Symposium on the Sharing Economy


Research Workshop Session IV: On-Demand Platforms and Social Media

On-Demand Service Platforms

An on-demand service platform connects waiting-time sensitive customers with independent service providers (agents). This presentation reviewed a project that examined how two defining features of an on-demand service platform—congestion-driven delay disutility and agent independence—impact the platform's optimal per-service price and wage. Congestion reduces expected utility for customers and agents, which suggests that the platform respond by decreasing the price (to encourage participation of customers) and increasing the wage (to encourage participation of agents). These intuitive price and wage prescriptions are valid in a benchmark setting without uncertainty in the customers' valuation or the agents' opportunity costs. However, uncertainty in either dimension can reverse the prescriptions: Congestion increases the optimal price when customer valuation uncertainty is moderate. Congestion decreases the optimal wage when agent opportunity cost uncertainty is high and expected opportunity cost is moderate. Under agent opportunity cost uncertainty, agent independence decreases the price. Under customer valuation uncertainty, agent independence increases the price if and only if valuation uncertainty is sufficiently high.

Terry Taylor is the Milton W. Terrill Associate Professor at U.C. Berkeley’s Haas School of Business. Prior to his position at Berkeley, Taylor was a professor at Columbia University’s Graduate School of Business and a consultant for McKinsey & Company. His current research focuses on social responsibility in operations. He is an associate editor for Management ScienceManufacturing and Service Operations Management, and Operations Research, and a departmental editor for Production and Operations Management.

Leveraging Socially Networked Mobile ICT Platforms for the Last Mile Delivery Problem

Dr. Timothy M. Smith is director of the NorthStar Initiative for Sustainable Enterprise at the University of Minnesota's Institute on the Environment and an associate professor of environmental sciences, policy and management, and bioproducts and biosystems engineering at the university. His work focuses on policy and market adoption of technologies that enhance environmental performance, public and private governance of sustainability, and sustainability systems modeling in decision making.

Dr. Smith has held the rotating chair in sustainable entrepreneurship at Wageningen University, Netherlands, served on the faculty at INCAE Business School in Costa Rica, and taught in marketing and logistics management at the Carlson School of Management and in the College of Continuing Education at UMN. He is a former AT&T Industrial Ecology Fellow and has advised the Environmental Protection Agency, the General Services Administration, the National Research Council's Committee on Certification of Sustainable Products and Services, and numerous companies and organizations on supply chain sustainability and product-based policies.

Repeated Interactions vs. Social Ties: Quantifying the Economic Value of Trust, Forgiveness, and Reputation Using a Field Experiment

The growing importance of online social networks provides fertile ground for researchers seeking to gain a deeper understanding of fundamental constructs of human behavior, such as trust, forgiveness, and their linkage to social ties. Through a field experiment that uses data from the Facebook API to measure social ties that connect our subjects, the research team separated forward-looking instrumental trust from static intrinsic trust and showed that the level of instrumental trust and forgiveness, and the effect of forgiveness on deterring future defections, crucially depend on the strength of social ties. The team found that the level of trust under social repeated play is greater than the level of trust under anonymous repeated play, which in turn is greater than the level of trust under anonymous one shot games. The team also uncovered forgiveness as a key mechanism that facilitates the cooperative equilibrium being more stable in the presence of social ties: If the trading partners are socially connected, the equilibrium is more likely to return to the original cooperative one after small disturbances.

Dr. Ravi Bapna is the Curtis L. Carlson Chair in Business Analytics and Information Systems, the program director for the MS-Business Analytics program, and the academic director of the Carlson Analytics Lab. In addition, Bapna is the founding academic co-director of University of Minnesota's Social Media and Business Analytics Collaborative (SOBACO), an interdisciplinary research center that views the billion-strong, online social-graph as a giant global laboratory, a sandbox to gain a deeper causal understanding of how consumers, firms, industries, and societies are being reshaped by the social media and big-data revolution.

Dynamic Type Matching

This presentation considered an intermediary's problem of dynamically matching demand and supply of heterogeneous types in a periodic-review fashion. More specifically, there are two disjoint sets of demand and supply types. There is a reward associated with each possible matching of a demand type and a supply type. In each period, demand and supply of various types arrive in random quantities. The platform's problem is to decide on the optimal matching policy to maximize the total discounted rewards minus costs, given that unmatched demand and supply will incur waiting or holding costs, and will be carried over to the next period with abandonments. This problem includes many classic problems in operations and economics as special cases. For this general dynamic matching problem, the researchers obtained a set of distribution-free structural results on the optimal and heuristic matching policies.

Ming Hu is an associate professor of operations management at Rotman School of Management, University of Toronto. 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. His research explores strategic interactions among firms and between firms and consumers, in the context of revenue management, supply chain management, and service operations management. His research has been published in leading journals of operations management, including 14 papers in UT Dallas ranking’s 24 leading journals in business disciplines. His research has been featured the Financial Times (UK), Toronto Star (Canada) and Inc. Magazine (U.S.).

He has given more than 40 research seminars at prominent universities including Stanford and MIT. He has consulted for Siemens and Hewlett Packard and holds six patents from his consulting works. He is the recipient of the Innovation Research Award by Hewlett-Packard Labs (2008-2010); Junior Faculty Interest Group Paper Competition, Honorable Mention by INFORMS (2014); Annual Conference Best Paper Award, First Prize by Chinese Scholars Association for Management Science and Engineering (2015); and Roger Martin Excellence in Research Award by Rotman School of Management, University of Toronto (2015). Most recently, he has focused on operations management in the context of social buying, crowdfunding, crowdsourcing, and two-sided markets, with the goal of exploiting operational-level decision making to the benefit of society.