Hu Sharing Economy

Making Supply Meet Demand
1. Auflage 2019
ISBN: 978-3-030-01863-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 6, 536 Seiten

Reihe: Springer Series in Supply Chain Management

This edited book examines the challenges and opportunities arising from today's sharing economy from an operations management perspective.  Individual chapter authors present state-of-the-art research that examines the general impact of sharing economy on production and consumption; the intermediary role of a sharing platform; crowdsourcing management; and context-based operational problems.Sharing economy refers to a market model that enables and facilitates the sharing of access to goods and services. For example, Uber allows riders to share a car. Airbnb allows homeowners to share their extra rooms with renters. Groupon crowdsources demands, enabling customers to share the benefit of discounted goods and services, whereas Kickstarter crowdsources funds, enabling backers to fund a project jointly. Unlike the classic supply chain settings in which a firm makes inventory and supply decisions, in sharing economy, supply is crowdsourced and can be modulated by a platform. The matching-supply-with-demand process in a sharing economy requires novel perspectives and tools to address challenges and identify opportunities.The book is comprised of 20 chapters that are divided into four parts.  The first part explores the general impact of sharing economy on the production, consumption, and society.  The second part explores the intermediary role of a sharing platform that matches crowdsourced supply with demand.  The third part investigates the crowdsourcing management on a sharing platform, and the fourth part is dedicated to context-based operational problems of popular sharing economy applications.
'While sharing economy is becoming omnipresence, the operations management (OM) research community has begun to explore and examine different business models in the transportation, healthcare, financial, accommodation, and sourcing sectors. This book presents a collection of the state-of-the-art research work conducted by a group of world-leading OM researchers in this area. Not only does this book cover a wide range of business models arising from the sharing economy, but it also showcases different modeling frameworks and research methods that cannot be missed. Ultimately, this book is a tour de force - informative and insightful!'
Christopher S. Tang
Distinguished Professor and Edward Carter Chair in Business Administration
UCLA Anderson School of Management

Ming Hu is a Professor of Operations Management at Rotman School of Management, University of Toronto and one of the 2018 Poets & Quants Best 40 Under 40 MBA Professors. His research has been featured in media such as Financial Times. Most recently, he focuses on operations management in the context of sharing economy, social buying, crowdfunding, crowdsourcing, and two-sided markets, with the goal to exploit operational decisions to the benefit of the society. He is the recipient of Wickham Skinner Early-Career Research Accomplishments Award by POM Society (2016) and Best Operations Management Paper in Management Science Award by INFORMS (2017). He currently serves as the editor-in-chief of Naval Research Logistics, co-editor of a special issue of Manufacturing & Service Operations Management on sharing economy and innovative marketplaces, and associate editor of Operations Research and Manufacturing & Service Operations Management, and senior editor of Production and Operations Management. He received a master's degree in Applied Mathematics from Brown University in 2003, and a Ph.D. in Operations Research from Columbia University in 2009.

Autoren/Hrsg.

Hu, Ming

Inhaltsverzeichnis

1;Preface;5
2;Acknowledgments;6
3;Contents;7
4;Contributors;16
5;1 Introduction;19
5.1;1.1 Overall Structure;19
5.2;1.2 Chapter Highlights;20
5.2.1;1.2.1 Part I: Impact of Sharing Economy;20
5.2.1.1;1.2.1.1 Economic Impact;20
5.2.1.2;1.2.1.2 Operational Opportunity and Challenge;21
5.2.2;1.2.2 Part II: Intermediary Role of a Sharing Platform;21
5.2.2.1;1.2.2.1 Intermediation via Pricing and Matching;21
5.2.2.2;1.2.2.2 Intermediation via Information and Payment;22
5.2.2.3;1.2.2.3 Intermediation in the Presence of Self-Scheduling Suppliers;23
5.2.3;1.2.3 Part III: Crowdsourcing Management;24
5.2.3.1;1.2.3.1 Group Buying and Crowdfunding;24
5.2.3.2;1.2.3.2 Crowdsourcing Contest;24
5.2.4;1.2.4 Part IV: Context-Based Operational Problems in Sharing Economy;25
5.2.4.1;1.2.4.1 Bike Sharing;25
5.2.4.2;1.2.4.2 Vehicle Sharing;25
5.2.4.3;1.2.4.3 Short-Term Rental;26
5.2.4.4;1.2.4.4 Online Advertising;26
5.3;References;26
6;Part I Impact of Sharing Economy;27
6.1;2 Peer-to-Peer Product Sharing;28
6.1.1;2.1 Introduction;29
6.1.2;2.2 Literature Review;32
6.1.3;2.3 Model Description;34
6.1.3.1;2.3.1 Matching Supply with Demand;36
6.1.4;2.4 Equilibrium Analysis;38
6.1.4.1;2.4.1 Impact of Collaborative Consumption on Ownership and Usage;39
6.1.4.2;2.4.2 Impact of Collaborative Consumption on Consumers;42
6.1.5;2.5 The Platform's Problem;43
6.1.5.1;2.5.1 The For-Profit Platform;44
6.1.5.2;2.5.2 The Not-for-Profit Platform;46
6.1.5.3;2.5.3 Systems with Negative Externalities;48
6.1.5.4;2.5.4 The Impact of Extra Wear and Tear and Inconvenience Costs;50
6.1.6;2.6 Concluding Comments;50
6.1.7;References;52
6.2;3 The Strategic and Economic Implications of Consumer-to-Consumer Product Sharing;54
6.2.1;3.1 Introduction;54
6.2.2;3.2 Modeling Framework;57
6.2.3;3.3 Effects of Sharing on Firm's Pricing Strategy, Profit, and Consumer Surplus;60
6.2.4;3.4 Effects of Sharing on Product Quality and Distribution Channel;65
6.2.4.1;3.4.1 Effects of Sharing on Product Quality;65
6.2.4.2;3.4.2 Effects of Sharing on Distribution Channel;66
6.2.5;3.5 Conclusions and Discussions;68
6.2.6;References;70
6.3;4 Operational Factors in the Sharing Economy: A Framework;72
6.3.1;4.1 Introduction;72
6.3.2;4.2 The Framework;73
6.3.3;4.3 Examples;77
6.3.3.1;4.3.1 Ride Sharing;78
6.3.3.2;4.3.2 Group Buying;81
6.3.4;4.4 Concluding Remarks;83
6.3.5;References;85
6.4;5 Ride Sharing;89
6.4.1;5.1 Introduction;89
6.4.2;5.2 Anatomy of a Modern Ridesharing Platform;91
6.4.2.1;5.2.1 Timescales;91
6.4.2.2;5.2.2 Strategic Choices;92
6.4.2.3;5.2.3 Operation and Market Design;93
6.4.3;5.3 A Modeling Framework for Ridesharing Platforms;93
6.4.3.1;5.3.1 Modeling Stochastic Dynamics of the Platform;94
6.4.3.2;5.3.2 Platform Controls;97
6.4.3.3;5.3.3 Platform Objectives;99
6.4.3.4;5.3.4 Local Controls and Closed Queueing Models;100
6.4.3.5;5.3.5 Modeling Endogenous Entry of Drivers;102
6.4.4;5.4 Analyzing the Model: Key Findings;103
6.4.4.1;5.4.1 Fast-Timescale Control of Platform Dynamics;104
6.4.4.2;5.4.2 The Slow Timescale: Pricing and Driver Entry;105
6.4.5;5.5 Related Literature;108
6.4.6;5.6 Conclusion;111
6.4.7;References;112
7;Part II Intermediary Role of a Sharing Platform;114
7.1;6 The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity;115
7.1.1;6.1 Introduction;116
7.1.2;6.2 Literature Review;117
7.1.3;6.3 Model;119
7.1.4;6.4 Profitability of Commission Contract;122
7.1.5;6.5 Impact of Dynamic Prices on Consumers;124
7.1.6;6.6 Conclusion;125
7.1.7;References;126
7.2;7 Time-Based Payout Ratio for Coordinating Supply and Demand on an On-Demand Service Platform;128
7.2.1;7.1 Introduction;129
7.2.2;7.2 Literature Review;130
7.2.3;7.3 A Model of Wait-Time Sensitive Demand and Earnings Sensitive Supply;132
7.2.3.1;7.3.1 Customer Request Rate ? and Price Rate p;133
7.2.3.2;7.3.2 Number of Participating Providers k and Wage Rate w;133
7.2.3.3;7.3.3 Problem Formulation;135
7.2.4;7.4 The Base Model;135
7.2.4.1;7.4.1 Special Case 1: When the Payout Ratio w/p Is Fixed;137
7.2.4.2;7.4.2 Special Case 2: When the Service Level Is Exogenously Given;138
7.2.5;7.5 Numerical Illustrations Based on Didi Data;140
7.2.5.1;7.5.1 Background Information;140
7.2.5.2;7.5.2 Number of Rides and Drivers Across Different Hours;141
7.2.5.3;7.5.3 Travel Distance and Travel Speed;141
7.2.5.4;7.5.4 Pricing and Wage Rates;142
7.2.5.5;7.5.5 Strategic Factors and Their Implications;143
7.2.5.6;7.5.6 Numerical Examples for Illustrative Purposes;143
7.2.6;7.6 Conclusion;147
7.2.7;References;148
7.3;8 Pricing and Matching in the Sharing Economy;150
7.3.1;8.1 Introduction;151
7.3.1.1;8.1.1 Two-Sided Pricing;151
7.3.1.2;8.1.2 Two-Sided Matching;151
7.3.1.3;8.1.3 Pricing and Matching Under Strategic Behavior;153
7.3.2;8.2 Two-Sided Pricing and Fixed Commission;154
7.3.2.1;8.2.1 The Price and Wage Optimization Problem;154
7.3.2.2;8.2.2 The Fixed Commission Contract;156
7.3.2.3;8.2.3 Numerical Study;158
7.3.3;8.3 Dynamic Matching with Heterogeneous Types;159
7.3.3.1;8.3.1 Priority Properties of the Optimal Matching Policy;160
7.3.3.1.1;8.3.1.1 Unidirectional Horizontal Types;162
7.3.3.1.2;8.3.1.2 Vertical Types;163
7.3.3.2;8.3.2 Bound and Heuristic;164
7.3.3.2.1;8.3.2.1 Numerical Study;165
7.3.4;8.4 Pricing and Matching with Strategic Suppliers and Customers;166
7.3.4.1;8.4.1 Upper Bound of the Intermediary's Optimal Profit;170
7.3.4.2;8.4.2 A Simple Dynamic Policy: Asymptotic Optimality;171
7.3.4.2.1;8.4.2.1 Optimal Policy in an Auxiliary Setting;171
7.3.4.2.2;8.4.2.2 Waiting Adjusted Fixed Pricing Policy;173
7.3.5;8.5 Conclusion;176
7.3.6;References;176
7.4;9 Large-Scale Service Marketplaces: The Roleof the Moderating Firm;178
7.4.1;9.1 Introduction;178
7.4.2;9.2 Literature Review;181
7.4.3;9.3 Model Formulation;183
7.4.4;9.4 No-Intervention Model;184
7.4.4.1;9.4.1 Characterization of SPNE;186
7.4.5;9.5 Operational Efficiency Model;188
7.4.5.1;9.5.1 Characterization of the Market Equilibrium;191
7.4.5.1.1;9.5.1.1 Buyer's Market;193
7.4.5.1.2;9.5.1.2 Seller's Market;194
7.4.6;9.6 Communication Enabled Model;198
7.4.6.1;9.6.1 Characterization of the (?,?)-Market Equilibrium;199
7.4.7;9.7 A Marketplace with Non-identical Agents;201
7.4.8;9.8 Conclusion;202
7.4.9;References;204
7.5;10 Inducing Exploration in Service Platforms;206
7.5.1;10.1 Introduction;206
7.5.2;10.2 Related Literature;207
7.5.3;10.3 Illustrative Example;210
7.5.4;10.4 Benchmark Model;211
7.5.5;10.5 Inducing Exploration;212
7.5.5.1;10.5.1 Strategic Information Disclosure;215
7.5.5.2;10.5.2 The Value of Information Obfuscation;218
7.5.5.3;10.5.3 Minimizing Regret;219
7.5.5.4;10.5.4 Incentivizing Customers Using Payments;221
7.5.6;10.6 Promising Directions;223
7.5.6.1;10.6.1 Learning in Dynamic Contests;223
7.5.6.2;10.6.2 Dealing with Misinformation;225
7.5.7;10.7 Concluding Remarks;226
7.5.8;References;227
7.6;11 Design of an Aggregated Marketplace Under Congestion Effects: Asymptotic Analysis and Equilibrium Characterization;230
7.6.1;11.1 Introduction;231
7.6.1.1;11.1.1 Background and Motivation;231
7.6.1.2;11.1.2 Overview of Results;233
7.6.1.3;11.1.3 Literature Review;235
7.6.2;11.2 Model;237
7.6.2.1;11.2.1 Description of the Market;237
7.6.2.2;11.2.2 Problems to Address;239
7.6.3;11.3 Asymptotic Analysis of Marketplace Dynamics;240
7.6.3.1;11.3.1 Background: Revenue Maximization for an M/M/1 Monopolistic Supplier;241
7.6.3.2;11.3.2 Setup for Asymptotic Analysis;242
7.6.3.3;11.3.3 Transient Dynamics via a Fluid Model Analysis;242
7.6.3.4;11.3.4 State-Space Collapse and the Aggregate Marketplace Behavior;243
7.6.3.5;11.3.5 Limit Model and Discussion;244
7.6.3.6;11.3.6 A Numerical Example;245
7.6.4;11.4 Competitive Behavior and Market Efficiency;247
7.6.4.1;11.4.1 Suppliers' First-Order Payoffs and the Capacity Game;247
7.6.4.2;11.4.2 Suppliers' Second-Order Payoffsand the Pricing Game;248
7.6.4.3;11.4.3 Centralized System Performance;249
7.6.4.4;11.4.4 Competitive Equilibrium;250
7.6.4.4.1;11.4.4.1 Homogeneous Service Rate Case;250
7.6.4.4.2;11.4.4.2 Heterogeneous Service Rate Case;251
7.6.4.4.3;11.4.4.3 Numerical Results;252
7.6.4.4.4;11.4.4.4 A Remark on the Suppliers' Participation;255
7.6.4.5;11.4.5 Coordination Scheme;256
7.6.4.5.1;11.4.5.1 Sufficient Condition for Coordination;256
7.6.4.5.2;11.4.5.2 ``Compensation-While-Idling'' Mechanism That Achieves Coordination;257
7.6.4.6;11.4.6 Simulation Results;258
7.6.5;11.5 Conclusions;260
7.6.6;References;261
7.7;12 Operations in the On-Demand Economy: Staffing Services with Self-Scheduling Capacity;262
7.7.1;12.1 Introduction;263
7.7.2;12.2 Model;266
7.7.3;12.3 Analysis;269
7.7.3.1;12.3.1 The Cost of Self Scheduling;269
7.7.3.2;12.3.2 Earnings Constraint and Agent Flexibility;272
7.7.3.3;12.3.3 Time-Varying Demand;272
7.7.3.4;12.3.4 The Benefit of Flexible Capacity;273
7.7.4;12.4 Variants of the Base Model;274
7.7.4.1;12.4.1 Volume-Dependent Compensation Schemes;276
7.7.4.2;12.4.2 Price-Dependent Newsvendor;278
7.7.4.3;12.4.3 When Maintaining a Larger Pool Costs More;280
7.7.4.4;12.4.4 Period-Dependent Threshold Distributions;282
7.7.5;12.5 Concluding Remarks;283
7.7.6;Appendix;285
7.7.6.1;Proof of Theorem 1;285
7.7.6.2;Proof of Lemma 2;285
7.7.6.3;Proof of Lemma 3;286
7.7.6.4;Proof of Theorem 2;288
7.7.6.5;Proof of Theorem 3;288
7.7.6.6;Proof of Lemma 4;290
7.7.7;References;290
7.8;13 On Queues with a Random Capacity: Some Theory, and an Application;292
7.8.1;13.1 Introduction;292
7.8.2;13.2 Theoretical Background: Queues with Uncertain Parameters;294
7.8.2.1;13.2.1 Self-Scheduling Servers: A Binomial Distribution;297
7.8.2.2;13.2.2 What Do the Asymptotic Results Mean?;298
7.8.3;13.3 Self-Scheduling Agents: A Long-Term Staffing Decision;302
7.8.3.1;13.3.1 The Model;302
7.8.3.2;13.3.2 Fluid Formulation;303
7.8.3.3;13.3.3 Optimal Staffing Policy;304
7.8.3.3.1;13.3.3.1 No Self-Scheduling;304
7.8.3.3.2;13.3.3.2 Self-Scheduling Capacity;305
7.8.4;13.4 Short-Term Controls;307
7.8.4.1;13.4.1 Delay Announcements: Performance Impact;308
7.8.4.1.1;13.4.1.1 When Do the Announcements Reduce the Cost of Self-Scheduling?;310
7.8.4.1.2;13.4.1.2 A New Staffing Problem;311
7.8.5;13.5 Joint Control of Compensation and Delay Announcements;312
7.8.6;13.6 Jointly Optimizing Long and Short-Term Controls;315
7.8.6.1;13.6.1 Low Minimum Wage;315
7.8.6.2;13.6.2 High Minimum Wage;316
7.8.7;13.7 Conclusions;316
7.8.8;Technical Appendix;317
7.8.8.1;Proof of Theorem 1;317
7.8.8.1.1;The Overloaded Regime;317
7.8.8.1.2;The Underloaded Regime;322
7.8.8.1.3;The Critically-Loaded Regime;323
7.8.8.2;Proofs of Propositions;324
7.8.9;References;328
8;Part III Crowdsourcing Management;330
8.1;14 Online Group Buying and Crowdfunding: Two Cases of All-or-Nothing Mechanisms;331
8.1.1;14.1 Introduction;331
8.1.2;14.2 Consumer Behavior Under All-or-Nothing Mechanisms;334
8.1.2.1;14.2.1 Empirical Model;335
8.1.2.1.1;14.2.1.1 The Base Model;335
8.1.2.1.2;14.2.1.2 The Extended Model with Lagged Variables;336
8.1.2.2;14.2.2 Results;337
8.1.2.3;14.2.3 Potential Mechanisms Behind Threshold Effects;343
8.1.3;14.3 Coordination Under All-or-Nothing Mechanisms;345
8.1.3.1;14.3.1 Information Disclosure;345
8.1.3.1.1;14.3.1.1 Model Setup;345
8.1.3.1.2;14.3.1.2 Equilibrium Analysis Under Simultaneous Mechanism;347
8.1.3.1.3;14.3.1.3 Equilibrium Analysis Under Sequential Mechanism;349
8.1.3.1.4;14.3.1.4 Mechanism Design: Simultaneous or Sequential?;349
8.1.3.2;14.3.2 Pricing;351
8.1.3.2.1;14.3.2.1 Model Setup;351
8.1.3.2.2;14.3.2.2 Alternative Pricing Policies;352
8.1.3.2.3;14.3.2.3 Optimal Pricing Strategy;354
8.1.4;14.4 Conclusion;356
8.1.5;References;357
8.2;15 Threshold Discounting: Operational Benefits, Potential Drawbacks, and Optimal Design;359
8.2.1;15.1 Introduction;360
8.2.2;15.2 Literature Review;362
8.2.3;15.3 The Model;364
8.2.3.1;15.3.1 Preliminaries;364
8.2.3.2;15.3.2 The Traditional Approach: Seasonal Closure or Regular Discounting;365
8.2.3.3;15.3.3 Threshold Discounting;369
8.2.3.3.1;15.3.3.1 Sequence of Events;369
8.2.3.3.2;15.3.3.2 Customer Continuation Game;370
8.2.3.3.3;15.3.3.3 Optimal Announcement and Equilibrium Outcome;372
8.2.3.4;15.3.4 Comparing Threshold Discounting with the Traditional Approach;373
8.2.3.4.1;15.3.4.1 Responsive Duality;373
8.2.3.4.2;15.3.4.2 Strategic Scarcity Effect;374
8.2.3.4.3;15.3.4.3 A Novel Operational Advantage;375
8.2.3.5;15.3.5 Impact of Strategic Customers on Threshold Discounting Performance;376
8.2.3.6;15.3.6 Mediated Threshold Discounting;378
8.2.3.7;15.3.7 Design Considerations in ThresholdDiscounting Offers;381
8.2.3.7.1;15.3.7.1 Opaque Activation Rule;381
8.2.3.7.2;15.3.7.2 Time When the Outcome of the Deal Is Announced;382
8.2.3.7.3;15.3.7.3 Time Restricted Discounts;384
8.2.3.7.4;15.3.7.4 Focused Threshold Discounting;385
8.2.4;15.4 Discussion;387
8.2.5;References;388
8.3;16 Innovation and Crowdsourcing Contests;390
8.3.1;16.1 Introduction;390
8.3.2;16.2 A General Model Framework for Innovation Contests;393
8.3.3;16.3 A Brief Taxonomy of Contest Literature;399
8.3.4;16.4 Contests with Uncertainty;401
8.3.4.1;16.4.1 Optimal Award Scheme;401
8.3.4.2;16.4.2 Open Innovation and Agents' Incentives;403
8.3.5;16.5 Contests with Heterogenous Agents;406
8.3.5.1;16.5.1 Optimal Award Scheme;407
8.3.5.2;16.5.2 Open Innovation and Agents' Incentives;408
8.3.6;16.6 Conclusion and Future Research;411
8.3.7;Appendix;412
8.3.8;References;416
9;Part IV Context-Based Operational Problems in Sharing Economy;418
9.1;17 Models for Effective Deployment and Redistribution of Shared Bicycles with Location Choices;419
9.1.1;17.1 Introduction;420
9.1.1.1;17.1.1 Review of the Bicycle-Sharing Systems;420
9.1.1.2;17.1.2 Research Issues and Structure of the Chapter;422
9.1.2;17.2 The Stochastic Network Flow Model;423
9.1.2.1;17.2.1 Equilibrium State in Time Invariant System;427
9.1.2.2;17.2.2 Bicycle-Sharing System Design with Location Choice;429
9.1.3;17.3 Bicycle Sharing as Substitute for Train Rides;430
9.1.3.1;17.3.1 Bicycle Deployment and Utilization;431
9.1.3.2;17.3.2 Number of Bicycle Docks Needed;434
9.1.3.3;17.3.3 Effectiveness of Bicycle Redistribution;435
9.1.4;17.4 Case Study on Bicycle Sharing with Location Decisions;437
9.1.5;17.5 Concluding Remarks;442
9.1.6;References;444
9.2;18 Bike Sharing;445
9.2.1;18.1 Introduction;445
9.2.2;18.2 Data and Statistical Challenges;449
9.2.3;18.3 Motorized Rebalancing;452
9.2.3.1;18.3.1 User Dissatisfaction Function;452
9.2.3.2;18.3.2 Optimal Allocation Before the Rush;453
9.2.3.3;18.3.3 Resulting Routing Problems;455
9.2.4;18.4 Allocating Capacity;458
9.2.4.1;18.4.1 Model formulation;459
9.2.4.2;18.4.2 Long-Run Average;460
9.2.4.3;18.4.3 Measuring the Impact;461
9.2.5;18.5 Beyond Motorized Rebalancing;462
9.2.5.1;18.5.1 Incentives;462
9.2.5.2;18.5.2 Valets and Corrals;463
9.2.6;18.6 Expansion Planning;464
9.2.7;18.7 Conclusion;466
9.2.8;References;467
9.3;19 Operations Management of Vehicle Sharing Systems;470
9.3.1;19.1 Introduction;470
9.3.2;19.2 Service Region Design;473
9.3.2.1;19.2.1 Basic Model;473
9.3.2.2;19.2.2 Customer Adoption;475
9.3.2.3;19.2.3 Operational Profit;476
9.3.2.4;19.2.4 Numerical Results;480
9.3.3;19.3 Fleet Sizing;481
9.3.3.1;19.3.1 Two-Stage Stochastic Optimization Model;481
9.3.3.2;19.3.2 Numerical Results;482
9.3.4;19.4 Fleet Repositioning;483
9.3.4.1;19.4.1 Stochastic Dynamic Program Formulation;484
9.3.4.2;19.4.2 The 2-Region System;486
9.3.4.3;19.4.3 The N-Region System;488
9.3.5;19.5 Other Topics;488
9.3.5.1;19.5.1 Dynamic Pricing;490
9.3.5.2;19.5.2 Reservation Management;490
9.3.6;19.6 Discussion;491
9.3.7;References;492
9.4;20 Agent Pricing in the Sharing Economy: Evidence from Airbnb;494
9.4.1;20.1 Introduction;494
9.4.2;20.2 Literature Review and Hypothesis Development;496
9.4.2.1;20.2.1 Literature Review;496
9.4.2.2;20.2.2 Hypotheses Development;498
9.4.3;20.3 Empirical Setting and Data;500
9.4.3.1;20.3.1 Empirical Setting: The Airbnb Platform;500
9.4.3.2;20.3.2 Airbnb Data: Listings and Transactions;500
9.4.4;20.4 Performance of Professional vs. Nonprofessional Hosts: Econometric Specifications and Results;503
9.4.4.1;20.4.1 Daily Revenue;503
9.4.4.2;20.4.2 Occupancy Rate and Average Rent Price;505
9.4.4.3;20.4.3 Exit Probability;507
9.4.5;20.5 Understanding the Differences in Performance;507
9.4.6;20.6 Conclusion;510
9.4.7;References;511
9.5;21 Intermediation in Online Advertising;513
9.5.1;21.1 Introduction;514
9.5.1.1;21.1.1 Main Contributions;515
9.5.1.2;21.1.2 Literature Review;515
9.5.1.2.1;21.1.2.1 Intermediary Problems;516
9.5.1.2.2;21.1.2.2 Online Advertising and Ad Exchanges;516
9.5.1.2.3;21.1.2.3 Mechanism Design with Budget Constraints;517
9.5.2;21.2 Optimal Contracts for Intermediaries in Online Advertising;517
9.5.2.1;21.2.1 Mechanism Design Problem;519
9.5.2.2;21.2.2 Optimal Mechanism Characterization;522
9.5.2.2.1;21.2.2.1 Dual Problem;522
9.5.2.2.2;21.2.2.2 Support Function Characterization;523
9.5.2.2.3;21.2.2.3 Synthesis;524
9.5.2.2.4;21.2.2.4 Optimal Bidding Policy;524
9.5.2.3;21.2.3 Economic Insights;525
9.5.2.3.1;21.2.3.1 Intermediation Profit and the Advertiser Surplus;526
9.5.2.3.2;21.2.3.2 Market Efficiency;526
9.5.3;21.3 Multi-stage Intermediation in Display Advertising;527
9.5.3.1;21.3.1 Equilibrium Characterization;529
9.5.3.2;21.3.2 Economic Insights;531
9.5.4;21.4 Concluding Remarks;535
9.5.5;References;535