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- All HBS Web
(3,378)
- Faculty Publications (777)
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details
Boxer, Kate S., Edward McFowland III, and Daniel B. Neill. "Auditing Predictive Models for Intersectional Biases." Working Paper, June 2023.
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- May 2023 (Revised June 2023)
- Case
Harvard University and Urban Mining Industries: Decarbonizing the Supply Chain
By: Shirley Lu and Robert S. Kaplan
The case describes Harvard University’s consideration to decarbonize its supply chain by replacing cement with a low-carbon substitute called Pozzotive®. Developed and produced by Urban Mining Industries, Pozzotive® is a ground-glass material made with post-consumer... View Details
Keywords: Carbon Emissions; Blockchain; Supply Chain; Green Technology; Climate Change; Environmental Sustainability
Lu, Shirley, and Robert S. Kaplan. "Harvard University and Urban Mining Industries: Decarbonizing the Supply Chain." Harvard Business School Case 123-076, May 2023. (Revised June 2023.)
- May 2023
- Article
How Do Campaigns Shape Vote Choice? Multi-Country Evidence from 62 Elections and 56 TV Debates
By: Caroline Le Pennec and Vincent Pons
We use two-round survey data from 62 elections in 10 countries since 1952 to study the formation of vote choice, beliefs, and policy preferences and assess how televised debates contribute to this process. Our data include 253,000 observations. We compare the... View Details
Keywords: Political Debates; TV Debates; Voting; Political Elections; Decision Choices and Conditions
Le Pennec, Caroline, and Vincent Pons. "How Do Campaigns Shape Vote Choice? Multi-Country Evidence from 62 Elections and 56 TV Debates." Quarterly Journal of Economics 138 (May 2023): 703–767.
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity as labor-augmenting
tools for programming, writing, and many other processes that benefit from quick text
generation. In this paper we explore the uses and benefits of LLMs for researchers and
practitioners... View Details
Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using LLMs for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2024.)
- Spring 2023
- Article
Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field
By: Wei Cai, Susanna Gallani and Jee-Eun Shin
This study examines how the design of incentive contracts for tasks defined as workers’ official responsibilities (i.e., standard tasks) influences workers’ propensity to engage in employee-initiated innovation (EII). EII corresponds to innovation activities that are... View Details
Keywords: Employee-initiated Innovation; Contract Design; Rank-and-file; Extra-role Behaviors; Compensation and Benefits; Motivation and Incentives; Innovation and Management
Cai, Wei, Susanna Gallani, and Jee-Eun Shin. "Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field." Contemporary Accounting Research 40, no. 1 (Spring 2023): 292–323.
- April 2023
- Article
Perceptions Related to Engaging in Non-driving Activities in an Automated Vehicle While Commuting: A Text Mining Approach
By: Yilun Xing, Linda Ng Boyle, Raffaella Sadun, John D. Lee, Orit Shaer and Andrew Kun
Automated vehicles (AVs) offer human operators the opportunity to participate in non-driving activities while on the move. In this study, we examined and compared drivers' perception of non-driving activities in two driving modes: highly AVs in the future and current... View Details
Xing, Yilun, Linda Ng Boyle, Raffaella Sadun, John D. Lee, Orit Shaer, and Andrew Kun. "Perceptions Related to Engaging in Non-driving Activities in an Automated Vehicle While Commuting: A Text Mining Approach." Transportation Research Part F: Traffic Psychology and Behaviour 94 (April 2023): 305–320.
- April 2023
- Article
The Real Exchange Rate, Innovation and Productivity
By: Laura Alfaro, Alejandro Cuñat, Harald Fadinger and Yanping Liu
We evaluate manufacturing firms' responses to changes in the real exchange rate (RER) using detailed firm-level data for a large set of countries for the period 2001-2010. We uncover the following stylized facts about regional variation of manufacturing firms'... View Details
Keywords: Real Exchange Rate; Firm Level Data; Innovation; Productivity; Exporting; Importing; Credit Constraints; Currency Exchange Rate; Innovation and Invention; Performance Productivity
Alfaro, Laura, Alejandro Cuñat, Harald Fadinger, and Yanping Liu. "The Real Exchange Rate, Innovation and Productivity." Journal of the European Economic Association 21, no. 2 (April 2023): 637–689.
- March 2023
- Background Note
A Primer on OKRs
By: Suraj Srinivasan and Li-Kuan (Jason) Ni
The OKR framework is a popular goal-setting and strategy execution tool that uses goal setting through “Objectives” and measuring performance using “Key Results” on a periodic basis to measure and drive performance. The OKR framework has been adopted and practiced at... View Details
Keywords: Business Organization; Talent and Talent Management; Framework; Corporate Governance; Goals and Objectives; Growth and Development; Growth and Development Strategy; Growth Management; Management Analysis, Tools, and Techniques; Management Practices and Processes; Management Skills; Management Systems; Measurement and Metrics; Outcome or Result; Performance Effectiveness; Performance Evaluation; Performance Expectations; Performance Productivity; Performance Efficiency
Srinivasan, Suraj, and Li-Kuan (Jason) Ni. "A Primer on OKRs." Harvard Business School Background Note 123-081, March 2023.
- March 2023 (Revised June 2023)
- Case
Layoffs in the Tech Industry: 2022–2023
By: Sandra J. Sucher and Marilyn Morgan Westner
This case examines the mass layoffs that swept through the tech industry (2022-2023) through the lens of four companies: Twitter, Stripe, Meta, and Google. How these companies implemented workforce change through mass layoffs raises critical questions applicable beyond... View Details
Keywords: Layoffs; Human Resource Management; Workforce Reductions; Ethics; Human Resources; Management; Values and Beliefs; Employee Relationship Management; Resignation and Termination; Compensation and Benefits; Technology Industry; United States; United Kingdom
Sucher, Sandra J., and Marilyn Morgan Westner. "Layoffs in the Tech Industry: 2022–2023." Harvard Business School Case 323-095, March 2023. (Revised June 2023.)
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- 2023
- Article
Bridging the Gap with the ‘New’ Economic History of Africa
By: Ewout Frankema and Marlous van Waijenburg
This review article seeks to build bridges between mainstream African history and the more historically oriented branch of the ‘new’ economic history of Africa. We survey four central topics of the new economic history of Africa—growth, trade, labor, and inequality—and... View Details
Keywords: Economic Growth; Trade; Labor; Equality and Inequality; Development Economics; History; Africa
Frankema, Ewout, and Marlous van Waijenburg. "Bridging the Gap with the ‘New’ Economic History of Africa." Journal of African History 64, no. 1 (2023): 38–61.
- 2024
- Working Paper
Everyone Steps Back?: The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High
By: John (Jianqui) Bai, William R. Kerr, Chi Wan and Alptug Yorulmaz
We study racial biases on Kickstarter across multiple ethnic groups from 2009-2021. Scaling the concept of racially salient events, we quantify the close co-movement of minority funding gaps to inflamed political rhetoric surrounding migration. The racial funding gap... View Details
Bai, John (Jianqui), William R. Kerr, Chi Wan, and Alptug Yorulmaz. "Everyone Steps Back? The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High." Harvard Business School Working Paper, No. 23-046, January 2023. (Revised February 2024.)
- January–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- Working Paper
Group Fairness in Dynamic Refugee Assignment
By: Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt and Wentao Weng
Ensuring that refugees and asylum seekers thrive (e.g., find employment) in their host countries is a profound humanitarian goal, and a primary driver of employment is the geographic
location within a host country to which the refugee or asylum seeker is... View Details
Freund, Daniel, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt, and Wentao Weng. "Group Fairness in Dynamic Refugee Assignment." Harvard Business School Working Paper, No. 23-047, February 2023.
- February 2023
- Article
The Effect of Systems of Management Controls on Honesty in Managerial Reporting
By: Aishwarrya Deore, Susanna Gallani and Ranjani Krishnan
While budgetary controls with capital rationing are optimal in theory and widespread in practice, empirical research documents their association with higher employee dishonesty compared to budgetary controls without rationing. In this study, we examine whether... View Details
Keywords: Directing Controls; Misreporting; Mission Statements; Participative Budgeting; Stewardship Theory; Systems Of Management Controls; Capital; Budgets and Budgeting; Mission and Purpose
Deore, Aishwarrya, Susanna Gallani, and Ranjani Krishnan. "The Effect of Systems of Management Controls on Honesty in Managerial Reporting." Art. 101401. Accounting, Organizations and Society 105 (February 2023).
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
- January 2023
- Article
Firm-Induced Migration Paths and Strategic Human-Capital Outcomes
By: Prithwiraj (Raj) Choudhury, Tarun Khanna and Victoria Sevcenko
Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We... View Details
Keywords: Worker Relocation; Turnover; Firm-induced Migration; Smaller Towns; Employee Mobility; Geographic Mobility; Migration; Clusters; Employees; Geographic Location; Performance; Opportunities; Retention; Human Capital; Talent and Talent Management
Choudhury, Prithwiraj (Raj), Tarun Khanna, and Victoria Sevcenko. "Firm-Induced Migration Paths and Strategic Human-Capital Outcomes." Management Science 69, no. 1 (January 2023): 419–445.
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose... View Details
Kristensen, Thomas Borup, Henrik Saabye, and Amy Edmondson. "Becoming a Learning Organization While Enhancing Performance: The Case of LEGO." International Journal of Operations & Production Management 42, no. 13 (2022): 438–481.
- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
Keywords: AI and Machine Learning
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).