Pricing and Revenue Optimization

Cover
Contents
Preface to the Second Edition
Chapter 1 Background
	1.1 Historical Background and Context
	1.2 The Financial Impact of Pricing and Revenue Optimization
	1.3 Organization of the Book
	1.4 Further Reading
Chapter 2 Introduction to Pricing and Revenue Optimization
	2.1 The Challenges of Pricing
	2.2 Traditional Approaches to Pricing
	2.3 The Scope of Pricing and Revenue Optimization
	2.4 The Pricing and Revenue Optimization Process
	2.5 Summary
	2.6 Further Reading
	2.7 Exercise
Chapter 3 Models of Demand
	3.1 The Price-Response Function
	3.2 Measures of Price Sensitivity
	3.3 Common Price-Response Functions
	3.4 Summary
	3.5 Further Reading
	3.6 Exercise
Chapter 4 Estimating Price Response
	4.1 Data Sources for Price-Response Estimation
	4.2 Price-Response Estimation Using Historical Data
	4.3 The Estimation Process
	4.4 Challenges in Estimation
	4.5 Updating the Estimates
	4.6 Data-Free Approaches to Estimation
	4.7 Summary
	4.8 Further Reading
	4.9 Exercises
Chapter 5 Optimization
	5.1 Elements of Contribution
	5.2 The Basic Price Optimization Problem
	5.3 Existence and Uniqueness of Optimal Prices
	5.4 Optimization with Multiple Prices
	5.5 A Data-Driven Approach to Price Optimization
	5.6 Competitive Response and Optimization
	5.7 Optimization with Multiple Objective Functions
	5.8 Summary
	5.9 Further Reading
	5.10 Exercises
Chapter 6 Price Differentiation
	6.1 The Economics of Price Differentiation
	6.2 Limits to Price Differentiation
	6.3 Tactics for Price Differentiation
	6.4 Calculating Differentiated Prices
	6.5 Price Differentiation and Consumer Welfare
	6.6 Nonlinear Pricing
	6.7 Summary
	6.8 Further Reading
	6.9 Exercises
Chapter 7 Pricing with Constrained Supply
	7.1 The Nature of Supply Constraints
	7.2 Optimal Pricing with a Supply Constraint
	7.3 Opportunity Cost
	7.4 Market Segmentation and Supply Constraints
	7.5 Variable Pricing
	7.6 Variable Pricing in Action
	7.7 Summary
	7.8 Further Reading
	7.9 Exercises
Chapter 8 Revenue Management
	8.1 History
	8.2 Levels of Revenue Management
	8.3 Revenue Management Strategy
	8.4 The System Context
	8.5 Booking Control
	8.6 Tactical Revenue Management
	8.7 Revenue Management Metrics
	8.8 Incremental Costs and Ancillary Revenue in Revenue Management
	8.9 Revenue Management in Action
	8.10 Summary
	8.11 Further Reading
	8.12 Exercise
Chapter 9 Capacity Allocation
	9.1 The Two-Class Problems
	9.2 Capacity Allocation with Multiple Fare Classes
	9.3 Capacity Allocation with Dependent Demands
	9.4 A Data-Driven Approach to Capacity Control
	9.5 Capacity Allocation in Action
	9.6 Measuring Capacity Allocation Effectiveness
	9.7 Summary
	9.8 Further Reading
	9.9 Exercises
Chapter 10 Network Management
	10.1 When Is Network Management Applicable?
	10.2 A Linear Programming Approach
	10.3 Virtual Nesting*
	10.4 Network Bid Pricing
	10.5 Network Management in Action
	10.6 Summary
	10.7 Further Reading
	10.8 Exercises
Chapter 11 Overbooking
	11.1 Background
	11.2 Approaches to Overbooking
	11.3 A Deterministic Heuristic
	11.4 Risk-Based Policies
	11.5 Service-Level Policies
	11.6 Hybrid Policies
	11.7 Extensions
	11.8 Measuring and Managing Overbooking
	11.9 Alternatives to Overbooking
	11.10 Summary
	11.11 Further Reading
	11.12 Exercises
Chapter 12 Markdown Management
	12.1 Background
	12.2 Markdown Optimization
	12.3 Estimating Markdown Sensitivity
	12.4 Strategic Customers and Markdown Management
	12.5 Markdown Management in Action
	12.6 Summary
	12.7 Further Reading
	12.8 Exercises
Chapter 13 Customized Pricing
	13.1 Background and Business Setting
	13.2 Calculating Optimal Customized Prices
	13.3 Bid Response
	13.4 Extensions and Variations
	13.5 Customized Pricing in Action
	13.6 Summary
	13.7 Further Reading
	13.8 Exercises
Chapter 14 Behavioral Economics and Pricing
	14.1 Violations of the Law of Demand
	14.2 Price Presentation and Framing
	14.3 Fairness
	14.4 Implications for Pricing and Revenue Optimization
	14.5 Summary
	14.6 Further Reading
	14.7 Exercises
Appendix A: Optimization
	A.1 Continuous Optimization
	A.2 Linear Programming
	A.3 Duality and Complementary Slackness
	A.4 Discrete Optimization
	A.5 Reinforcement Learning and Bandit Approaches
	A.6 Further Reading
Appendix B: Probability
	B.1 Probability Distributions
	B.2 Continuous Distributions
	B.3 Discrete Distributions
	B.4 Sample Statistics
References
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	X
	Y
	Z