Coordination in sharing economy: a study of ride-hailing platforms

Abstract

Recent years have witnessed an emergence of sharing economy, defined as an economic system in which assets or services are shared between private individuals. Ride-hailing has emerged as a key area of sharing based business models as cars are resources with high value and low utilization. Further, technological advances like Global Positioning System (GPS), and increasing penetration of Internet connected smartphones have reduced information search costs for coordinating market based transactions in ridehailing. These changes have led to evolution of ride-hailing from a traditional decentralized model in which taxis operated independently to organizations owning and managing the fleet to multi-sided platforms sourcing rides for matching supply and demand. Coordination is central to understand the shift from the decentralized model to the centralized model of ride-hailing. In the centralized model of ride-hailing, the ride-sourcing platforms centrally coordinate the operations of ride-hailing and unlock value through matching demand and supply. Quantifying the value of coordination provides a decision metric for the key stakeholders in ride-hailing. The value of coordination in ride-hailing platforms has not received due importance in the existing operations and supply chain literature, which focuses on the product-based firms organized as hierarchies while ridehailing platforms source rides as a service in a market-based organizational structure. Through this research, we quantify the value of coordination provided by the ride-hailing platforms to the primary stakeholders like drivers and customers. We evaluate the impact of change in the levels of demand and supply, situational contexts like spatial and temporal distribution of demand, characteristics of taxi drivers and customers, and network characteristics like topography on the value of coordination. We build an agent-based network model for our analysis with drivers and customers as agents operating on the road network with separate decision rules for matching for each ride-hailing model. Our analysis offers insights for the ride-sourcing platforms regarding market entry/exit decisions, operational decisions for an existing market, and to the drivers and customers on the efficacy of centralized ride-hailing in different contexts. An understanding of the value generated through the centralized ride-hailing can also be helpful for policymakers working in the area of urban mobility.