This century, organizations will be transformed, as they embrace digital infrastructure, implement  massively-scaleable platforming practices, re-balance the work of  humans and machines, and embrace more scientific and data-driven  management methodologies. My research seeks to better understand optimal approaches to designing, building and scaling these 21st Century organizations.
Kevin Boudreau Ph.D. Behavioral and Policy Sciences, MIT;  M.A. Economics, University of Toronto; B.A.Sc. Engineering, University of Waterloo

  • Visiting Fulbright Canada Distinguished Research Chair of Entrepreneurship,
    visiting Carleton U and Ottawa, as part of 1-year Fulbright Scholarship

  • Northeastern University: DMSB, CSSH, KCCS 

  • Harvard University: Institute for Quantitative Social Science

  • National Bureau of Economic Research: Productivity, Innovation & Entrepreneurship

Other responsibilities:
  • Associate Editor of Management Science
    • Business Strategy
    • Innovation & Entrepreneurship
    • Data Science (ad hoc)
    • Information Systems (ad hoc)
    • Behavioral and Decision Sciences (ad hoc)
    • Market Analytics (ad hoc)
  • Editorial board member of Strategic Management Journal
  • Co-editor of Journal of Economics & Management Strategy

Prior to academic research, I worked as as an engineer, strategy consultant and executive in several large tech firms and and startups in platform-based industries. I led multi-disciplinary teams for large M&A and telecoms infrastructure projects for Qualcomm; led the creation of The Economist Intelligence Unit's Western European and US technology and media advisory practice; and consulted on business strategy in network industries for Braxton Associates. I also advised and founded several platform and data science startups. My earliest engineering responsibilities involved designing and running engineering research randomized controlled experiments and building statistical production tools for Bell Northern Research, Canada's Bell Labs.

Optimally Designing Digital Platform Business Models

Organizing Science & Universities as Knowledge Platforms

Implementing Scientific Large-Scale Experiments on "Live" Platforms

I study how to design large-scale platforms and digital infrastructure to scale up and organize large numbers of actors most productively. 

I contribute to general lessons and theoretical insights by empirically studying the micro-mechanisms shaping behaviors of individual actors in these systems (incentives, knowledge, diversity, sociology, psychology, cognition). This fine-grained understanding of behavior then serves as a means to understand optimal overall optimal design at the aggregate level of organizations, platforms and industry. Thus, I build up a grounded understanding of governance, precise business model design, scaling, innovation, and competitiveness.

My research increasingly involves embedding large-scale field experiments within "live platforms" in partnership with industry and government. This results in better-designed business models for parner organizations, based on discerning data analysis and experiments, while also generating generalizable lessons for the academic literature. 

I kindly thank a number of generous funders and supporters of my research: Fulbright Foundation, G.E. Corp., Google, the Kaufmann Foundation, Microsoft, the National Bureau of Economic Research, the Paris Chamber of Commerce, and the Sloan Foundation.