Risk Theory and Pricing of "Pay-for-Performance" Business Models

Paper: arXiv 2212.09585

Authors: Roger Knecktys, Henrik Bette, Rüdiger Kiesel, Thomas Guhr

Abstract

Technology trends as digitalization and Industry 4.0 initiate a growing demand for new business models. Most of this models requires a fundamental shift of operational and financial risks between seller and buyer. A key question is therefore how to include additional risk pricing and hedging. In this paper we propose a new approach for a risk theory of innovative performance based business models as “Pay-for-Performance” or “Product as a Service”. A new model and calculation method for determination the risk premium is presented. It contains beside financial price fluctuations also operational failure behaviour of products. We apply the model for a typical industrial application and simulate the pricing dependency for different cost distributions.

Complexity vs Empirical Score

• Math Complexity: 5.5/10
• Empirical Rigor: 4.5/10
• Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper introduces an intriguing framework for pricing operational and failure risks in Pay-for-Performance and Equipment-as-a-Service models. While mathematically solid in combining financial and reliability engineering approaches, it relies primarily on illustrative simulations rather than extensive empirical backtesting with real-world datasets.

Research Flowchart

  flowchart TD
    A[Research Goal: Model and price operational/financial risks in Pay-for-Performance models] --> B[Inputs: Product failure rates, cost distributions & market price volatility]
    B --> C[Methodology: Integrate reliability theory with financial risk premium calculation]
    C --> D[Computational Process: Monte Carlo simulation of combined risk scenarios]
    D --> E[Outcomes: Quantitative risk premium model & optimal hedging strategies for industrial assets]