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- ACKNOWLEDGEMENTS
| Extracting Airline and Passenger Behavior from Online Distribution Channels: Applications using Online Pricing and Seat Map Data
A Dissertation Presented to The Academic Faculty by
Stacey M. Mumbower In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the School of Civil and Environmental Engineering Georgia Institute of Technology August, 2013 Copyright © Stacey M. Mumbower 2013 Extracting Airline and Passenger Behavior from Online Distribution Channels: Applications using Online Pricing and Seat Map Data
ACKNOWLEDGEMENTSThe five years I spent in graduate school at Georgia Tech were amazing. I’ve had the privilege of working with many great people, and I am extremely grateful to them all! First, I would like to acknowledge my doctoral advisor, Dr. Laurie Garrow, who gave me leeway to explore my interest in statistics by supporting my decision to pursue a Master’s in statistics while also working towards a doctorate. My research has greatly benefited from her input, ideas and suggestions. I truly cannot thank her enough. I would also like to thank my Ph.D. committee members for providing helpful feedback along the way: Dr. Matthew Higgins for his help with endogeneity, Dr. John Leonard for his involvement with my early work in online pricing, Dr. Jeffrey Newman for his assistance optimizing airline seat fees, and Dr. Mark Ferguson for his ideas and recommendations with respect to revenue management. I am grateful and honored to have received research and tuition funding from several different sources. I received an Airport Cooperative Research Program (ACRP) Graduate Research Award in my first year at Georgia Tech, which led to my first publication in aviation. I’d like to thank ACRP program mentors John Fischer of Congressional Research Service and Richard Golaszewski of GRA, Inc., along with program officers Lawrence Goldstein and Christine Gerencher. I am also grateful to have received a three year fellowship from the National Science Foundation’s Graduate Research Fellowship Program, and to have received tuition and travel scholarships from the Dwight D. Eisenhower Graduate Transportation Fellowship Program. I would like to extend a special thanks to the students in Dr. Garrow’s research group. I would particularly like to thank Brittany Luken for her helpful ideas in our brainstorming lunches, for the many discussions we had about statistical methods, and for making school fun. I would also like to thank Susan Hotle who was always happy to help with proofreading and Stata® codes. I’d also like to thank Gregory Macfarlane for his enthusiasm in discussing econometrics with me, especially the topic of endogeneity. I am grateful to the many people who aided in collecting and compiling the large datasets needed for this dissertation. Thanks to Andres Nagel for his patience in programming for a project that took much longer than originally anticipated. I am appreciative of support provided by Georgia Tech’s IT staff. I’d also like to thank Lauren Bankston and Paul Campbell of QL2® Software for providing data, along with Angshuman Guin, Dr. John Leonard, and Shawn Pope for help with data compilation. Working at the Georgia Department of Transportation (GDOT) is what inspired me to pursue a degree in transportation engineering. I would like to thank my former supervisors at GDOT, Paul Tanner and Tim Christian, for their support along the way. A special thanks goes to all of my undergraduate professors in Valdosta State University’s Math department, especially Dr. Andreas Lazari, Dr. Denise Reid, Dr. Charles Kicey, and Dr. Ashok Kumar. They inspired me more than they will ever know. I would like to thank my family for always being supportive and for their interest in hearing about my progress: my father and mother, Lamar and Linda Pittman; my sister, Lindsey Blakeley; my grandmother, Lilly Carter Moore. Lastly, I would like to acknowledge my wonderful husband, Lyndsey, who supported and encouraged me every step along the way. Thank you for everything! TABLE OF CONTENTS Page
ACKNOWLEDGEMENTS 3 LIST OF TABLES 7 LIST OF FIGURES 8 LIST OF SYMBOLS AND ABBREVIATIONS 9 SUMMARY 10 CHAPTER 1: INTRODUCTION 12 1.1. Background and Motivation 12 1.2. Research Objectives 15 1.3. Major Contributions 17 1.4. Dissertation Structure 19 1.5. References 21 CHAPTER 2: Competitive Airline Pricing Policies 23 2.1. Abstract 23 2.2. Background 23 2.3. Price Dispersion Literature 25 2.4. Methodology 31 2.4.1. Data 31 2.4.2. Analysis of Data 34 2.5. Case Studies 38 2.5.1. The Case of Advance Purchase Restrictions 41 2.5.2. The Case of Business vs. Leisure Markets 43 2.5.3. The Case of Codeshare Markets 48 2.5.4. The Case of Monopoly Markets 50 2.5.5. The Case of Competitive Markets with Two Low Cost Carriers 55 2.6. Implications for Public Policy 57 2.7. Future Research 58 2.8. References 59 CHAPTER 3: Product Debundling 61 3.1. Abstract 61 3.2. Introduction 62 3.3. Methodology 64 3.4. U.S. Airline Market Characteristics 66 3.5. Rapid Debundling 71 3.5.1. Ticket Exchange Fees 73 3.5.2. Baggage Fees 76 3.5.3. Seat Fees 81 3.6. Discussion of Policy and Customer Service Implications 84 3.6.1. Enhancing Customer Protections 85 3.6.2. Airport and Airway Trust Fund 88 3.6.3. Integration across Airline Systems 90 3.7. Looking Ahead 92 3.8. Summary 96 3.9. References 97 CHAPTER 4: Premium Coach Seat Purchasing Behavior 100 4.1. Abstract 100 4.2. Introduction 101 4.3. Premium Seat Fees 105 4.3.1. The Airline Perspective 106 4.3.2. The Customer Perspective 108 4.4. Data 111 4.4.1. Overview 111 4.4.2. Selection Bias 118 4.5. Methodology 121 4.5.1. Seat Availability Variables 123 4.5.2. Flight Price Variables 125 4.5.3. Group Booking Variables 127 4.6. Model Results 127 4.6.1. Seat Availabilities 128 4.6.2. Premium Seat Fees 129 4.6.3. Nonstop Flight Characteristics 133 4.6.4. Passenger Characteristics 134 4.6.5. Prediction Accuracy 135 4.7. Policy Analysis 137 4.7.1. Optimizing Static Seat Fees 137 4.7.2. Dynamically Pricing Seat Fees 138 4.7.3. Influence of Seat Map Displays that Block Seats 139 4.8. Discussion 141 4.9. Conclusion 143 4.10. References 145 CHAPTER 5: Review of Price Endogeneity 149 5.1. Abstract 149 5.2. Background 150 5.2.1. Causes of Endogeneity 150 5.2.2. Endogeneity Bias 151 5.2.2.1. Evidence of Endogeneity Bias in Air Travel Demand Literature 152 5.2.2.2. Evidence of Endogeneity Bias in Other Travel Demand Literature 153 5.2.2.3. Evidence of Endogeneity Bias in Other Industry Demand Literature 154 5.3. Methods to Correct for Price Endogeneity 154 5.4. The Search for Instrumental Variables 156 5.4.1. Cost-Shifting Variables as Instruments 156 5.4.2. Hausman-Type Price Instruments 157 5.4.3. Measures of Competition and Market Power as Instruments 160 5.4.4. Non-Price Product Characteristics of Other Products as Instruments 161 5.4.5. Other Types of Instruments 162 5.5. Tests for Instruments 162 5.6. References 164 CHAPTER 6: Flight-Level Daily Demand Models with Correction for Price Endogeneity 167 6.1. Abstract 167 6.2. Background 168 6.2.1. Demand Forecasting 169 6.2.2. Price Elasticity of Demand 173 6.3. Description of Data 175 6.3.1. Selection of Markets 175 6.4. Descriptive Statistics 178 6.4.1. Correlation Between Demand, Prices, and Advance Booking 178 6.4.2. Correlation Between Demand, Prices, and Departure Day of Week 180 6.4.3. Correlation Between Demand, Prices, and Departure Time of Day 180 6.4.4. Correlation Between Demand, Prices, and Booking Day of Week 182 6.4.5. Promotions, Sales, and Holidays 182 6.5. Methodology and Results 184 6.5.1. Average Price Elasticities for Corrected and Uncorrected Models 187 6.5.2. Price Elasticities as a Function of Advance Booking 188 6.6. Conclusions and Future Research Directions 188 6.7. References 190 CHAPTER 7: Conclusions and Future Research Directions 192 7.1. Introduction 192 7.2. Major Conclusions and Directions for Future Research 193 7.2.1. Competitive Airline Pricing Policies 193 7.2.2. Product Debundling 194 7.2.3. Premium Coach Seat Purchasing Behavior 195 7.2.4. Flight-Level Demand Models with Correction for Price Endogeneity 196 7.3. Concluding Thoughts 198 Appendix A: Online Pricing Database 200 A.1. Abstract 200 A.2. Introduction 201 A.3. Description of Datasets 203 A.3.1. Data Fields 203 A.3.2. Market Selection and Descriptive Statistics 209 A.4. Additional Data Details 212 A.4.1. Overview of the Data Collection Process 212 A.4.2. Limitations 214 A.4.2.1. Completeness of Data 214 A.5. Conclusions 215 A.6. References 217 Directory: bitstream -> handle -> 1853 handle -> The Economics of Technology Sharing: Open Source and Beyond Josh Lerner and Jean Tirole handle -> The Rise of Digital Curation and Cyberinfrastructure: From Experimentation to Implementation, and Maybe Integration handle -> Mobile augmented reality applications for library services handle -> Libraries, Archives, and Museums as Epistemic Infrastructure1 Download 1.47 Mb. Share with your friends:
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