Editor’s Choice Articles

Background: Effective supply chain management (SCM) is widely considered vital for enhancing business sustainability, yet empirical evidence across industries and contexts remains limited. This paper aims to address this gap by presenting empirical findings specific to a particular industry, business size, and economic setting. Methods: The data are collected from small- and medium-sized water bottling companies in Ethiopia utilizing a Likert scale questionnaire and analyzed using SPPS version 29 using multi-variable regression analysis. Results: The findings reveal a statistically significant positive influence of supply chain management practices on economic, environmental, and social sustainability business performances. Accordingly, supply chain internal practices and customer and supplier integration impact business economic sustainability, while customer and supplier integration affect business environmental sustainability performance. Customer integration, supplier integration, and supply chain internal practices significantly influence business social sustainability performance. Conclusions: These results highlight the potential for businesses to achieve holistic sustainability goals through targeted improvements in SCM practices. The research results are consistent with most previous studies on this topic, except for a few variations that may need further investigation. The discussion highlighted the intricate links between supply chain management practices and business sustainability, underscoring the need for comprehensive further empirical studies in various contexts. Full article

Background: Container terminals are a pivotal part of global logistics networks, influencing supply chain reliability and port competitiveness. Traditional performance evaluation methods, such as KPI-based assessments or multi-criteria analyses, often fail in dynamic operational conditions with inherent uncertainty and variability. Methods: This study proposes a normalization-based framework to evaluate container terminal performance by standardizing operational parameters, including availability, non-productive operations, operation time, energy consumption, and throughput. The methodology involves parameter definition, normalization, weight assignment, index calculation, and performance classification. Results: The findings demonstrate that normalization ensures a transparent and adaptable evaluation framework. Sample calculations show how parameter weights influence terminal assessments across varied scenarios, confirming the robustness of the proposed method in capturing dynamic operational changes. Conclusions: Normalization offers a practical tool for enhancing container terminal efficiency and competitiveness. It enables decision-makers to adapt strategies to changing priorities, such as throughput maximization or energy efficiency, ensuring comprehensive and reliable performance assessments. Full article

Background: Today’s healthcare requires a modern style of management that adapts to the needs of both patients and employees. Imaging diagnostics has its specificity in the entire area of hospital logistics and influences the organization of work and patient care. Modern managers should have special competencies to meet the expectations of patients, employees, and organizations. Aim: The main purpose of article was to define the role, competencies, and skills that managers should have in the field of diagnostic imaging. Methods: In the research part, a questionnaire survey and in-depth interviewing were used. The research group consisted of 10 managers and 300 medical staff, i.e., radiologists, nurses, and electroradiology technicians. Results: The decision-making role of the manager and their interpersonal skills were recognized to be most crucial. According to the respondents, managers should ensure good work organization and provide safe working conditions. Employees appreciated the manager’s ability to react in crisis situations as well as their high professionalism. The ability to communicate and resolve conflicts in a team was considered the most important psychological and social competence. Conclusions: A good manager, in the opinion of the respondents, is a decision-making, empathetic, and flexible person with strong leadership characteristics. Full article

Background: This study explores forklift operators’ situational awareness (SA) and human errors in logistic operations using a multiphase approach as an innovative methodology. Methods: Ethnography, eye tracking, error taxonomy, and retrospective think-aloud (RTA) were used to study the diverse cognitive, behavioral, and operational aspects affecting SA. After analyzing 566 events across 18 tasks, this research highlighted eye tracking’s potential by offering real-time insights into operator behavior and RTA’s potential as a method for cross-checking the causal factors underlying errors. Results: Critical tasks, like positioning forklifts and lowering pallets, significantly impact incident occurrence, while high-cognitive demand tasks, such as hoisting and identifying pedestrians/obstacles, reduce SA and increase errors. Driving tasks are particularly vulnerable to errors and are the most affected by operator risk generators (ORGs), representing 42% of incident risk events. This study identifies driving, hoisting, and lowering loads as the tasks most influenced by system factors. Limitations include the task difficulty levels, managing physical risk, and training. Future research is suggested in autonomous industrial vehicles and advanced driver assistance systems (ADASs). Conclusions: This study provides valuable insights into how we may improve safety in logistics operations by proposing a multiphase methodology to uncover the patterns of attention, perception, and cognitive errors and their impact on decision-making. Full article

Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders. Full article

Background: The rise in natural and man-made disasters has increased the need for effective search-and-rescue tools, particularly in resource-limited areas. Unmanned Aerial Vehicles (UAVs) are increasingly used for this purpose due to their flexibility and lower operational costs. However, finding the most efficient paths for these UAVs remains a challenge, as it is essential to maximize victim location and minimize mission time. Methods: This study presents an autonomous UAV-based approach for identifying victims, prioritizing high-risk areas and those needing urgent medical attention. Unlike other methods focused solely on minimizing mission time, this approach emphasizes high-risk zones and potential secondary disaster areas. Using a partially observable Markov decision process, it simulates victim detection through an image classification algorithm, enabling efficient and independent operation. Results: Experiments with real data indicate that this approach reduces risk by 66% during the mission’s first half while autonomously identifying victims without human intervention. Conclusions: This study demonstrates the capability of autonomous UAV systems to improve search-and-rescue efforts in disaster-prone, resource-constrained regions by effectively prioritizing high-risk areas, thereby reducing mission risk and improving response efficiency. Full article

Background: Despite the resurgence of interest in augmented reality (AR) due to Industry 4.0 and its ability to resolve several challenges faced by current business models, comprehensive research examining the capabilities of AR in supply chain management (SCM) and logistics remains limited. This article aims to investigate the potential effects of AR technology on organizational performance through the mediation role of SCM and logistics value chain functions to address the existing knowledge gap. Methods: This research employed a cross-sectional design and an explanatory survey as a deductive approach for hypothesis development. The primary data collection method involved the self-administration of a questionnaire to furniture suppliers located in the Gulf Cooperation Council (GCC), including six countries. Of the 656 questionnaires submitted to suppliers, 483 were considered usable, yielding a response rate of 73.6%. The research utilized partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) techniques to evaluate the gathered data. Results: The current paper’s statistical evidence demonstrates that AR implementation has a positive impact on the supply and logistics value chain activities and organizational performance of furniture suppliers in the GCC region. Moreover, it illustrates that the design and planning variable of supply chain value dominates as the primary predictor of organization performance. The results indicated that the ANN strategy provided a more comprehensive explanation of internally generated constructs compared to the PLS-SEM technique. Conclusions: This study demonstrates its usefulness by advising furniture industry decision-makers on what to avoid and what aspects to consider when creating plans and regulations. The report also suggests operations managers apply machine learning (ANN) for prediction and decision-making in supply and operations value chains. This essay looks at how the AR and resource-based supply value chain view may affect company performance across countries, firm sizes, and ages. Full article

Background: Warehousing operations, crucial to logistics and supply chain management, often seek innovative technologies to boost efficiency and reduce costs. For instance, AR devices have shown the potential to significantly reduce operational costs by up to 20% in similar industries. Therefore, this paper delves into the pivotal role of smart glasses in revolutionising warehouse effectiveness and efficiency, recognising their transformative potential. However, challenges such as employee resistance and health concerns highlight the need for a balanced trade-off between operational effectiveness and human acceptance. Methods: This study uses scenario and regression analyses to examine data from a German logistics service provider (LSP). Additionally, structured interviews with employees from various LSPs provide valuable insights into human acceptance. Results: The findings reveal that smart glasses convert dead time into value-added time, significantly enhancing the efficiency of order picking processes. Despite the economic benefits, including higher profits and competitive advantages, the lack of employee acceptance due to health concerns still needs to be addressed. Conclusions: After weighing the financial advantages against health impairments, the study recommends implementing smart glass technology in picking processes, given the current state of technical development. This study’s practical implications include guiding LSPs in technology adoption strategies, while theoretically, it adds to the body of knowledge on the human-technology interface in logistics. Full article

Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the rapid and secure delivery of medical samples, particularly in urban and remote regions where traditional transportation methods often face challenges. Drawing from recent studies and case reports, the review highlights the role of technologies such as artificial intelligence (AI)-driven navigation systems, real-time monitoring, and secure payload management in mitigating logistical barriers like traffic congestion and geographical isolation. Results: Based on findings from various case studies, the review demonstrates how drones can significantly reduce transportation time and costs, while improving accessibility to healthcare services in underserved areas. Conclusions: This paper concludes that, while challenges such as regulatory hurdles and privacy concerns remain, ongoing technological advancements and the development of supportive regulatory frameworks have the potential to revolutionize medical logistics, ultimately improving patient outcomes and healthcare delivery. Full article

Background: As road transport companies increasingly integrate electric trucks (eTrucks) into urban fleets, evaluating their performance in real-world conditions is essential for effective fleet management and infrastructure planning. Methods: This study introduces TraPodSim, a simulation system designed to assess the key performance indicators (KPIs) of eTrucks and other vehicle types. Using real geographic data, transportation routes, and technical vehicle specifications, the system simulates daily operations under user-defined conditions. Results: TraPodSim produces 20 physical indicators, providing detailed insights into the daily performance of each vehicle in the fleet. These indicators help evaluate fleet efficiency, energy consumption, and overall operational effectiveness. Conclusions: TraPodSim offers transport companies a valuable tool for optimizing fleet configurations and analyzing the use of private or public battery-charging stations, enabling the efficient integration of eTrucks into existing transportation networks. Full article

Background: The global pharmaceutical industry is crucial for providing medications but faces challenges in distributing products safely, especially in tropical and remote areas. Pharmaceuticals require careful transport control to maintain quality; therefore, manufacturers must adopt optimal distribution strategies to ensure product quality throughout the supply chain. The current research focused on creating a model to assess risk levels and predict risk categorization (low, moderate, and high) associated with thermal mapping across pharmaceutical transportation pathways. Methods: Data from a company for pharmaceutical logistics in Brazil were used. The data had 85,261 instances and six attributes (season, origin, destination, route, temperature, and temperature excursion). The dataset consisted of critical destinations, including the shipment time, cargo temperature, and route information. The classification algorithms (CART-Decision Tree, NB-Naive Bayes, and MP-Multilayer Perceptron) were used to build up a model of rules for predicting risk levels in thermal mapping routes; Results: The MP model presented the best performance, indicating a better application probability. The machine learning model is the basis for an automated risk prediction for routes of pharmaceutical transportation; Conclusions: the developed MP model might automatically predict risk during the distribution of pharmaceutical products, which might lead to optimizing time and costs. Full article

Background: This work is part of the regional research project PIPER—Intelligent Platform for the Optimization of Recycling Operations, which aims to develop a network design model for waste collection in the metropolitan city of Rome, Italy. The goal is to enhance the strategic planning of treatment and disposal facilities by incorporating transshipment locations to improve the efficiency of waste collection. The motivation for this study stems from the stringent targets set by the European Green Deal to achieve near-zero emissions and the critical role of waste management in realizing circular economy practices. Methods: The problem is formulated as a mixed integer linear program (MILP) that includes constraints on vehicle allocation to shifts and driver requirements. An additional feature of the model is its ability to account for vehicle maintenance issues when deployed on consecutive shifts. Results: The model was tested against a real-world case study in Rome and demonstrated significant potential savings, with a reduction in total traveled distance exceeding 10%. The mathematical model was also used for evaluating strategic scenarios in a “what-if” analysis, allowing the municipal collection company to assess location options for depots, waste treatment facilities, and transshipment points, as well as to optimize the fleet composition and driver allocation during work shifts. Conclusions: This study presents a robust tool for strategic planning in waste collection operations, highlighting the benefits of using transshipment locations to improve efficiency. The findings indicate substantial potential for cost savings and operational improvements, making the model a valuable asset for municipal waste management planning. Full article

Background: Various innovations have been proposed to improve the efficiency and sustainability of last-mile delivery in urban and rural environments. Notable examples of innovative delivery solutions are parcel lockers, cargo bicycles, crowdsourced delivery, and so on. Methods: This study contributes to the ongoing research by developing a large-scale digital model of England and Wales to evaluate a new generation of solutions for last-mile delivery challenges being faced in both rural areas and cities. The two innovations chosen for comparison in this study are (i) carrier consolidation and (ii) alternative delivery locations (i.e., delivery to the workplace instead of the home). As well as the effect on any individual locations, the digital model evaluates both the benefits for England and Wales as a whole. Furthermore, the influence of the market share on the results, as well as the effect of changing the number of depots, is assessed. Results: By delivering to the customer’s workplace instead of the home, the vehicle kilometres travelled (VKT) reduce slightly (less than 10%). Carrier consolidation shows significant potential in reducing the overall VKT (up to 53%). When looking at individual areas in isolation, the consolidation option reduces the VKT or changes it up and down all within tolerance. Naturally, the first option causes a significant shift in delivery activity across England and Wales. Areas of central London would see in-excess of a 10-fold increase in the number of parcels delivered, whereas the demand for parcels in rural areas is further, and significantly reduced. Conclusions: This study highlights the importance of large-scale and detailed digital models that not only calculate the overall benefits of an innovation but also their effect on each individual area. Full article

The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry. Full article

Background: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions reductions are constrained by technological and commercial realities. BEVs and FCEVs are expensive. Further, BEVs depend on existing electricity grids and FCEVs rely on steam–methane reforming (SMR) or electrolysis using existing grids to produce hydrogen. Methods: This study assembles publicly available data from reputable sources to estimate breakeven vehicle purchase prices under various conditions to match conventional (diesel) truck prices. It also estimates GHG emissions reductions. Results: BEVs face numerous obstacles, including (1) limited range; (2) heavy batteries and reduced cargo capacity; (3) long recharging time; and (4) uncertain hours-of-service (HOS) implications. On the other hand, FCEVs face two primary obstacles: (1) cost and availability of hydrogen and (2) cost of fuel cells. Conclusions: In estimating emissions reductions and economic feasibility of BEVs and FCEVs versus diesel trucks, the primary contributions of this study involve its consideration of vehicle prices, carbon taxes, and electricity grid capacity constraints and demand fees. As electricity grids reduce their emissions intensity, grid congestion and capacity constraints, opportunities arise for BEVs. On the other hand, rising electricity demand fees benefit FCEVs, with SMR-produced hydrogen a logical starting point. Further, carbon taxation appears to be less important than other factors in the transition to zero-emission trucking. Full article

Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time availability, and cost efficiency. Methods: This paper introduces an agent-based model (ABM) and a Monte Carlo simulation program to analyze in detail the activity of parcel locker points. The ABM describes the behavior of the agents (customers, parcels, lockers, delivery agents). The simulation is realized using ARENA 12 software. Two scenarios are created based on the number of daily delivery shifts; for each scenario, 300 simulation experiments with various input data are conducted. Results: Three measures of performance (MOPs) are selected to assess the system activity: the number of daily delivered parcels, the delivery time of an order, and the daily delayed orders. The simulation outputs reveal significant predictors of MOPs and disclose moments when actions need to be taken to increase system capacity or change customer behavior. Conclusions: The versatility of the simulation model in terms of input variables makes it a useful decision support tool for planning by highlighting quantitative assessments, organizing delivery activity, along with influences due to customer behavior changes. Full article

Background: Supply chain risk and resilience in non-profit-seeking industries involving governmental agencies and quasi-governmental agencies have been under-studied. This paper focuses on the military industrial supply chain to demonstrate the development of risk assessment and supplier resilience models considering one-off disruption events such as the COVID-19 disruption. Methods: We establish relevant resilience-based categories through a literature review, supported by the experiences of supply chain experts within the military industry. We quantify the severity of the identified resilience categories, their detectability, and their occurrence probabilities. The failure modes and effects analysis technique is used to evaluate the risk priorities for the resilience categories to develop a risk assessment model. The risk assessment model is then extended to a supplier resilience model by incorporating specific rare disruption factors, which can act as a scenario planning tool. Results: It is found that (i) the top four resilience sub-categories are financial, topical data, business continuity planning, and supply chain mapping, while cost reduction strategies and green material usage are the least important; (ii) the main areas requiring focus are topical data, supply chain depth awareness, business continuity management, and internal risk management; and (iii) suppliers have least resilience in the areas of ‘topical information’ and ‘business continuity strategy’. Conclusions: The tool developed can help military industrial supply chains identify the main areas to enhance resilience from multiple perspectives of severity, occurrence probability, detectability, and suppliers. Full article

Background: Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review of the existing literature, the main objective of this study is to analyze how AI is being applied and adopted in the demand planning process, identifying the resources needed to build the capacity of AI in the demand process, as well as the mechanisms and practices contributing to AI capability’s advancement and formation. Methodology: The approach was qualitative, and case studies of three different companies were conducted. Results: This study identified crucial resources necessary for fostering AI capabilities in demand planning. Our study extends the literature on AI capability in several ways. First, we identify the resources that are important in the formation of the capacity to implement AI in the context of demand planning. Conclusions: This study’s practical contributions underscore the multifaceted nature of AI implementation for demand planning, emphasizing the importance of resource allocation, human capital development, collaborative relationships, organizational alignment, and relational capital and AI. Full article

Background: This publication presents a review, multiple criteria optimization models, and a practical example pertaining to the integration of automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. This publication addresses challenges in logistics and transportation, aiming to enhance efficiency, reduce costs and improve customer satisfaction. This study integrates automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. Methods: A review of the existing literature synthesizes key concepts, such as facility location problems, vehicle routing problems and the mathematical programming approach, to optimize supply chain operations. Conceptual optimization models are formulated to solve the complex decision-making process involved in last-mile delivery, considering multiple objectives, including cost minimization, delivery time optimization, service level minimization, capacity optimization, vehicle minimization and resource utilization. Results: The multiple criteria approaches combine the vehicle routing problem and facility location problem, demonstrating the practical applicability of the proposed methodology in a real-world case study within a logistics company. Conclusions: The execution of multi-criteria models optimizes automated smart locker deployment, capillary distribution design, crowdshipping and last-mile delivery strategies, showcasing its effectiveness in the logistics sector. Full article

Background: Additive manufacturing (AM) for patient-specific medical care products offers great opportunities. However, evidence about the supply chain (SC) performance impact based on empirical data is limited. Methods: In this case study, we gathered real-life data about a traditional manufacturing orthopedic shoe SC and developed future scenarios in which AM is introduced at various points and with different degrees of penetration in the SC. Results: Presently, AM can only replace traditional manufacturing of tools and shoe components at a higher total cost. However, with maturing technology, the complete AM production of orthopedic shoes is expected to become feasible. Theoretically, that could disrupt existing SCs, eliminating 70% of the SC steps, improving SC lead time by 90%, and altering SC relations. However, certain thresholds currently prevent disruption. Specifically, the AM of complete orthopedic shoes has to become possible, manufacturing prices have to drop, and traditional craftsmanship has to be integrated into the digital product design. Conclusions: A framework for transition pathways, including directions for future research, is formed. Findings provide valuable insights for scholars and decision makers in the patient-specific products industry, health insurance providers, and healthcare policy makers to be better prepared by adjusting SC designs, relationships, and remuneration programs while AM technology develops towards maturity. Full article

Background: Increased maritime trade has led to a surge in drayage operations, causing congestion and environmental issues in port areas. Truck Appointment Systems (TASs) are commonly used to manage truck arrival rates, yet transparency and equity in slot allocation remain problematic, fostering distrust between Licensed Motor Carriers (LMCs) and Marine Terminal Operators (MTOs). Methods: This study proposes a polycentric approach to improve truck scheduling and ensure that those impacted by decisions are involved in the decision-making process. A single-round auction mechanism focused on optimizing the truck hauling process through a pricing policy that promotes sincere bidding is introduced. The proposed approach employs an optimization strategy to achieve equitable coordination in truck synchronization through means of adaptable capacity management. Results: Numerical experiments assessing scenarios of noncollaborative behavior against partial collaboration between MTOs and LMCs demonstrate the effectiveness of the proposed approach in enhancing user satisfaction and terminal conditions for a case study focused on a medium-sized terminal. Collaboration between trucking companies is shown to increase utility per monetary unit spent on slot acquisition. Conclusions: The polycentric strategy offers a solution to TAS limitations by ensuring stakeholder participation with respect to flexibility and transparency by ensuring that those impacted by decisions are involved in the decision-making process. Full article

Background: Effective humanitarian logistics (HL) is essential in disaster response. The “Internet of Things” (IoT) holds potential to enhance the efficiency and efficacy of HL, yet adoption is slowed by numerous barriers. Methods: This study employs interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) to explore and classify barriers to IoT integration in HL. Results: A total of 12 barriers were identified, classified, and ranked according to their driving power and dependence. Key barriers include lack of standardization, organizational resistance, data quality issues, and legal challenges. Conclusions: Overcoming these barriers could significantly improve relief operations, reduce errors, and enhance decision-making processes in HL. This investigation is the first of its kind into IoT barriers in HL, laying the groundwork for further research and providing valuable insights for HL managers. Full article

Background: The primary objective of this study was to examine the advancements in sustainable supplier selection through multi-criteria decision making (MCDM) from the years 2013 to 2022. In the recent past, researchers have carried out a significant amount of research in this field over the course of several years; Methods: a total of 121 scientific publications sourced from the Scopus database were chosen for analysis, employing the bibliometric method and graphical visualization of the VOS viewer application to visually analyze and map research networks and collaboration patterns, aiding in the evaluation of scientific impact and knowledge dissemination; Results: the findings of this study indicate that the research trend in sustainable supplier selection through MCDM witnessed its most significant growth in the year 2019. Researchers predominantly disseminated their scientific findings through articles, accounting for 81% of the publications, followed by conference papers at 14%, and book chapters at 2.5%; Conclusions: the primary area of focus in these studies pertains to decision-making processes involved in sustainable supplier selection. The implications and theoretical contributions derived from this research, coupled with the latest advancements, serve as a foundation for further exploration and development of sustainable supplier selection research through MCDM. Full article

Background: Transportation demand forecasting is an essential activity for logistics operators and carriers. It leverages business operation decisions, infrastructure, management, and resource planning activities. Since 2015, there has been an increase in the use of deep learning models in this domain. However, there is a gap in works comparing traditional statistics and deep learning models for transportation demand forecasts. This work aimed to perform a case study of aggregated transportation demand forecasts in 54 distribution centers of a Brazilian carrier. Methods: A computational simulation and case study methods were applied, exploring the characteristics of the datasets through autoregressive integrated moving average (ARIMA) and its variations, in addition to a deep neural network, long short-term memory, known as LSTM. Eight scenarios were explored while considering different data preprocessing methods and evaluating how outliers, training and testing dataset splits during cross-validation, and the relevant hyperparameters of each model can affect the demand forecast. Results: The long short-term memory networks were observed to outperform the statistical methods in ninety-four percent of the dispatching units over the evaluated scenarios, while the autoregressive integrated moving average modeled the remaining five percent. Conclusions: This work found that forecasting transportation demands can address practical issues in supply chains, specially resource planning management. Full article

Background: The COVID-19 pandemic is a worldwide threat that has positioned micro-enterprises under enormous tension to persevere. As a result, these businesses are obligated to respond to the epidemic in an efficacious manner. In order to weather this economic storm, micro-enterprises have implemented a variety of digital technologies. Methods: The research investigates the connection between the communications technology of driving schools and the public crisis responses of those driving schools using a data set obtained from a survey administered to those schools. Results: The quantitative findings demonstrate that digitalization has made it possible for driving schools to efficiently and successfully respond to the public dilemma by utilizing their resilient functionality. In addition, digitalization can greatly enhance driving schools’ performance. Conclusions: This paper provides drawings for digitalization and crisis responses for driving schools. Full article

Background: This article identifies and examines key performance indicators (KPIs) related to citizen mobility logistics in smart and sustainable urban areas. It begins with a comprehensive literature review to identify essential KPIs, offering valuable insights for both public and private stakeholders, including policymakers and mobility service providers. Drawing from various mobility projects in smart cities, the study extracts common KPIs and best practices. The focus of the paper then turns to Barcelona, Spain, where KPIs that matter most are analyzed. Methods: Using open data from the city council spanning from 2017 onwards, the study provides insights into the evolving mobility logistics landscape. KPIs from other European cities are also considered by utilizing similar open data sources. This comparative analysis provides valuable benchmarks and reveals disparities in mobility logistics. Throughout this investigation, the paper emphasizes the role of data quality in KPI selection. Results: Reliable open data significantly influence indicator choices and present challenges when comparing cities. Remarkably, the findings consistently highlight environmental data as an area requiring attention in sustainable mobility logistics. Conclusions: This paper makes contributions by identifying and examining KPIs relevant to citizen mobility logistics in smart and sustainable urban areas. It offers insights by applying these KPIs to Barcelona and conducting comparative analyses with other European cities. These findings serve as a valuable resource for policymakers, city planners, and mobility experts. Full article

Background: This study presents a comprehensive methodology for enhancing humanitarian logistics planning and management in natural disasters, focusing on earthquakes. Methods: The innovative approach combines a deterministic mathematical model with a simulation model to address the problem from multiple perspectives, aiming to improve efficiency and equity in post-disaster supply distribution. In the deterministic modeling phase, optimal locations for humanitarian distribution centers and points in Popayan, Colombia, were identified, enabling efficient resource allocation for affected families. Subsequently, the simulation model evaluated scenarios based on real earthquakes in Colombia and Latin America, providing a comprehensive view of the logistics system’s response capacity to different disaster conditions and magnitudes. Results: The results demonstrated that the proposed methodology significantly reduced supply delivery time, achieving a 30% improvement compared to traditional humanitarian logistics approaches. Moreover, it led to a more equitable coverage of affected communities, with a 25% increase in families served in previously underserved areas. Expert validation from the Disaster Risk Management Committee of the study area confirmed the methodology’s usefulness for informed and effective decision-making in real situations. Conclusions: This integrated approach of mathematical modeling and discrete event simulation offers valuable insights to address disaster management and support decision-making in humanitarian crises. Full article

Background: The classical mathematical formulation of the vendor-managed inventory (VMI) model assumes an infinite planning horizon, and consequently, the solution derived ignored the impact of the first cycle. The classical formulation is associated with another implicit assumption that input parameters remain static indefinitely. Methods: This paper develops two mathematical models for VMI for a joint economic lot-sizing (JELS) policy. Each model considers investment in green production, energy used for keeping items in storage, and carbon emissions from production, storage, and transportation activities under the carbon cap-and-trade policy. The first model underlies the first cycle, while the second underlies subsequent cycles. Results: The re-start-up production time for subsequent cycles commences only at the time required to produce and replenish the first lot, which implies further cost reduction. Mathematical formulations are perceived as important both for academics and practitioners. For example, the base model of the first cycle (subsequent cycles) generates an optimal produced quantity with 18.42% (4.35%) less total system cost when compared with the pest scenario in favor of the existing literature. Moreover, such a percentage of total system cost reduction increases as the production rate increases. Further, the proposed models not only produce better results but also offer the opportunity to adjust the input parameters for subsequent cycles, where each cycle is independent from the previous one. Conclusions: The emissions generated by the system are very much related to the demand rate and the amount of investment in green production. Illustrative examples, special cases, model overview, and managerial insights are given. The discussion related to the contribution of the proposed model, the concluding remarks, and further research are also provided. The proposed model rectifies the base model adopted by the existing literature, which can be further extended to be implemented in several interesting further inquiries related to JELS inventory mathematical modeling. Full article

Background: Blockchain adoption in agriculture is facing challenges. Some of its key challenges include lack of regulatory framework and unclear policies. Methods: This quantitative research based on a survey aims to examine the factors that influence blockchain implementation in the agricultural sector. Several theories including the technology acceptance model (TAM), the theory of planned behaviour (TPB), and the technology readiness index (TRI) were drawn upon to determine the factors influencing Blockchain adoption. The study was undertaken in Australia with 358 agricultural supply chain experts. Results: A range of novel findings were generated. While perceived usefulness, perceived ease of use, and attitude positively influenced Blockchain adoption, discomfort and insecurity were considered deterrents. Conclusions: The results can be used by relevant practitioners to improve the supply chain management for agriculture business. The findings can also inform a new direction for the research on the agricultural supply chain and the literature on logistics. Full article

Background: This paper is the first-ever discussion of sport logistics as an intersection of the academic disciplines of logistics and sport management. Methods: It reviews past literature and states that logistics in sport is widely overlooked in academic literature. It illustrates the importance and pervasive nature of logistics in the sport industry and questions how sport logistics can be positioned at the interface of logistics and sport management science. Both disciplines are contrasted under the common lens of Porter’s value chain. Results: Operations, organization and marketing are identified along with economics and strategy as areas of sport management (highly) involved with logistics. Sport logistics is defined as a research area dealing with storage and transportation issues in sport organizations. Conclusions: Based on a case example from practice, athlete equipment logistics, the authors elaborate on the unique characteristics of managing logistics in sport, e.g., low competition, personal relationships and high demand predictability. They call for a broader discourse on sport logistics in academia. Full article

Background: E-commerce’s convenience, speed, and ability to overcome geographical barriers have made it increasingly popular across industries. This study analyzed the impact of the COVID-19 pandemic on customer experience and satisfaction in supermarket retail e-commerce in the Brazilian market. The objective was to understand how the pandemic influenced satisfaction in this sector. Methods: A survey research method was employed, utilizing the Critical Incident Technique to identify key quality dimensions important to customers. A total of 133 valid responses underwent exploratory factor analysis. Results: Data analysis identified three dimensions significantly affecting overall customer satisfaction. “Presentation of Products in the Application (app)” had the highest correlation, while “Delivery Logistics” had the lowest. However, when considering the COVID-19 factor, “Delivery Logistics” showed the highest correlation. This indicates that the dimension most affected by the pandemic has the least impact on overall satisfaction in supermarket e-commerce. Conclusions: The study emphasizes the significance of understanding customer satisfaction in supermarket e-commerce, not just during the COVID-19 pandemic but also its post-pandemic consequences. Retailers should prioritize improving product presentation in apps, as it greatly influences overall satisfaction. Addressing the pandemic’s impact on delivery logistics is also crucial to ensure competitiveness in the e-commerce market. Full article

Background: To help ensure roadway safety, the federal government mandates trucking companies to conduct pre-employment urine drug tests before allowing drivers to operate a commercial motor vehicle. Unfortunately, urine testing has a short detection window and is easily thwarted, leading some carriers to employ hair testing. Methods: t-tests were utilized to compare hair and urine pre-employment drug test results provided by seven large U.S. trucking companies. Results: results indicate that hair’s positivity rate is statistically greater than urine for each examined drug and across all drugs combined. Conclusions: This paper is the only supply chain work of which we are aware that assesses the statistical differences between hair and urine testing positivity rates. Results support hair testing’s increased ability to prevent lifestyle drug users from operating commercial motor vehicles and should be considered by public policy makers considering whether hair testing results should be allowed into the Drug and Alcohol Clearinghouse. Full article

Background: Airports are essential drivers of spatial development; hence the placement of logistics facilities relative to airports is a topical subject. Despite the wealth of the literature on the subject, relatively little is known about the airfreight catchment of airports. To contribute to the existing knowledge, the paper used the study area of the City of Cape Town municipality, South Africa, to address three research objectives, namely analysis of factors that influence the placement of logistics firms in the municipality, analysis of the linkages of the logistics firms with Cape Town International Airport (CTIA), and analysis of the association between airfreight-related firms and the general attributes of logistics firms in the municipality. Methods: The study hinged on a quantitative design, which included a survey and spatial analysis. A total of 110 logistics firms were sampled through a stratified random sampling technique, and 66 firms participated in the telephonic interviews conducted in October and November 2021. Survey data were analyzed using Stata, and spatial analysis was undertaken using ArcGIS 10.8 and QGIS 3.16. Results: It was discovered that a quarter of the respondent logistics firms utilized CTIA for airfreight purposes. At a municipal scale, the potential airfreight catchment of CTIA extended to about a 20 km radius of the airport. Conclusions: In formulating the spatial plans, the planning authorities are encouraged to take cognizance of the possible extent of the catchment, wherein airfreight-related firms do not necessarily locate near the airport. Full article

Background: Nowadays, as a result of globalization, markets are more competitive, and customers are more demanding. To respond to these challenges, organizations must develop mechanisms for continuous improvement in order to eliminate waste and increase the efficiency and effectiveness of processes. Thus, the present study carried out at an industrial unit responsible for the customization of cork stoppers for wines had as its main objectives to identify and eliminate or at least reduce waste; improve production and internal logistics flows; balance workloads; improve productivity; reduce lead time; motivate employees and promote the spirit of continuous improvement. Methods: The action-research methodology was used, whereby several cycles of data recovery and analysis, identification and implementation of opportunities for improvement, assessment and standardization were carried out. Therefore, the Total Flow Management (TFM) model was implemented, and several methods and tools were used, such as Value Stream Mapping (VSM), work measurement and 5S’s. Results: Several wastes and overloads were identified, and some actions were implemented, such as workload balancing, layout changes, implementation of visual management and supermarkets. That said, it was possible to reduce lead time by 4 days, improve productivity from 26.63 ML (a thousand cork stoppers)/h to 35.75 ML/h, and promote flexibility. In addition, employees were motivated, and a culture of continuous improvement was fostered. Conclusions: This project demonstrated that it is possible to implement improvement actions, with good results, without high investments, as well as motivating employees and taking advantage of their best capabilities. Additionally, it was demonstrated that the use of TFM can be very useful in continuous improvement, with evident improvements in production and internal logistics flows. So, this project demonstrated the practical implementation of TFM regarding basic reliability, production and internal logistics flow, and the simultaneous use of several methods and tools to implement continuous improvement. Thus, significant improvements were possible on the factory floor, as well as improving employee motivation their personal development and encouraging the focus on continuous improvement. Therefore, it responds to the gap identified in the literature. Full article

Background: Digital twins have the potential to significantly improve the efficiency and sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks, planning for contingencies, and improving existing processes and resources. Additionally, they can add value to businesses by lowering costs and boosting customer satisfaction. This study is aimed at responding to common scientific questions on the application of digital twins in the agri-food supply chain, focusing on the benefits, types, integration levels, key elements, implementation steps, and challenges. Methods: This article conducts a systematic literature review of recent works on agri-food supply chain digital twins, using a list of peer-reviewed studies to analyze concepts using precise and well-defined criteria. Thus, 50 papers were selected based on inclusion and exclusion criteria, and descriptive and content-wise analysis was conducted to answer the research questions. Conclusions: The implementation of digital twins has shown promising advancements in addressing global challenges in the agri-food supply chain. Despite encouraging signs of progress in the sector, the real-world application of this solution is still in its early stages. This article intends to provide firms, experts, and researchers with insights into future research directions, implications, and challenges on the topic. Full article

Background: Since global warming is a crucial worldwide issue, carbon tax has been introduced in the global supply chain as an environmental regulation for the reduction of greenhouse gas (GHG) emissions. Costs, GHG emissions, and carbon tax prices differ in each country due to economic conditions, energy mixes, and government policies. Additionally, multiple countries have signed a Free Trade Agreement (FTA). While FTAs result in their economic benefit, they also increase the risk of carbon leakage, which increases GHG emissions in the global supply chain due to relocation production sites from a country with stricter emission constraints to others with laxer ones. Method: This study proposes a mathematical model for decision support to minimize total costs involving carbon taxes with FTAs. Results: Our model determines suppliers, factory locations, and the number of transported parts and products with costs, FTAs, carbon taxes, and material-based GHG emissions estimated using the Life Cycle Inventory (LCI) database. The FTA utilization on the global low-carbon supply chain is examined by comparing the constructed supply chains with and without FTAs, and by conducting sensitivity analysis of carbon tax prices. Conclusions: We found that FTAs would not cause carbon leakage directly and would be effective for reducing GHG emissions economically. Full article

Background: Finding trends in freight transportation activities enables businesses and policy makers to build an understanding of freight transportation patterns and their impact on logistics planning when making investments in a region’s transportation infrastructure and intermodal freight transport system. To the best of our knowledge, there is limited literature and data-driven analysis about trends in transportation mode choices and the influencing factors in Atlantic Canada. Methods: In this study, a data-driven method has been used to analyze the Canadian Freight dataset to identify trends in transportation activities within Maritime, Canada. Freight transportation mode, product categories, distance, number/weight of shipments, and revenue were examined. Results: The results revealed that the top five product categories exported from Atlantic provinces to the rest of Canada, the US, and Mexico are miscellaneous items, food products, forest products, minerals, and other manufactured goods, where Truck for Hire is the most deployed mode of transportation. A multiple linear regression analysis indicated that the weight, distance, and number of shipments are positively and rather strongly correlated with revenue generation. Conclusions: This study provides a unique overview of Canadian Freight Analysis Framework (CFAF) data with a focus on maritime activities. Full article

Background: UAVs (Unmanned Aerial Vehicles) and SUGVs (Sidewalk Unmanned Ground Vehicles) are two prominent options to revolutionize last mile home delivery. However, there is no literature yet addressing a comprehensive assessment of them. To bridge this research gap, this paper aimed to compare UAVs to SUGVs in the context of urban parcel delivery from a practical, conceptual, technological, commercial, and environmental perspective. Methodology: Based on structured literature and web research, this paper provided a comparative status quo review of these two delivery concepts. We introduced a parameter-based cost calculus model to estimate the costs per shipment for each technology. To detect the key cost drivers, we applied a one-way sensitivity analysis, as well as a “full factorial design of experiment” approach. Results: These key cost drivers for both operations are the “number of vehicles per operator” and the “average beeline service radius”. From today’s commercial point of view, our model indicated better profitability of SUGVs. However, technical and regulatory developments may render different results in the future. As SUGVs emit significantly less noise than UAVs, we assume that SUGVs have an additional advantage for usage in autonomous urban last mile delivery from a resident’s perspective. Conclusions: Both key cost drivers will significantly influence the commercial viability of unmanned home delivery services. Safety and security aspects will determine regulatory rules on “number of vehicles per operator”. To increase the “average beeline service radius”, UAVs could profit from mothership delivery concepts while SUGV delivery may co-use existing public transport infrastructure. Full article

Background: Food waste is a situation that triggers certain controversy, considering that there is still a significant number of people who do not have access to healthy and nutritious food every day. The management of food leftovers from school lunches depends on the creation of measurement mechanisms. Thus, current characteristics of schools should be identified in order to mitigate and better manage these leftovers. This study addresses this gap, that is, it seeks to understand how food waste management is carried out in schools from a circular economy perspective. Methods: Focusing on the management of school lunches in municipal schools, this study aims to build an inductive interpretive theory in order to understand how schools promote food waste management. Results: Loss estimates and their monetization were identified and explained, and alternatives for waste recovery using the ReSOLVE framework were proposed. Conclusions: Therefore, it was assumed that the perspective of circularity is a possible and viable way to manage food waste in school lunches. Stakeholder engagement and awareness raising become necessary premises for success in the food circularity journey. Full article

Background: In the current knowledge age, the performance of logistics firms increasingly depends on knowledge and capabilities they can leverage in value-creation processes. The objective of this paper is to investigate the relationship between knowledge-based human resource management (HRM) practices and organizational performance mediated by logistics capability. Methods: Data from 93 small Finnish logistics service providers was collected by a questionnaire survey. Structural equation modeling and partial least squares analysis were used to test the hypothesized relationships between HRM practices and the organizational performance of logistics companies, as well as the mediating impact of logistics capability. Results: The results demonstrate that logistics capability fully mediates the relationship between HRM practices and the organizational performance of small logistics companies. Each of the three knowledge-based HRM practices—knowledge-based recruitment, training and development, and motivation—significantly influences logistics capability, which is, in turn, associated with the organizational performance of companies. Conclusions: This paper is one of the few among discussing knowledge-based HRM practices in logistics service research. The paper contributes to the literature on logistics by demonstrating the value of knowledge-based HRM practices in acquiring, developing, and leveraging knowledge to create organizational capabilities and ensure organizational performance. This study provides an improved understanding of the role of HRM and the resulting logistics capability in the performance of small logistics service companies. Full article

Background: The purpose of this study is to analyse the role of the main 50 US cargo airports and 25 air cargo airlines in the logistics of e-commerce companies from 2000 to 2020, to highlight the importance of airports in the logistics and e-commerce industries. Methods: A review of the relevant literature on airports, air cargo carriers, logistics, and e-commerce sectors was undertaken to understand the link between them. The data were collected using four criteria: airport category, airport location, top 25 air cargo carriers, and other relevant data from the Federal Aviation Administration, International Air Transport Association, Organization for Economic Co-operation and Development, US Department of Transportation, amongst many others. Results: The findings reveal that there is a consolidated relationship between airports, air cargo airlines, and e-commerce, which has been especially evident during the COVID-19 pandemic. Airports and air cargo carriers are identified as the most relevant partners in the e-commerce industry. This is because of the e-commerce sector and its users’ demand for speed and reliability in the interaction between the demand for and supply of products and services. Conclusions: The pandemic has changed the way in which organizations operate and is likely to create new demand from companies and users in the aviation and e-commerce industries. E-commerce companies are highly dependent on the quality and efficiency of air cargo airlines and airports because they need to provide a good shipping service for their products to customers. Full article

Background: Due to the growing demand for energy and environmental issues related to using fossil fuels, it is becoming tremendously important to find alternative energy sources. Bioethanol produced from switchgrass is considered as one of the best alternatives to fossil fuels. Methods: This study develops a two-stage supply chain modeling approach that first determines feasible locations for constructing switchgrass-based biorefineries in the state of North Dakota by using Geographic Information Systems (GIS) analysis. In the second stage, the profit of the corresponding switchgrass-based bioethanol supply chain is maximized by developing a mixed-integer linear program that aims to commercialize the bioethanol production while impacts of energy use and carbon emission costs on the supply chain decisions and siting of biorefineries are included. Results: The numerical results show that carbon emissions and energy consumption penalties affect optimal biorefinery selections and supply chain decisions. Conclusions: We conclude that there is no need to penalize both emissions and energy use simultaneously to achieve desirable environmental benefits, otherwise, the supply chain becomes non-profitable. Moreover, imposing emissions or energy consumption penalties makes the optimization model closer to supply sources while having higher land rental costs. Such policies would promote sustainable second-generation biomass production, thus decreasing reliance on fossil fuels. Full article

Background: Order picking process is critical for accurate and efficient order fulfilment. Pick-by-vision is a promising technology that may support order picking process, however there is still a limited amount of research concerning the impact of this technology on the performance of order-picking. The purpose of this paper is to investigate certain operational and technical parameters that affect the performance of pick-by-vision technology in item-level order picking via a series of laboratory tests. Methods: A systematic literature review is conducted for the identification of parameters that affect pick-by-vision performance. Subsequently, the analytical hierarchy process is adopted to rank these parameters, concerning their impact on order picking. Then, the design of experiment and NASA task load index methodology are implemented for assessing pick-by-vision efficiency and perceived workload. Results: The results reveal the parameters that significantly affect the performance of the pick-by-vision system, as well as the best configuration of parameters for the implementation of the proposed system in real environments. Conclusions: The results obtained are encouraging, showing how pick-by-vision technology can support order picking efficiency. Furthermore, practical implications are presented that deal with the organizational culture, process re-engineering, staff resistance to change, and motivation for maintaining the new way of executing order-picking processes. Full article

Background: Centuries after its introduction in Africa, the western-style logistics system has not replicated the same results as it has in other parts of the world. The continent continues to grapple with poor logistics infrastructure and low intra-Africa trade at a time when governments in Africa are committed towards the expansion of trade and manufacturing through the implementation of the African Continental Free Trade Area (AfCFTA) agreement. There is a pressing need, therefore, for the development of a logistics system designed for the African socioeconomic environment and the peculiarities of the people. Methods: This paper examines the operations of the Indigenous Logistics Systems (ILS) in pre-colonial Nigeria and its development over time through qualitative data gathered from the six geopolitical zones in Nigeria and a review of literature. Results: ILS in Nigeria is the cultural creation of the people through the efficient management of available resources and the use of indigenous knowledge. The system derives its strengths and effectiveness from its availability, simplicity, affordability, and trust. Conclusions: The paper concludes that if improved with the application of simple technology, ILS has the answers to the challenges of logistics and Supply Chain Management (SCM) in Africa. Full article

Background: The COVID-19 pandemic has moved the world in every way, directly impacting supply chains globally and bringing major challenges to management, decision-makers, and companies of all sizes and sectors. This intensifies when it comes to the Brazilian Amazon region, a place that historically already lives with several maintenance projects focused on supply chain management (SCM). Methods: Thus, this research aimed to understand the main challenges faced by professionals in the supply chain area in the Amazon region through the development of a survey with professionals in the area. This study conducted a structured questionnaire containing 10 challenges related to SCM during the pandemic period to generate a ranking of these challenges using data analysis using means and comparative ordering using the TOPSIS Multicriteria Technique. Results: It was observed that the most relevant challenges for companies in this region were, respectively, distribution, economic problems, and interruptions in supply and demand. These obstacles promote debates with the literature and foster the expansion of knowledge about the insertion of resilience elements in supply chains in the Amazon. Conclusions: From a theoretical point of view and because it is exploratory research, the results serve as a basis for researchers in the area who aim to understand and expand the debates on this topic through future research. From a practical point of view, the results can help supply chain managers in the Amazon region who work directly in its maintenance and aim to maintain its resilience, since they already have the main challenges for the proper functioning of supply chains identified and ranked. Because it is an exploratory study, the results achieved can contribute significantly to the expansion of debates in the area and in a practical way with managers involved in activities that compose supply chains. Full article

Background: Automobile terminals play a key role in global finished car supply chains. Due to their connecting character between manufacturers on the one side and distributers on the other side, they are continuously faced with volatile demand fluctuations and unforeseen dynamic events, which cannot be handled adequately by existing planning methods. Autonomous control concepts already showed promising results coping with such dynamics. Methods: This paper describes the causes of dynamics and the terminal systems’ inherent shortcomings in dealing with such dynamics. On this basis, it derives terminal’s demand for novel planning approaches and presents a new integrated autonomous control method for automobile terminals. This novel autonomous control approach combines yard and berth assignments. This paper evaluates the performance of the new approach in a small comprehensive generic scenario. It compares classical planning approaches with the new autonomous control approach, by using a discrete event simulation model. Moreover, it analyses all relevant parameters of the new approach in a full factorial experiment design. In a second step this paper proves the applicability of the combined autonomous control approach to real-world terminals. It presents a simulation model of a real-world terminal and compares the new method with the existing terminal planning approaches. Results: This paper will show that the autonomous control approach is capable of outperforming existing centralized planning methods. In the generic and in the real-world case the new combined method leads to the best logistic target achievement. Conclusions: The new approach is highly suitable to automobile terminal systems and helps to overcome existing shortcomings. Especially in highly dynamic and complex settings, autonomous control performs better than conventional yard planning approaches. Full article

Background: An increasing number of container and chassis staging, “dray-off”, drop yard, and depot facilities are being established outside of North American marine container terminals. The increased use of these “second-tier” facilities implies that there must be some capacity, delivery time, service, or reliability benefit that offset the additional cost and complexity. Methods: This paper builds on the previously developed integrated drayage scheduling model to determine the impact of second-tier port facilities on drayage operation. It modifies the previously developed model by incorporating the following features: (1) trucks do not have to wait at customers’ locations during the import unloading and export loading operations; (2) drayage operations can include a drop yard (i.e., second-tier facility) for picking up or/and dropping off loaded containers outside the marine container terminal; and (3) a customer is allowed to request any of the following jobs: pick up an empty container, pick up a loaded container, drop off an empty container, and drop off a loaded container. Results: The results indicated that by moving the location of import pickup and export delivery from inside the marine container terminal to a location outside the terminal, the efficiency of drayage operation could increase. Additionally, when import pickup and export delivery take place inside the marine container terminal, the most efficient location for the chassis yard and empty container depot is inside the terminal. However, when the location of import pickup and/or export delivery are outside the terminal, the most efficient location for the chassis yard and empty container depot is also outside the terminal. Conclusions: The modeling results suggest that in addition to adding reserved capacity for marine terminals or as buffers to reconcile the preferred delivery times of importers, the second-tier facilities could also yield operational savings. However, the potential drayage efficiencies depend heavily on shorter queuing and turn time at these less-complex facilities compared to marine container terminals. Lastly, the modeling results suggest that the observed evolution of North American marine container terminals from self-contained entities into multi-tier systems is likely to continue to add additional capacities to accommodate container trade growth. This finding has important implications for regions and communities concerned over the impact of growing container ports. Full article

Background: The Irish government has put forth sustainable transport policy measures, yet the emphasis is mainly on the active travel and sustainable mobility for passenger transport. Contrariwise, freight transport has not received equal consideration in policy measures, regulatory frameworks, and support schemes towards the low-carbon transition. This study seeks to address this imbalance. Methods: The paper proposes an adaptation of the ASI framework for freight transport and assesses the applicability of a number of international sustainable transport measures based on their potential sustainability impact if adopted in Ireland. The research applied a Policy Delphi Method to a heterogeneous expert panel. Results: The findings indicate that the current sustainable freight transport policy measures in Ireland are limited, and the paper suggests 38 measures for supply chains, maritime transport, rail transport and urban freight transport. The analysis further suggests that decarbonisation measures in Ireland should first formulate on the decarbonisation stages ‘avoid’ and ‘shift’, and then move to the ‘improve’ stage, thus leading to a greater impact on decarbonising the freight sector. Conclusions: An ‘ASI for freight transport’ framework is proposed as a taxonomy to systematically compare freight decarbonisation policy measures locally and internationally. This updated framework can serve as a new lens to prioritise sustainable freight policy measures. Recommendations are proposed for developing policy measures for sustainable freight transport in Ireland. Full article

Background: The logistics network design with cross-docking operations enables shipping service providers to integrate the physical flow of products between vendors and dealers in logistics management. The collective goal is to synchronize the goods in both pickup and delivery operations concurrently to reduce the handling cost, inventory cost, and operation cost generated. Therefore, the optimal vehicle routing plan is crucial to generate a truck routing schedule with minimal total cost, fulfilling the purchasing requirements and the distribution demand. Global warming and climate change are important topics due to increasing greenhouse gas emissions. Sustainable logistics management with optimized routes for trucks can assist in reducing greenhouse gas emissions and easing the effects of temperature increases on our living environment. Methods: A heuristic approach based on Particle Swarm Optimization, called ePSO, was proposed and implemented in this paper to solve the vehicle routing problems with cross-docking and carbon emissions reduction at the same time. Results: Performance comparisons were made with the Genetic Algorithm (GA) through the experiments of several vehicle routing problems with pickup and delivery benchmark problems to validate the performance of the ePSO procedure. Conclusions: Experimental results showed that the proposed ePSO approach was better than the GA for most cases by statistical hypothesis testing. Full article

Background: Food loss management (FLM), which is discussed at length in the literature, lacks a scientific basis on which to determine the current engagement of actors in the food value chain and what is relevant to derive appropriate measures according to the circumstances in the organisations concerned. Therefore, this paper aims to derive patterns by which the engagement of actors can be distinguished and, on this basis, to make recommendations for further action. Methods: Based on an online survey of 40 participants, a clustering analysis was conducted using the unsupervised learning method and hierarchical clustering (R and R Studio). Results: Five clusters representing different profiles were derived, showing how actors in the food value chain have addressed FLM in the past. The derived profiles do not represent stages of development but rather characteristics of organisations that have addressed FLM in a certain way in the past. Conclusions: For the five organisational profiles, recommendations for action were given for further engagement with FLM. As the level of engagement with FLM increases, organisations should tackle increasingly complex measures to reduce food losses. At the same time, a shift in measures from the tactical to the strategic planning level was derived. Full article