How To… Earn the Entrepreneurship Doctorate

A doctorate begins where the textbook ends. Before you can add to a field, you have to stand at its frontier and see clearly what is known, what is contested, and what is merely assumed. This tier maps that frontier for entrepreneurship and small-business strategy.

1. Effectuation vs. Causation — the core theoretical fault line

This isn't a management fad; it is the central debate in modern entrepreneurship theory about how expert founders actually think under true uncertainty. You will learn the four effectual principles — the affordable-loss principle, the bird-in-hand principle, the crazy-quilt principle, and the lemonade principle — and the empirical critiques leveled against them (measurement problems, survivorship in the samples, boundary conditions).

2. Lean & Agile Theory — and its scholarly discontents

"Build-measure-learn" and the minimum viable product entered the academy as practitioner theory and are now studied rigorously. You'll read what the research actually supports (validated learning, pivot cost reduction) and where scholars push back — the risk of premature scaling, the vanity-metric trap, and the fact that "the lean startup" was never designed for capital-intensive or regulated ventures. You'll place lean/agile inside the older tradition of discovery-driven planning.

3. Immigrant & Diaspora Entrepreneurship — a literature of its own

This is a full research stream, not a footnote. You'll cover mixed-embeddedness theory (how immigrant ventures sit inside both the opportunity structure of the host economy and their own social networks), ethnic-enclave economies, the role of co-ethnic labor and rotating-credit associations, and the ongoing debate over "blocked mobility" vs. "opportunity" explanations for why immigrants found businesses at high rates.

4. The Resource-Based View (RBV) & its frontier

You'll master VRIN, the dynamic-capabilities extension (Teece), and the sharpest critiques — that RBV can be tautological ("you won because you had winning resources") and hard to falsify. Then you'll apply it honestly to a small business, where the "inimitable resource" is often something the owner has never named.

5. Current, unresolved debates you must be able to hold

• Is opportunity discovered (it exists, waiting) or created (it comes into being through the entrepreneur's action)? The Shane–Venkataraman vs. Alvarez–Barney divide.
• Does entrepreneurship education actually increase venture success, or select for people who'd succeed anyway?
• Are "necessity" and "opportunity" entrepreneurship a clean binary, or a false one that erases mixed motives common in immigrant founding?
• How much of measured founder "grit" is trait vs. survivorship narrative?

Tier I mastery test: you can walk into any of these debates, state both sides in their strongest form, and say where you stand and why — without strawmanning the other side.

The single skill that separates a doctoral candidate from a well-read operator is the systematic literature review: the ability to take a chaotic field of thousands of papers and turn it into a defensible map of what is settled, what is fought over, and what nobody has answered yet. This tier builds that engine.

1. Scholarly reading — the three-pass method

You'll learn to read a research paper the way a candidate does, not the way a student does. Pass one (five minutes): title, abstract, headings, conclusion — decide if it's even relevant. Pass two (an hour): figures, tables, claims, and the boundary of what the authors actually tested. Pass three (deep): reconstruct the argument well enough to challenge it. You'll practice extracting a paper's claim, evidence, method, and limitation in four lines.

2. The systematic review — a repeatable protocol

Not "I read some articles." A real protocol you can defend: define the question, set inclusion/exclusion criteria in advance, search named databases with recorded search strings, screen by title/abstract then full text, and log every decision so another person could reproduce your funnel. You'll learn the PRISMA-style flow (records identified → screened → excluded with reasons → included) adapted for a solo builder without university library access, using open sources.

3. Mapping the debate — the argument, not the pile

You'll build a concept matrix (sources down the side, themes across the top) so the map organizes by idea, not by author. Then a debate map: who claims what, who answers whom, and where the disagreement actually lives — is it about evidence, about definitions, or about assumptions? Most "disagreements" in a field are really definitional, and spotting that is a doctoral-grade move.

4. Finding YOUR gap — and testing it for worthiness

A gap is only worth a dissertation if it passes three tests: it is real (genuinely unaddressed, not just unknown to you), reachable (you can gather evidence on it), and it matters (filling it changes what someone believes or does). You'll pressure-test candidate gaps against all three before committing — the same triage a committee applies.

A question without a method is an opinion. This tier gives you the research toolkit a doctoral candidate in a business school actually uses — enough to design defensible evidence, and enough to know the limits of your own claims.

1. The case-study method — done rigorously, not casually

"Case study" is the most abused phrase in business writing. Done right (Yin, Eisenhardt) it is a rigorous method with a design: your unit of analysis, your propositions, your logic linking data to those propositions, and your criteria for interpreting findings. You'll learn single vs. multiple cases, the difference between a revelatory and a typical case, and how theory-building case work differs from theory-testing.

2. Survey design — measuring without fooling yourself

You'll cover constructs vs. items, the sins of double-barreled and leading questions, response scales, and the difference between a valid measure and a question that merely sounds right. Sampling frames, response bias, and why a survey of your own happy customers answers a different question than the one you think you're asking.

3. Qualitative coding — from raw talk to defensible themes

You'll code a short transcript by hand, build a codebook, and see how the same three interviews yield either insight or wishful thinking depending on the discipline of the method.

4. Quant basics — enough to be honest, not dangerous

• Descriptive vs. inferential statistics, and never confusing them.
• Correlation vs. causation — the phrase everyone says and few respect. Confounds, reverse causation, and why an RCT is the gold standard.
• What a p-value actually means (and the four things people wrongly think it means).
• Effect size vs. statistical significance — why "significant" can still be trivial.
• Sample size intuition: why n=8 happy customers proves almost nothing.

5. Validity, reliability & reproducibility — the ethics of evidence

You'll learn to write a limitations section that a committee respects — one that names the threats to validity before the examiner does. In doctoral work, naming your own weaknesses first is a sign of strength, not concession.

Before a candidate is allowed to research, they must survive the comprehensive exam — hours across a table from scholars whose job is to find where your thinking breaks. You can't hire that committee. So you build it: the Sumo-Librarian runs the quals, and every objection below is one examiner's challenge. Answer it in your own words before you open the response.

Tap each challenge. Each one is tagged with the Sumo-Librarian memory move that makes the answer stick.

Passing the quals means you can face any of these cold, hold both sides, name your own weakness first, and scope your claims exactly to your evidence. Do that, and you are ABD-caliber in fact, whatever the paper says.

Everything before this was preparation. Here you produce the two artifacts that define a doctoral candidate: a defensible research proposal and a real contribution to knowledge — in your case, a rigorous case study of the venture you know better than any outside researcher ever could.

1. The research proposal — the five-chapter spine

• Chapter 1 — Introduction & problem: the specific problem, why it matters, your research question, and the boundary of the study.
• Chapter 2 — Literature & gap: the map you built in Tier II, ending in the defended gap.
• Chapter 3 — Methods: the design from Tier III — unit of analysis, data sources, coding plan, and validity safeguards.
• Chapter 4 — (Proposed) findings & analysis plan: what evidence you'll gather and how you'll interpret it before you're allowed to fool yourself.
• Chapter 5 — Contribution & limitations: the so-what ladder, and the threats you name before the committee does.

You'll draft each chapter to a defensible standard, with a template and a worked example built around a small-business case.

2. The capstone — a real case study of your own venture

This is where the whole program pays off: the frontier theory tells you which lens to use, the literature engine tells you what's already known, the methods tell you how to gather honest evidence, and the quals tell you how to defend it. The result is a document you could hand to a scholar and have taken seriously — and hand to another founder and have it change what they do.

3. The Committee-in-a-Box

You get the exact prompts to summon each committee member — including how to use an AI as each voice — plus a defense-day script that walks you through presenting, absorbing hard questions without flinching, and revising with grace.

4. The honest finish line

At the end you hold three things no university handed you: a proposal that survives its own committee, a real case study that contributes something, and a defended mind. That is the ABD-caliber threshold — earned, not conferred. "A life worth living, is a life always worth recording."