Given the increasing concerns about energy consumption and rising consumer social responsibility, firms producing brown products should consider transitioning to greener alternatives that are less harmful to the environment. To examine this, we employ a Stackelberg model to analyze the price and quality of brown and green products (e.g., gasoline and electric vehicles) across three product-line strategies:

Low-carbon technology sharing (LTS) is often viewed as a positive factor for enterprise operations, which can not only encourage the spread of low carbon technologies but also serve as a source of financing for capital-constrained manufacturers. However, it is not clear how LTS works in a capital-constrained supply chain. This study incorporates LTS into the design of supply chain finance schemes,

This paper investigates a reliable ship fleet planning problem with the uncertainties of container shipping demand, transport costs and freight rates in liner shipping services, and this problem is formulated as a two-stage robust optimization model. In our model, the first-stage decision is to determine the types and quantities of ships, as well as their allocation to different routes, and the second-stage

This study investigates the disclosure strategies for quality information in a dual-channel supply chain comprising a manufacturer and a dual-purpose online platform focusing on both profit and consumer surplus. We elaborate on two disclosure formats: the P-C format, in which the platform discloses quality information, and the M-C format, in which the manufacturer discloses quality information. The

This study investigates a two-echelon supply chain comprising a retailer, who considers whether to sell products as online-exclusive (products available only online) versus hybrid (products available both online and offline), and a supplier, who considers whether to encroach the online market. Given that there are more product varieties online than offline and competitive online marketplace, it remains

Truck platooning is a promising technology for reducing energy consumption, increasing vehicle safety, and improving traffic efficiency. In this paper, we examine the cost-effectiveness of truck platooning from the perspective of a freight company fulfilling full truckload pickup and delivery requests over a transportation network. During transportation, trucks can form platoons on the traversed road

Container shipping demands are usually classified into long-term contract demands from large shippers and ad hoc demands from spot shippers. Compared with stable long-term contract demands, spot container shipping demands are often unstable due to their high frequent cancellations during the slot booking period and their uncertain arrivals even no-shows. This poses a challenge for shipping companies

Logistics service affects product sales and therefore plays a vital role in influencing the selling mode strategy. We investigate how two types of logistics service, namely third-party service and platform service, impact the selling mode choice between reselling and agency selling. We identify that the platform’s commission rate and product-service efficiency jointly shape the selling mode strategy

This study investigates an on-demand first-and-last-mile ridesharing service (FLRS) problem considering the time-dependent travel time for an operator who manage a heterogeneous vehicle fleet. The operator, aiming to minimize the total operational cost, needs to simultaneously serve both first-mile (FM) and last-mile (LM) trips around a public transportation hub, such as a metro station. To holistically

Massive COVID-19 vaccination can significantly reduce both mild and severe infection rates. Some governments have adopted mobile vaccination vehicles, offering a more convenient and flexible service compared to static walk-in sites. This paper addresses a new scheduling problem arising from the mobile COVID-19 vaccination planning practice. Given a set of communities, each with a specific number of

This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing

Trade-in and resale programs are increasingly adopted by retail platforms, boosting sales and generating additional profits through the resale of used products. Consequently, manufacturers selling new products on these platforms should re-evaluate their selling strategies (wholesale or agency). We construct a game-theoretic model to examine when a retail platform should introduce trade-in and resale

Online-ordered meal logistics services (OMLSs) that accept online bookings and make vehicle plans to deliver meals from restaurants to customers have recently emerged. Customers have the option to cancel orders that are not delivered by appointment times, leading to significant financial, reputational, and customer losses for the OMLS providers. This study aims to make an appropriate vehicle plan for

The ongoing advancement of 3D printing technology provides an innovative approach to addressing challenges in disaster relief operations. By utilizing a variety of printing materials, 3D printers can produce essential disaster relief resources needed for disaster relief, effectively satisfying the varied demands that arise after disasters. This paper examines the joint optimization of pre-disaster

By leveraging the derived revenue from subscription services, our study investigates the feasibility of shared bicycle platforms using pricing strategies for these services to enhance their market competitiveness. We establish that, in scenarios where platforms set prices independently, the derived revenue can effectively counterbalance the potential deficits stemming from service expenditures. In

Current methods for detecting outliers in traffic streaming data often struggle to capture real-time dynamic changes in traffic conditions and differentiate between genuine changes and anomalies. This study proposes a novel approach to outlier detection in traffic streaming data that effectively addresses stochasticity and uncertainty in observations. The proposed method utilizes Stochastic Differential

Travel time estimation is important for instant delivery, vehicle routing, and ride-hailing. Most studies estimate the travel time of specified routes, and only a few studies pay attention to origin–destination travel time estimation (OD-TTE) without a specified route. Moreover, most of these studies on OD-TTE ignore the personalized route preference and the cost of data annotation. To fill this research

As ride-hailing services have experienced significant growth, most research has concentrated on the dispatching mode, where drivers must accept the platform’s assigned trip requests. However, the broadcasting mode, in which drivers can freely choose their preferred orders from those broadcast by the platform, has received less attention. One crucial but challenging task in such a system is the determination

Our study identifies major impediments (or inhibitors) faced by Transportation Network Companies (TNCs) such as Uber, Lyft, and Ola within the context of developing nations. While existing studies on TNCs centered on passenger adoption and drivers’ perspectives, we quantitively assess the inhibitors and provide mitigation strategies. To achieve this, we use machine learning methods, particularly Latent

Volatility in freight rates and shipping demand poses financial risks for charterers and ship owners. Freight forward agreements (FFAs) are popular hedging tools for fixing freight rates in advance by specifying the amount of cargo to be transported at the maturity period of the agreement. Procurement decisions with FFAs require assessing future freight rates and shipping demand. Accepting an FFA price

Motivated by the widespread adoption of corporate social responsibility (CSR), we investigate a socially responsible e-commerce supply chain where the E-platform owns a store brand product and supports online sales of the manufacturer’s product under agency selling or reselling. The socially responsible firm has a mixed objective of its profit and consumer surplus. We explore how the firms’ CSR concern

This paper investigates an urban Emergency Evacuation Network Design (EEND) problem on a large scale when geographical risk in different areas varies. The decisions to make are (i) determining active shelters, (ii) selecting evacuation routes, and (iii) managing the supply of relief commodities from distribution centers to shelters. A region prone to floods and hurricanes is divided into zones, each

Stockyard allocation is a crucial segment of operational decision-making in dry bulk ports (DBPs). The stockyard allocation plan determines the storage position and duration of each stockpile to avoid operational delays in stockyards. Spraying operations, a unique operation in DBPs, are significantly influenced by stockyard allocation plans. Port operators regularly conduct spraying operations to prevent

Quota systems play a crucial role in regulating public-interest goods and controlling negative externalities, with a primary focus on social impacts rather than economic benefits. This paper examines the decision-making process for quota release, aiming to control growth rates and ensure price stability over time. We first develop a chance-constrained problem for quota systems, solving it using sample

The multi-modal public transportation system incorporating the electric bus network and the metro network plays a crucial role in meeting the daily transportation demands in urban areas. However, the inadequate connectivity between the electric bus network and the metro network has resulted in poor resilience of the multi-modal public transportation system. When disruptions occur at metro links or

The Cyber-Physical Internet (CPI) is a cutting-edge concept that brings together physical systems and cyber technologies to enable seamless interaction between the physical and virtual worlds. This innovative approach is revolutionizing the transportation industry by paving the way for a new era of logistics and transport networks. Introducing CPI into the procurement of transport services is leading

Vaccination is a crucial way to combat the pandemic; in other words, vaccines play an important role in controlling the spread of the virus and ultimately ending the pandemic. This study presents a multi-objective mixed integer linear programming model for the vaccine supply chain considering uncertain cost, vaccine purchase, and lead time. Through the utilization of Internet of Things technology,

During a pandemic, transportation authorities and policymakers face significant challenges in identifying and validating new travel behavior and how it affects traffic crash patterns to develop effective safety strategies. A timely assessment of an emergency incident’s long-term impact and the development of appropriate response strategies are critical for managing future occurrences. This study investigates

With the escalating issue of plastic pollution, exploring suitable post-consumer plastic waste (PCPW) recycling holds significant importance for global environmental protection. To address this issue, this paper proposes a novel PCPW recycling platform (PRP) that offers two recycling strategies to improve the recycling level of PCPW. Then, we construct a Stackelberg game model to analyze and compare

In this paper, we explore the impact of carbon trading on the safety stock placement optimization in multi-echelon supply chains. The carbon emission in each stage of the supply chain is measured through a function of the service time quoted by the stage as a key variable. Adopting the guaranteed service time modelling framework, we develop a safety stock placement model under the carbon cap-and-trade

This study proposes a simulation-based optimization approach to address the recharging scheduling problem of electric buses to minimize charging waiting time. Poor scheduling could lead to longer waiting times and potentially affect operation schedules regarding time and service quality. This study addresses a simulation-based optimization framework to evaluate various performance metrics during electric

The majority of related research has traditionally focused on examining the individual influences of national governance capacity and technological innovation on carbon emissions and economic performance, neglecting the effects and influence mechanisms on carbon efficiency within agricultural supply chains, which is not conducive to advancing a low-carbon transition that includes agricultural concerns

This paper studied the optimal pricing strategy based on a highly realistic pricing scheme in order to maximize the revenue of a service modeled as an M/G/m/m loss system. The blocking probability is considered together to prevent compromising the quality of service. Customers’ willingness-to-pay is regarded to be randomly distributed, indicating price-dependent arrival. Considering the severe complexity

Perturbations are universal in supply chains, and their appearance has become more frequent in the past few years due to global events. These perturbations affect industries and could significantly impact production, quality, cost/profitability, and consumer satisfaction. In large-scale contexts, companies rely on operations research techniques. In such a case, re-optimization can support companies

This paper develops a mathematical model to characterize a generalized ride-sourcing market with a third-party integrator and multiple competitive ride-sourcing platforms. Different from earlier works which normally assume instant matching strategies, our model can characterize the integrator’s and platforms’ decisions on choosing flexible matching strategies under batch matching mechanisms and their

Amid increasing environmental concerns, electric vehicles (EVs) are gaining traction as a sustainable transportation alternative. However, the widespread adoption of EVs is hindered by range limitations, inadequate charging infrastructure, and unpredictable access to charging facilities. The battery swapping van (BV) has been proposed as an innovative approach to actively offer on-demand charging at

Severe shortages of healthcare resources are major challenges in pandemics, especially in their early stages. To improve emergency management efficiency, this paper proposes a novel rolling predict-then-optimize framework that includes three interactive modules, i.e., data-driven demand prediction, healthcare resource allocation, and parameter rolling update. Such a framework uses historical data to

Remanufacturing activities in reverse logistics hold significant theoretical and practical value for their obvious economic and environmental benefits. However, the ever-changing market demand and the uncertain quality of returned items make the management of remanufacturing production highly challenging. Previous studies have mainly focused on determining the optimal remanufacturing decisions based

This paper investigates the sellers’ optimal rebate provision strategies in a supply chain setting wherein two competing sellers offer substitutable products via a common platform, and can choose whether to provide rebates to boost their respective sales. We consider two selling formats: wholesale format and agency format (with exogenous commission rate) to capture the interaction between the sellers

This article studies a novel makespan minimization problem for locker-based drone delivery in which several automatic drones take lockers as launching and landing platforms. It is a vehicle routing and machine scheduling hybrid problem with formulation and solution challenges. Firstly, we formally define the problem and analyze its complexity. Secondly, we formulate an integer linear program model

As one of China’s three development strategies, the Yangtze River Economic Belt (YEB) strategy plays an important role in strengthening the development of port–city synergy. This study uses the difference-in-differences (DID) approach to investigate the impact of the YEB strategy on port–city synergy development, with panel data for 15 port–city pairs along the YEB over the period 2005–2019. The results

In a prolonged transitional period, the urban transportation infrastructure is expected to accommodate two different types of vehicles. One type of vehicle is the human-driven vehicle (HV) and the other is the connected and autonomous vehicle (CAV). Nevertheless, the conflict between HVs and CAVs in the mixed traffic scenario significantly impedes the efficiency-improvement benefit of implementing

In online sales, e-commerce platforms commonly employ marketplace and reselling modes. Motivated by this industry practice, this study investigates which sales mode a platform should choose and how the platform should contract with a manufacturer in each mode. We consider that advertising effectiveness is the platform’s private information. A game-theoretic model is developed to explore the advertising

The fleet sizing problem is one of the main concerns for an industry shipping company under various uncertainty of market conditions. This paper addresses the problem in a single period with uncertain shipment demand for an oil shipping company, who transports the refined petroleum products among multiple origin–destination (OD) pairs. Besides the self-owned vessels, the time-chartered and voyage-chartered

This paper examines a two-echelon supply chain consisting of a retailer and a manufacturer under two-way information asymmetry, in which the two actors have private demand and cost information, respectively. In response to the uncertainty caused by information asymmetry, a robust optimization approach is used to model the risk-averse behavior of the enterprises in the game. We incorporate an information

High-accuracy long-coverage vehicle trajectory data can benefit the investigations of various traffic phenomena. However, existing datasets frequently contain broken trajectories due to sensing limitations, which impedes a thorough understanding of traffic. To address this issue, this paper proposes a Physics-Informed Neural Network (PINN)-based method for stitching broken trajectories. The proposed

In the luxury industry, fashion brands like Burberry and Cartier are reported to destroy leftover products at the end of the selling season (Scenario BC). This helps to maintain products’ exclusivity image but creates a loss of goodwill because consumers in the market commonly value sustainability and responsibility. In the sharing economy, luxury fashion brands can sell their leftover products to

Shipping freight contracts are heterogeneous services surrounded by asymmetric information and traded in over-the-counter markets, where the physical market agents help match ship operators and charterers. These contracts create opportunities for negotiations tailored to traders’ needs. Despite the ubiquitous role of bargaining in establishing freight contracts, the shipping literature lacks systematic

The rise of unmanned aircraft systems (UAS) for urban drone delivery introduces significant risks, particularly the potential for crash-induced fatalities on the ground. A crucial strategy to address this challenge is through risk assessment and mitigation of flight routes that consider the stochastic nature of urban populations. Traditional strategies treat drone flight route approval and execution

An urban mobility system serves as a highly intricate and nonlinear mega-system facilitating the movement of people, goods, and services across spatio-temporaldomains. This complexity stems from factors such as intricate interactions between transportation supply and demand, and the inherent stochastic nature of an open, heterogeneous, and adaptable system. Successfully comprehending and navigating

The food transportation and distribution industry has been radically disrupted over the last few years, especially amid the COVID-19 pandemic. Food prices, for example, have been seen to increase considerably in the wave of economic inflation. As two main driving factors in the context of food transportation, (1) the rising diesel prices and (2) the prevailing shortage of truck drivers have posed threatening

This study examines the joint optimization decisions on production quantity and sustainable investment of two competing low-carbon manufacturers with loss aversion and reference dependence under the cap-and-trade policy. We focus on exploring the impacts of manufacturers’ risk attitude, encompassing factors like the degree of loss aversion and reference dependence, the cap-and-trade policy, and heterogeneous

The multicommodity capacitated fixed-charge network design problem has been extensively studied in the literature due to its wide range of applications. Despite the fact that many sophisticated solution methods exist today, finding high-quality solutions to large-scale instances remains challenging. In this paper, we explore how a data-driven approach can help improve upon the state of the art. By

The frequency and intensity of global disasters, including the COVID-19 pandemic, and natural disasters such as earthquakes, floods, and wildfires, are increasing, necessitating effective emergency logistics management. Climate change significantly contributes to these events, emphasizing the importance of limiting human and environmental impacts. The transportation sector, particularly the automobile

Coordinated truck and drone delivery is gaining popularity in logistics as it can greatly reduce operation costs. However, existing studies on related operations management problems typically ignore the following important features: (i) the random appearance of requests, which require operators to dynamically respond to the requests; and (ii) the decisions of optimal launch and retrieval locations

Rising demand for ride-hailing services and e-commerce delivery intensifies competition for urban curbside spaces, leading to uncoordinated travel behavior, increased traffic congestion and social costs. One possible solution to address those issues is Smart Loading Zones (SLZs), equipped with advanced technologies to optimize curbside use. Yet, the real-world impact of SLZs on traffic flow is unclear

About three years after the start of the COVID-19 pandemic disrupting global supply chains, companies increasingly focus on creating supply chains that are resilient to the next disruption. While researchers have developed multiple frameworks and quantitative models for assessing risk in supply chains, the question of how to measure supply chain resilience (SCR) with key performance indicators (KPIs)

This paper investigates reverse channel selection within a closed-loop supply chain, emphasizing the dynamic characteristics and potential stochastic disturbances inherent in the collection process. We construct three stochastic differential games to model scenarios where the manufacturer, retailer, and third-party each manage the collection of used products, deriving the corresponding equilibrium

This paper studies how different types of demand cannibalization take place during product rollovers and their effects on a firm’s profitability. Due to continuous product upgrades, demand cannibalization among various generations of products has become a common practice, raising interesting investigations from professionals and academics. Within this context, we model firms’ and customers’ decision-making

This study presents a comprehensive literature analysis to explore the role of Alternative Delivery Points (ADPs), such as parcel lockers (PLs), within logistics and transportation. Through a structured methodology that includes the ‘Plan,’ ‘Design,’ and ‘Evaluation’ stages, this research provides a new perspective on the research gaps, obstacles, and prospective areas for future study in the domain