| # | Place to Embed | Description | Main Purpose | Key Visual Elements | | --------------------------------------------------- | -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Fig 1 – The Promise-Vendor Problem Lens** | [[🟣alert]] | **Variable Explosion vs Constraint Shrinkage**: Shows how entrepreneurial decisions face expanding variables (2→8+) while constraints shrink from solid historical data to ephemeral future projections. Three transformation arrows (⏰ temporal inversion, ↕️ spatial discretization, ♻️ endogenous interaction) illustrate the multiplicative complexity increase. | Immediate visual hook showing why entrepreneurial overpromising is structurally rational, not cognitively biased. | Left: Newsvendor's tractable world (2 vars, 3 constraints). Right: Promise vendor's explosion (8+ vars, 1.5 constraints). Arrows show transformations. | | **Fig 2 – Three Conceptual Gaps** | [[♻️dig]] | **Where Classical OM Fails**: Three horizontal panels showing the orthogonal dimensions where entrepreneurship diverges from classical operations. Each panel contrasts newsvendor assumptions (green) with entrepreneurial reality (red), using the three icons (⏰, ↕️, ♻️) to categorize the gaps. | Diagnoses precisely where and why classical models break when applied to entrepreneurial contexts. | Three panels: Time (past→present vs future→present), Space (continuous vs discrete), Interaction (exogenous vs endogenous). | | **Table 1 – Newsvendor ⇄ Promise-Vendor Crosswalk** | [[♻️dig]] | **Systematic Comparison**: Two-column table mapping newsvendor elements to promise-vendor equivalents. Uses notation clarification: "We denote promise level as P (replacing newsvendor's Q) to emphasize the fundamental inversion: while Q represents physical units to stock, P represents capability commitments about non-existent futures." | Line-by-line translation guide helping readers understand what changes when you invert causality and discretize state-space. | Decision variables (red), Random variables (blue), Objectives, Time flow, Risk types, with mathematical notation (Q→P, D→D, etc.) | | **Fig 3 – Information Flow Swimlanes** | [[🟧grow]] | **Temporal Mechanics Visualization**: Swimlane diagram showing how information flows differently in newsvendor (top lane, green) vs promise vendor (bottom lane, red). Newsvendor: past data → present decision. Promise vendor: future vision ← → present promise, with resources→capability feedback loop and value V emerging when P and D align. | Bridge from diagnosis to mathematical model—readers visualize the mechanics before seeing equations. | Two swimlanes across Past-Present-Future timeline, with arrows showing flow direction, ⏰↕️♻️ icons marking transformations. | | **Fig 4 – Policy Heatmap for Promise Calibration** | [[🔴core]] | **Actionable Design Tool**: 2D heatmap showing optimal promise level q* = ln[(2Cu+V)/(2Co+V)] across different cost structures (Cu/Co ratios) and matching values (V). Warmer colors = more aggressive promises. Includes industry examples (hardware vs software vs platform) and stage guidance (seed vs Series C). | Transforms theoretical model into practical tool for entrepreneurs and ecosystem designers. | Heatmap grid with Cu/Co on x-axis, V on y-axis, color gradient for q*, annotated with real-world contexts. |