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Articles 1 - 30 of 175
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia
Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia
Research Collection School Of Computing and Information Systems
The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …
T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng
T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng
Research Collection School Of Computing and Information Systems
Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …
Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao
Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao
Research Collection School Of Computing and Information Systems
This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …
Cooperative Trucks And Drones For Rural Last-Mile Delivery With Steep Roads, Jiuhong Xiao, Ying Li, Zhiguang Cao, Jianhua Xiao
Cooperative Trucks And Drones For Rural Last-Mile Delivery With Steep Roads, Jiuhong Xiao, Ying Li, Zhiguang Cao, Jianhua Xiao
Research Collection School Of Computing and Information Systems
The cooperative delivery of trucks and drones promises considerable advantages in delivery efficiency and environmental friendliness over pure fossil fuel fleets. As the prosperity of rural B2C e-commerce grows, this study intends to explore the prospect of this cooperation mode for rural last-mile delivery by developing a green vehicle routing problem with drones that considers the presence of steep roads (GVRPD-SR). Realistic energy consumption calculations for trucks and drones that both consider the impacts of general factors and steep roads are incorporated into the GVRPD-SR model, and the objective is to minimize the total energy consumption. To solve the proposed …
Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang
Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …
Lean Six Sigma Body Of Knowledge For Healthcare Industry Administrators: Implementation Of Lessons Learned In Applied Engineering, Mohammed Ali
Technology Faculty Publications and Presentations
The purpose of this paper is to propose a Lean Six Sigma (LSS) course curriculum for healthcare administration and management majors. It identifies the relevant opportunities and challenges for the application of LSS within the healthcare industry. The paper also discusses the cultural changes necessary to provide an appropriate climate for its long-term success. This work contains a comprehensive description of the body of knowledge in LSS, which were successful in applied engineering. Additionally, the paper describes how LSS may be applied in the hospital setting to improve processes in patient-care services. Upon successful completion of the course, the healthcare …
Domain Restriction Zones: An Evolution Of The Military Exclusion Zone, Cole M. Mooty, Robert A. Bettinger, Mark G. Reith
Domain Restriction Zones: An Evolution Of The Military Exclusion Zone, Cole M. Mooty, Robert A. Bettinger, Mark G. Reith
Faculty Publications
Since the early part of the twenty-first century, US adversaries have expanded their military capabilities within and their access to new warfighting domains. When faced with the growth of adversaries’ asymmetric capabilities, the means, tactics, and strategies previously used by the US military lose their proportional effectiveness. To avoid such degradation of capability, the operational concept of the military exclusion zone (MEZ) should be revised to suit the modern battlespace while also addressing the shifts in national policy that encourage diplomacy over military force. The concept and development of domain restriction zones (DRZs) increase the relevancy of traditional MEZs in …
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Research Collection School Of Computing and Information Systems
This work concerns the estimation of recursive route choice models in the situation that the trip observations are incomplete, i.e., there are unconnected links (or nodes) in the observations. A direct approach to handle this issue could be intractable because enumerating all paths between unconnected links (or nodes) in a real network is typically not possible. We exploit an expectation–maximization (EM) method that allows dealing with the missing-data issue by alternatively performing two steps of sampling the missing segments in the observations and solving maximum likelihood estimation problems. Moreover, observing that the EM method could be expensive, we propose a …
Electrical Vehicle Charging Infrastructure Design And Operations, Yu Yang, Hen-Geul Yeh
Electrical Vehicle Charging Infrastructure Design And Operations, Yu Yang, Hen-Geul Yeh
Mineta Transportation Institute Publications
California aims to achieve five million zero-emission vehicles (ZEVs) on the road by 2030 and 250,000 electrical vehicle (EV) charging stations by 2025. To reduce barriers in this process, the research team developed a simulation-based system for EV charging infrastructure design and operations. The increasing power demand due to the growing EV market requires advanced charging infrastructures and operating strategies. This study will deliver two modules in charging station design and operations, including a vehicle charging schedule and an infrastructure planning module for the solar-powered charging station. The objectives are to increase customers’ satisfaction, reduce the power grid burden, and …
Multiobjective Stochastic Optimization: A Case Of Real-Time Matching In Ride-Sourcing Markets, Guodong Lyu, Wang Chi Cheung, Chung-Piaw Teo, Hai Wang
Multiobjective Stochastic Optimization: A Case Of Real-Time Matching In Ride-Sourcing Markets, Guodong Lyu, Wang Chi Cheung, Chung-Piaw Teo, Hai Wang
Research Collection School Of Computing and Information Systems
Problem Definition: The job of any marketplace is to facilitate the matching of supply with demand in real-time. Success is often measured using various metrics. The challenge is to design matching algorithms to balance the trade-offs among multiple objectives in a stochastic environment, to arrive at a “compromise” solution, which minimizes say the ℓp-norm-based distance function (for some 1 ≤p ≤∞) between the attained performance metrics and the target performances.Methodology/Results: We observe that the sample-average-approximation formulation of this multi-objective stochastic optimization problem can be solved by an online algorithm that uses only gradient information from “historical” (i.e., past) sample information, …
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Research Collection School Of Computing and Information Systems
Recent works using deep reinforcement learning (RL) to solve routing problems such as the capacitated vehicle routing problem (CVRP) have focused on improvement learning-based methods, which involve improving a given solution until it becomes near-optimal. Although adequate solutions can be achieved for small problem instances, their efficiency degrades for large-scale ones. In this work, we propose a newimprovement learning-based framework based on imitation learning where classical heuristics serve as experts to encourage the policy model to mimic and produce similar or better solutions. Moreover, to improve scalability, we propose Clockwise Clustering, a novel augmented framework for decomposing large-scale CVRP into …
Optimization Of Station-Skip In A Cyclic Express Subway Service, Jingfeng Yang, Hai Wang, Jiangang Jin
Optimization Of Station-Skip In A Cyclic Express Subway Service, Jingfeng Yang, Hai Wang, Jiangang Jin
Research Collection School Of Computing and Information Systems
With rapid population growth and increasing demand for urban mobility, metropolitan areas such as Singapore, Tokyo, and Shanghai are increasingly dependent on public transport systems. Various strategies are proposed to improve the service quality and capacity of bus and subway systems. Express trains—i.e., trains that skip certain stations—are commonly used because they can travel at higher speeds, potentially reduce travel time, and serve more passengers. In this paper, we study cyclic express subway service (CESS), in which express trains provide routine transport service with cyclic (periodic) station-skip patterns that can be used in daily service. We propose an exact Mixed …
Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures, Pitiporn Asvapathanagul, Simone Galano, Andrea Calabrese, Mehran Rahmani, Maggie Ly, Daniela Flores, Michael Hernandez, Nicholas Banuelos
Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures, Pitiporn Asvapathanagul, Simone Galano, Andrea Calabrese, Mehran Rahmani, Maggie Ly, Daniela Flores, Michael Hernandez, Nicholas Banuelos
Mineta Transportation Institute Publications
Although concrete is the most widely used building material in the world, its limited tensile strength makes cracking a common phenomenon in concrete elements. This study investigates the potential of autonomous self-healing as an eco-friendly and lowcost method to increase the durability of concrete. The crack-healing potential of different types of high-alkaline-tolerant bacteria or calcite-precipitation microorganisms is investigated. High-alkaline-tolerant bacteria and calcite-precipitation microorganisms were used to retrofit lab-fractured concrete samples. The samples healed with each of these bacteria groups were cast and tested under compressive load up to failure to measure the compressive strength of the concrete samples. The outcomes …
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Research Collection School Of Computing and Information Systems
Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.
Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar
Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar
Research Collection School Of Computing and Information Systems
Rapid developments in city infrastructure and technol-ogies are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances and have been reshaped significantly. They enable innovative new urban services, which are now booming and changing everyday life for urban residents.This special issue of Service Science explores perspectives on innovation in transportation-enabled urban services. We hope that the special issue will enhance the understanding of the planning, operation, and management of such services. Contributions are expected to demonstrate rigorous model development, economic/ econometric analysis, and decision-making tools based …
An Ioe Blockchain-Based Network Knowledge Management Model For Resilient Disaster Frameworks, Amir Javadpour, Farinaz Sabz Ali Pour, Arun Kumar Sangaiah, Weizhe Zhang, Forough Ja'far, Ashish Singh
An Ioe Blockchain-Based Network Knowledge Management Model For Resilient Disaster Frameworks, Amir Javadpour, Farinaz Sabz Ali Pour, Arun Kumar Sangaiah, Weizhe Zhang, Forough Ja'far, Ashish Singh
Engineering Management & Systems Engineering Faculty Publications
The disaster area is a constantly changing environment, which can make it challenging to distribute supplies effectively. The lack of accurate information about the required goods and potential bottlenecks in the distribution process can be detrimental. The success of a response network is dependent on collaboration, coordination, sovereignty, and equal distribution of relief resources. To facilitate these interactions and improve knowledge of supply chain operations, a reliable and dynamic logistic system is essential. This study proposes the integration of blockchain technology, the Internet of Things (IoT), and the Internet of Everything (IoE) into the disaster management structure. The proposed disaster …
Critical Space Infrastructure: A Complex System Governance Perspective, Adrian V. Gheorghe, James C. Pyne, Joseph Sisti, Charles B. Keating, Polinpapilinho F. Katina, William Edmonson
Critical Space Infrastructure: A Complex System Governance Perspective, Adrian V. Gheorghe, James C. Pyne, Joseph Sisti, Charles B. Keating, Polinpapilinho F. Katina, William Edmonson
Engineering Management & Systems Engineering Faculty Publications
This paper examines the applicability of Complex System Governance (CSG) to advance the Critical Space Infrastructure field (CSI). CSI encompasses space related hardware, workforce, environment, facilities, and businesses that are necessary for societal well-being. CSI is increasing in importance as more societal serving systems are becoming dependent on CSI to operate. Given this increasing dependence on CSI, societal sectors are increasingly at risk should something go wrong with CSI upon which they depend. CSI has been developing is a fragmented way and lacks coherent organization. CSG is focused on design, execution, and evolution of system functions that provide for communications, …
Strengthening Urban Resilience: Understanding The Interdependencies Of Outer Space And Strategic Planning For Sustainable Smart Environments, Ulpia-Elena Botezatu, Olga Bucovetchi, Adrian V. Gheorghe, Radu D. Stanciu
Strengthening Urban Resilience: Understanding The Interdependencies Of Outer Space And Strategic Planning For Sustainable Smart Environments, Ulpia-Elena Botezatu, Olga Bucovetchi, Adrian V. Gheorghe, Radu D. Stanciu
Engineering Management & Systems Engineering Faculty Publications
The conventional approach to urban planning has predominantly focused on horizontal dimensions, disregarding the potential risks originating from outer space. This paper aims to initiate a discourse on the vertical dimension of cities, which is influenced by outer space, as an essential element of strategic urban planning. Through an examination of a highly disruptive incident in outer space involving a collision between the Iridium 33 and Cosmos 2251 satellites, this article elucidates the intricate interdependencies between urban areas and outer space infrastructure and services. Leveraging the principles of critical infrastructure protection, which bridge the urban and outer space domains, and …
Computational Decision Support For Socio-Technical Awareness Of Land-Use Planning Under Complexity—A Dam Resilience Planning Case Study, Andreas Tolk, Jennifer A. Richkus, F. Leron Shults, Wesley J. Wildman
Computational Decision Support For Socio-Technical Awareness Of Land-Use Planning Under Complexity—A Dam Resilience Planning Case Study, Andreas Tolk, Jennifer A. Richkus, F. Leron Shults, Wesley J. Wildman
VMASC Publications
Land-use planning for modern societies requires technical competence as well as social competence. We therefore propose an integrative solution enabling better land-use planning and management through better-informed decision-making. We adapt a method developed for cross-disciplinary team building to identify the stakeholders and their various objectives and value systems. We use these results to populate artificial societies embedded into a dynamic data analytics framework as a tool to identify, explore, and visualize the challenges resulting from the different objectives and value systems in land-use planning and management. To prove the feasibility of the proposed solution, we present two use cases from …
Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau
Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This work is motivated by a real-world problem of coordinating B2B pickup-delivery operations to shopping malls involving multiple non-collaborative logistics service providers (LSPs) in a congested city where space is scarce. This problem can be categorized as a vehicle routing problem with pickup and delivery, time windows and location congestion with multiple LSPs (or ML-VRPLC in short), and we propose a scalable, decentralized, coordinated planning approach via iterative best response. We formulate the problem as a strategic game where each LSP is a self-interested agent but is willing to participate in a coordinated planning as long as there are sufficient …
A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu
A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu
Research Collection School Of Computing and Information Systems
The electric vehicle routing problem (EVRP) has been studied increasingly because of environmental concerns. However, existing studies on the EVRP mainly focus on time windows and sole linehaul customers, which might not be practical as backhaul customers are also ubiquitous in reality. In this study, we investigate an EVRP with time windows and mixed backhauls (EVRPTWMB), where both linehaul and backhaul customers exist and can be served in any order. To address this challenging problem, we propose a diversity-enhanced memetic algorithm (DEMA) that integrates three types of novel operators, including genetic operators based on adaptive selection mechanism, a selection operator …
Exploring The Effects Of Meaningful Tactile Display On Perception And Preference In Automated Vehicles, Kimberly D. Martinez, Gaojian Huang
Exploring The Effects Of Meaningful Tactile Display On Perception And Preference In Automated Vehicles, Kimberly D. Martinez, Gaojian Huang
Mineta Transportation Institute Publications
There is an existing issue in human-machine interaction, such that drivers of semi-autonomous vehicles are still required to take over control of the vehicle during system limitations. A possible solution may lie in tactile displays, which can present status, direction, and position information while avoiding sensory (e.g., visual and auditory) channels overload to reliably help drivers make timely decisions and execute actions to successfully take over. However, limited work has investigated the effects of meaningful tactile signals on takeover performance. This study synthesizes literature investigating the effects of tactile displays on takeover performance in automated vehicles and conducts a human-subject …
Fed-Ltd: Towards Cross-Platform Ride Hailing Via Federated Learning To Dispatch, Yansheng Wang, Yongxin Tong, Zimu Zhou, Ziyao Ren, Yi Xu, Guobin Wu, Weifeng Lv
Fed-Ltd: Towards Cross-Platform Ride Hailing Via Federated Learning To Dispatch, Yansheng Wang, Yongxin Tong, Zimu Zhou, Ziyao Ren, Yi Xu, Guobin Wu, Weifeng Lv
Research Collection School Of Computing and Information Systems
Learning based order dispatching has witnessed tremendous success in ride hailing. However, the success halts within individual ride hailing platforms because sharing raw order dispatching data across platforms may leak user privacy and business secrets. Such data isolation not only impairs user experience but also decreases the potential revenues of the platforms. In this paper, we advocate federated order dispatching for cross-platform ride hailing, where multiple platforms collaboratively make dispatching decisions without sharing their local data. Realizing this concept calls for new federated learning strategies that tackle the unique challenges on effectiveness, privacy and efficiency in the context of order …
Beyond The High Ground: A Taxonomy For Earth-Moon System Operations, Adam P. Wilmer, Robert A. Bettinger
Beyond The High Ground: A Taxonomy For Earth-Moon System Operations, Adam P. Wilmer, Robert A. Bettinger
Faculty Publications
Situational and space domain awareness in the space domain can no longer be confined to that which is found in geosynchronous orbit. International activities—commercial and military—and threats to the planet itself exist and are increasing across the entire Earth-Moon system. This reality requires a new taxonomy to accurately classify space domain awareness missions and better apply resources to and development of the same. This work presents such a taxonomy for the classification of space domain awareness regions.
Time Dependent Orienteering Problem With Time Windows And Service Time Dependent Profits, M. Khodadadian, A. Divsalar, C. Verbeeck, Aldy Gunawan, P. Vansteenwegen
Time Dependent Orienteering Problem With Time Windows And Service Time Dependent Profits, M. Khodadadian, A. Divsalar, C. Verbeeck, Aldy Gunawan, P. Vansteenwegen
Research Collection School Of Computing and Information Systems
This paper addresses the time dependent orienteering problem with time windows and service time dependent profits (TDOPTW-STP). In the TDOPTW-STP, each vertex is assigned a minimum and a maximum service time and the profit collected at each vertex increases linearly with the service time. The goal is to maximize the total collected profit by determining a subset of vertices to be visited and assigning appropriate service time to each vertex, considering a given time budget and time windows. Moreover, travel times are dependent of the departure times. To solve this problem, a mixed integer linear model is formulated and a …
Multi-Agent Reinforcement Learning For Traffic Signal Control Through Universal Communication Method, Qize Jiang, Minhao Qin, Shengmin Shi, Weiwei Sun Sun, Baihua Zheng
Multi-Agent Reinforcement Learning For Traffic Signal Control Through Universal Communication Method, Qize Jiang, Minhao Qin, Shengmin Shi, Weiwei Sun Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
How to coordinate the communication among intersections effectively in real complex traffic scenarios with multi-intersection is challenging. Existing approaches only enable the communication in a heuristic manner without considering the content/importance of information to be shared. In this paper, we propose a universal communication form UniComm between intersections. UniComm embeds massive observations collected at one agent into crucial predictions of their impact on its neighbors, which improves the communication efficiency and is universal across existing methods. We also propose a concise network UniLight to make full use of communications enabled by UniComm. Experimental results on real datasets demonstrate that UniComm …
Hierarchical Value Decomposition For Effective On-Demand Ride Pooling, Hao Jiang, Pradeep Varakantham
Hierarchical Value Decomposition For Effective On-Demand Ride Pooling, Hao Jiang, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
On-demand ride-pooling (e.g., UberPool, GrabShare) services focus on serving multiple different customer requests using each vehicle, i.e., an empty or partially filled vehicle can be assigned requests from different passengers with different origins and destinations. On the other hand, in Taxi on Demand (ToD) services (e.g., UberX), one vehicle is assigned to only one request at a time. On-demand ride pooling is not only beneficial to customers (lower cost), drivers (higher revenue per trip) and aggregation companies (higher revenue), but is also of crucial importance to the environment as it reduces the number of vehicles required on the roads. Since …
Competition And Third-Party Platform-Integration In Ride-Sourcing Markets, Yaqian Zhou, Hai Yang, Jintao Ke, Hai Wang, Xinwei Li
Competition And Third-Party Platform-Integration In Ride-Sourcing Markets, Yaqian Zhou, Hai Yang, Jintao Ke, Hai Wang, Xinwei Li
Research Collection School Of Computing and Information Systems
Recently, some third-party integrators attempt to integrate the ride services offered by multiple independent ride-sourcing platforms. Accordingly, passengers can request ride through the integrators and receive ride service from any one of the ride-sourcing platforms. This novel business model, termed as third-party platform-integration in this work, has potentials to alleviate market fragmentation cost resulting from demand splitting among multiple platforms. Although most existing studies focus on operation strategies for one single monopolist platform, much less is known about the competition and platform-integration and their implications on operation strategy and system efficiency. In this work, we propose mathematical models to describe …
The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo
The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo
Research Collection School Of Computing and Information Systems
We study the role of ride-hailing surge factors on the allocative efficiency of taxis by combining a reduced-form estimation with structural analyses using machine-learning-based demand predictions. Where other research study the effect of entry on incumbent taxis, we use higher frequency granular data to study how location-time-specific surge factors affect taxi bookings to bound the effect of customer decisions while accounting for various confounding variables. We find that even in a unique market like Singapore, where incumbent taxi companies have app-based booking systems similar to those from ride-hailing companies like Uber, the estimated upper bound on the cross-platform substitution between …
Grounding Evaluation Capacity Development In Systems Theory, Sarah D. Klier, Raphael J. Nawrotzki, Nataly Salas-Rodríguez, Sven Harten, Charles B. Keating, Polinpapilinho F. Katina
Grounding Evaluation Capacity Development In Systems Theory, Sarah D. Klier, Raphael J. Nawrotzki, Nataly Salas-Rodríguez, Sven Harten, Charles B. Keating, Polinpapilinho F. Katina
Engineering Management & Systems Engineering Faculty Publications
While “systemic thinking” is popular in the context of capacity development and evaluation, there is currently a lack of understanding about the benefits to employing systems theory in evaluation capacity development. Systems theory provides a useful orientation to the work involved in complex systems (e.g. national evaluation systems). This article illustrates how evaluation capacity development practitioners can use systems theory as a conceptual tool to gain a better understanding of the functional aspects and interrelationships present within a given evaluation system. Specifically, the systems theory perspective can help elucidate the reasons for the success or failure of a given evaluation …