In the face of unprecedented global supply chain disruptions, enhancing supply chain resilience (SCR) has become a critical priority. This empirical study examines the crucial role of resource orchestration, encompassing internal reconfiguration and external integration, across the three dynamic capabilities of SCR: readiness, response, and recovery. Additionally, it investigates the moderating effect

In emergency disaster response, the dynamic nature and uncertainty of resource transportation pose significant challenges for vehicle routing planning. We address a truck-drone collaborative routing problem in humanitarian logistics, where a set of truck-drone tandems collaboratively deliver relief resources from a distribution center to a set of affected areas which is dynamically updated as disaster

This paper considers a green vehicle routing problem termed the time-dependent green vehicle routing problem with time windows (TDGVRPTW). The TDGVRPTW is an extension of the green vehicle routing problem with time windows in green logistics. It considers time-dependent vehicle speed and aims to minimize carbon emissions. Since the travel times and carbon emissions between locations depend on the departure

This paper shows that, in a static traffic model with elastic demand, increasing a toll may raise the equilibrium trip rate through a network. The result is obtained in models with horizontal queues and rules about merges and diverges assumed in the Cell Transmission Model for Network Traffic. The paper looks at three networks: (i) a road with a fixed bottleneck at the end; (ii) a road with a “triggerneck”

Ride-hailing services, which are offered by companies such as Uber and Lyft, have the potential to produce both benefits and negative externalities. In particular, ride-hailing can help improve mobility and accessibility, but can also contribute to increases in vehicle-miles traveled, congestion, and emissions. Induced ride-hailing trips (i.e., trips that would not have been made if ride-hailing was

This study presents a comprehensive decision-making framework that employs eXplainable Artificial Intelligence (XAI)-based methods to improve proactive road transport safety management, which is critical for global supply chain networks. The framework offers explainable predictions as well as suggestions pertaining to the near-future digitization of safety tools and their usage, customized for road

Detecting zero-day attacks is a critical challenge in the Internet of Vehicles (IoV). Due to the limited availability of labeled attack data, anomaly-based methods are predominantly employed. However, the variability in the driving environment and behavioral patterns of vehicles introduces significant fluctuations in normal behavior, which in turn leads to high false positive rates when using these

In the initial phase of implementing connected and automated vehicle (CAV) technology, the coexistence of human-driven vehicles (HVs) and CAVs is anticipated for the foreseeable future. While dedicated CAV lane is recognized as an effective solution to enhance traffic safety and efficiency in mixed traffic scenarios, it faces the challenges of road resource wastage, especially at low CAV penetration

In this increasingly highly turbulent environment, firms are facing demand changes, many of which are unpredictable. Furthermore, the magnitude of such uncertainties is unpredictable. Thus, firms have limited options as to how to prepare for such uncertainties. A viable strategy that firms may employ to cope with uncertainties effectively is operational flexibility. Firms’ operational flexibility is

The urgent need for rapid disaster response mechanisms, particularlyin the event ofearthquakes, is critical. In response to directives from the National Crisis Management Supreme Council, a plan has been initiated to establish distribution centers across all zones of Tehran, Iran,which signalsa significant shift towards decentralization. However, land scarcity and road blockages hinder thefull realization

The next generation (5G/B5G) vehicular cognitive radio networks (VCRNs) flag the track to intelligence-based autonomous driving in the initiation of future wireless networking and make daily vehicular operation more convenient, greener, efficient, and safer. However, with the continuous evolution of vehicles, the vehicular network becomes large-scale, dynamic, and heterogeneous, making it tough to

Flying ad hoc networks (FANETs) are a new example of ad hoc networks, which arrange unmanned aerial vehicles (UAVs) in an ad hoc form. The features of these networks, such as the movement of UAVs in a 3D space, high speed of UAVs, dynamic topology, limited resources, and low density, have created vital challenges for communication reliability, especially when designing routing methods in FANETs. In

Transit frequency design is critical in determining the performance of public transit services. In the literature, single-period frequency design is often considered but ignores the demand variation over time of day. Moreover, in high-demand bus networks, the demand patterns are asymmetric in both directions of some bus routes. This study investigates a bus operation strategy to address these two issues

The rapid growth of passengers has led to overcrowding in urban rail transit (URT) systems, especially during holidays, posing significant challenges to the safe management and operation of URT systems. Accurate and real-time short-term passenger inflow and outflow prediction on holidays is essential for operation management and resource allocation to alleviate such overcrowding. However, short-term

Anti-congestion policies, such as urban spatial planning, transport infrastructure, and economic incentives, are often regarded as effective structural measures for relieving citywide traffic congestion. However, few studies have empirically investigated and compared the intervention effects of such structural policies on relieving congestion. Using longitudinal AutoNavi’s big-data-based congestion

In this article, we formulate a hybrid model that allows to identify the triggers of instant utilities using psychophysiological indicators (PPIs). Instant utilities are understood as momentary emotions perceived in every instant of an experience. We build the model using transport and environmental variables associated with the experience to explain instant utilities, which are measured by PPIs and

Synchromodal freight transport is characterized by its inherent dynamicity, necessitating the need for optimal decision-making in the presence of uncertainties in the real world. However, most prior research has overlooked the complexities of uncertainty modeling, often relying on assumed probability distributions that may not accurately reflect real-world conditions. This study presents a learning-based

With the increasing demand for air transport, numerous airports have exceeded their available capacity, resulting in more frequent congestion and disruptions. Therefore, airport gate assignment plans must prioritise robustness to alleviate congestion, absorb disruptions, and maintain high service levels. Given the uncertainties in airside operations, providing robust decisions is challenging. To address

Connected Vehicles (CVs) are a crucial element in the evolution of smart transportation systems, utilizing communication and sensing technologies to interact with each other and with infrastructure. As these vehicles become more interconnected, the risk of their components being affected by anomalies or intentional malicious attacks grows. It is essential, therefore, to identify and filter out any

Maritime cybersecurity has emerged as a critical and rapidly evolving research field, necessitated by the increasing reliance on digital technologies and interconnectivity within the global maritime industry. In this paper, we adopt a bibliometric analysis method to review the existing academic publications pertaining to maritime cybersecurity, aiming to provide a comprehensive overview of the development

It is well known that supply chains should leverage information sharing from stakeholders as a measure to drive business growth. However, the practice of information sharing for supply chain management has been fairly limited due to the high cost of meeting differential user needs, information-island from centralized storage, and inefficient information value capture. To address these concerns, we

In a technology-intensive supply chain, branding can significantly enhance consumers’ perception of a technology’s contribution to the final products, making it potentially beneficial for the technology provider. However, many technology providers operate behind the scenes as pure suppliers, rather than branding themselves. The reasons behind these heterogeneous branding decisions among technology

Data aggregation is evolving into an extremely crucial role for facilitating decision-making in Internet of Vehicles (IoV). Multi-region data is a typical attribute of IoV, containing sensitive information and driving trajectories. However, the existing privacy-preserving schemes face problems such as regional statistics, messages integrity, and collusion attacks. In order to tackle this challenge

In low-altitude economic logistics scenarios, trajectory planning for unmanned aerial vehicles (UAVs) can be treated as a typical traveling salesman problem (TSP). High-rise buildings in urban areas not only severely impact the flight safety of UAVs, but also increase their energy consumption when avoiding obstacles, thereby affecting their delivery ranges. To address these issues, this paper proposes

This paper investigates a dynamic inventory-pricing system with perishable products of multiple freshness levels. The firm may set different prices for items of different freshness levels, and customers either balk or choose to buy the freshness level that maximizes their utility. We model this inventory-pricing problem as a Markov decision process, where the assortment dynamically changes based on

Remanufacturing is a viable and indispensable method to restore used electronics to near-new condition, combating the alarming rise of end-of-life (EOL) products, particularly in the field of electronic waste. It aligns with Environmental, Social, and Governance (ESG) principles, emphasizing sustainability and responsible resource management. In this paper, we consider a remanufacturer’s problem in