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

Auteur

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.

Contenu
TABLE OF CONTENTS
Section 1 Impact of Sharing Economy• Chapter 1 Peer-to-Peer Product Sharing: Implications for Ownership, Usage, andSocial Welfareo Saif Benjaafar (University of Minnesota - Industrial & System Engineering)o Guangwen Kong (University of Minnesota - Industrial & SystemEngineering)o Xiang Li (University of Minnesota - Industrial & System Engineering)o Costas Courcoubetis (Singapore University of Technology and Design(SUTD))• Chapter 2 Collaborative Consumption: Strategic and Economic Implications ofProduct Sharingo Baojun Jiang (Washington University in Saint Louis - John M. Olin BusinessSchool)o Lin Tian (Fudan University - School of Management)• Chapter 3 The Sharing Newsboyso Ming Hu (University of Toronto - Rotman School of Management)
Section 2 Intermediary Role of a Sharing Platform• Chapter 4 The Role of Surge Pricing on a Service Platform with Self-SchedulingCapacityo Gerard P. Cachon (University of Pennsylvania - Wharton School)o Kaitlin M. Daniels (University of Pennsylvania - Wharton School)o Ruben Lobel (University of Pennsylvania - Wharton School)• Chapter 5 On-Demand Service Platformso Terry Taylor (U.C. Berkeley - Haas School of Business)• Chapter 6 Managing Congestion in Decentralized Matching Marketso Nick Arnosti (Stanford University - Department of Management Science andEngineering)o Ramesh Johari (Stanford University - Department of Management Scienceand Engineering)o Yash Kanoria (Columbia University - Columbia Business School)• Chapter 7 Price and Wage Selections for an On-demand Service Platformo Jiaru Bai (University of California, IrvinePaul - Merage School of Business)o Rick So (University of California, Irvine Paul - Merage School of Business)o Christopher S. Tang (University of California, Los Angeles)• Chapter 8 Take-Rate Crowdsourcing Contractso Ming Hu (University of Toronto - Rotman School of Management)o Yun Zhou (University of Toronto - Rotman School of Management)• Chapter 9 Dynamic Type Matchingo Ming Hu (University of Toronto - Rotman School of Management)o Yun Zhou (University of Toronto - Rotman School of Management
Section 3 Crowdsourcing Management (Group Buying, Crowdfunding, CrowdsourcingContest)• Chapter 10 Simultaneous vs. Sequential Group-Buying Mechanismso Ming Hu (University of Toronto - Rotman School of Management)o Mengze Shi (University of Toronto - Rotman School of Management)o Jiahua Wu (Imperial College London - Imperial College Business School)• Chapter 11 Operational Advantages and Optimal Design of Threshold DiscountingOfferso Simone Marinesi (University of Pennsylvania - Wharton School)o Karan Girotra (INSEAD)o Serguei Netessine (INSEAD)• Chapter 12 Product and Pricing Decisions in Crowdfundingo Ming Hu (University of Toronto - Rotman School of Management)o Xi Li (University of Toronto - Rotman School of Management)o Mengze Shi (University of Toronto - Rotman School of Management)• Chapter 13 A Dynamic Model of Crowdfundingo Saeed Alaei (Google, Inc.)o Azarakhsh Malekian (University of Toronto - Rotman School ofManagement)o Mohamed Mostagir (University of Michigan, Stephen M. Ross School ofBusiness)• Chapter 14 Dynamic Stimulus in Crowdfundingo Longyuan Du (University of Toronto - Rotman School of Management)o Ming Hu (University of Toronto - Rotman School of Management)• Chapter 15 Idea Generation and the Quality of the Best Ideao Karan Girotra (INSEAD)<div...