Skills Data Science Academic Exhibit Preparation for Business Journals

Academic Exhibit Preparation for Business Journals

v20260724
jbv-tables-figures
A comprehensive guide for structuring and polishing empirical tables and figures for top-tier academic journals, such as the Journal of Business Venturing (JBV). It covers the standards for presenting descriptives, main model coefficients, interaction plots, survival curves, process models, and qualitative data structures. This skill ensures exhibits are self-contained, interpretable, and adhere to rigorous academic house styles.
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Overview

Tables & Figures (jbv-tables-figures)

When to trigger

  • Tables/figures are cluttered, redundant, or not self-explanatory
  • You need the standard exhibit set for an entrepreneurship empirical paper
  • A reviewer says an exhibit is "not interpretable" or "off house style"
  • You are presenting survival, interaction, or qualitative-process results

JBV exhibit conventions

JBV publishes via Elsevier/ScienceDirect, so prepare figures for both print and online, with self-contained captions and references that can be reconciled to the journal's numbered style. Each exhibit must stand alone: a reader should grasp it without the text.

The standard exhibit set (match to your design)

  • Table 1 — Descriptives & correlations: venture-level means, SDs, and correlations; note the sampling frame (e.g., Crunchbase/PSED) and the time window. Flag survivorship in the note if the sample conditions on survival.
  • Table 2+ — Main models: nested model columns; report coefficients with SEs, the SE-clustering level (cohort/region/industry), and fit. For survival models report hazard ratios with a clear baseline and the risk set; for selection models show both the selection and outcome equations.
  • Interaction plots: when you theorize moderation by an entrepreneurial condition (uncertainty, resource scarcity, ecosystem support), plot simple slopes with a clear region of significance — do not leave the interaction to a coefficient alone.
  • Survival/Kaplan-Meier curves: for time-to-IPO/exit/failure, show curves by key group with at-risk counts.
  • Process model / framework figure: a boxes-and-arrows model of the entrepreneurial mechanism (opportunity → action → outcome) — earns its place only if it adds beyond the text.
  • Qualitative data structure: for inductive work, a Gioia-style figure (first-order codes → second-order themes → aggregate dimensions) plus a power-quote table.

Quality bar

  • Every table note defines abbreviations, significance stars, SE type, and N (and venture-level vs. event-level units).
  • Figures are legible in grayscale; lines/markers distinguishable without color.
  • No exhibit duplicates the text; no number in a table contradicts the prose.
  • Units and scales are stated (e.g., USD funding, log employees, months-to-exit).

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of body-vs-appendix drift). Full map: execution-with-mcp. JBV studies founders and ventures where selection / survivorship threatens every claim; lead with identification and selection-correction tooling.

  • Tables: etable (multi-model columns) or did_summary_to_latex straight from the result_id.
  • Figures: plot_from_result / enhanced_event_study_plot / event_study_table — axis units and the SE/clustering note baked in.
  • Every note names the estimator + clustering and states the effect size in interpretable units.

See a full fitted-result → exhibit chain in the JF execution walkthrough.

Checklist

  • Descriptives/correlation table with frame, window, and survivorship note
  • Main-model table reports SEs, clustering level, fit; HRs/selection eqs if used
  • Interaction plotted with simple slopes + significance region
  • Survival curves with at-risk counts where time-to-event is the outcome
  • Process model or framework figure earns its place (adds beyond text)
  • Qualitative data structure + power quotes for inductive work
  • Self-contained captions; grayscale-legible; no text duplication

Anti-patterns

  • Coefficient-only moderation with no simple-slope plot.
  • Mega-table dumping every model and control with no narrative.
  • Color-only figures that collapse in print.
  • Decorative framework figure that merely restates the abstract.

Exhibit pass for Journal of Business Venturing

Treat this skill as an executable review pass, not a prose hint. First lock the entrepreneurial mechanism, level of analysis, evidence design, and boundary conditions for ventures; then judge whether the current manuscript answers the venue's real reader: entrepreneurship reviewers who ask whether the paper advances venture formation, opportunity, founder, or ecosystem theory.

  • Do the pass: For every table or figure, state the estimand or object, sample or case base, uncertainty display, and one sentence the exhibit proves for the venue audience.
  • Return a ledger: give claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.
  • Sibling guard: compare against Entrepreneurship Theory and Practice for broader entrepreneurship, Strategic Entrepreneurship Journal for strategy interface, AMJ for general management; if a sibling owns the contribution, recommend re-routing before polishing format.
  • Stop condition: do not give submission-ready advice until the pack's resources/official-source-map.md has been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.

Output format

【Exhibit list】T1 descriptives; T2.. models; F1 interaction; F2 survival; F3 model ...
【Survival/selection reporting】HRs / two equations shown? ...
【Moderation】simple-slope plot present? ...
【Qual】Gioia data structure + quotes? ...
【House-style fixes】captions, grayscale, units ...
【Next step】jbv-writing-style
Info
Category Data Science
Name jbv-tables-figures
Version v20260724
Size 5.97KB
Updated At 2026-07-28
Language