Etp methods

Methods & Research Design (etp-methods)

When to trigger

• You are choosing a design and unsure it can observe the entrepreneurial process you theorize
• A reviewer flags selection into entrepreneurship, survivorship bias, or an undocumented sampling frame
• The design is cross-sectional but the theory is a venturing process
• You are weighing inductive qualitative work, experiments, archival venture panels, or mixed methods
• Construct validity for an entrepreneurial measure (alertness, effectuation, SEW, passion) is in doubt

ETP is method-plural but theory-first

ETP publishes strong quantitative, qualitative, and mixed-methods work; it has no single preferred method. The constant is that the design must let you build or test entrepreneurship theory and that it confronts the inference problems that are endemic to studying new ventures. Choose the design that can actually observe the mechanism, then design against the entrepreneurship-specific threats below — these are the things ETP referees reflexively probe.

Entrepreneurial question / claim	Fitting design
How ventures/opportunities emerge; sensemaking; identity work	Inductive qualitative (Gioia, process), longitudinal cases
Founder decision logic / cognition under uncertainty	Experiments, conjoint / policy-capturing, verbal protocols
Antecedents/consequences across many ventures	Archival venture panels (Crunchbase, PitchBook, GEM, PSED/KFS, registries)
Founding, exit, IPO, failure, time-to-event	Survival / event-history models
Financing signals (VC, angels, crowdfunding)	Field/natural experiments; panels with funding events
Family-firm behavior (SEW)	Survey + archival; sometimes dyadic/family data
Theory-building plus generalization	Mixed methods (qual to build, quant to test)

The four threats ETP referees reflexively probe

• Selection into entrepreneurship. Founders self-select; comparing them to non-founders, or treating "who became an entrepreneur" as random, invites a Heckman/Roy or design-based response. Ignoring selection is a near-automatic flag.
• Survivorship. New-venture samples lose failed ventures fast; a sample of survivors silently conditions on success and biases any "what makes ventures succeed" claim. Push the frame upstream to nascent/registry panels (PSED-style) that capture pre-founding and failed ventures.
• Process observability and temporal precedence. To claim antecedents or a process, the design must order constructs in time — longitudinal waves, pre/post a shock, staged measurement. A single cross-section cannot carry a venturing-process claim.
• Construct validity for entrepreneurial constructs. Effectuation, alertness, passion, SEW, and entrepreneurial orientation are contested measures; cite the validated scale, report reliability, and show discriminant validity from the generic relabel (e.g., effectuation ≠ improvisation; SEW ≠ ownership concentration).

Qualitative rigor at ETP

For inductive work, ETP expects a visible trustworthiness apparatus: a clear data structure (1st-order codes → 2nd-order themes → aggregate dimensions), an audit trail, representative quotations tied to informants, and a process model as the output. Sampling logic (theoretical, not convenience) and saturation should be argued. A rich story without this scaffolding reads as journalism to a methods-attentive ETP reviewer.

Execution bridge (StatsPAI / Stata MCP)

For the empirical / causal lane, estimate and audit rather than only specify. Full map: execution-with-mcp. ETP is entrepreneurship, where selection and survival bias are pervasive — foreground identification and selection corrections.

• detect_design → recommend → fit with as_handle=true → audit_result to enumerate the checks the design owes.
• Panel / staggered DiD: callaway_santanna / sun_abraham + bacon_decomposition
  • honest_did_from_result. IV: effective_f_test + anderson_rubin_ci. RDD: rdrobust + mccrary_test.
• Experiments: randomization-based inference and romano_wolf for the many-outcome family-wise correction reviewers expect.

Match the toolchain to the reviewer pool, and report the effect size the venue wants. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.

Checklist

• The design can actually observe/test the theorized entrepreneurial mechanism
• Selection into founding is modeled or addressed by design
• Survivorship/attrition handled in the sampling frame, not patched statistically later
• Temporal precedence supports any antecedent/process claim
• Entrepreneurial constructs use validated scales with reliability + discriminant validity
• Qualitative: data structure, audit trail, theoretical sampling, quotations, process model
• Sample frame, coverage, and construction documented (especially for novel datasets)

Anti-patterns

• Survivor-only sample treated as representative of venture creation
• Cross-sectional self-report used to claim a dynamic entrepreneurial process
• Selection ignored — founders compared to non-founders as if assignment were random
• Construct relabeling — a generic measure renamed as an entrepreneurial one
• Convenience startup sample with an undocumented frame
• Thin qual — vivid quotes, no data structure or audit trail

Worked vignette (illustrative)

A study claims that founders' prior startup failure causes faster pivoting in their next venture, using a panel of funded startups. An ETP methods reviewer sees three traps at once. Survivorship: the panel only includes ventures that secured funding and survived long enough to be observed pivoting — failures that died before pivoting are invisible, so "failure speeds pivoting" may be an artifact of who survived. Selection: founders who start again after failure differ systematically from those who quit; the comparison is not random. Temporal precedence: pivoting must be measured after the prior-failure exposure, not concurrently. The design fix moves the frame upstream to a nascent/registry panel (PSED-style) that captures ventures from formation regardless of survival, models the founding/restart decision (Heckman or a design-based shock to who restarts), and times the pivot measurement strictly after the failure. Only then does the antecedent claim survive — and the analysis hands off to an event-history model in etp-data-analysis.

Output format

【Journal】Entrepreneurship Theory and Practice
【Question→design fit】design + why it observes the entrepreneurial mechanism
【Selection】founding-choice strategy (model / design-based / N/A + why)
【Survivorship/attrition】sampling-frame handling
【Temporal precedence】how constructs are ordered in time
【Construct validity】scale + reliability + discriminant evidence
【Qual rigor】data structure / audit trail / saturation (if applicable)
【Next skill】etp-data-analysis