; United States
Rose, Clayton S., and William T. Bielby. "Race at the Top: How Companies Shape the Inclusion of African Americans on Their Boards in Response to Institutional Pressures." Social Science Research 40, no. 3 (May 2011): 841–859.
- January–February 2011
- Article
Adverse Selection in Online 'Trust' Certifications and Search Results
By: Benjamin Edelman
Widely used online "trust" authorities issue certifications without substantial verification of recipients' actual trustworthiness. This lax approach gives rise to adverse selection: the sites that seek and obtain trust certifications are actually less trustworthy than... View Details
Keywords: Online Advertising; Governing Rules, Regulations, and Reforms; Policy; Safety; Trust; Internet; Search Technology; Web Sites
Edelman, Benjamin. "Adverse Selection in Online 'Trust' Certifications and Search Results." Electronic Commerce Research and Applications 10, no. 1 (January–February 2011): 17–25.
- Research Summary
Airline Schedule Disruptions
Increasing congestion and frequent schedule disruptions throughout the National Air Transportation System, both at airports and en route, have led to significant flight and passenger delays. Professor Fearing's primary research focus is on measuring and reducing... View Details
- January 2020
- Article
Rethinking Measurement of Pay Disparity and Its Relation to Firm Performance
By: Ethan Rouen
I develop measures of firm-level pay disparity and examine their relation to firm performance. Using comprehensive compensation data for a large sample of firms, I find no statistically significant relation between the ratio of CEO-to-mean employee compensation and... View Details
Keywords: Pay Disparity; Pay Ratio; CEO Pay Ratio; Income Inequality; Executive Compensation; Employees; Wages; Equality and Inequality; Business Ventures; Performance
Rouen, Ethan. "Rethinking Measurement of Pay Disparity and Its Relation to Firm Performance." Accounting Review 95, no. 1 (January 2020): 343–378.
- September 2016
- Case
Hotel Vertu: Analyzing the Opportunity in the Boutique Hotel Industry
By: Howard H. Stevenson and Michael J. Roberts DBA
Two soon-to-be MBA graduates are considering a business opportunity in the boutique hotel industry. Having found a seemingly attractive property in Savannah, Georgia, Yvonne D'Arcy and Elisabeth Whiting face questions about career issues, planning, financing, and the... View Details
Stevenson, Howard H., and Michael J. Roberts DBA. "Hotel Vertu: Analyzing the Opportunity in the Boutique Hotel Industry." Harvard Business School Brief Case 917-501, September 2016.
- 05 Jul 2006
- Working Paper Summaries
Bringing History into International Business
- November 2021
- Article
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details
Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning Research (PMLR) 84 (2018): 425–434. (Also presented at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.)
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.