Logistics

17 pages, 1606 KiB

Open AccessArticle

The Lean Advantage: Transforming E-Commerce Warehouse Operations for Competitive Success

by Mohammad Anwar Rahman and E. Daniel Kirby

Logistics 2024, 8(4), 129; https://doi.org/10.3390/logistics8040129 - 9 Dec 2024

This study investigates the transformation of e-commerce warehouse operations by integrating Lean Six Sigma tools to enhance efficiency and sustainability. Beginning with Value Stream Mapping (VSM) to identify inefficiencies, followed by a Hoshin Kanri plan to align improvement initiatives with strategic objectives, the [...] Read more.

This study investigates the transformation of e-commerce warehouse operations by integrating Lean Six Sigma tools to enhance efficiency and sustainability. Beginning with Value Stream Mapping (VSM) to identify inefficiencies, followed by a Hoshin Kanri plan to align improvement initiatives with strategic objectives, the study implemented measures such as pallet pooling, process standardization, automation in inspection and picking, layout optimization, and Kanban systems for continuous improvement. A case study of a local e-commerce warehouse specializing in medical devices and healthcare products identified 29 activities across receiving, inspection, storing, picking, packing, and shipping, highlighting inefficiencies addressed through Lean-driven initiatives. These efforts resulted in a 23% reduction in total lead time, doubled value-added time, and significant improvements in inspection, picking, packing, and automation, reducing delays, lowering costs, and enhancing workflow. The study fills a gap in the literature by integrating multiple Lean tools and utilizing the Critical to Quality (CTQ) matrix to ensure sustainable improvements in e-commerce warehousing, emphasizing the strategic value of Lean Six Sigma in creating efficient, customer-focused operations. Full article

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22 pages, 5957 KiB

Open AccessSystematic Review

A Study on the Research Clusters in the Humanitarian Supply Chain Literature: A Systematic Review

by Anchal Patil and Jitender Madaan

Logistics 2024, 8(4), 128; https://doi.org/10.3390/logistics8040128 - 6 Dec 2024

Abstract

Background: The humanitarian supply chain (HSC) literature has observed significant growth in past years. The wide range of research areas and the interdisciplinary nature of humanitarian work have generated the need to examine and classify the literature. Previous reviews have examined particular research [...] Read more.

Background: The humanitarian supply chain (HSC) literature has observed significant growth in past years. The wide range of research areas and the interdisciplinary nature of humanitarian work have generated the need to examine and classify the literature. Previous reviews have examined particular research domains such as quality, data analytics, performance measurement, and dynamics capabilities. This article examines the HSC literature, tracing its evolution and proposing a systematic review and roadmap for future researchers. Method: We adopted bibliometric, network, and citation analyses to extract insights into the HSC literature. Results: The integrated approach helped map the previous literature and identified research keywords, clusters, authors’ collaborative network, and seven research fields. The literature classification and clustering were performed for the articles published before the literature surge during the COVID-19 pandemic to avoid potential biases that could arise from the significant increase in HSC research published during this period. Conclusions: Some of the original contributions to this article include the classification of research clusters and the identification of emerging research topics in the HSC domain. Our findings indicate research opportunities in the sustainability, performance measurement, and innovation aspects of the HSC. This study provides potential research roadmaps for future research in this field. Full article

(This article belongs to the Section Humanitarian and Healthcare Logistics)

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19 pages, 1374 KiB

Open AccessArticle

Critical Factors for Green Public Procurement: The Case of Greece

by Varvara S. Orfanidou, Dimitrios J. Dimitriou, Nikolaos P. Rachaniotis and Giannis T. Tsoulfas

Logistics 2024, 8(4), 127; https://doi.org/10.3390/logistics8040127 - 5 Dec 2024

Abstract

Background: Green Public Procurement (GPP) is a sector that has been growing in recent years through policies encouraged by the European Union. In the Greek public sector, the respective National Action Plan (NAP), which sets specific targets for GPP, has very recently [...] Read more.

Background: Green Public Procurement (GPP) is a sector that has been growing in recent years through policies encouraged by the European Union. In the Greek public sector, the respective National Action Plan (NAP), which sets specific targets for GPP, has very recently come into force. However, although the influencing factors that contribute to the success of the implementation of green procurement are a crucial element of this policy, they have not yet been explored for the Greek public sector. Methods: This study applied data collection and a combined qualitative and quantitative data analysis. The research was divided into two phases: (i) the identification of critical factors (CFs) based on the literature, and (ii) an analysis of fourteen experts’ insights into those factors employing the Grey DEMATEL approach. Results: Based on the surveyed literature, fourteen CFs that contribute to the successful implementation of GPP were identified. From the analysis of the experts’ views, the factors were classified into two groups. Each group contains seven CFs. The CFs in the first group (causes) affect the CFs in the second group (effects). Conclusions: This study of the success factors in implementing green procurement in Greek public organizations can be further improved by incorporating new factors, as well as by utilizing the presented results in the follow-up of the NAP. Full article

(This article belongs to the Special Issue Advancements in Building Resilient Reverse Supply Chains: Strategies, Technologies, and Sustainable Practices)

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31 pages, 1377 KiB

Open AccessReview

Indoor Positioning Systems in Logistics: A Review

by Laura Vaccari, Antonio Maria Coruzzolo, Francesco Lolli and Miguel Afonso Sellitto

Logistics 2024, 8(4), 126; https://doi.org/10.3390/logistics8040126 - 4 Dec 2024

Abstract

Background: Indoor Positioning Systems (IPS) have gained increasing relevance in logistics, offering solutions for safety enhancement, intralogistics management, and material flow control across various environments such as industrial facilities, offices, hospitals, and supermarkets. This study aims to evaluate IPS technologies’ performance and applicability [...] Read more.

Background: Indoor Positioning Systems (IPS) have gained increasing relevance in logistics, offering solutions for safety enhancement, intralogistics management, and material flow control across various environments such as industrial facilities, offices, hospitals, and supermarkets. This study aims to evaluate IPS technologies’ performance and applicability to guide practitioners in selecting systems suited to specific contexts. Methods: The study systematically reviews key IPS technologies, positioning methods, data types, filtering methods, and hybrid technologies, alongside real-world examples of IPS applications in various testing environments. Results: Our findings reveal that radio-based technologies, such as Radio Frequency Identification (RFID), Ultra-wideband (UWB), Wi-Fi, and Bluetooth (BLE), are the most commonly used, with UWB offering the highest accuracy in industrial settings. Geometric methods, particularly multilateration, proved to be the most effective for positioning and are supported by advanced filtering techniques like the Extended Kalman Filter and machine learning models such as Convolutional Neural Networks. Overall, hybrid approaches that integrate multiple technologies demonstrated enhanced accuracy and reliability, effectively mitigating environmental interferences and signal attenuation. Conclusions: The study provides valuable insights for logistics practitioners, emphasizing the importance of selecting IPS technologies suited to specific operational contexts, where precision and reliability are critical to operational success. Full article

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28 pages, 1362 KiB

Open AccessArticle

Assessing Risky Riding Behaviors Among Food Delivery Motorcyclists in Thailand: Insights from the Motorcycle Rider Behavior Questionnaire and Health Belief Model

by Wimon Laphrom, Thanapong Champahom, Chamroeun Se, Supanida Nanthawong, Panuwat Wisutwattanasak, Vatanavongs Ratanavaraha and Sajjakaj Jomnonkwao

Logistics 2024, 8(4), 125; https://doi.org/10.3390/logistics8040125 - 3 Dec 2024

Abstract

Background: Food delivery motorcyclists face unique risks that often lead to risky riding behaviors. Thailand, with one of the highest rates of motorcycle-related injuries and fatalities globally, has seen a surge in food delivery services following the COVID-19 pandemic, increasing the number of [...] Read more.

Background: Food delivery motorcyclists face unique risks that often lead to risky riding behaviors. Thailand, with one of the highest rates of motorcycle-related injuries and fatalities globally, has seen a surge in food delivery services following the COVID-19 pandemic, increasing the number of motorcyclists on the roads. Delivery motorcyclists are especially vulnerable due to frequent exposure to traffic congestion, time pressures, and adverse weather. This study aims to identify key health beliefs and external factors contributing to risky riding behaviors among food delivery motorcyclists in Thailand. Methods: The study surveyed 2000 food delivery motorcyclists across five regions in Thailand, employing the Motorcycle Rider Behavior Questionnaire and the Health Belief Model. Structural equation modeling was used to analyze the relationships between health beliefs and risky riding behaviors. Results: The analysis revealed that health motivation, perceived susceptibility, perceived severity, perceived benefits, and cues to action were negatively associated with risky riding behaviors. Conversely, perceived barriers positively influenced these behaviors. Fatigue and aggressive riding were significant predictors of increased risky behaviors at the 0.001 level. Conclusions: Addressing individual health beliefs and external factors like fatigue and aggression is essential for reducing risky riding behaviors and preventing severe injuries. Full article

(This article belongs to the Special Issue Sustainable Logistics in the New Era)

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23 pages, 295 KiB

Open AccessArticle

Information Requirements and Legal Framework for Multimodal Transport System Coordination

by Dominik Wittenberg, Anne Paschke, Andre Kukuk and Jürgen Pannek

Logistics 2024, 8(4), 123; https://doi.org/10.3390/logistics8040123 - 3 Dec 2024

Abstract

Background: In multimodal transport the interplay of coordination methods and legal requirements is a challenging task. To address the latter, a combined approach for the coordination of a multimodal passenger transport system in accordance with European data protection law is required. Method: As [...] Read more.

Background: In multimodal transport the interplay of coordination methods and legal requirements is a challenging task. To address the latter, a combined approach for the coordination of a multimodal passenger transport system in accordance with European data protection law is required. Method: As a first step the paper analyses coordination related delays and outlines a combined optimisation problem. The problem formulation spans the strategic, tactical and operational level, to identify information requirements depending on coordinationmechanisms. The European legal systemregularly sets a pioneering standard, often serving as a model for other countries. Additionally, European data regulations frequently influence international data flows, as references to European traffic standards are often indispensable. To ensure compliance with data protection legislation, in a second step, this paper analyses the European Union’s legal framework for the protection of personal and non-personal data. Result: A respective system architecture for the integration of selected methods is proposed and the resulting analysis outlines the legal requirements for data usage under the Data Governance Act (DGA) and the General Data Protection Regulation (GDPR). Conclusions: Achieving a sustainable and efficient transportation system requires a balanced integration of advanced data-driven solutions and legal strategies, ensuring system efficiency and compliance with EU protection laws. Full article

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35 pages, 6919 KiB

Open AccessArticle

Situational Awareness Errors in Forklift Logistics Operations: A Multiphase Eye-Tracking and Think-Aloud Approach

by Claudia Yohana Arias-Portela, Jaime Mora-Vargas, Martha Caro and David Ernesto Salinas-Navarro

Logistics 2024, 8(4), 124; https://doi.org/10.3390/logistics8040124 - 2 Dec 2024

Abstract

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, [...] Read more.

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

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28 pages, 9169 KiB

Open AccessArticle

Economic Justice in the Design of a Sugarcane-Derived Biofuel Supply Chain: A Fair Profit Distribution Approach

by Jimmy Carvajal, William Sarache and Yasel Costa

Logistics 2024, 8(4), 122; https://doi.org/10.3390/logistics8040122 - 18 Nov 2024

Abstract

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 [...] Read more.

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

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27 pages, 7162 KiB

Open AccessArticle

A Combined Capacity Planning and Simulation Approach for the Optimization of AGV Systems in Complex Production Logistics Environments

by Péter Kováts and Róbert Skapinyecz

Logistics 2024, 8(4), 121; https://doi.org/10.3390/logistics8040121 - 18 Nov 2024

Abstract

Background: The capacity planning of production systems is one of the most fundamental strategic problems in the creation of a production plant. However, the implementation of increasingly complex production systems combined with sophisticated automated material handling justifies the development of novel approaches [...] Read more.

Background: The capacity planning of production systems is one of the most fundamental strategic problems in the creation of a production plant. However, the implementation of increasingly complex production systems combined with sophisticated automated material handling justifies the development of novel approaches to solve the combined capacity planning and material handling problem, which is also the objective of the current study. Methods: The presented approach combines the use of capacity planning formulas and discrete event simulation for optimizing extensive automated guided vehicle (AGV) systems from the aspect of the number of required vehicles. Extensive series of simulation experiments are applied in the case of each model variant for optimal results and to account for machine failures in the system. Results: The application of the proposed method is demonstrated through a realistic sample problem in a plastic industry setting with the use of the Siemens Tecnomatix Plant Simulation software (version 2302.0003, Educational license). Conclusions: The results from the sample problem demonstrate the usefulness of the approach, as a non-intuitive solution proved to be the most efficient. Additionally, the main advantage of the method is that it provides a standardized framework for the simulation-based optimization of AGV systems starting out from the comprehensive production capacity parameters. Full article

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29 pages, 6476 KiB

Open AccessArticle

Real-World Data Simulation Comparing GHG Emissions and Operational Performance of Two Sweeping Systems

by Bechir Ben Daya, Jean-François Audy and Amina Lamghari

Logistics 2024, 8(4), 120; https://doi.org/10.3390/logistics8040120 - 18 Nov 2024

Abstract

Background: In northern countries, spring requires the removal of large volumes of abrasive materials used in winter road maintenance. This sweeping process, crucial for safety and environmental protection, has traditionally relied on conventional mechanical brooms. Recent technological innovations, however, have introduced more [...] Read more.

Background: In northern countries, spring requires the removal of large volumes of abrasive materials used in winter road maintenance. This sweeping process, crucial for safety and environmental protection, has traditionally relied on conventional mechanical brooms. Recent technological innovations, however, have introduced more efficient and environmentally friendly sweeping solutions; Methods: This study provides a comprehensive comparative analysis of the environmental and operational performance of these innovative sweeping systems versus conventional methods. Using simulation models based on real-world data and integrating fuel consumption models, the analysis replicates sweeping behaviors to assess both operational and environmental performance. A sensitivity analysis was conducted using these models, focusing on key parameters such as the collection rate, the number of trucks, the payload capacity, and the truck unloading duration; Results: The results show that the innovative sweeping system achieves an average 45% reduction in GHG emissions per kilometer compared to the conventional system, consistently demonstrating superior environmental efficiency across all resources configurations; Conclusions: These insights offer valuable guidance for service providers by identifying effective resource configurations that align with both environmental and operational objectives. The approach adopted in this study demonstrates the potential to develop decision-making support tools that balance operational and environmental pillars of sustainability, encouraging policy decision-makers to adopt greener procurement policies. Future research should explore the integration of advanced technologies such as IoT, AI-driven analytics, and digital twin systems, along with life cycle assessments, to further support sustainable logistics in road maintenance. Full article

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21 pages, 3324 KiB

Open AccessArticle

A Web-Interface Based Decision Support System for Optimizing Home Healthcare Waste Collection Vehicle Routing

by Kubra Sar and Pezhman Ghadimi

Logistics 2024, 8(4), 119; https://doi.org/10.3390/logistics8040119 - 18 Nov 2024

Abstract

Background: The significant increase in home healthcare (HHC) driven by technological advancements, an ageing population, and heightened disease outbreaks—especially evident during the COVID-19 pandemic—has created an urgent need for improved medical waste management. Methods: This paper presents the development of a decision [...] Read more.

Background: The significant increase in home healthcare (HHC) driven by technological advancements, an ageing population, and heightened disease outbreaks—especially evident during the COVID-19 pandemic—has created an urgent need for improved medical waste management. Methods: This paper presents the development of a decision support system with a web-based interface designed for efficient medical waste collection in the HHC sector. Results: The system utilises Flask for backend operations, with HTML and CSS for the user interface, and manages data using JSON files. Its flexible design supports real-time adjustments for various vehicle types and changing waste production locations. It incorporates dynamic routing by employing two sophisticated metaheuristic algorithms: the Strength Pareto Evolutionary Algorithm (SPEA-2) and the Non-Dominated Sorting Genetic Algorithm (NSGA-II). This setup supports different dataset sizes and vehicle fleets, including Internal Combustion Engine (ICE) vehicles and Electric Vehicles (EVs). Conclusions: The automation reduces uncertainties in waste collection by minimising human intervention. The system is built to be easily adaptable for other sectors with minor modifications and can be expanded to test various scenarios with new selectable parameters. Full article

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19 pages, 2279 KiB

Open AccessArticle

Factors Affecting Truck Payload in Recycling Operations: Towards Sustainable Solutions

by Irina Harris, Diego Enrique Bermudez Bermejo, Thomas Crowther and James McDonald

Logistics 2024, 8(4), 118; https://doi.org/10.3390/logistics8040118 - 14 Nov 2024

Abstract

Background: One of the ongoing challenges in freight transport operations is to balance efficiency, effectiveness, and sustainability through the integration of sustainable practices to minimize the environmental impact. When it comes to truck payload and sustainability, the emphasis is on optimizing space, [...] Read more.

Background: One of the ongoing challenges in freight transport operations is to balance efficiency, effectiveness, and sustainability through the integration of sustainable practices to minimize the environmental impact. When it comes to truck payload and sustainability, the emphasis is on optimizing space, and minimizing empty miles and the wastage of resources. Ensuring that truck loads meet their targets has many challenges, and our empirical research examines the factors influencing the payloads of recycled fibre across the network in the UK paper industry. Methods: A mixed method approach includes interviews, business process analysis, the identification of opportunity areas, a site visit, simulation, and viability analysis to assess factors as part of the sustainable solution. Results: The research identified aspects related to processes, data availability and fragmentation, consistent procedures, practices, and operational considerations. Refining cage-loading procedures, enhancing baling processes and the visibility of upstream processes, and establishing robust information-sharing mechanisms improve efficiency and support sustainability. Conclusions: The empirical research extends the knowledge related to freight efficiency movements on the road and focuses on practical actions in utilizing recycled fibre’s carrying capacity. Full article

(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)

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25 pages, 4062 KiB

Open AccessArticle

Formalizing Sustainable Urban Mobility Management: An Innovative Approach with Digital Twin and Integrated Modeling

by Andrea Grotto, Pau Fonseca i Casas, Alyona Zubaryeva and Wolfram Sparber

Logistics 2024, 8(4), 117; https://doi.org/10.3390/logistics8040117 - 11 Nov 2024

Abstract

Background: Urban mobility management faces growing challenges that require the analysis and optimization of sustainable solutions. Digital twins (DTs) have emerged as innovative tools for this assessment, but their implementation requires standardized procedures and languages; Methods: As part of a broader [...] Read more.

Background: Urban mobility management faces growing challenges that require the analysis and optimization of sustainable solutions. Digital twins (DTs) have emerged as innovative tools for this assessment, but their implementation requires standardized procedures and languages; Methods: As part of a broader methodology for continuous DT validation, this study focuses on the conceptual validation phase, presenting a conceptualization approach through formalization using Specification and Description Language (SDL), agnostic to simulation tools. The conceptual validation was achieved through stakeholder engagement in the Bolzano context, producing 41 SDL diagrams that define both elements common to different urban realities and specific local data collection procedures; Results: The feasibility of implementing this stakeholder-validated conceptualization was demonstrated using Simulation of Urban MObility (SUMO) for traffic simulation and optimization criteria calculation, and its framework SUMO Activity GenerAtion (SAGA) for generating an Activity-Based Modeling (ABM) mobility demand that can be improved through real sensor data; Conclusions: The SDL approach, through its graphical representation (SDL/GR), enables conceptual validation by enhancing stakeholder communication while defining a framework that, while adapting to the monitoring specificities of different urban realities, maintains a common and rigorous structure, independent of the chosen implementation tools and programming languages. Full article

(This article belongs to the Topic New Technological Solutions, Research Methods, Simulation and Analytical Models That Support the Development of Modern Transport Systems)

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28 pages, 4514 KiB

Open AccessArticle

Evaluating Supply Chain Network Models for Third Party Logistics Operated Supply-Processing-Distribution in Thai Hospitals: An AHP-Fuzzy TOPSIS Approach

by Duangpun Kritchanchai, Daranee Senarak, Tuangyot Supeekit and Wirachchaya Chanpuypetch

Logistics 2024, 8(4), 116; https://doi.org/10.3390/logistics8040116 - 9 Nov 2024

Abstract

Background: This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, [...] Read more.

Background: This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, hospitals can enhance their operational efficiency, allowing healthcare professionals to focus on core tasks and ultimately improving service delivery. Methods: This research employed a dual methodology, combining an analytic hierarchy process (AHP) with a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). These approaches evaluated various SCM models based on multiple hospital logistics performance attributes. Results: The AHP results highlighted on-time delivery, patient safety, utilisation rate, and emergency procurement as critical criteria for selecting the optimal model. Fuzzy TOPSIS analysis identified the SCIII: W-G-H model as the most suitable for implementation in Thai hospitals. This model incorporates a centralised warehouse for negotiation leverage, a Group Purchasing Organisation (GPO) for cost efficiency, and regional SPD hubs for effective inventory management and rapid responses to demand fluctuations or emergencies. Conclusions: Adopting this SCM model is expected to significantly enhance supply chain performance, reduce operational costs, and improve the quality and safety of patient care in Thai hospitals. Full article

(This article belongs to the Section Supplier, Government and Procurement Logistics)

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19 pages, 1529 KiB

Open AccessSystematic Review

Mountain Logistics: A Systematic Literature Review and Future Research Directions

by Mehari Beyene Teshome, Faisal Rasool and Guido Orzes

Logistics 2024, 8(4), 115; https://doi.org/10.3390/logistics8040115 - 8 Nov 2024

Abstract

Background: The sustainable development of mountain areas, which have fragile ecosystems, has increasingly attracted the attention of researchers and practitioners. Logistics systems are crucial in supporting these regions and addressing mountainous terrain’s unique challenges. While many studies have examined aspects of mountain [...] Read more.

Background: The sustainable development of mountain areas, which have fragile ecosystems, has increasingly attracted the attention of researchers and practitioners. Logistics systems are crucial in supporting these regions and addressing mountainous terrain’s unique challenges. While many studies have examined aspects of mountain logistics, a comprehensive and systematic review of the field is still lacking. Design/Methodology/Approach: This paper aims to fill the gap by systematically reviewing the existing literature on mountain logistics using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. Results/Conclusions: We identify four main research foci: design of logistics infrastructure or vector, optimization of logistics systems, safety in logistics systems, and impact of logistics systems on mountain communities. In addition to categorizing these themes, we conduct a detailed descriptive analysis of published studies in this domain. Our findings highlight significant research gaps, particularly in integrating digital technologies, sustainable mass transportation solutions, and logistics systems’ socioeconomic and environmental impacts. We propose targeted directions for future research to advance sustainable logistics practices in mountain regions. Full article

(This article belongs to the Section Sustainable Supply Chains and Logistics)

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21 pages, 10558 KiB

Open AccessArticle

Automating Logistics Operations: Qualitative Insights from Four European Sites

by Guglielmo Papagni, Setareh Zafari, Johann Schrammel and Manfred Tscheligi

Logistics 2024, 8(4), 114; https://doi.org/10.3390/logistics8040114 - 8 Nov 2024

Abstract

Background: Automated vehicles are increasingly entering logistics operations, driven by factors like controllability, standardization, and reduced risk. However, successful automation requires understanding the diverse perspectives of logistics stakeholders. Method: This paper investigates these perspectives through 28 interviews with representatives from five key stakeholder [...] Read more.

Background: Automated vehicles are increasingly entering logistics operations, driven by factors like controllability, standardization, and reduced risk. However, successful automation requires understanding the diverse perspectives of logistics stakeholders. Method: This paper investigates these perspectives through 28 interviews with representatives from five key stakeholder groups within the European Project AWARD’s four pilot sites. Results: Key findings highlight positive expectations for efficiency, safety, and reliability, but also identify critical prerequisites still to be met: further technological advancements, shifts in logistics roles and working conditions, regulatory improvements, and careful narrative building around technology. Conclusions: A deeper analysis of individual stakeholder groups and pilot site representatives reveals nuanced needs and concerns, emphasizing the importance of considering different perspectives and need for further research involving a wider range of stakeholder groups to fully capture the complexities of this emerging field. Full article

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25 pages, 5137 KiB

Open AccessArticle

A POMDP Approach to Map Victims in Disaster Scenarios

by Pedro Gabriel Villani and Paulo Sergio Cugnasca

Logistics 2024, 8(4), 113; https://doi.org/10.3390/logistics8040113 - 7 Nov 2024

Abstract

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 [...] Read more.

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

(This article belongs to the Section Humanitarian and Healthcare Logistics)

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19 pages, 1823 KiB

Open AccessArticle

Studying the Moderating Effects of Additive Manufacturing Best Practices Between Supply Chain Complexity and Its Performance

by Tekalign Lemma, Hirpa G. Lemu and Endalkachew Mosisa Gutema

Logistics 2024, 8(4), 112; https://doi.org/10.3390/logistics8040112 - 6 Nov 2024

Abstract

Background: Supply chain performance (SCP) is impacted by complexity brought about by static and dynamic drivers. This study aims to investigate the effects of supply chain complexity (SCC) on SCP and ascertain whether additive manufacturing best practices have moderating effects on this relationship. [...] Read more.

Background: Supply chain performance (SCP) is impacted by complexity brought about by static and dynamic drivers. This study aims to investigate the effects of supply chain complexity (SCC) on SCP and ascertain whether additive manufacturing best practices have moderating effects on this relationship. Methods: Using data from 29 Ethiopian footwear industries and 205 respondents, the relationship established in the theoretical framework was validated using structural equation modelling (SEM). Results: The study’s findings provided several important insights. First, upstream supply chain complexity (USSCC), midstream supply chain complexity (MSSCC), and downstream supply chain complexity (DSSCC) negatively affect SCP. Second, additive manufacturing best practices have significant moderation effects between supply chain complexity and supply chain performance. Third, the negative impacts of USSCC and MSSCC on SCP are reduced at a higher level of additive manufacturing adaptation. The findings of this study also revealed that the effects of DSSCC on SCP have no difference at both low and high levels of additive manufacturing best practices. Conclusions: This work offers the first empirical investigation to which the detrimental effects of SCC on SCP are mitigated or improved through the moderating role of additive manufacturing best practice. Full article

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26 pages, 392 KiB

Open AccessArticle

Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization

by Meriem Riad, Mohamed Naimi and Chafik Okar

Logistics 2024, 8(4), 111; https://doi.org/10.3390/logistics8040111 - 6 Nov 2024

Abstract

Background: Amid growing global uncertainty and increasingly complex disruptions, the ability of supply chains to rapidly adapt and recover is critical. The incorporation of artificial intelligence (AI) into supply chain management represents a transformative strategy for enhancing resilience. By harnessing advanced AI [...] Read more.

Background: Amid growing global uncertainty and increasingly complex disruptions, the ability of supply chains to rapidly adapt and recover is critical. The incorporation of artificial intelligence (AI) into supply chain management represents a transformative strategy for enhancing resilience. By harnessing advanced AI technologies, such as machine learning, predictive analytics, and real-time data processing, organizations can more effectively anticipate, respond to, and recover from disruptions.AI improves demand forecasting accuracy, optimizes inventory management, and increases real-time visibility across the supply chain, reducing the risks of stockouts and surplus inventory. Furthermore, I-driven automation and robotics enhance operational efficiency by minimizing human error and streamlining processes. Methodology/Approach: This paper proposes a conceptual framework for strengthening supply chain resilience through AI integration. The framework leverages AI technologies to improve key aspects of supply chain resilience, including risk management, operational efficiency, and real-time visibility. Result/Conclusions: Additionally, it underscores the importance of collaborative relationships with supply chain partners, enabled by AI-powered data-sharing and communication tools that foster trust and coordination within the network. Originality/Value: This comprehensive framework offers a strategic approach to integrating AI into supply chain management, highlighting its potential to significantly enhance resilience, operational efficiency, and sustainability, thereby empowering organizations to navigate the complexities of modern supply chains more effectively. Full article

(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)

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