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Jbv Methods

ASecurity

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).

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Added 6/5/2026
ai-agentsrustgit

Security Analysis

A100/100

Scanned 6/5/2026

Install to Claude Code

$npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill jbv-methods --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
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:

| Entrepreneurial question / claim                         | Fitting design                                                   |
|----------------------------------------------------------|-------------------------------------------------------------------|
| Process of how ventures emerge / sensemaking             | Inductive qualitative (Gioia, process), longitudinal case studies |
| Entrepreneurial judgment / cognition under uncertainty   | Experiments, conjoint/policy-capturing, vignettes (Prolific/lab)  |
| Antecedents/consequences across many ventures            | Archival venture panels (Crunchbase, PitchBook, GEM, KFS, PSED)   |
| Founding choice, exit, IPO, failure                      | Survival/event-history; selection models                          |
| Financing signals (VC, crowdfunding)                     | Field/natural experiments, panel with funding events              |
| Theory-building plus generalization                      | Mixed methods (qual to build, quant to test)                      |

## 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.

## 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

## 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
```

Attribution

brycewang-stanfordbrycewang-stanford
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