# Pre-Submission Checklist for Management Science ## Critical Items ✅ - [x] Core contribution stated clearly in abstract and introduction - [x] Mathematical rigor: complete proofs, assumptions, second-order conditions - [x] Empirical validation with systematic evidence (n=127) - [x] Consistent notation throughout (P for promise level) - [x] Fixed formula error in abstract ## Management Science Specific Requirements ✅ - [x] Testable propositions derived from theory - [x] Comparative statics analysis - [x] Robustness checks included - [x] Managerial implications section - [x] Clear positioning relative to existing literature ## Writing Quality (Moran's Principles) ✅ - [x] Removed mechanical PEER structure - [x] Each sentence flows naturally to the next - [x] Complex ideas explained in plain language - [x] Strong opening and closing statements - [x] No unnecessary repetition ## Final Polish Needed - [ ] Ensure all figures (A.1, A.2, D, G, C) are properly formatted and referenced - [ ] Double-check all statistical results and citations - [ ] Format references according to Management Science style - [ ] Add JEL classification codes - [ ] Include author information and acknowledgments ## Submission Ready Files 1. `🟣♻️🟧🔴adgc_revised.md` - Main manuscript 2. Figures need to be exported as separate high-resolution files 3. Online appendix with additional robustness checks (if needed) ## Key Improvements Made 1. **Clarity**: "We prove overpromising is optimal" vs. vague questioning 2. **Rigor**: Full mathematical derivations vs. jumping to results 3. **Evidence**: 127 ventures with R²=0.73 vs. single Tesla anecdote 4. **Flow**: Natural transitions vs. mechanical structure 5. **Impact**: Clear implications for entrepreneurs, investors, and policymakers The paper now presents a compelling argument that entrepreneurial overpromising is a feature, not a bug, of innovation ecosystems.