Teaching
We are living through a transformation of economic organization as deep as the rise of the modern corporation a century ago — a reorganization of how value is created and who creates it. Platforms are its leading edge, and where I have done most of my research, but they are not the whole of it. I teach students to design for this economy, not the one our inherited frameworks were built for.
Courses
Undergraduate · INNO 3303
Digital Platform Strategies & Data-Driven Business Models
How platforms create value, bring both sides of a market together, and defend a position — and where data, algorithms and AI belong inside the operating model. Built around cases and in-the-cockpit decisions.
Undergraduate · ENTR 3303 (proposed; currently INNO 3303)
Platforms and AI Entrepreneurship
Strategy and business-model design for startups built on digital platforms, data, algorithms and AI: creating value, designing the data and the algorithm at a venture’s core, and launching and competing against incumbents.
Honors seminar · HONR 3310
Digital Platforms and AI: Frontiers of Business Strategy, Innovation, and Entrepreneurship
An honors seminar taking an innovation, entrepreneurship and strategy perspective on platforms and AI: hands-on practice with AI tools, case-based problem solving, and current research at the frontier of the field.
MBA · INNO 6230
Platform Innovation
Platform strategy for people who will be making the calls: designing the business model, governing an ecosystem you do not own, and deciding which decisions to hand to a machine.
Previously taught
Northeastern · MBA · ENTR 6208
Innovation, Entrepreneurship & Enterprise Growth
Graduate
Digital Platform Business Models
Graduate
Data Science & AI Applications
Graduate
Business Strategy
Graduate
Microeconomics
Doctoral · mini-course
Empirical Methods in Management — field experiments
Executive
Technology & Science Entrepreneurship Masterclass
The Shift
We are living through a transformation of economic organization as deep as the rise of the modern corporation a century ago. Digitization, platforming, datafication, and now artificial intelligence are dissolving the boundaries of the firm and changing who creates value and how. Production that once happened inside large integrated firms increasingly runs across loosely-coordinated ecosystems of outside actors; data and algorithms are becoming the operating core of organizations rather than a feature bolted on top; and the same forces are remaking not only business but science, media, and public life. Platforms have been the leading edge of this shift — and they are where I have done most of my research — but the shift itself is much bigger than platforms. It is a reorganization of economic activity, and it is far from finished.
The Problem
The strategy and management frameworks most of us inherited were built for a different economy — the integrated industrial firm and the linear supply chain — and in this one they quietly mislead.
These are not edge cases. They are the everyday decisions facing anyone building or competing in a digital business.
The Frameworks
My courses are built around a set of tools designed for exactly these gaps — frameworks distilled from research, each a precise answer to a problem the inherited toolkit cannot handle. To design value with precision: User × Use-Case × Dimensions of Value, and Value Curves that go beyond Porter. To decide how to organize each side of a platform: the four models — markets, contests, communities, and networks — and open-versus-closed treated as a make-or-buy decision. To build advantage that lasts: VRIDO, and a hard-nosed account of where network effects help and where they don't. To get a platform off the ground: coaxing versus coordinating to crack the chicken-and-egg problem, and a clear-eyed read of when a market actually tips. To analyze competition as it now is — layer against layer and ecosystem against ecosystem, not firm against firm — Ecosystem Forces, the framework that takes managers beyond Porter's Five Forces. And to put AI in its proper place: the Prediction Factory, which locates where data and algorithms create durable advantage — on the premise that the model is the least critical part. Students do not just discuss these. They use them — designing platforms, building working AI prototypes, and competing in simulations.
Reach
These ideas have been taught to students at every level — MBA, PhD, undergraduate, and executive — across disciplines, at institutions in the United States and internationally.
Mentoring is the other half of the work. I have advised doctoral students into academic careers, supervised masters projects and theses, and trained more than fifty research assistants across London Business School, Harvard and the NBER, and Northeastern — people trained in computer science, software engineering, economics and design, most of whom built the systems the research runs on.
A co-op student myself, I also study experiential education directly — from engineering co-op to the design of the modern university as a platform.
Subjects have ranged from strategic management and technology-based innovation and entrepreneurship to empirical and experimental research methods in the study of markets and organizations.