Skills Data Science Structuring Exhibits for Operations Management Papers

Structuring Exhibits for Operations Management Papers

v20260724
pom-tables-figures
A comprehensive guide for designing and presenting empirical evidence (tables and figures) in Production and Operations Management (POM) manuscripts. It helps authors manage the limited 'exhibit budget' across the main paper and the online e-companion, ensuring that all visuals are decision-legible, operationally relevant, and adhere to journal standards.
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Overview

Tables & Figures (pom-tables-figures)

When to trigger

  • Exhibits are cluttered, off house style, or not self-explanatory
  • You are over the 32-page cap and must decide what moves to the e-companion
  • A reviewer cannot follow the contribution from the table/figure sequence

The POM exhibit budget: main paper vs. e-companion

POM's 32-page limit counts tables, figures, appendices, and references (1.5 spacing, 11-pt). Treat exhibits as a scarce budget: only the displays that carry the core operational insight belong in the main paper; full proofs, large parameter grids, extended robustness, and supplementary tables go to the unlimited online e-companion. Number e-companion exhibits distinctly (e.g., EC.1, Table EC.2) and cross-reference them stably from the main text.

Match the exhibit to the method track

  • Analytical/modeling: a model schematic (decision timeline, information structure); a comparative-statics or sensitivity figure showing how the optimal policy moves with cost, lead time, or competition; a table of structural results. Lead with the managerial reading of the curve, not just its monotonicity.
  • Empirical OM: a descriptive/summary table; the main results table with effect sizes and standard errors; robustness columns. Put units in decision-relevant terms (cost, fill rate, days).
  • Behavioral OM: treatment-by-condition means with error bars; manipulation-check evidence.
  • Operations data science: validation/performance tables plus a figure showing the operational gain (e.g., cost or service improvement from predict-then-optimize), not just accuracy.
  • Simulation: plots with confidence intervals across sensitivity ranges.

Make every exhibit decision-legible

  • Title and note each exhibit with its decision implication, not only the statistical or mathematical object.
  • State operational units explicitly.
  • Ensure a Department Editor can grasp the contribution from the first one or two exhibits.
  • Avoid duplicating main-paper content in appendices or the e-companion.

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. POM spans analytical and empirical OM; apply the chain below to its empirical-OM papers, and note when a contribution is analytical / optimization.

  • 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

  • Core insight exhibits in the main paper; depth in the e-companion
  • Exhibits counted against the 32-page budget
  • Operational units and decision implications labeled
  • E-companion exhibits numbered (EC.*) and cross-referenced stably
  • No duplication between main paper, appendix, and e-companion

Exhibit pass for Production and Operations Management

Treat this skill as an executable review pass, not a prose hint. First lock the operational decision, the performance metric, and the implementable lever; then judge whether the current manuscript answers the venue's real reader: POM reviewers who want operational insight tied to production, service, supply-chain, or platform decisions.

  • 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 Management Science for broader OR/MS theory, Operations Research for method-first optimization, MSOM for manufacturing/service operations depth; 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】table / figure / schematic / appendix item
【Purpose】mechanism / result / robustness / implication / method detail
【Placement】main paper / e-companion (EC.*)
【Problem】readability / page budget / missing units
【Revision】specific design change
【Next step】pom-writing-style
Info
Category Data Science
Name pom-tables-figures
Version v20260724
Size 5.14KB
Updated At 2026-07-29
Language