Efficient operation of demand-responsive transport (DRT) systems:Active requests rejection

Demand-responsive transport (DRT) systems, where users generate requests for transportation from a pickup point to a delivery point, are expected to increase in usage dramatically as the inconvenience of privately-owned cars in metropolitan areas becomes excessive. However, despite the increasing role of DRT systems, there are very few rigorous results characterizing achievable performance (in terms, e.g., of stability conditions). In this paper, our aim is to bridge this gap for a rather general model of DRT systems, which takes the form of a generalized Dynamic Pickup and Delivery Problem. The key strategy is to develop analytical bounds for the optimal cost of the Euclidean Stacker Crane Problem (ESCP), which represents a general static model for DRT systems. By leveraging such bounds, we characterize a necessary and sufficient condition for the stability of DRT systems; the condition depends only on the workspace geometry, the stochastic distributions of pickup and delivery points, customers' arrival rate, and the number of vehicles. Our results exhibit some surprising features that are absent in traditional spatially-distributed queueing systems.

Demand responsive transport (DRT) may be a feasible alternative when conventional transportation services provided by private companies are not available at a satisfactory level in terms of both price and quality. Nevertheless, these unconventional transportation systems are still not consolidated due to technical and economic issues. Beyond technical feasibility, DRT needs to be based on prices and pricing policies that ensure the attractiveness of the service without compromising its economic viability. Nevertheless, there is little evidence on the conditions of economic viability of DRT services and on the cost structure of such systems. In this article, we use a strategic activity based costing model to analyze the conditions of economic viability of a DRT system in a Portuguese rural municipality. The case presented was analyzed in terms of costs and profitability. They were defined a set of important variables which should be taken into account in the design and economic evaluation of DRT projects namely, ticket price, trip distance and passengers. Thus, this costing model can be used to assist decision making and support strategic and operational decisions. Furthermore, it can be embedded in a decision support system designed to support the real time operation of intelligent flexible transportation systems.

Serving a low demand, rural areas with public transport is efficient with the use of a flexible and demand-responsive transport (DRT) solution. To improve the service quality of a DRT service, the accessibility of the service, namely the collection points, should be allocated considering the travelers’ needs. This paper presents a collection point allocation method for a many-to-one type DRT service, which type connects many points (e.g. a neighborhood) with one point (e.g. local center, high-capacity public transport station providing a feeder service). Our research addresses how to optimize the collection point locations by considering walking distances, geographical characteristics, and demand data. Two approaches have been developed: a demand-centric approach, where demand points are known, and a general approach based on spatial characteristics in the absence of demand data. The proposed methods have been validated through a case study in Szentendre, Hungary, focusing on demand-responsive school bus service. Both approaches significantly reduce the walking distance compared to conventional public transport services, while the limited number of collection points ensures that the performance of the service remains within realistic limits. The results of this research can provide guidance for the development of existing services and the introduction of new DRT systems.

Demand Responsive Transport as Being Paratransit Mode: Istanbul Modelling

This research presents a multi-agent based metropolitan demand responsive transport (DRT) system intelligent control model, which adopts a practical multi-agents planning approach for urban DRT services control that satisfies the main constraints: minimize total slack time, travel time, waiting time, client's special requests, and using minimum number of vehicle. In this paper, we propose an agent based multi-layer distributed hybrid planning model for the real-time problem. By computational experiments, we examine an effectiveness of the proposed method for the large real-time metropolitan transport system.

Demand responsive transport (DRT) systems have emerged as innovative solutions to address transportation inequality in areas underserved by conventional public transit. However, some recent DRT services have struggled because of a limited understanding of local contexts and user needs. A growing number of studies have investigated successful modal shift cases, the advantages of DRT, and user satisfaction. Nevertheless, studies conducting in-depth analyses of the factors influencing satisfaction and deriving the factors contributing to modal shifts are rare, with most evaluations limited to simple score-based assessments. This study aims to fill this gap by identifying factors affecting the three core characteristics of DRT services: mobility, accessibility, and user convenience. Using survey data from passengers, we analyzed both satisfaction and dissatisfaction using Binary Logistic Regression with a structured dataset. The analysis revealed several pivotal factors that influence user satisfaction. Key findings include the following: satisfaction levels are positively influenced by a ‘stronger intention to continue using DRT’, ‘reduced first-mile walking time’, and ‘lower detour rates’. Satisfaction with mobility and user convenience is particularly enhanced by the ‘experience of travelling to previously inaccessible locations’. Accessibility satisfaction was significantly affected by a ‘stronger intention to continue using DRT’. Furthermore, user convenience satisfaction is notably influenced by ‘female passengers’, ‘booking via phone’, and ‘no experience with call cancellations’. These findings have significant implications for the DRT service design and operational strategies.

Optimization of demand-responsive transport: The rolling horizon approach

With the rapid pace of urbanization and the subsequent dominance of private vehicle usage, cities are under increasing pressure to offer sustainable alternatives to public transportation. Demand-responsive transport (DRT) systems provide flexible, technology-enabled services that bridge first- and last-mile connectivity gaps. This study assesses the operational and financial viability of Dubai's Bus-on-Demand (DBOD) service using Daganzo's continuum approximation framework, calibrated with empirical data from two service areas in Dubai. From the agency perspective, the Alternating Priorities routing strategy (i.e., alternating between nearest pickup and drop-off) was identified as optimal, balancing distance optimization with service consistency and contributing to shorter travel and waiting times. Cost efficiency is highest in compact service areas with moderate demand, with optimal vehicle occupancy of 10–15 passengers to minimize agency costs. To incorporate the user perspective, value of time (VOT) was calibrated for DBOD and integrated with agency costs. Based on the calibrated VOT, fleet size and operational parameters were optimized within a system framework. Moreover, a comparative analysis of three routing strategies across occupancy levels confirmed the superior cost-effectiveness of the Alternating Priorities approach, as implemented in DBOD. The study recommends that transit agencies refine vehicle dispatching, routing, and scheduling strategies to achieve optimal occupancy levels, and emphasizes the necessity of balancing agency and user costs for sustainable DRT implementation. These findings provide transit agencies with an empirical, data-driven framework to evaluate and optimize DRT services, supporting informed decision-making for sustainable urban mobility.

In recent years, a change in demand trends has influenced the development of public passenger transport, causing a number of critical issues and consequences for the environment, the management policies of these services and, especially, the users. Various passenger transport services have evolved to reduce the use of private vehicles, including DRT systems that consider technological developments like Mobility ad a Service (MaaS). This article focuses on a European literature review on user-oriented research development. The overall objective is to: i) highlight, among all the critical aspects of service development, the factors influencing the economic and ethical aspects; ii) finally identify a discrepancy between the perception of DRT and the empirical research design. The study concludes by providing potential suggestions for improving DRT service deployment and reducing some of the factors influencing users' modal choices. Finally, the paper proposes implications for policy makers and operators.

A Flexible Transport Service for Passengers

Optimised flexible transport mode without advanced reservations by a DES approach

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of the DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT using multi-agent transport simulation (MATSim). Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.

Aim/Purpose: This study examined how service fairness and SERVQUAL dimensions influenced customer satisfaction and loyalty in mobile financial applications (MFAs) in Phnom Penh, Cambodia. As digital transformation reshapes financial services, understanding these factors is crucial for improving user experiences and fostering long-term engagement. Introduction/Background: Mobile financial applications (MFAs) have become an essential part of Cambodia’s urban financial ecosystem by providing accessible and cost-effective financial solutions. Despite their increasing usage, limited research exists on the factors influencing customer satisfaction and loyalty in this sector. This study aimed to bridge this gap by examining how service fairness dimensions (distributive, procedural, interpersonal, and informational) and SERVQUAL dimensions (reliability, responsiveness, assurance, and empathy) impacted customer satisfaction and loyalty. Methodology: A quantitative research methodology was employed to explore the relationships among service fairness, SERVQUAL factors, customer satisfaction, and loyalty. The study targeted individuals aged 18 and above who actively use MFAs in Phnom Penh. Due to the absence of precise population data, stratified purposive sampling was used to ensure diverse representation across Phnom Penh’s districts. Using Cochran’s formula with a 95% confidence level and a 5% margin of error, the study aimed for a sample size of 400 respondents, but 560 surveys were distributed to enhance reliability, yielding 470 valid responses. Data collection took place between May and July 2024 through online surveys and self-administered questionnaires distributed across various digital platforms. The survey instrument was structured into four key sections: demographic information, MFA usage experience, behavioral factors, and service fairness/SERVQUAL dimensions, which were measured on a five-point Likert scale. Survey items were adapted from prior studies to ensure measurement reliability and validity. The questionnaire was pretested with 30 respondents, and refinements were made to improve clarity and relevance. Advanced statistical techniques were used to analyze the data. Descriptive statistics provided an overview of respondent demographics and usage behavior. Cronbach’s Alpha was employed to assess reliability, while Confirmatory Factor Analysis (CFA) validated the construct dimensions. Structural Equation Modeling (SEM) was utilized to test the relationships among service fairness, service quality, customer satisfaction, and loyalty, with results presented through detailed statistical models and tables. Findings: The study revealed that both service fairness and SERVQUAL dimensions significantly influenced customer satisfaction, which, in turn, drives customer loyalty. Among service fairness dimensions, distributive and procedural fairness had the strongest effects on satisfaction, highlighting the importance of transparent processes and fair service outcomes. Customers responded positively to equitable resource allocation and well-structured procedural guidelines. Regarding SERVQUAL dimensions, responsiveness and assurance emerged as the most influential factors shaping customer satisfaction. Customers highly valued prompt responses to inquiries and the expertise and reliability of service providers. While empathy contributed to satisfaction, its impact was comparatively less pronounced. Customer satisfaction was found to mediate the relationships between service fairness, service quality, and loyalty. This underscored the necessity of fostering positive user experiences to enhance long-term customer retention and loyalty. The findings suggest that MFA providers should prioritize procedural fairness and responsiveness to optimize customer satisfaction and long-term engagement. Contribution/Impact on Society: This study provides empirical evidence of the role of service fairness and SERVQUAL factors in shaping customer satisfaction and loyalty in the Cambodian MFA market. While previous research has examined these factors in other industries, this study uniquely focused on MFAs in a developing Southeast Asian context. The findings emphasize the importance of fair service design and high-quality service delivery in building customer trust and loyalty. By implementing transparent service processes and prioritizing customer support quality, MFA providers can foster financial inclusion and promote sustainable business growth in emerging markets. Recommendations: For MFA providers, the study recommends emphasizing transparency, equitable service outcomes, and efficient customer support to enhance satisfaction and trust. Specifically, providers should: Improve distributive and procedural fairness by implementing clear, transparent, and fair resource allocation policies. Enhance responsiveness by ensuring customer inquiries are addressed promptly and effectively. Strengthen assurance through professional training programs that enhance staff expertise and reliability. Invest in customer service training to improve staff empathy and engagement with users. For researchers, further exploration into additional variables such as trust, security, and digital literacy could offer a more comprehensive understanding of MFA user behavior. Research Limitation: This study had several limitations. Its cross-sectional research design captured data at a single point in time, limiting the ability to infer causal relationships. Additionally, the study focused exclusively on Phnom Penh, restricting the generalizability of findings to other regions or countries. The reliance on self-reported data may have introduced potential bias, including social desirability bias. Future studies should adopt longitudinal designs and include a broader geographic scope to enhance research validity Future Research: Future studies should expand on this research by incorporating additional factors such as perceived security, trust, and digital literacy to provide deeper insights into customer satisfaction and loyalty in MFAs. Comparative studies across different regions or countries could reveal cultural differences in how service fairness and quality affect customer perceptions. Additionally, longitudinal studies tracking changes in satisfaction and loyalty over time would provide a dynamic perspective on user behavior and evolving service expectations.

This paper describes the concepts and system approach of FAMS, Flexible Agency for Collective Demand Responsive Mobility Services, a European project founded by the EU-IST Programme and operating in the Florence Metropolitan area. The objective of FAMS Project is to scale up the technology, service and business models currently adopted in demand responsive transport (DRT) and support the evolution from single DRT applications to the concept of an agency for such services. State-of-the-art DRT technology-i.e. booking and reservation systems, route and service planning systems, communication services, service management services, service and customer repositories, etc.-will be further extended and adapted to work within an innovative e-Business infrastructure in order to to achieve networking of the different transport operators involved in Transport services and to allow sharing of information and service interoperability among them. This will ultimately allow different transport operators to cooperate and the overall transport system to work as a virtual, flexible organization. FAMS will implement and trial the concept in the Tuscany region (Italy) and the Angus region (UK).

Over the last years, various extensions of Vehicle Routing Problem, Considering the pick -up and delivery vehicle routing problem have been studied. In this work we tackle the pickup and delivery of passengers namely Demand Responsive Transport. Its idea is to group a number of passengers in the same vehicle with the respecting of the capacity of each vehicle in order to reduce operational cost with the maintaining of high quality service. This paper presents an exact Method which is the Branch and Bound Algorithm to solve a new variant of Demand Responsive Transport which is based on service quality but not as an option it is an obligation. The Multi-Vehicle Demand Responsive Transport Problem Based on Service Quality in the case of Oneto-One(MVSDRTPBSQ1-t-1) under study presented the following characteristics: Users specify transportation requests between origins and destinations, each customer have his own origin and own destination, they may provide a time window on their desired departure or arrival time. All demands are knows before the pacification of vehicles tours and the transportation is supplied by a fleet of vehicle based at a common depot. The aim of this paper is to find the best routing scheduled of all receipt requests with the respecting of hard Time Windows of each customer, its mean that the most important is the service quality of each customer. The novelty of our paper is presented in the new manner of algorithm application. However, we will trying to take the general architecture of Branch & Bound algorithm and using valuation rules in a different way which can adapted for such problem to find an optimal solution.