jbv-methods

name: jbv-methods description: Use when designing or defending the research design for a Journal of Business Venturing (JBV) manuscript — matching a methodologically pluralistic but theory-first approach (venture panels, experiments, qualitative process work, mixed methods) to an entrepreneurial question, and handling selection, survival, and novel-dataset issues. Designs the study; it does not estimate it (jbv-data-analysis) or frame the contribution (jbv-contribution-framing).

Methods & Research Design (jbv-methods)

When to trigger

• You are choosing a design and unsure which fits a venture-creation question
• The design may not let you observe the entrepreneurial process you theorize
• A reviewer flags selection into entrepreneurship, survivorship bias, or sample novelty
• You are weighing qualitative process work, experiments, archival venture panels, or mixed methods

JBV is methodologically pluralistic — but theory-first

JBV prizes a clear, substantive theoretical contribution to entrepreneurship over any single method. Well-executed qualitative, conceptual, quantitative, and mixed-method studies are equally welcomed; the unifying demand is that the work advance theory about the entrepreneurial phenomenon, not merely apply a method. Choose the design that can actually test or build your theory:

Design issues specific to the entrepreneurial setting

• Selection into entrepreneurship: founders self-select; model the choice (Heckman/Roy) or use design-based identification rather than ignoring it.
• Survivorship: new-venture samples lose failed ventures fast; a sample of survivors silently conditions on success. Design to observe pre-founding and failed ventures (PSED-style nascent panels, registry data).
• Novel datasets: JBV values new entrepreneurship data; document construction, coverage, and the sampling frame transparently — novelty is an asset only if the frame is defensible.
• Temporal precedence: to claim antecedents/mechanisms, the design must order them in time (longitudinal, pre/post a shock, staged measurement).

Co-submission of method artifacts

The Editorial Manager workflow lets you attach a MethodsX article (detailed protocol) or Data in Brief descriptor on the "Attach files" page — useful for novel measures, hand-coded datasets, or experimental protocols.

Execution bridge (StatsPAI / Stata MCP)

For the empirical / causal lane, estimate and audit rather than only specify. Full map: execution-with-mcp. JBV studies founders and ventures where selection / survivorship threatens every claim; lead with identification and selection-correction tooling.

• 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

• Design can actually observe/test the theorized entrepreneurial mechanism
• Selection into founding addressed (modeled or design-based)
• Survivorship/attrition handled in the sampling frame, not just statistically later
• Novel dataset's construction, coverage, and frame documented
• Temporal precedence supports the antecedent/mechanism claim
• Qual studies: trustworthiness plan (data structure, audit trail, quotations)
• Considered MethodsX / Data in Brief co-submission for protocols/data

Design referee-pushback patterns and the JBV-specific fix

Worked micro-example (illustrative)

A hypothetical JBV study claims perceived environmental uncertainty causes founders to evaluate ambiguous opportunities more favorably. Design reasoning:

• Why an experiment: the claim is causal and about entrepreneurial judgment, so a vignette experiment (240 founders, illustrative) manipulates uncertainty while holding the opportunity fixed — isolating the targeted cognition.
• Construct guard: the vignette describes a new-venture opportunity under Knightian uncertainty, not a generic managerial decision, so a referee cannot recast it as ordinary risk-taking.
• Triangulation: pair it with an archival panel where a plausibly exogenous uncertainty shock shifts real founding/financing — answering "lab artificiality" by design.
• Temporal precedence: in the archival arm, measure uncertainty before the founding outcome so the antecedent claim is ordered in time.

Calibration anchors (hedged)

• JBV is method-pluralist: a deep inductive study and a clean field experiment clear the same bar if both advance entrepreneurship theory. The dividing line is theory payoff, not method prestige.
• The desk-reject-adjacent failure is the survivor-only, single-wave, generic-construct combination; design against all three up front.
• Artifact options (MethodsX, Data in Brief) can change; confirm against the journal's current author guidelines.

Anti-patterns

• Method-led, theory-light — a clean identification with no entrepreneurship-theory payoff.
• Survivor-only sample treated as representative of venture creation.
• Cross-sectional self-report used to claim a dynamic entrepreneurial process.
• Convenience startup sample with an undocumented frame.

Output format

【Question→design fit】design chosen + why it fits the entrepreneurial claim ...
【Selection】founding-choice strategy ...
【Survivorship/attrition】sampling-frame handling ...
【Data novelty】construction + coverage + frame ...
【Temporal precedence】how ordered in time ...
【Artifacts】MethodsX / Data in Brief? ...
【Next step】jbv-data-analysis