Dynamic Pricing: Economics, Algorithms and Market Design
Buch in deiner Nähe kaufen
Beschreibung
This textbook provides a comprehensive and rigorously structured analysis of Dynamic Pricing—the practice of flexibly adjusting prices based on real-time market conditions, demand patterns, and competitive dynamics. The book's primary subject is the shift from traditional, cost-plus pricing to algorithmic, data-driven optimization across eighteen distinct industry contexts. It synthesizes economic theory, mathematical modeling, and empirical evidence to establish a unified framework for understanding how value is created, exchanged, and captured in the modern, hyper-competitive economy.
The work's special feature lies in its didactic, applied approach. The content is structured logically, moving from general economic principles to specific mathematical frameworks before analyzing extensive real-world case studies (e.g., Singapore's ERP, the WeWork model, the T-Mobile 'Un-carrier' disruption). Each chapter includes robust Discussion Questions and Quantitative Exercises designed for both classroom use and self-study, allowing readers to apply the complex models directly. The extensive use of mathematical notation (integrals, optimization functions, game-theoretic equations) ensures academic rigor while supporting practical application.
This textbook provides a comprehensive and rigorously structured analysis of Dynamic Pricing—the practice of flexibly adjusting prices based on real-time market conditions, demand patterns, and competitive dynamics. The book's primary subject is the shift from traditional, cost-plus pricing to algorithmic, data-driven optimization across eighteen distinct industry contexts. It synthesizes economic theory, mathematical modeling, and empirical evidence to establish a unified framework for understanding how value is created, exchanged, and captured in the modern, hyper-competitive economy.
The work's special feature lies in its didactic, applied approach. The content is structured logically, moving from general economic principles to specific mathematical frameworks before analyzing extensive real-world case studies (e.g., Singapore's ERP, the WeWork model, the T-Mobile 'Un-carrier' disruption). Each chapter includes robust Discussion Questions and Quantitative Exercises designed for both classroom use and self-study, allowing readers to apply the complex models directly. The extensive use of mathematical notation (integrals, optimization functions, game-theoretic equations) ensures academic rigor while supporting practical application.
Integrates advanced mathematical modeling, such as GSP/FPA Auctions, Reinforcement Learning, with applied case studies Focuses on emerging paradigms like token-based pricing in AIaaS and retail media networks Emphasizes causal inference, incrementality testing, and the economics of privacy in the digital era
Autor*in
Michael Z.F. Li
Themen in »Dynamic Pricing: Economics, Algorithms and Market Design«
Bidirectional Revenue Management in Networks Economics of AI-as-a-Service Advanced Auction Mechanism Design Multi-Stream Revenue Optimization Modern Pricing Strategy Algorithmic, Data-driven Optimization of Pricing