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- All HBS Web
(1,959)
- Faculty Publications (567)
- 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.)
- Article
Games of Threats
By: Elon Kohlberg and Abraham Neyman
A game of threats on a finite set of players, N, is a function d that assigns a real number to any coalition, S ⊆ N, such that d(S) = -d(N\S). A game of threats is not necessarily a coalitional game as it may fail to satisfy the condition d(Ø) = 0. We show that analogs... View Details
Kohlberg, Elon, and Abraham Neyman. "Games of Threats." Games and Economic Behavior 108 (March 2018): 139–145.
- 2019
- Working Paper
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Harvard Business School Working Paper, No. 18-064, January 2018. (Revised May 2019.)
- January 2018 (Revised August 2020)
- Background Note
Continuous Software Development: Agile's Successor
By: Jeffrey J. Bussgang, Samuel Clemens and Olivia Hull
In recent years, the twin software development methodologies of continuous delivery and continuous deployment have risen to prominence in the start-up world and beyond. These methods have enabled technology companies large and small to accelerate their product... View Details
Keywords: Continuous Improvement; Continuous Development; Continuous Delivery; Continuous Integration; Product Development Processes; Computer Programming; Agile; Waterfall; Software Applications; Software Engineering; Applications and Software; Information Technology; Technological Innovation; Product Development; Customer Focus and Relationships; Entrepreneurship; Organizational Change and Adaptation; Organizational Structure; Quality; Product Marketing; Product; Infrastructure; Information Infrastructure; Computer Industry; Technology Industry; Information Technology Industry; Web Services Industry; Massachusetts; Boston
Bussgang, Jeffrey J., Samuel Clemens, and Olivia Hull. "Continuous Software Development: Agile's Successor." Harvard Business School Background Note 818-055, January 2018. (Revised August 2020.)
- January 2018
- Background Note
Math Tools for Strategists
By: Tarun Khanna and Jan W. Rivkin
Great strategists rely heavily on numbers as they go about their work. This note offers an overview of the highbrow and lowbrow quantitative tools that individuals commonly encounter during strategy courses and in actual strategy work. The note focuses especially on... View Details
Khanna, Tarun, and Jan W. Rivkin. "Math Tools for Strategists." Harvard Business School Background Note 718-477, January 2018.
- Article
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
By: Seth Neel and Aaron Leon Roth
Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details
Neel, Seth, and Aaron Leon Roth. "Mitigating Bias in Adaptive Data Gathering via Differential Privacy." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- Article
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- 2017
- Working Paper
Investment Timing with Costly Search for Financing
By: Samuel Antill
I develop a dynamic model of investment timing in which firms must first choose when to search for external financing. Search is costly and the arrival of investors is uncertain, leading to delay in financing and investment. Depending on parameters, my model can... View Details
Keywords: Real Options; Search And Bargaining; Time-varying Financial Conditions; Investment; Venture Capital; Mathematical Methods
Antill, Samuel. "Investment Timing with Costly Search for Financing." Working Paper, December 2017.
- 2017
- Working Paper
The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond
By: Josh Lerner
Patents and citations are powerful tools for understanding innovative activity inside the firm and are increasingly used in corporate finance research. But due to the complexities of patent data collection and the changing spatial and industry composition of innovative... View Details
Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond." Harvard Business School Working Paper, No. 18-042, November 2017.
- 2017
- Working Paper
Identifying Sources of Inefficiency in Health Care
By: Amitabh Chandra and Douglas O. Staiger
In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted and push standardization of care as a way of reducing allocative inefficiency. However, an... View Details
Keywords: Health Care and Treatment; Performance Efficiency; Performance Productivity; Mathematical Methods
Chandra, Amitabh, and Douglas O. Staiger. "Identifying Sources of Inefficiency in Health Care." NBER Working Paper Series, No. 24035, November 2017.
- 2017
- Working Paper
Deep Help in Complex Project Work: Guiding and Path-Clearing Across Difficult Terrain
By: Colin M. Fisher, Julianna Pillemer and Teresa M. Amabile
How do teams working on complex projects get the help they need? Our qualitative investigation of the help provided to project teams at a prominent design firm revealed two distinct helping processes, both characterized by deep, sustained engagement that far exceeds... View Details
- September 2017
- Article
Winning the War for Talent: Modern Motivational Methods for Attracting and Retaining Employees
By: Anais Thibault-Landry, Allan Schweyer and Ashley V. Whillans
Given the struggle that many organizations face hiring and retaining talent in today's tight labor market, it is critical to understand how to effectively reward employees. To address this question, we review relevant evidence that explains the importance of workplace... View Details
Keywords: Rewards; Total Reward Strategies; Incentives; Recognition; Motivation; Psychological Needs; Employees; Retention; Motivation and Incentives; Working Conditions
Thibault-Landry, Anais, Allan Schweyer, and Ashley V. Whillans. "Winning the War for Talent: Modern Motivational Methods for Attracting and Retaining Employees." Compensation & Benefits Review 49, no. 4 (September 2017): 230–246.
- 2018
- Working Paper
Class Matters: The Role of Social Class and Organizational Sector in High-Achieving Women's Legitimacy Narratives
By: Judith A. Clair, Rachel D. Arnett, Katherine Chen, Beth K. Humberd and Kathleen L. McGinn
While prior research recognizes that women struggle to maintain legitimacy for their successes and that self-narratives play a key role in building such legitimacy, theory provides limited insight into how women build legitimacy through their self-narratives. Our... View Details
Keywords: Personal Development and Career; Gender; Success; Diversity; Perception; Situation or Environment
Clair, Judith A., Rachel D. Arnett, Katherine Chen, Beth K. Humberd, and Kathleen L. McGinn. "Class Matters: The Role of Social Class and Organizational Sector in High-Achieving Women's Legitimacy Narratives." Harvard Business School Working Paper, No. 18-014, August 2018. (Revised August 2018 for requested resubmission.)
- 14 Aug 2017
- Conference Presentation
A Convex Framework for Fair Regression
By: Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the range from notions of group fairness to strong individual fairness. By varying... View Details
Berk, Richard, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. "A Convex Framework for Fair Regression." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), August 14, 2017.
- Article
Who Will Vote Quadratically? Voter Turnout and Votes Cast Under Quadratic Voting
By: Louis Kaplow and Scott Duke Kominers
Who will vote quadratically in large-N elections under quadratic voting (QV)? First, who will vote? Although the core QV literature assumes that everyone votes, turnout is endogenous. Drawing on other work, we consider the representativeness of endogenously... View Details
Keywords: Voting Turnout; Paradox Of Voting; Quadratic Voting; Pivotality; Elections; Voting; Political Elections; Mathematical Methods
Kaplow, Louis, and Scott Duke Kominers. "Who Will Vote Quadratically? Voter Turnout and Votes Cast Under Quadratic Voting." Special Issue on Quadratic Voting and the Public Good. Public Choice 172, nos. 1-2 (July 2017): 125–149.
- 2017
- Chapter
Marketing Models for the Customer-Centric Firm
By: Eva Ascarza, Peter S. Fader and Bruce G.S. Hardie
A customer-centric firm takes the view that there are three key drivers of (organic) growth and overall profitability: Customer acquisition, customer retention, and customer development (i.e., increasing the value of each existing customer (per unit of time) while they... View Details
Ascarza, Eva, Peter S. Fader, and Bruce G.S. Hardie. "Marketing Models for the Customer-Centric Firm." In Handbook of Marketing Decision Models. 2nd ed. Edited by Berend Wierenga and Ralf van der Lans, 297–330. International Series in Operations Research & Management Science. Springer, 2017.
- 2019
- Chapter
Quantitative and Qualitative Methods in Organizational Research
By: Amy C. Edmondson and Tiona Zuzul
Selecting the appropriate method for a given research question is an essential skill for organizational researchers. High-quality research involves a good fit between the methods used and the nature of the contribution to the literature. This article describes a... View Details
Edmondson, Amy C., and Tiona Zuzul. "Quantitative and Qualitative Methods in Organizational Research." In The Palgrave Encyclopedia of Strategic Management. Continuously updated edition, edited by Mie Augier and David J. Teece. Palgrave Macmillan, 2017. Electronic. (Pre-published, October 2013.)
- Article
Statistical Physics of Human Cooperation
By: Matjaž Perc, Jillian J. Jordan, David G. Rand, Zhen Wang, Stefano Boccaletti and Attila Szolnoki
Extensive cooperation among unrelated individuals is unique to humans, who often sacrifice personal benefits for the common good and work together to achieve what they are unable to execute alone. The evolutionary success of our species is indeed due, to a large... View Details
Keywords: Human Cooperation; Evolutionary Game Theory; Public Goods; Reward; Punishment; Tolerance; Self-organization; Pattern Formation; Cooperation; Behavior; Game Theory
Perc, Matjaž, Jillian J. Jordan, David G. Rand, Zhen Wang, Stefano Boccaletti, and Attila Szolnoki. "Statistical Physics of Human Cooperation." Physics Reports 687 (May 8, 2017): 1–51.
- May 2017
- Article
Agent-based Modeling: A Guide for Social Psychologists
By: Joshua Conrad Jackson, David Rand, Kevin Lewis, Michael I. Norton and Kurt Gray
Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to... View Details
Jackson, Joshua Conrad, David Rand, Kevin Lewis, Michael I. Norton, and Kurt Gray. "Agent-based Modeling: A Guide for Social Psychologists." Social Psychological & Personality Science 8, no. 4 (May 2017): 387–395.
- 2018
- Working Paper
Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets
By: Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to higher operational costs through more product returns in the online retail industry. Dynamic pricing has been widely applied by many online retailers. Research has shown that, in response to dynamic pricing, some customers... View Details