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      • 2023
      • Working Paper

      Incentivizing Innovation in Open Source: Evidence from the GitHub Sponsors Program

      By: Annamaria Conti, Vansh Gupta, Jorge Guzman and Maria P. Roche
      Open source is key to innovation, but we know little about how to incentivize it. In this paper, we examine the impact of a program providing monetary incentives to motivate innovators to contribute to open source. The Sponsors program was introduced by GitHub in...  View Details
      Keywords: Open Source Distribution; Innovation and Invention; Motivation and Incentives; Technology Industry
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      Conti, Annamaria, Vansh Gupta, Jorge Guzman, and Maria P. Roche. "Incentivizing Innovation in Open Source: Evidence from the GitHub Sponsors Program." Harvard Business School Working Paper, No. 24-014, September 2023. (NBER Working Paper Series, No. 31668, September 2023.)
      • 2023
      • Article

      On the Impact of Actionable Explanations on Social Segregation

      By: Himabindu Lakkaraju and Ruijiang Gao
      As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research...  View Details
      Keywords: Forecasting and Prediction; AI and Machine Learning; Outcome or Result
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      Lakkaraju, Himabindu, and Ruijiang Gao. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
      • July 2023 (Revised July 2023)
      • Background Note

      Generative AI Value Chain

      By: Andy Wu and Matt Higgins
      Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are...  View Details
      Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers
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      Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
      • July 2023
      • Article

      Marketplace Scalability and Strategic Use of Platform Investment

      By: Jin Li, Gary Pisano, Richard Xu and Feng Zhu
      The scalability of a marketplace depends on the operations of the marketplace platform as well as its sellers’ capacities. In this study, we explore one strategy that a marketplace platform can use to enhance its scalability: providing an ancillary service to sellers....  View Details
      Keywords: Two-sided Platforms; Services; Digital Platforms
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      Li, Jin, Gary Pisano, Richard Xu, and Feng Zhu. "Marketplace Scalability and Strategic Use of Platform Investment." Management Science 69, no. 7 (July 2023): 3958–3975.
      • 2023
      • Article

      Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse

      By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
      As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means...  View Details
      Keywords: AI and Machine Learning; Decision Choices and Conditions; Mathematical Methods
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      Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
      • April 2023
      • Article

      On the Privacy Risks of Algorithmic Recourse

      By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
      As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected...  View Details
      Keywords: Recourse; Privacy Threats; AI and Machine Learning; Information
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      Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
      • March, 2023
      • Article

      Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes

      By: Maria P. Roche
      The transfer of complex knowledge and skills is difficult, often requiring intensive interaction and extensive periods of co-working between a mentor and mentee, which is particularly true in apprenticeship-like settings and on-the-job training. This paper studies a...  View Details
      Keywords: Entrepreneurship; Higher Education; Training; Personal Development and Career; Knowledge Dissemination
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      Roche, Maria P. "Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes." Organization Science 34, no. 2 (March, 2023): 959–986.
      • March 2023
      • Article

      Attracting the Sharks: Corporate Innovation and Securities Class Action Lawsuits

      By: Elisabeth Kempf and Oliver Spalt
      This paper provides novel evidence suggesting that securities class action lawsuits, a central pillar of the U.S. litigation and corporate governance system, can constitute an obstacle to valuable corporate innovation. We first establish that valuable innovation output...  View Details
      Keywords: Class-action Litigation; Turnover; Lawsuits and Litigation; Innovation and Invention; Risk and Uncertainty
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      Kempf, Elisabeth, and Oliver Spalt. "Attracting the Sharks: Corporate Innovation and Securities Class Action Lawsuits." Management Science 69, no. 3 (March 2023): 1323–1934.
      • January 2023
      • Case

      First to Fight? Culture, Tradition and the United States Marine Corps (USMC)

      By: Ranjay Gulati, Akhil Iyer and Joel Malkin
      Over a history of more than 240 years, the United States Marine Corps has forged a distinct culture and institutional identity centered on its “warrior ethos.” In the wars of American history, Marines fought with uncommon valor, rising to international prominence for...  View Details
      Keywords: Change Management; Transformation; Talent and Talent Management; Government Administration; Management Practices and Processes; Management Systems; Organizational Change and Adaptation; Organizational Culture; Performance Effectiveness; United States
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      Gulati, Ranjay, Akhil Iyer, and Joel Malkin. "First to Fight? Culture, Tradition and the United States Marine Corps (USMC)." Harvard Business School Case 423-051, January 2023.
      • October 25, 2022
      • Article

      Why Sharing Economic Growth with the Community Is Good Business

      By: José A. Tiburcio, Lino Miguel Dias and Robert S. Kaplan
      Subsistence dairy ranchers in Central America struggle to stay afloat during the dry season when grass is scarce. Global life sciences company Bayer has launched a program to enable them to produce their own corn silage feed. The results of this program are helping to...  View Details
      Keywords: Sharing Economy; Innovation; Economic Growth; Poverty; Production; Supply Chain; Social Enterprise; Agriculture and Agribusiness Industry; Central America
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      Tiburcio, José A., Lino Miguel Dias, and Robert S. Kaplan. "Why Sharing Economic Growth with the Community Is Good Business." Harvard Business Review (website) (October 25, 2022).
      • 2022
      • Working Paper

      Training, Communications Patterns, and Spillovers Inside Organizations

      By: Miguel Espinosa and Christopher T. Stanton
      We study direct productivity changes and spillovers after a randomized training program for the frontline workers in a Colombian government agency. While trained workers improved their individual production, we also find substantial spillovers that affected managers'...  View Details
      Keywords: Spillovers; Labor Productivity; Firm Objectives, Organization, And Behavior; Training; Performance Productivity
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      Espinosa, Miguel, and Christopher T. Stanton. "Training, Communications Patterns, and Spillovers Inside Organizations." NBER Working Paper Series, No. 30224, July 2022. (Revise and Resubmit at Journal of Political Economy .)
      • 2022
      • Conference Presentation

      Towards the Unification and Robustness of Post hoc Explanation Methods

      By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
      As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...  View Details
      Keywords: AI and Machine Learning
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      Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.
      • 2022
      • Article

      Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

      By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
      As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
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      Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
      • Other Article

      Sustainable Strategies and Net-Zero Goals

      By: Mark L. Frigo, Robert S. Kaplan and Karthik Ramanna
      In a recent Harvard Business Review article, Kaplan and Ramanna describe a rigorous approach, the E-liability method, for companies’ ESG reporting, especially as it pertains to GHG emissions measurements. They argue that the current standards for measuring...  View Details
      Keywords: Measurement; Sustainability; Net-zero Emissions; Environmental Sustainability; Integrated Corporate Reporting; Measurement and Metrics; Strategy
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      Frigo, Mark L., Robert S. Kaplan, and Karthik Ramanna. "Sustainable Strategies and Net-Zero Goals." Special Issue on Sustainability. Strategic Finance 103, no. 10 (April 2022): 42–49.
      • 2022
      • Working Paper

      The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

      By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
      As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how...  View Details
      Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods
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      Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
      • January 2022
      • Background Note

      Common Prosperity? China Shifts Left

      By: William C. Kirby and Noah B. Truwit
      Since the founding of the People’s Republic of China in 1949, the ruling Chinese Communist Party (CCP) has been mistrustful of entrepreneurs and the private sector that operates outside the government’s authority. In its first decades under Mao Zedong, the CCP...  View Details
      Keywords: Market Reform; Gdp; Government Administration; Government and Politics; Private Sector; Governing Rules, Regulations, and Reforms; Economy; Globalized Economies and Regions; Entrepreneurship; Business and Government Relations; Globalized Markets and Industries; Social Issues; Society; Economic Growth; China
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      Kirby, William C., and Noah B. Truwit. "Common Prosperity? China Shifts Left." Harvard Business School Background Note 322-069, January 2022.
      • 2022
      • White Paper

      Building from the Bottom Up: What Business Can Do to Strengthen the Bottom Line by Investing in Front-line Workers

      By: Joseph B. Fuller and Manjari Raman
      A significant number of American workers—44%—are employed in low wage jobs at the front line of industries. Despite undertaking some of the most tedious, dirtiest, and most dangerous jobs, low-wage workers are—and have long been—the most likely to be overlooked by...  View Details
      Keywords: COVID-19; Labor Market; Low-wage Workers; Worker Welfare; Churn/retention; Morale; Jobs and Positions; Employees; Wages; Retention; Well-being; Human Resources
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      Fuller, Joseph B., and Manjari Raman. "Building from the Bottom Up: What Business Can Do to Strengthen the Bottom Line by Investing in Front-line Workers." White Paper, Harvard Business School, January 2022.
      • Article

      Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

      By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
      As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...  View Details
      Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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      Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • August 2021 (Revised February 2023)
      • Case

      Fair Park Covid-19 Mass Vaccination Site (A)

      By: Willy Shih
      This case is an opportunity to apply the methods of the Toyota Production System (TPS) to the analysis of an everyday service application: administering Covid-19 vaccines. It describes the start-up of a drive-up Covid-19 mass vaccination site at the Texas State Fair...  View Details
      Keywords: Operations Improvement; Operations And Processes; Toyota Production System; COVID-19 Pandemic; Operations; Service Operations; Health Pandemics; Problems and Challenges; Goals and Objectives; Measurement and Metrics; Health Care and Treatment; Health Industry; United States; Texas
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      Shih, Willy. "Fair Park Covid-19 Mass Vaccination Site (A)." Harvard Business School Case 622-003, August 2021. (Revised February 2023.)
      • August 2021 (Revised February 2023)
      • Supplement

      Fair Park Covid-19 Mass Vaccination Site (B)

      By: Willy Shih
      This case is an opportunity to apply the methods of the Toyota Production System (TPS) to the analysis of an everyday service application: administering Covid-19 vaccines. It describes the start-up of a drive-up Covid-19 mass vaccination site at the Texas State Fair...  View Details
      Keywords: Operations Management; Operations Improvement; Operations And Processes; Toyota Production System; COVID-19 Pandemic; Operations; Service Operations; Health Pandemics; Service Delivery; Problems and Challenges; Goals and Objectives; Measurement and Metrics; Health Industry; United States
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      Shih, Willy. "Fair Park Covid-19 Mass Vaccination Site (B)." Harvard Business School Supplement 622-004, August 2021. (Revised February 2023.)
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