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      • Faculty Publications  (43)

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      • February 2024
      • Case

      ReSpo.Vision: The Kickstart of an AI Sports Revolution

      By: Paul A. Gompers, Elena Corsi and Nikolina Jonsson
      This case study explores the growth journey of Polish computer vision sports start-up ReSpo.Vision in an emerging entrepreneurial ecosystem. By providing 3D data and analysis to soccer clubs, ReSpo.Vision achieved significant milestones with a €1 million seed round, an... View Details
      Keywords: Business Startups; Business Plan; Experience and Expertise; Talent and Talent Management; Decisions; Decision Choices and Conditions; Forecasting and Prediction; Entrepreneurship; Venture Capital; AI and Machine Learning; Analytics and Data Science; Applications and Software; Business Strategy; Sports Industry; Technology Industry; Poland; Europe
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      Gompers, Paul A., Elena Corsi, and Nikolina Jonsson. "ReSpo.Vision: The Kickstart of an AI Sports Revolution." Harvard Business School Case 824-151, February 2024.
      • February 2024 (Revised March 2024)
      • Teaching Note

      X: The Foghorn Decision

      By: Kyle Myers and Walter Frick
      Teaching Note for HBS Case No. 618-060. View Details
      Keywords: Alternative Energy; Energy Generation; Energy Sources; Climate Change; Green Technology; Selection and Staffing; Knowledge; Product Design; Product Development; Research and Development; Risk and Uncertainty; Science-Based Business; Innovation and Invention; Computer Industry; Computer Industry; Computer Industry; Computer Industry; Computer Industry; Computer Industry; Computer Industry
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      Myers, Kyle, and Walter Frick. "X: The Foghorn Decision." Harvard Business School Teaching Note 624-065, February 2024. (Revised March 2024.)
      • January 2024 (Revised February 2024)
      • Technical Note

      Computer Science for Strategists

      By: Andy Wu and Matt Higgins
      Two of the most important computer science principles in the technology industry are abstraction and platformization. Our aim with this note is to explain these concepts in an approachable way that brings managers and computer scientists a little closer together. View Details
      Keywords: Strategist; Computer Science; Strategy; Management Practices and Processes
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      Wu, Andy, and Matt Higgins. "Computer Science for Strategists." Harvard Business School Technical Note 724-429, January 2024. (Revised February 2024.)
      • November–December 2023
      • Article

      Look the Part? The Role of Profile Pictures in Online Labor Markets

      By: Isamar Troncoso and Lan Luo
      Profile pictures are a key component of many freelancing platforms, a design choice that can impact hiring and matching outcomes. In this paper, we examine how appearance-based perceptions of a freelancer’s fit for the job (i.e., whether a freelancer "looks the part"... View Details
      Keywords: Freelancers; Gig Workers; Demographics; Prejudice and Bias; Selection and Staffing; Jobs and Positions; Analytics and Data Science
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      Troncoso, Isamar, and Lan Luo. "Look the Part? The Role of Profile Pictures in Online Labor Markets." Marketing Science 42, no. 6 (November–December 2023): 1080–1100.
      • September 2023 (Revised April 2024)
      • Case

      Atomwise: Strategic Opportunities in AI for Pharma

      By: Satish Tadikonda
      Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details
      Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry
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      Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
      • September 2023
      • Article

      Top Talent, Elite Colleges, and Migration: Evidence from the Indian Institutes of Technology

      By: Prithwiraj Choudhury, Ina Ganguli and Patrick Gaulé
      We study migration in the right tail of the talent distribution using a novel dataset of Indian high school students taking the Joint Entrance Exam (JEE), a college entrance exam used for admission to the prestigious Indian Institutes of Technology (IIT). We find a... View Details
      Keywords: Higher Education; Immigration; Talent and Talent Management; India
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      Choudhury, Prithwiraj, Ina Ganguli, and Patrick Gaulé. "Top Talent, Elite Colleges, and Migration: Evidence from the Indian Institutes of Technology." Art. 103120. Journal of Development Economics 164 (September 2023).
      • 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; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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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.)
      • 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–April 2023
      • Article

      Market Segmentation Trees

      By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
      Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
      Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
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      Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
      • 2023
      • Working Paper

      Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

      By: Daniel Yue, Paul Hamilton and Iavor Bojinov
      Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)... View Details
      Keywords: Analytics and Data Science
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      Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
      • December 2022
      • Article

      The Rise of People Analytics and the Future of Organizational Research

      By: Jeff Polzer
      Organizations are transforming as they adopt new technologies and use new sources of data, changing the experiences of employees and pushing organizational researchers to respond. As employees perform their daily activities, they generate vast digital data. These data,... View Details
      Keywords: Organizational Change and Adaptation; Analytics and Data Science; Technology Adoption; Employees
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      Polzer, Jeff. "The Rise of People Analytics and the Future of Organizational Research." Art. 100181. Research in Organizational Behavior 42 (December 2022). (Supplement.)
      • April 2021
      • Case

      Codecademy: Where to Next?

      By: Jeffrey F. Rayport, Max Mailman and Sarah Ascherman
      In March 2020, Zach Sims, co-founder and CEO of online education platform Codecademy, prepared for a meeting with his Chief of Staff Kunal Ahuja to discuss the company’s goals. Codecademy billed itself as the largest online resource for computer science literacy and... View Details
      Keywords: Monetization Strategy; Business Model; Change Management; Venture Capital; Leading Change; Growth and Development Strategy; Growth Management; Management Teams; Marketing Channels; Product Marketing; Network Effects; Product Development; Organizational Change and Adaptation; Strategic Planning; Internet and the Web; Digital Platforms; United States
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      Rayport, Jeffrey F., Max Mailman, and Sarah Ascherman. "Codecademy: Where to Next?" Harvard Business School Case 821-093, April 2021.
      • January 2021 (Revised June 2023)
      • Case

      Biobot Analytics

      By: Raymond Kluender, Joshua Krieger and Mitchell Weiss
      In 2017, Newsha Ghaeli and Mariana Matus were deciding whether to leave their labs at the Massachusetts Institute of Technology, put other job opportunities aside, and dive full-time into founding a wastewater analysis start-up, Biobot. Ghaeli, an architect, and Matus,... View Details
      Keywords: Entrepreneurship; Information Technology; City; Analytics and Data Science; Personal Development and Career; Technology Industry; Utilities Industry; Health Industry; Information Technology Industry; Information Industry; Biotechnology Industry; United States; Kuwait; Korean Peninsula
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      Kluender, Raymond, Joshua Krieger, and Mitchell Weiss. "Biobot Analytics." Harvard Business School Case 821-045, January 2021. (Revised June 2023.)
      • December 2020
      • Article

      The Parable of the Auctioneer: Complexity in Paul R. Milgrom's Discovering Prices

      By: Scott Duke Kominers and Alexander Teytelboym
      Designing marketplaces in complex settings requires both novel economic theory and real-world engineering, often drawing upon ideas from fields such as computer science and operations research. In Discovering Prices, Milgrom (2017) explains the theory and design... View Details
      Keywords: Pricing; Design; Auctions; Market Design; Complexity
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      Kominers, Scott Duke, and Alexander Teytelboym. "The Parable of the Auctioneer: Complexity in Paul R. Milgrom's Discovering Prices." Journal of Economic Literature 58, no. 4 (December 2020): 1180–1196.
      • September 2020
      • Article

      Creativity, Artificial Intelligence, and a World of Surprises

      By: Teresa M. Amabile
      In recent years, progress has been made toward AI Creativity, which I define as the production of highly novel, yet appropriate, ideas, problem solutions, or other outputs by autonomous machines. I argue that organizational researchers of creativity and innovation... View Details
      Keywords: Artificial Intelligence; AI Creativity; Computer Science; Organizational Behavior; Psychology; Creativity; Technological Innovation; AI and Machine Learning
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      Amabile, Teresa M. "Creativity, Artificial Intelligence, and a World of Surprises." Academy of Management Discoveries 6, no. 3 (September 2020): 351–354.
      • Article

      Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

      By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
      Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
      Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
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      Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
      • May 2020
      • Article

      Scalable Holistic Linear Regression

      By: Dimitris Bertsimas and Michael Lingzhi Li
      We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
      Keywords: Mathematical Methods; Analytics and Data Science
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      Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
      • Article

      Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

      By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani
      Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant... View Details
      Keywords: Computational Biology; Bioinformatics; Innovation Competitions; Research; Collaborative Innovation and Invention
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      Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." PLoS ONE 14, no. 9 (September 2019).
      • 2019
      • Working Paper

      The Impact of Professionals' Contributions to Online Knowledge Communities on Their Workplace Knowledge Work

      By: Hila Lifshitz - Assaf and Frank Nagle
      Knowledge work is becoming increasingly challenging as pace of change in the knowledge frontier is increasing. Organizations have created multiple mechanisms to minimize knowledge gaps and increase learning such internal training, mentorship programs as well as... View Details
      Keywords: Open Source; Future Of Work; Software Development; Knowledge Work; Online Community; Learning; Knowledge Sharing; Applications and Software; Open Source Distribution; Performance Productivity
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      Lifshitz - Assaf, Hila, and Frank Nagle. "The Impact of Professionals' Contributions to Online Knowledge Communities on Their Workplace Knowledge Work." Working Paper, April 2019.
      • 2018
      • Article

      Insight into Gender Differences in STEM: Evidence from Peer Reviews in an Engineering Class

      By: Jacqueline N. Lane, Bruce Ankenman and Seyed Iravani
      As the service industry moves toward self-service, peer feedback serves a critical role in this shift for educational services. Peer feedback is a process by which students provide feedback to each other. One of its major benefits is that it enables students to become... View Details
      Keywords: Peer Review; Peer Feedback; STEM Education; Anonymity; Education; Gender; Education Industry
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      Lane, Jacqueline N., Bruce Ankenman, and Seyed Iravani. "Insight into Gender Differences in STEM: Evidence from Peer Reviews in an Engineering Class." Service Science 10, no. 4 (2018): 442–456.
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