Technology Restriction and Demand Shifts in Transportation Dynamics: An Empirical Study

Abstract

A transportation network company (TNC) is an app-based, two-sided platform that matches riders with vehicles via information technology (IT). In 2015, the Shanghai government introduced a policy to restrict taxi drivers’ use of TNC apps during certain hours. We leverage this policy shock and collect comprehensive data on various transportation usages to gauge the economic benefits of information sharing and IT-enabled operations via TNC apps for existing capacity and its subsequent externalities on alternative transportation modes. We identify significant decreases in the operational efficiency of a TNC-enabled taxi fleet during the policy’s enforcement time but a significant increase during some non-enforcement times. Further, the traffic on public transportation via the city’s transportation cards significantly increases after launching the policy during both enforcement and most non-enforcement times. Moreover, the congestion on the surface streets and expressways during the policy enforcement and part of non-enforcement times significantly increase, indicating a spillover to the use of vehicles other than the affected taxis such as private automobiles. Interestingly, our mechanism analysis shows an increased average distance after the restriction, which reveals that information sharing and IT-enabled operations via TNC apps reduce drivers’ search cost, and, thus, enable them to match not only with more orders but also with those of higher marginal profit. This study contributes to the information systems literature by revealing and justifying the economic value of information sharing and IT-enabled operations via TNC apps for use under the existing capacity. Practically, we not only evaluate the policy studied and make post-revision suggestions but also provide managerial insights on precise policy-making that best extracts the economic value of IT in TNCs and general forms of online two-sided platforms.