Model of information system for combined ride-sourcing service

Abstract

Abstract-Efficiency enhancement for urban mobility is one of the key elements in smart city conceptions. Nowadays, there is significant underutilization of vehicle capacities in the case of individual vehicles, taxis, and vehicles, especially for food or small package delivery services. The motivation of our research is to reveal opportunities for so-called dynamic, combined ridesourcing service. Passengers and certain goods sharing the same destination can be transported in shared vehicles. Since such novel service concepts are based on new forms of information management, the research question is: how the information systems and the operations are to be modeled in order to create the service. In such a service, demands and capacities are coordinated by dynamic prices based on real-time data. The logical correspondences of pricing are also revealed. During model development, we considered autonomous vehicles as well, because their emergence requires fundamentally new operational approaches.Accordingly, the developed information management method can be adopted for services based on autonomous vehicles. The results provide a basis for innovation and development of these services.Index Terms-system structure, operational model, dynamic price, package delivery, ride-sourcing, taxi

Collaborative urban transportation: Recent advances in theory and practice

“…When considering planning from an OR perspective, challenges of information management, as summarized under the term 'collaborative transport management' in Okdinawati et al (2015) should not be forgotten. Related ideas are exemplified for ride-sharing in Földes and Csiszár (2017). This could also mean applying predictive analytics to the data available to coalition partners in urban transport as indicated by Ilie-Zudor et al (2015) for general less-than-truckload transport.…”

Customer acceptance of ride-hailing in Indonesia

“…Its on-demand business model is built on asset sharing, where private cars are the assets to be used to provide the transportation services. Individual drivers use their own cars for the taxi services in exchange for money (Kavadias et al , 2016; Smith, 2016; Földes and Csiszár, 2017). More transportation network companies (TNC) have emerged globally such as Lyft, Grab (Malaysia), DiDi (China) and GO-JEK (Indonesia) to provide ride-hailing services, which use modern internet-based mobile applications on smartphones.…”

“…This feature of using the ride-hailing platforms provides the convenience compared to traditional taxi where customers need to stop a random taxi on the streets to request a ride. Fares depend on current demands for rides and availability of vehicles, and they are paid virtually through the payment system on the mobile application (Földes and Csiszár, 2017). The ride-hailing app also has a built-in rating system where customers are allowed to rate their drivers.…”

A Threshold Policy for Dispatching Vehicles in Demand-responsive Transit Systems

“…The outline of the simulation model written in MATLAB is (Fu [4]), (b) compare flexible with conventional transit (Shinoda [5]), (c) explore the impact of zoning strategies and time windows on system-wide performance measures (Quadrifoglio et al [6]), and (d) study feasibility of a flexible transit system with electric vehicles (Jung et al [26]) that would be particularly suitable for serving smaller communities (Wang and Gonzalez [27]). In systems where demands and capacities are coordinated by dynamic prices based on real-time data, there is need for the information systems and the operations modelled in order to create the service (Földes et al [28]). Another real time service is a concept of Flexible Mobility on Demand, a demand-responsive system in which a list of travel options is provided in real-time to each passenger request (Atasov et al [29]).…”