Professor · Economics & Strategy of Innovation
Kevin Boudreau
I study how to harness massively-scaled innovation, knowledge creation, and economic experimentation — focusing on platforms, digital infrastructure and AI, and science and discovery.
I use field experiments and other methods, often working with engineering teams to design and deploy the underlying infrastructure, while collecting data to derive lessons and optimize systems.
Northeastern · NBER · Harvard IQSS · Associate Editor, Management Science · former Chief Economist, NASA Tournament Lab
About
Kevin Boudreau is a Professor at Northeastern University's D'Amore-McKim School of Business, in the Department of Entrepreneurship & Innovation, with courtesy appointments in the College of Computer Science and the College of Social Sciences & Humanities. His work sits at the intersection of strategy, innovation, and the economics of knowledge and science, with a particular focus on platforms, digital organization, and how new ideas and technologies are produced and evaluated.
A defining feature of his research is the use of large-scale randomized field experiments — run with partners including NASA and industry platforms — to study questions long thought impossible to test cleanly: how platforms attract and govern complementors, how competition and incentives shape innovation, how scientific collaborations form, and how knowledge moves across disciplinary frontiers. As Chief Economist of the NASA Tournament Lab (2011–2015), he helped build the infrastructure for running such experiments at scale. This draws on a career in industry, where he led M&A and large-deal digital-infrastructure teams at QUALCOMM, built a European telecoms consulting and advisory practice at the Economist Intelligence Unit, and advised on strategy at Deloitte. It continues today in hands-on technical work: he assembles engineering teams to build platforms and scale their adoption through the IoT Open Innovation Lab, NUgig, the Cyber-Physical Marketing Challenge, and Digital Scientific Twins, both to prototype for industry partners and to generate the data behind his research. He was also part of the founding faculty team of Northeastern's Wireless Internet Research Center. His papers appear in Management Science, Strategic Management Journal, Organization Science, Research Policy, the RAND Journal of Economics, the Review of Economics and Statistics, Science, and Nature Biotechnology.
He is a Research Associate at the NBER and a Faculty Research Fellow at Harvard's Institute for Quantitative Social Science, an Associate Editor at Management Science, and a former Fulbright Scholar (2022–2023). His research has been supported by more than $1.5 million in funding — from the Kauffman, Sloan, Google, and Microsoft programs, NASA, GE, and Northeastern's RIELS, among others — and his work has earned multiple best-paper honors — two Copeland Awards, and recognition from INFORMS, Management Science, and Harvard Business Review. He earned his PhD from the MIT Sloan School (as an MIT Presidential Fellow), an MA in Economics from the University of Toronto, and a BASc in Engineering (summa cum laude) from the University of Waterloo.
Research & Publications
Publications
One question runs through all of this: how do you harness innovation and knowledge creation at massive scale — when it takes large numbers of loosely-organized people to produce something genuinely new? I pursue it across two settings that turn out to be the same problem — digital platforms (increasingly AI platforms) and science itself — using theory, large-scale data, and field experiments. The work is grouped by program below.
Current Projects & Working Papers
Management & Strategy of AI
- AI-Enabled Job Markets & Market Participation
- AI in Science
- Properly Platforming AI as a GPT
Platform Strategy & Innovation
- Managing Your Long Tail Innovation
Science & the Innovation Workforce
- Field Experiment on Interdisciplinary Science
- Development of Engineers & STEM Workers
Platform Strategy, Entrepreneurship & Innovation
How open should a platform be? Who should control its complements? What makes participation take off? This stream develops a set of ideas — granting access vs. devolving control, platform boundaries, complementor incentives, self-fulfilling expectations — from early conceptual work to recent experiments at the platform edge and on AI platforms.
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Artificial Intelligence as a Platform Technology: Strategic Implications of Competing on Top of an AI Platform
The strategy of competing on top of someone else's AI platform — who captures value, and how, when AI is the platform everyone builds on.
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Free(mium) Strategies for Digital Goods
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Gender Differences in Response to Competitive Organization: Evidence from a Product Development Platform
A field experiment on an IoT platform finding men and women respond differently to competitively-organized work, with the gap varying across STEM and non-STEM domains.
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Competing on Freemium: Digital Competition with Network Effects
How “freemium” pricing interacts with network effects to shape digital competition — when giving the product away free is the winning move.
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Profiting from Digital Innovation: Patents, Copyright, and Performance
When formal IP (patents, copyright) actually improves app developers’ performance — and when, in fast-moving digital markets, it doesn’t.
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Crowdfunding as Donations to Entrepreneurial Firms
Many crowdfunding backers behave more like donors than investors or buyers — funding firms for reasons beyond expected returns.
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Promoting Platform Takeoff and Self-Fulfilling Expectations: Field Experimental Evidence
A field experiment showing platform takeoff is partly self-fulfilling: shifting participants’ expectations of success measurably increased their participation.
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Protecting Digital Assets: The Use of Formal and Informal Appropriability Strategies by App Developers
How app developers actually protect what they build — leaning on informal strategies (speed, complexity, secrecy) as much as formal IP.
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"Crowds" of Amateurs and Professional Entrepreneurs in Marketplaces
Distinguishes amateur hobbyists from professional entrepreneurs among platform complementors, and shows they contribute innovation in different ways.
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Platform Boundary Choices and Governance: Entrepreneurship, Innovation, and Growth in Mobile Computing
A framework for where platforms draw their boundaries — how to open up to outside innovators while still coordinating and orchestrating the whole.
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Performance Responses to Competition Across Skill Levels in Rank-Order Tournaments
More competition in a tournament motivates some skill levels and discourages others — so contest design must account for who is competing.
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Unpaid Platform Complementors and the Network Effect Mirage
A platform’s network-effect “value” can be a mirage: many complementors are unpaid amateurs, and adding more can crowd each other out rather than add value.
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Let a Thousand Flowers Bloom? An Early Look at Large Numbers of Software App Developers and Patterns of Innovation
Bigger, more varied crowds of app developers generate more — and more novel — innovation, up to a point, with crowding effects.
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The Confederacy of Heterogeneous Software Organizations and Heterogeneous Developers: Field Experimental Evidence on Sorting and Worker Effort
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Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis
Adding competitors to an innovation contest lowers each entrant’s effort but raises the odds of a breakthrough solution — and which effect wins depends on how uncertain the problem is.
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Open Platform Strategies and Innovation: Granting Access vs. Devolving Control
“Opening” a platform isn’t one thing: granting outside developers more access sharply raised the rate of innovation, while devolving control did not — distinct levers with different effects.
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Platform Rules: Multi-Sided Platforms as Regulators
Platform owners act as private regulators, governing their ecosystems through rules, not just prices.
Management of Knowledge, Science & Discovery
The same levers — openness, rules, incentives, the cost of search — shape how science produces knowledge. This stream studies how scientific work is organized, evaluated, and recombined: peer review as an institution, how new collaborations form, who does multidisciplinary science, and how ideas move across the knowledge frontier.
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Scientific Peer Review: Institutional Workings and Performance
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Field Experiments in the Science of Science: Lessons from Peer Review and the Evaluation of New Knowledge
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Randomized Experiments in the Science of Science
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This Time Is Different: A Comparison of Three Waves of AI Adoption in Science
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From Theory to Practice: Field Experimental Evidence on Early Exposure of Engineering Majors to Professional Work
Early exposure to real professional engineering work (e.g., co-op) measurably shapes students’ later trajectories.
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Randomized Insights: Field Experiments in Understanding Knowledge Production in the Sciences
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A Field Experiment on Search Costs and the Formation of Scientific Collaborations
A field experiment showing that simply lowering the cost of finding each other significantly increased the formation of new scientific collaborations.
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Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance, Novelty, and Resource Allocation in Science
Evaluating new science is shaped by bounded rationality: the more expert an evaluator is in a proposal’s area, the lower they tend to score it — expertise surfaces more information cues (more potential problems) — and highly novel proposals get discounted too. Both distort how research resources are allocated.
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Innovation Experiments: Researching Technical Advance, Knowledge Production, and the Design of Supporting Institutions
An agenda for using field experiments to study how technical advance and knowledge get produced — and to design the institutions that support them.
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"Open" Disclosure of Innovations, Incentives, and Follow-on Reuse: Theory and a Field Experiment in Computational Biology
A field experiment in computational biology testing how openly disclosing intermediate results changes follow-on reuse and the pace of cumulative innovation.
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Prize-Based Contests Can Provide Solutions to Computational Biology Problems
An open prize contest produced computational-biology solutions that beat the established benchmark — evidence that opening a hard problem to a crowd can outperform the experts.
Translation to Practice
Harvard Business Review · MIT Sloan Management Review · HBS
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A Short Guide to Strategy for Entrepreneurs
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Designing Your Company: Creating, Delivering, and Capturing Value
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Using the Crowd as an Innovation Partner
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Experiments in Open Innovation at the Harvard Medical School
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How to Manage Outside Innovation: Competitive Markets or Collaborative Communities?
Honors & Funding
More than $1.5 million in competitive research funding over the years — from federal agencies, foundations, and industry — alongside multiple best-paper honors.
Selected Honors & Awards
- Copeland Best Paper Award — Promoting Platform Takeoff and Self-Fulfilling Expectations (2022)
- INFORMS TIM Best Paper Runner-Up — Looking Across and Looking Beyond the Knowledge Frontier (2020)
- IoT Colleges & Universities Innovator Organization Award (2018)
- Copeland Best Paper Award — Looking Across & Looking Beyond the Knowledge Frontier (2017)
- INFORMS TIM Best Paper — Let a Thousand Flowers Bloom? (2017)
- Management Science Distinguished Service Award (2015)
- HBR / McKinsey & Co. Award Runner-Up — Using the Crowd as an Innovation Partner (2014)
- Management Science Best Paper Finalist (2013)
- Management Science Meritorious Service Award (2013)
Selected Funding
- Platform Innovation & AI — $50k
- Advancing NUgig's AI, DMSB — $35k
- Fulbright Scholarship — $50k
- IoT Open Innovation Collaborative Platform Build — Kauffman $200k · DMSB $50k · GE Corp $15k
- NUgig, Kauffman Foundation — $50k
- CIGREF Grant — $120k
- Sloan Foundation Research Grant — $60k
- NASA Tournament Lab, with K. Lakhani — $600k
- Google Faculty Research Grant — $150k
- London Management Lab Research Award — $75k
- Microsoft Research Faculty Award — $60k
Professional Background & Service
Professional & Industry Experience
- President, Babbage Innovation & Data Analytics
- Director, European Internet, Media & Telecoms — Economist Intelligence Unit
- Senior Manager, Latin America M&A — QUALCOMM
- Strategy Consultant — Deloitte
- Strategy & advisory — Canadian Space Agency
- Earlier: Braxton Strategy Consulting · Nortel / Bell-Northern Research
Labs, Research & Industry Collaborations
- RPDIES — Research Program on Digital Innovation, Entrepreneurship & Strategy
- IoT Open Innovation Lab
- Wireless Internet of Things Research Center — founding faculty
- NUgig — experiential-education venture
- Digital Scientific Twins
- Cyber-Physical Marketing Challenge
- RIELS — Research Institute for Experiential Learning Science, Northeastern
- Harvard Institute for Quantitative Social Science — Faculty Research Fellow
- Harvard Business School AI Institute — Research Affiliate
- NASA Tournament Lab — former Chief Economist
Editorial & Professional Service
- Management Science — Associate Editor, 2011–present
- Strategic Management Journal — Editorial Board, 2016–present
- Boston University Digital Management — Scientific Committee, 2023–present
- Journal of Economics & Management Strategy — co-Editor, 2022–2023
- Academy of Management Journal — Editorial Board, 2012–2014
- AOM Doctoral Consortium Co-Leader & Organizer (BPS / TIM)
- Reviewer: ASQ, Management Science, SMJ, Org Science, Research Policy, AMJ, AMR, Science, PNAS, NSF, ISR, MISQ, AER, QJE, JPE
Education
- PhD, Behavioral & Policy Sciences (Technology, Innovation, Entrepreneurship & Strategy), MIT Sloan School, 2006. MIT Presidential Fellow. Dissertation: "How Open Should an Open System Be?"
- MA, Economics, University of Toronto, 1998 — focus on industrial & organizational economics and econometrics
- BASc, Engineering (minor: Management Science), University of Waterloo, 1996. Summa cum laude; Canada Scholarship. Designed and ran experimental projects and built statistical tools in microelectronics.