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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
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
- 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
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
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
Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
- 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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).
- 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
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.
- May 2016 (Revised April 2018)
- Case
Building the Digital Manufacturing Enterprise of the Future at Siemens
By: Willy Shih
This case describes the motivation for and the development of Siemens' digital manufacturing enterprise vision, which became the foundation for its implementation of Industrie 4.0. While the effort started with a purely defensive move by Anton Huber, head of the... View Details
Keywords: Big Data; Internet Of Things; Internet Of Everything; Industrie 4.0; Digital Factory; Digital Enterprise; Digital Manufacturing; Manufacturing; Production Management; Production Planning; Computer Software; Germany; German Manufacturing; Machinery and Machining; Information Technology; Digital Platforms; Technological Innovation; Production; Supply Chain; Applications and Software; Information Infrastructure; Internet and the Web; Analytics and Data Science; Manufacturing Industry; Germany
Shih, Willy. "Building the Digital Manufacturing Enterprise of the Future at Siemens." Harvard Business School Case 616-060, May 2016. (Revised April 2018.)
- October 2015 (Revised October 2016)
- Case
Building Watson: Not So Elementary, My Dear! (Abridged)
By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details
Keywords: Analytics; Big Data; Business Analytics; Product Development Strategy; Machine Learning; Machine Intelligence; Artificial Intelligence; Product Development; AI and Machine Learning; Information Technology; Analytics and Data Science; Information Technology Industry; United States
Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)