ABSTRACT. Humanitarian supply chains (HSCs) face major challenges in critical operations, including disaster relief, conflict support, and rapid response. This research, based on a literature review, develops a system dynamics (SD) framework to improve understanding of HSC resilience (HSCRES). By examining stakeholder interactions and trade-offs, this paper aims to offer practical insights to strengthen the resilience of HSCs. Specifically, enhancing IT capabilities through technologies such as blockchain, IoT, and cloud computing can improve transparency, coordination, and decision-making, thereby fostering agility and long-term resilience in HSCs.

ABSTRACT. Warehouses are increasingly exploring collaborative mobile robots (CMRs) to automate intralogistics processes. However, making strategic decisions to implement CMRs is complex and multi-phased. Through a structured literature review and theoretical insights, the author identifies critical factors influencing successful adoption of CMRs from technological and economic to human and organizational factors. This paper proposes a theoretical framework for strategic decision-making in deploying CMRs for warehouse automation. The framework holistically integrates economic evaluation and environmental sustainability assessment, and human-centric considerations such as workforce readiness, focusing on training and employee acceptance, and sustainable operations. For the setup of framework empirical data and causal analysis (using VAR-LiNGAM) will be used to review the impact of implementation factors over time. The theoretical decision-support framework will help logistics managers and stakeholders systematically evaluate and plan CMRs' implementations. The paper offers insights aligning advanced automation with strategic goals and stakeholder values in the era of Industry 4.0.

ABSTRACT. This paper explores the current state of generative artificial intelligence (GenAI) adoption in the logistics sector in Croatia. With the rapid global development of tools such as ChatGPT, Microsoft Copilot, and other AI-enhanced systems, this study investigates how logistics professionals in Croatia are engaging with these technologies in their daily work. A structured 19-item questionnaire was distributed to 552 professionals, yielding 23 valid responses. The survey examined the use of both general-purpose GenAI tools and specialized office-based applications, along with broader automation practices. Results indicate that while overall usage and satisfaction levels remain low, there is a growing awareness and strong intent to adopt GenAI tools in the near future. These findings provide a valuable foundation for understanding the early stages of GenAI integration in Croatian logistics and offer guidance for future research, policy, and industry initiatives aimed at supporting digital transformation.

ABSTRACT. Retailers are keen to adopt self-service technologies to increase productivity. However, some retailers have found it difficult to implement as there is resistance among consumers. In a survey of 760 respondents, it was found that consumers are more likely to use self-checkout counters when they can see that it is more efficient, easy to use and compatible with their lifestyle. In addition, it was found that gender and age did not predict the use of self-checkout counters. This suggests that retailers need to communicate the relative merits of self-checkout counters to consumers. In particular, the perception that self-checkout counters are easy to use may be the most important factor affecting their decision to use self-service technologies.

ABSTRACT. The reliability of blowout preventers (BOPs) is critical to preventing severe accidents in offshore oil and gas operations. Some failures may originate from inadequate storage conditions and poor warehousing practices, which expose components to adverse environments, compromising their performance. This study applies a Soft Design Science Research (Soft-DSR) methodology to propose a warehousing plan focused on improving the reliability and availability of BOP components. The proposal integrates aspects of protective packaging, appropriate environmental control, and life cycle considerations to ensure optimal storage throughout the components’ shelf life. The research emphasizes a structured, problem-solving approach supported by stakeholder engagement and iterative refinement. By improving storage practices, the plan aims to reduce failure rates and enhance operational safety. The results are expected to contribute both to academic discussions on Soft-DSR applications and to practical advancements in offshore equipment maintenance logistics.

ABSTRACT. Supply chain visibility refers to the ability to track and monitor all activities and processes within the supply chain promptly. Gaining visibility into sup-ply chain processes is becoming increasingly crucial for businesses, as it un-derpins improvements in economic, environmental, and social aspects. In outbound logistics, the numerous stakeholders, process complexity, and sub-stantial investments required make it difficult for many companies to devel-op effective monitoring tools. Additionally, competing objectives among stakeholders and the low quality of data provided are major challenges that hinder the success of such projects. This paper introduces a probabilistic model designed to guide investments that enhance overall visibility and data quality. The model is applied to a realistic scenario inspired by the case of a leading Italian food and beverage company, illustrating that targeted invest-ments can significantly boost visibility during the initial project phases, even in resource-constrained environments.

ABSTRACT. Recent technological advancements have facilitated the coordination of automated vehicles into platoons train like formations that offer notable benefits, including reduced energy consumption. However, forming such platoons efficiently requires careful planning of both travel routes and charging schedules, particularly for long-haul electric commercial vehicles. In this study, we propose a polynomial-time heuristics to address the platoon formation planning problem with charging. The performance of the proposed approach is evaluated against a Mixed-Integer Linear Programming (MILP) model. Through numerical experiments, we show that the heuristic obtains close to optimal solutions for small to medium instances and is able to solve instances of up to 2,000 vehicles in just 7 seconds, whereas the MILP requires over an hour to solve instances with more than 100 vehicles. These findings underscore the potential of the proposed method for scalable and real-time deployment in large scale electric vehicle coordination.

ABSTRACT. Because ships consume less fuel when operating at lower speeds, the practice of slow steaming has emerged as a cost-effective strategy during periods of reduced market demand. The downside of slow steaming is the increased voyage dura-tion, which may necessitate deploying more vessels to maintain the same annual transport capacity. Throughout a voyage, ship encounters varying sea conditions, which can influence both fuel usage and emission levels, thereby affecting the overall effectiveness of slow steaming. Evaluating the true advantages of slow steaming under realistic sailing conditions becomes essential. This study esti-mates the benefits of this strategy for a Post Panamax containership operating on one of the primary global container routes. Findings indicate that the time of year plays a critical role in determining the effectiveness of slow steaming. Further-more, the variation in fuel savings along different segments of the route under-scores the need for precise modeling of sea state conditions.

ABSTRACT. In recent years, the growth of e-commerce has driven a trend toward order fulfillment strategies that draw products from multiple dispersed ware-houses. This evolution has heightened the need for optimal product alloca-tion to warehouse locations to minimize inter-warehouse shipment flows and reduce order completion times and costs. Despite the practical signifi-cance of this allocation problem, there is a lack of heuristic approaches capa-ble of addressing large‐scale, real-world instances. This paper proposes a nov-el genetic algorithm to solve the multi-warehouse product allocation prob-lem, integrating tailored genetic operators and constraint-handling mecha-nisms to enhance solution quality. We evaluate the approach on an industri-al case study drawn from an e-commerce company, comprising realistic de-mand and distribution scenarios. Computational experiments demonstrate that our genetic algorithm outperforms baseline methods in reducing total inter-warehouse flow, achieving significant improvements in logistical effi-ciency. These results clearly confirm the proposed method’s practical ap-plicability and robustness for complex e-commerce fulfillment networks.

ABSTRACT. Inspired by the real-world case of the urban area a Bologna, northern Italy, and targeting the United Nations SDG-11 - Sustainable Cities and Communi-ties, this paper focuses on the high impact logistic problem of the last-mile delivery of products in urban areas, generalizing, modeling using linear pro-gramming, and exemplifying the strategic and tactical design of an urban lo-gistic network for last-mile deliveries using intermediate lockers as transit points and the crowd as a key mobility vector next to traditional professional drivers. The goals to reach and best balance are both economic and envi-ronmental, while the final purpose and implication is contributing to the long-term urban sustainability transition by assessing the feasibility and con-venience of promoting ‘hybrid’ last-mile delivery networks mixing profes-sional carriers and private people, as the crowd, with potential benefit for the end-users, the local communities and the society as a whole. Results for the urban area of Bologna showcase the feasibility and convenience of this po-tentially disruptive delivery system.

ABSTRACT. This paper presents a framework that assists in the coordination of the marketing and operations functions when the firm is adopting price promotions to enhance sales. We investigate the effect of operational factors on price promotions under a periodic review policy. Sales are affected both by price promotions and improved service levels, operationalized through higher safety stocks. We show that operational parameters such as lead time, review period, and inventory holding cost negatively affect the annual number of price promotions to be adopted. This points out that an efficient operations function, as reflected in lower values of the previous three operational parameters, allows the firm to use these cost savings and fund its price promotional campaign. This further points to the fact that an Every-Day-Low-Price (EDLP) pro-gram can be supported by the operations function when the lead time and review period are low. Numerical examples demonstrate the above findings.

ABSTRACT. This study aims to analyze the global shipping patterns of vehicle carriers on a port-specific basis using the Automatic Identification System (AIS) vessel movement database. Unlike flexible routes for container ships or fixed tanker patterns, vehicle carriers operate within a specialized hub-and-spoke network. Concentrated production and widespread distribution create unique operational and strategic dynamics that reflect the centralized manufacturing and global market structure of the automotive industry. Two analytical perspectives are employed: time-period models to examine the evolution of the network, and company-specific models to capture distinct patterns among major shipping operators. The significance and connectivity of ports in maritime transport networks are evaluated using network theory metrics, including closeness centrality, betweenness centrality, degree, and authority. Gephi is used for network visualization and enabling a detailed comparison of centrality measures. Port efficiency is evaluated to assess how shipping companies utilize ports and to identify those handling vessel calls most efficiently. This research provides a comprehensive understanding of the global vehicle carrier shipping network and highlights the critical hubs driving its efficiency and connectivity. The findings clarify how the network evolves over time and reveal how different shipping companies shape network structures and utilize ports.

ABSTRACT. The “Made in X” label remains the dominant transparency signal in global trade, but it oversimplifies how goods are made. This paper examines its limits in buyer-driven commodity chains wherein production spans multiple countries. Using concepts from traceability and supply chain visibility, we identify three problems. First, the label reduces multi-tier production to a single country, generating information loss and obscuring supply chain complexity. Second, labels shape consumer beliefs in ways that can hide upstream labor and environmental risks. Third, maintaining label accuracy is costly for firms and stretches regulators whose resources are thin relative to trade volumes and changing rules. We outline research needs: models to measure disclosure loss, tiered disclosure designs that integrate with logistics systems, and Industry 5.0 architectures to attribute value and responsibility more fairly across countries. These directions chart a path toward transparency systems fit for Industry 5.0 supply chains.

ABSTRACT. Government procurement often suffers from subjectivity because reviewers rely on variable and partially unknown value functions to score multi-attribute bids. We address this challenge with a few-shot value function estimation framework and propose a greedy online heuristic solver that incrementally approximates both the structure and weights of the underlying value function. We apply the algorithm to a public works case study, where our results show that a 7-attribute value function can be accurately recovered in under 20 iterations, enabling bidders to adapt quickly and effectively in multi-stage scoring auctions.

ABSTRACT. This paper examines causal links among growth, productivity, and return on investment (ROI) in Estonia’s logistics sector using 111 sector–year observations across nine entities (2006–2020). A disciplined, three-stage design separates instantaneous structure from dynamic pass-through. First, a VAR(1) with a LiNGAM contemporaneous layer recovers a single on-impact arrow—growth → productivity—and no contemporaneous links involving ROI. Second, a structural equation model aligned with this spine quantifies paths and allows nonlinearity in the ROI channel: productivity raises ROI with delay, whereas the ROI → productivity effect is non-positive within the observed ROI range, with the implied U-shape’s minimum lying beyond that range. Third, fixed-effects panel checks and stress-tests (piecewise slopes at high-ROI percentiles, winsorisation, leave-one-sector-out, alternative clustering, and a turning-point bootstrap) corroborate the hierarchy and guard against out-of-support claims. The operating message is traditional yet actionable: growth is the prime mover, converting directly into productivity on impact; productivity is the transmission mechanism, flowing into ROI over time; ROI is the scoreboard, useful for governance and capital allocation but not a same-period production lever at realised levels. By decoupling contemporaneous from dynamic effects and benchmarking curvature against empirical support, the paper provides an audit-ready account of how to prioritise demand, protect capabilities, and let margins follow.

ABSTRACT. Logistics road transportation is challenged by a reduction of fleet emissions with the target to decrease the impact on climate change. This leads to a transition from traditional fossil fuel - driven combustion engines to alternative propulsion systems, and will result in a considerable share of battery-electric - driven vehicles in the near future. In this context, a successful ramp-up of electric trucks requires both, dedicated vehicle technology providing sufficient driving range and a suitable charging infrastructure. The present article introduces to the latest status and development trends of battery-electric propulsion systems for commercial vehicles. In addition, requirements on future charging infrastructure are introduced and discussed, covering both charging technologies and the development of charging system networks, which are able to fulfill the demands of future electrified logistics road transportation.

ABSTRACT. Generative artificial intelligence (gen. AI) is quickly improving its capabilities and constantly extends its areas of application, one of which is logistics. Major issues in logistics are a high environmental burden due to CO2 emissions and waste production from one-way transport items, e.g., cardboard-based boxes. While environmentally friendly circular economy solutions based on returnable transport items (RTI) exist, the adoption of suitable reverse logistics processes is sluggish. There is considerable potential to expedite a transition to RTI-based lo-gistics, using gen. AI tools for planning and data analysis. This review paper provides an overview of the most recent scientific publications about the applica-tion of gen. AI in reverse logistics and closed-loop supply chains. It will identify the most promising gen. AI use cases for further consideration in research and development and provides a critical assessment of their potential impact.

ABSTRACT. The take-use-dispose (Linear Economy) model has shaped forward logistics operations for years. The result of these activities is a diminishing amount of natural resources and progressive environmental degradation. The idea of a Circular Economy, which is the opposite of a linear economy, is to make greater use of products throughout their life cycle, thus eliminating previous waste. The Circular Economy concept changes the center of gravity of modern logistics by imple-menting the 3R practices (Reduce, Reuse, Recycle) from the 4R to the 10R prac-tices (3R+Refuse, Rethink, Repair, Refurbish, Remanufacture, Repurpose, Re-cover), the concept of Circular Economy shifting the focus of modern logistics, emphasizing its transition towards Reverse Logistics. The article presents a systematic literature review on the conditions for the functioning of Reverse Logistics in the context of implementing the Circular Economy practices. The research results identified 103 different Circular Economy practices and 263 articles analized. Recycling remains the dominant strategy of the 10 classic strategies most frequently considered and appears in over 58% of publications. A comprehensive discussion of all 3Rs in the context of Reverse Logistics was addressed in just over 2.2% of all articles analyzed, and the 3R model in only 1.4%. The research results show the lack of a systematic approach to the issue of Reverse Logistics, in favour of searching for solutions for individual Circular Economy practices. This demonstrates a significant research gap in the comprehensive approach to Reverse Logistics in the context of the challenges of the Circular Economy.

ABSTRACT. The rapid increase in textile waste poses critical challenges for recycling supply chains, especially in reverse logistics. This study identifies and prioritizes key logistics barriers to post-consumer textile recycling in India using expert interviews and multi-criteria decision-making tools, DEMATEL and Best-Worst Method (BWM). Eight major barriers were identified, with informal, unstandardized reverse networks and unsorted textile flows emerging as the most influential. These issues drive further inefficiencies such as irregular supply, complex routing, and weak data systems. The results suggest that improving collection systems, enabling basic sorting at source, and connecting informal actors to formal networks can significantly enhance reverse logistics performance. The findings provide practical insights for policymakers and industry leaders to strengthen India’s recycling ecosystem. This work contributes to Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production), 9 (Industry, Innovation and Infrastructure), and 11 (Sustainable Cities and Communities) by advancing circular practices in the textile sector.

ABSTRACT. Accurate estimation of solid waste (SW) generation according to type (contaminated, recycling, garbage, etc.,) is necessary to plan the location of disposal sites and choose an appropriate route for trash treatment. To forecast the amount of waste generated throughout the city of Austin, Texas, the Long Short-Term Memory (LSTM) and TimeGPT (generative pretrained transformer) models were developed for a variety of waste kinds. The construction of demand constraints for the purpose of minimizing route energy usage also makes use of these univariate prediction models. The developed mathematical model takes into account a route's cost and energy consumption and aids in the analysis of the best routes to make well-informed decision about route scheduling and other forms of SW allocation, guaranteeing that energy use is kept to a minimum during all scheduled time periods. Current study is carried out on the solid waste dataset of 2020-2021. The proposed framework is able to achieve better allocation of waste based on its type while minimizing the energy and cost of transportation.

ABSTRACT. Supply Chain Performance Management and Measurement Systems (SCPMMSs) is a topic that has grown in recent years. However, most of the research in SCPMMSs focuses on manufacturing industries, and there are few studies in the field of oil and gas. Oil companies have unique character-istics, which make the application of traditional models more complex and challenging compared to other industries. Considering this, the main objec-tive of this paper is to propose a conceptual metamodel, that can be used as the basis for the development of a performance management and measure-ment model, applicable to the supply chain of offshore drilling industry. Us-ing Design Science Research (DSR) integrated with a Systematic Literature Review (SLR) it was possible to develop a metamodel that integrates differ-ent artifacts found in the literature, as well as two recognized performance management reference models, SCOR and Balanced Scorecard, applicable to the offshore drilling industry supply chain.

ABSTRACT. This article proposes a set of stages for sizing resources for the design of a distribution center in a cleaning services company with projected increasing demand for its products. The stages consisted of information collection and analysis; design of the new facilities; and simulation and interpretation of the results. The simulation software Flexsim 2024 was used to identify the processes and infrastructure that would support the movements and operations of the new distribution center design. The stages allowed for choosing the future scenario to improve service levels at the lowest cost. It was concluded that the best scenario presents a percentage of complete orders and on-time deliveries of over 86%, making it feasible for the company to plan its logistics management in the medium and long term to achieve its goals.

ABSTRACT. Purpose – Drawing on the institutional theory and the self-determination theory, the current study examined the effect of internal pressures (INT_PRE), external pressures (EXT_PRE), and supply chain sustainability practices (SCS_PRA) on sustainability performance, namely economic performance (ECO_PER), environmental performance (ENV_PER), and social performance (SOC_PER). It also investigates the mediating role of collaboration and shared responsibility (CO_S_RE). Design/methodology/approach – Data were collected by questionnaire survey from 150 Canadian manufacturing firms. Structural equation modeling (SEM) was used to test the hypotheses. Findings—The findings showed that CO_S_RE fully mediated the link between EXR_PRE, INT_PRE, and SCS_PRA and SSCP. However, EXT_PRE is negatively related to CO_S_RE. CO_S_RE among SC members improves the benefits of supply chain sustainability and indeed has a bottom-line influence on sustainability performance. Originality/value—There is a lack of research on the collaboration and shared responsibility involved in mediating the relationship between pressures, sustainability practices, and SSCP. The current study aims to fill this knowledge gap and advance the ongoing discussion on the components supply chains require to improve SSCP. Unexplored future research opportunities are also addressed.

ABSTRACT. The success, costs, functionality, and quality of a product, as well as the necessary logistics structures, are already determined during development. More complex, global supply chains and a dramatically increasing product diversity require agile and increasingly complex logistics structures.

To integrate the requirements of networked production with the necessary logistics networks into product design as early as possible, logistics requirements are considered during product development using the Design for Logistics method. Manufacturing aspects are also incorporated early into the product development process by applying the Design for Manufacture and Assembly (DFMA) method to ensure a product design that is suitable for production and assembly.

This article outlines the fundamentals of the DFMA and DfL methods and how logistical complexity can be reduced by reducing the number of parts. Successful company examples illustrate this using reduced part counts and cost reductions.

ABSTRACT. This paper presents a simulation-based evaluation of mobile robot performance in a marina, focusing on beverage delivery to yachts. A simplified discrete-event model uses analytical estimates of patrol and delivery times to assess key metrics such as robot utilization, waiting times, and system throughput under various demand and configuration scenarios. Results highlight the impact of travel distances and limited robot speed, with waiting times growing exponentially as demand increases. A complementary 3D simulation, based on realistic marina geometry, serves as both a visualization tool and a basis for digital twin development. Initial integration with a ROS2-based robotic system demonstrates potential for real-time interaction and system planning.