China’s national centralized drug procurement policy, as a form of group purchasing, has successfully improved drug affordability and accessibility through significant price reductions. While prior studies have examined the long-term policy effects on pharmaceutical firms, critical gaps exist in understanding the immediate financial consequences for pharmaceutical firms, and how firm characteristics

Rail freight is vital for economic growth due to its efficiency and environmental benefits, but its lack of fixed schedules due to various delay factors poses challenges for accurate Expected Travel Time (ETT) predictions. This research addresses the need for real-time, accurate and dynamic ETT predictions crucial for maintaining efficient supply chains by developing a novel predictive model that leverages

This paper explores flight scheduling and pricing strategies for airlines under coopetition with high-speed rail (HSR) in intercity travel markets, considering the impact of potential delays and missed connections on passenger choices. A stochastic user equilibrium model is developed to account for the passenger route choices under travel time variability, security control delays, and competition with

The online food-ordering service industry experienced substantial growth due to the COVID-19 pandemic. Several online food delivery service (OFDS) providers enhanced their logistical capabilities and introduced instantdelivery choices (Instant OFDS)to improve customer experiences. However, research concerning the logistical factors that influence customers’ adoption of Instant OFDS is scarce. Therefore

This research introduces a blood distribution system under vendor-managed inventory that considers uncertain supply and demand. We present it as the Blood Stochastic Inventory Routing Problem, formulating it as a two-stage stochastic programming model. To solve this problem, this study proposes a three-stage matheuristic that combines a perturbation heuristic, Adaptive Large Neighborhood Search, and

The internet has entered the 3.0 era, significantly boosting the development of the gig economy. Gig work, as a flexible form of employment, is increasingly recognized as a vital component of the modern economy. However, research on the gig economy remains in its early stages, highlighting the need for a comprehensive conceptual framework to define the boundaries of this field and to identify potential

Bus holding control is a widely-adopted strategy for maintaining stability and improving the operational efficiency of bus systems. Traditional model-based methods often face challenges with the low accuracy of bus state prediction and passenger demand estimation. In contrast, Reinforcement Learning (RL), as a data-driven approach, has demonstrated great potential in formulating bus holding strategies

The surge in popularity of electric vehicles (EVs) has created a need for adaptable and flexible charging infrastructure. Intelligent Charging Robots (ICRs) have emerged as a promising solution to overcome issues faced by fixed charging stations, such as insufficient coverage, station occupancy, spatial constraints, and strain on the power grid. Nonetheless, optimizing the operational efficiency of

Despite current policies, retailer hoarding continues to occur frequently during specific emergency situations, highlighting the significance of understanding the underlying mechanism. This study employs Stackelberg game models within a two-tier supply chain consisting of a supplier and a retailer to analyse their decisions during persistent emergencies. The models incorporate the interactions between

The booking service, a key feature of autonomous public transport vehicle (APTV) systems, has been designed to introduce a new, real-time, on-demand, and reliable element to service improvement, similar to ride-hailing. However, the current APTV system has yet to fully realize the potential of a smart public transport service in optimizing the balance between supply and demand. This study proposes

While large humanitarian organizations (HOs) such as the United Nations Humanitarian Response Depot preposition relief items at strategic hubs during the preparedness phase, many local HOs procure relief supplies only after assessing beneficiaries’ needs in the response phase. This often leads to procurement and last-mile distribution challenges due to disrupted road infrastructure, coordination issues

As the scale of container shipping continuously increases driven by mega vessels and rising transportation demands, Automated Container Terminals (ACTs) have emerged as a promising solution to enhance operational efficiency, leveraging technologies such as automated guided vehicles (AGVs) for container transporting tasks. The AGV traffic within the transportation area, serving as a critical link between

The emerging modular autonomous vehicle (MAV) provides new opportunities to address the imbalance between supply and demand in the public transportation system. The continuous approximation (CA) model can efficiently solve the optimal time-varying headway of bus corridors, but the current CA model for MAV corridors does not consider the demand uncertainty, and its vehicle formation method still has

The global ship recycling industry, dominated by South Asia, faces increasing scrutiny over environmental and safety practices. Simultaneously, a growing move away from coal in the run-up to 2050 will threaten coal ports, challenging them to diversify. This study explores the potential of embedding ship recycling into the transport geography of coal ports that are diversifying to circular economy hubs

Operational efficiency in last-mile logistics (LML) is often hindered by fluctuating e-commerce demand, unforeseen disruptions, and diverse stakeholders with evolving objectives. This paper aims to evaluate the effectiveness of Physical Internet hubs (PI-hubs) in addressing LML challenges by developing an intelligent multi-agent system (iMAS) that focuses on stakeholders’ interactions. In the iMAS

The road transportation contributes to a large portion of global carbon emissions each year. This carbon emission can be significantly reduced through collaboration among carriers. In this paper, a multi-round combinatorial double auction with both requests exchange and carbon emission permits trading is proposed for carrier collaboration, where each carrier may play a double role as both a seller

Urban rail transit systems exhibit substantial energy consumption, underpinning the significance of energy-saving optimization strategies for train timetables. Conventionally, trains operate according to an energy-efficient timetable formulated offline. However, station incidents and disturbances often result in deviations from the planned schedule, leading to additional energy expenditure. To address

The autonomous garbage truck armed with garbage collector robots for unloading/loading waste will be essential for municipal waste collection in Industry 5.0. Due to the juvenility of garbage collector robots, it is significant to reconcile autonomous garbage trucks and sanitation workers in municipal waste management in transition to Industry 5.0. This paper focuses on reconciling the multiple-period

The rapid expansion of online marketplaces has given rise not only to private label (PL) introduction but also to an efficiency and security trade-off in sharing consumer data. This research constructs a supply chain model based on game theory that includes a manufacturer and an e-tailer. The model examines how the manufacturer distributes the national brand (NB) through either a reselling approach

Web 3.0 leverages blockchain technology to build trustless and transparent systems, ensuring that data and transactions are recorded on decentralized ledgers. Consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS) are crucial for maintaining the decentralized and secure nature of blockchain networks, ensuring that all transactions are verified and consistent across the network. This

The age of automation and intelligence requires upgrading conventional terminals (CTs) with automated ones in the port industry. This paper examines how to optimally decide the size and timing of this upgrade under demand and technological uncertainties. We use the real options approach to derive the optimal upgrade decisions for two options: the upgrade option when the port decision maker upgrades

Ridesharing (RS), with one driver serving a rider with similar route and schedule, has long been regarded as a charming paradigm for eco-friendly mobility. However, despite the rapid growth of shared mobility platforms, ridesharing demand remains relatively low. To design appropriate network-based policies to stimulate ridesharing, solving the traffic assignment problem in the presence of ridesharing

The emergence of live-streaming channels has changed the traditional online channels though, and has opened up opportunities for manufacturers. We consider a manufacturer cooperating with an online platform operating with two selling channels: live-streaming and agency channels. The manufacturer can choose an internal or external anchor to introduce its products in the live-streaming channel. The external

While an increasing number of firms are recognizing the benefits of supply chain (SC) digitalization and implementing it, many still struggle to realize the expected returns. To address this challenge, we propose a model grounded in the practice-based view, aiming to thoroughly investigate the relationships between SC digitalization, resource orchestration capabilities (ROCs), business model design

Disruptions can render parts of the critical transportation systems unavailable, forcing both trains and passengers to adapt. This study addresses the integrated rescheduling problem in a high-speed railway network during severe disruptions, focusing on train routing, timetable adjustments, and passenger reassignment. We employ rescheduling strategies that allow disrupted trains to reroute through

Supply chain networks face the critical challenge of enhancing resilience to disruptions while controlling the costs associated with resilience improvements. In this paper, we introduce an adaptive resilience improvement framework designed to sustain material flow by responding dynamically to emerging network vulnerabilities. Our framework centers on the production chain as a core element in resilience

Multiple discrete–continuous extreme value (MDCEV) model has received increasing attention in modeling travelers’ time allocation. However, the MDCEV model primarily focuses on activity choices that generate increased utility over time, overlooking the fact that travel, as a derived activity, is typically something people prefer to save time on. To bridge the research gap, we introduce the bi-mode

We analyze a crowdfunding market with backers, a platform, and a creator to identify potential causes of delivery delay issues and evaluate the effectiveness of solutions. There are two types of actual delivery times for the creator, and the delivery time of the high-type is stochastically faster than the delivery time of the low-type. We first analyze the promised delivery time decisions and the first-best

In the context of escalating global geopolitical risk, relying solely on a firm’s own risk awareness is insufficient to ensure operational continuity. Different risk perceptions among supply chain members can lead to inconsistencies in risk assessment and response strategies, thereby undermining a firm’s ability to effectively manage political risk. However, existing research often overlooks the presence

Maritime chokepoints are crucial nodes in international supply chains, facilitating most of the global freight transport and the distribution of industrial raw materials and goods. However, these chokepoints are vulnerable to disruptions from severe weather, traffic accidents, and unpredictable factors, significantly impacting global maritime networks. Therefore, it is crucial to understand the role

This paper addresses a critical yet underexplored contract selection and design problem for manufacturers in a decentralized two-echelon system with multiple contractors. We analyze two prevalent outsourcing service contracts – semi-outsourcing and full outsourcing – where the manufacturer must simultaneously optimize inventory allocation and pricing decisions to strategically influence contractor

Advancements in digital technologies have catalyzed the emergence of the ship-then-shop subscription service, which offers consumers a personalized shopping experience. Using this service, consumers could either receive products regularly at a fixed frequency, i.e., fixed shipment frequency service (FSF), or place orders as needed under on-demand service (ODS) by paying a service fee for each shipment

In reality, more and more airlines outsource maintenance tasks to the maintenance, repair, and overhaul (MRO) service provider to achieve cost-effective operational planning. However, the existing literature mainly focuses on the optimal decisions from the perspective of the airline, which usually ignores the resource scarcity of the maintenance service provider (MSP) and provides “virtual optimal”

E-commerce has been growing at an unprecedented rate over the last decade. Nowadays, products are sold either on online e-platforms or at traditional offline stores. Two online operation modes between suppliers and e-platforms are dominant: reselling and agency. We examine the supplier’s trade-offs for blockchain technology adoption in both online operation modes. There are two potential win–win scenarios

E-commerce platforms (EPs) commonly provide information services. This study explores an EP’s information service strategy and an original equipment manufacturer’s (OEM) quality strategy in a supply chain. The OEM outsources production to a competing contract manufacturer (CM), and both the OEM and the CM sell their products through the platform, paying a preset commission. The EP decides whether to

With significant advancements in platform economy and big data technologies, service providers can implement highly targeted discriminatory pricing strategies, as exemplified by charging different prices to fresh and frequent customers for identical products. This practice raises significant concerns about fairness and consumer protection. Motivated by these real-world observations, we develop a two-period

Graph neural networks (GNNs) have been widely applied in traffic demand prediction, and traffic modes can be divided into station-based modes, such as buses and subways, and station-free modes, such as ride-hailing and bike-sharing. Existing research in traffic graph construction primarily relies on the distribution of actual traffic stations to build graphs based on the road network. However, station-free

The growth of e-commerce has driven numerous suppliers to adopt live-stream channels. However, most studies fail to account for capacity limitations in supply chains. This study examines a supplier with limited capacity collaborating with a streamer to conduct live-stream sales. Using a game-theoretical approach, we analyze how capacity constraints affect a supplier’s decision to introduce live streaming

Inland waterway transport (IWT) has gained significant attention for its environmental sustainability. Consequently, there is an increasing focus on boosting IWT’s market share to reduce transportation emissions. Accurate forecasting of IWT freight demand is crucial for ports to plan long-term targets and support a mode shift towards sustainable transport. However, forecasting IWT demand is challenging

As advanced driver-assistance systems (ADAS) are more widely implemented—particularly the adaptive cruise control (ACC) system in car-following behavior—accurate modeling of ACC vehicles’ behavior is needed. Currently, each vehicle manufacturer develops its ACC systems with unique controllers, creating “black boxes” that are not openly accessible for analysis. In addition, the vehicle dynamics that

New retail concepts that embrace a hybrid “online + offline” business paradigm promise super-fast order fulfillment of groceries within the next hour. In this ”online + offline” retail scenario, it is crucial to efficiently fulfill many online orders within the stipulated time while adhering to the layout rules of offline retail products. Zone-picking and overhead conveyors have been introduced to

Ports are central to global trade and transportation, playing a significant role in worldwide carbon emissions. Estimating carbon emissions from ports is crucial for identifying emission sources and devising strategies for their reduction. The procedure of port carbon emission estimation follows the logic of “estimation methods — data acquisition and preprocessing — application realization” and faces

The rise in geopolitical conflicts has created unprecedented risks for firms, particularly in their operations and supply chains. In the wake of the 2022 Russo–Ukrainian War, many multinational enterprises have faced significant challenges in managing these risks, with some becoming “locked-in” to such high-risk regions as Russia. This study explores how firms manage operations under geopolitical conflict

This paper investigates a multi-shift drayage planning problem arising from container truck transportation across multiple terminals within a port area. We consider it at the tactical planning level and determine the optimal truck workload for each shift. The main distinction between our problem and others is the incorporation of multiple shift planning, handling container transportation requests—each

With the development of new technologies, blockchain-based digital maritime trade platforms have been developed to enhance interaction efficiency by involving participants in the platforms and encouraging them to share their related business data. However, it is challenging for platform enterprises to popularize their platforms and encourage participants involved with their platforms to share data

The increased financing demand on retailers and the risk aversion from banks have brought extensive attention on group lending (GL), the emerging bank loan mode in addition to credit financing (CF), which requires the retailers to apply for a group loan with joint liability and the bank to set uniform interest rates. In order to investigate how GL impacts the operational decisions and profits in the

This study explores brand management dynamics in a co-opetitive supply chain, where a strong-brand Original Equipment Manufacturer (OEM) outsources production to a competitively weaker brand Contract Manufacturer (CM). The CM can leverage this outsourcing relationship to engage in a brand-freeriding strategy, enhancing its brand power through spillover effects from the OEM’s brand. However, managing

Remanufacturing faces significant challenges including negative consumer perception and the complex dynamics of cannibalization between new and remanufactured product sales. This paper explores the potential of blockchain technology to enhance consumer value perceptions of remanufactured products and presents a decision-making framework that examines both blockchain adoption strategies and online sales

As consumer demand for fresh products continues to rise, the inefficiencies in cold chain logistics have emerged as a pressing issue, resulting in substantial food waste and compromised product quality. Meanwhile, logistics companies face the dual challenge of reducing costs and carbon emissions while ensuring product freshness. In response to these challenges, this paper proposes a novel target-oriented

Generative Artificial Intelligence (GenAI) is emerging as a transformative force in supply chain resilience, offering new ways to enhance decision-making, automate operations, and improve adaptability to disruptions. Unlike traditional AI, which relies on historical data for prediction and optimization, GenAI can generate novel solutions and simulate alternative scenarios in real time. Despite its

We study a shared vacant private parking spaces allocation problem that considers the uncertain parking duration of demanders. To solve the problem, we first formulate a stochastic programming model (P model). The objective is to maximize the weighted sum of the total expected profits from the platform parking revenue, overload cost and idle cost. On this basis, we reformulate the P model into the

In a mixed traffic environment that consists of both Connected Autonomous Vehicles (CAVs) and Human-driven Vehicles (HVs), the platoon sizes of CAVs play a significant role in traffic flow analysis. However, the statistical properties of these platoon sizes have not been thoroughly addressed in existing research. This study aims to fill this critical gap by modeling CAV platoon sizes as a random variable

With our study, we aimed to enrich the discourse on supply chain disruptions by exploring the strategic responses of firms to supply chain uncertainty (SCUn) that enhance supply chain resilience (SCRes). Drawing on the dynamic capabilities view (DCV), we investigated whether and how firms utilise uncertainty amid geopolitical turmoil as a catalyst to enhance SCRes. This contrasts with the predominant

Accurate prediction of vessel prices across multiple ship types is crucial for providing scientific decision-making support to shipping enterprises, investment institutions, and policymakers. However, traditional statistical methods and machine learning models face significant limitations in accuracy, generalization, applicability, interpretability, and data coverage, rendering them inadequate for

Globally, the expansion of charging infrastructure has lagged behind the rapid adoption of electric vehicles (EVs), causing inconvenience to users due to limited charging station availability. To address this issue, this study proposes a day-ahead scheduling strategy for charging service providers (CSPs) managing multiple stations within their jurisdictions. The strategy optimally assigns charging

In the context of freeway traffic state estimation, this study introduces prescriptive analytics—also known as “predict-then-optimize”—for integrating data from Electronic Toll Collection (ETC) systems and traffic sensors. Traditional single-method data fusion techniques are constrained by inherent limitations. For instance, optimization-based methods are generally predicated on prior assumptions that

The healthcare sector is a major contributor to global carbon emissions, accounting for approximately 4%–5% of greenhouse gases. Despite growing concerns about environmental impacts, existing research largely isolates carbon reduction strategies specific to certain medical processes or supply chain components, neglecting the integrated nature of decision-making among key healthcare stakeholders. This

As a newly emerging mode of shared micro-mobility, the e-bike sharing system (EBSS) is increasingly establishing more stations to meet rising user demand. Due to the vast number of stations and the limited space available on urban streets, the operation of the EBSS largely relies on the platform’s battery swapping. This paper, for the first time, models the EBSS battery swapping problem as a variant

The Russia-Ukraine conflict and international sanctions against Russia have destabilized European segments of Sino-Russian trade corridors, necessitating a shift toward alternative routes. In order to improve the reliability of Sino-Russian trade transportation, a bi-level network optimization model is constructed with considering the geopolitical risks and seasonal Arctic shipping route, where the

Precise and dependable identification of traffic states is crucial for optimizing traffic system, which forms the foundation for mitigating congestion and enhancing the overall efficiency and stability of traffic operations. Existing research has mainly adopted methods such as signal processing methods and traffic fundamental diagrams, but each has its own shortcomings. Therefore, this study introduces