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<p>Capacity-constrained firms keep prices fixed regardless of utilisation, leaving idle capacity unmonetised and excluding price-sensitive customers. Revenue management and dynamic pricing address this but typically require demand-function estimation or algorithmic optimisation, limiting accessibility. This study introduces the Cost–Demand–Capacity (CDC) Pricing Framework: a closed-form heuristic constructed as a boundary-consistent interpolation between unit cost <i>C</i> and capacity-clearing anchor price <i>P₀</i>, motivated by—but not algebraically derived from—a Taylor approximation of a profit-maximisation problem. Its slope, (P₀ − C)/K, plays the local role of the unobservable demand-slope parameter 1/<i>b</i>, and the condition under which the two coincide is derived. Benchmarking against the two-case optimum confirms CDC recovers the capacity-clearing optimum at equilibrium; approximation error reaches 66.7% at D₀/K = 0.25, narrowing to zero as D₀ = K. A scarcity extension captures rents above capacity under latent-demand interpretation. Simulations across six industries and illustrations in airlines, hotels, and ride-hailing show consistent structural predictions. Among the pricing rules reviewed, CDC alone satisfies three conditions for replicable Creating Shared Value: optimisation-anchored construction, no explicit demand-function estimation, and a structural cost floor—a comparative claim against those frameworks, not a general uniqueness proof. The framework is a heuristic for constrained firms, not a claim to optimality.</p>

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Capacity-aware pricing as shared value creation: Ehsan’s CDC (cost–demand–capacity) pricing framework

  • 期刊论文

  • 发表日期：

    2026年7月30日

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  • Ehsan Shareef Salih

摘要

Capacity-constrained firms keep prices fixed regardless of utilisation, leaving idle capacity unmonetised and excluding price-sensitive customers. Revenue management and dynamic pricing address this but typically require demand-function estimation or algorithmic optimisation, limiting accessibility. This study introduces the Cost–Demand–Capacity (CDC) Pricing Framework: a closed-form heuristic constructed as a boundary-consistent interpolation between unit cost C and capacity-clearing anchor price P₀, motivated by—but not algebraically derived from—a Taylor approximation of a profit-maximisation problem. Its slope, (P₀ − C)/K, plays the local role of the unobservable demand-slope parameter 1/b, and the condition under which the two coincide is derived. Benchmarking against the two-case optimum confirms CDC recovers the capacity-clearing optimum at equilibrium; approximation error reaches 66.7% at D₀/K = 0.25, narrowing to zero as D₀ = K. A scarcity extension captures rents above capacity under latent-demand interpretation. Simulations across six industries and illustrations in airlines, hotels, and ride-hailing show consistent structural predictions. Among the pricing rules reviewed, CDC alone satisfies three conditions for replicable Creating Shared Value: optimisation-anchored construction, no explicit demand-function estimation, and a structural cost floor—a comparative claim against those frameworks, not a general uniqueness proof. The framework is a heuristic for constrained firms, not a claim to optimality.