Journal Description
Logistics
Logistics
is an international, scientific, peer-reviewed, open access journal of logistics and supply chain management published quarterly online by MDPI. The first issue has been released in December 2017.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), RePEc, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 25.4 days after submission; acceptance to publication is undertaken in 9.9 days (median values for papers published in this journal in the second half of 2023).
- Journal Rank: JCR - Q2 (Operations Research and Management Science) / CiteScore - Q1 (Management Information Systems)
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.6 (2023);
5-Year Impact Factor:
3.7 (2023)
Latest Articles
Zero-Emission Heavy-Duty, Long-Haul Trucking: Obstacles and Opportunities for Logistics in North America
Logistics 2024, 8(3), 64; https://doi.org/10.3390/logistics8030064 - 27 Jun 2024
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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
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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
Open AccessReview
Analysis of Supply Chain Response Frameworks: A Literature Review
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Raúl Antonio Díaz Pacheco and Ernest Benedito
Logistics 2024, 8(3), 63; https://doi.org/10.3390/logistics8030063 - 25 Jun 2024
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Background: Various supply chain response frameworks (SCRFs) have been proposed in the supply chain (SC) literature, but there is no in-depth analysis. This study analyzes the applicability of SCRFs in scenarios that require SC responses by examining the frameworks’ design and use
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Background: Various supply chain response frameworks (SCRFs) have been proposed in the supply chain (SC) literature, but there is no in-depth analysis. This study analyzes the applicability of SCRFs in scenarios that require SC responses by examining the frameworks’ design and use in response situations. Methods: A qualitative analysis of 38 studies revealed weaknesses in SCRFs, which include the entity proposing the framework, the stimulus being responded to, the adaptation of activities to the stimulus that is responded to, objectives, and response evaluation criteria. Results: The analysis reveals that while these frameworks have been designed for specific situations involving single SC processes, they demonstrate weaknesses by failing to meet two requirements: (1) the stimulus being responded to is different from changes in demand, and (2) the response is generated by a process distinct from manufacturing. Conclusions: Further, SCRF research that incorporates these weaknesses will promote the fragmented development of the SCR concept. Conversely, a robust SCRF can be successfully utilized in various SCRs, facilitating the comparison and evaluation of responses of different SCs to the same stimulus.
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Open AccessArticle
Optimal Strategy of Unreliable Flexible Production System Using Information System
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Sadok Rezig, Sadok Turki, Ayoub Chakroun and Nidhal Rezg
Logistics 2024, 8(2), 62; https://doi.org/10.3390/logistics8020062 - 17 Jun 2024
Abstract
Background: Optimization approaches and a models can be applied for critical production systems that experience equipment failure, repair delays and product quality control in order to maximize the total profit. We can cite, as an example, flexible manufacturing systems. Methods: Our
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Background: Optimization approaches and a models can be applied for critical production systems that experience equipment failure, repair delays and product quality control in order to maximize the total profit. We can cite, as an example, flexible manufacturing systems. Methods: Our methodology involves developing a decision model integrated with an information system to coordinate various system operations, ensuring timely response to customer requests. The module of the information system is provided to optimally manage the production flow and parts ordering according to machine availability. The objective is to determine the optimal order thresholds of part batches that maximize the total profit. Results: Numerical results are provided to analyze the influence of system reliability and uncertainty on decision variables, offering insights into the system’s performance and robustness. By using our method, the advancement of the flexible production systems is carried out by addressing key operational challenges and optimizing production processes for enhanced efficiency and profitability. Conclusions: To achieve this, an optimization algorithm is employed to identify optimal solutions that enhance profitability.
Full article
(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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Open AccessArticle
Performance Analysis of Automated Parcel Lockers in Urban Delivery: Combined Agent-Based–Monte Carlo Simulation Approach
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Eugen Rosca, Florin Rusca, Mircea Augustin Rosca and Aura Rusca
Logistics 2024, 8(2), 61; https://doi.org/10.3390/logistics8020061 - 14 Jun 2024
Abstract
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
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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
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Open AccessReview
Humanitarian Logistics Prioritization Models: A Systematic Literature Review
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María Fernanda Carnero Quispe, Amanda Silveira Couto, Irineu de Brito Junior, Luiza Ribeiro Alves Cunha, Regiane Máximo Siqueira and Hugo Tsugunobu Yoshida Yoshizaki
Logistics 2024, 8(2), 60; https://doi.org/10.3390/logistics8020060 - 7 Jun 2024
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Background: Disasters have caused suffering across the world throughout history. Different types of disaster events can manifest themselves in different ways, originating from natural phenomena, human actions and their interconnected interactions. In recent years, organizations in charge of disaster management have faced a
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Background: Disasters have caused suffering across the world throughout history. Different types of disaster events can manifest themselves in different ways, originating from natural phenomena, human actions and their interconnected interactions. In recent years, organizations in charge of disaster management have faced a series of challenges in humanitarian logistics, leading to an increasing consideration of the use of models of prioritization, in most multi-criteria models, to define the best alternatives for more assertive and strategic decision-making. Methods: This article aims to conduct a systematic review of the literature on the application of prioritization models in humanitarian logistics. To this end, an analysis was carried out of 40 articles, indexed in the Scopus or Web of Science databases. Results: The descriptive analysis revealed that the majority of applications are aimed at dealing with sudden-onset natural-induced disasters. However, there are still gaps in relevant areas, such as addressing inventory management problems at a tactical decision level. Conclusions: The development of prioritization models necessitates the integration of various methodologies, combining optimization models with multi-criteria decision analysis to yield superior outcomes. It is advised to incorporate four distinct criteria—efficiency, effectiveness, equity, and sustainability—to ensure a comprehensive assessment of the decision-making process.
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Open AccessArticle
Study on the Relationship between Port Governance and Terminal Operation System for Smart Port: Japan Case
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Hideyo Inutsuka, Kinya Ichimura, Yoshihisa Sugimura, Muneo Yoshie and Takeshi Shinoda
Logistics 2024, 8(2), 59; https://doi.org/10.3390/logistics8020059 - 6 Jun 2024
Abstract
Background: To improve port productivity, safety, and sustainability, the use of information and communication technology is being promoted as a smart port. The utilization of a terminal operation system (TOS) is important for advanced port operations, and it is necessary to organize
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Background: To improve port productivity, safety, and sustainability, the use of information and communication technology is being promoted as a smart port. The utilization of a terminal operation system (TOS) is important for advanced port operations, and it is necessary to organize the issues and characteristics of the TOS. Methods: The characteristics of TOSs introduced in Japan and those widely introduced in Europe and Southeast Asia will be investigated and discussed according to the port management system in Japan. Results: Japanese TOSs are characterized by a lack of automated functions, such as ship loading plans, and by the fact that they are designed to allow the crane driver to select the order of operations, which may be attributed to a system wherein stakeholders are segmented and on-site decisions are emphasized. The promotion of smart ports in Japanese-style ports requires a system for information linkage between stakeholders. Conclusions: TOS capabilities for smart ports should be implemented according to the characteristics of port management in each region, and the studies conducted in this paper are useful in examining port system implementation strategies.
Full article
(This article belongs to the Section Maritime and Transport Logistics)
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Open AccessArticle
Use of End-to-End Tool for the Analysis of the Digital Governance of Ports
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Nicoletta González-Cancelas, Alberto Camarero Orive, Alberto Rivas Vilarchao and Javier Vaca-Cabrero
Logistics 2024, 8(2), 58; https://doi.org/10.3390/logistics8020058 - 6 Jun 2024
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Background: Digital governance currently presents challenges in the context of ports, where efficiency and transparency are key elements for the success of operations. In ports, the effective adoption of digital governance can have a significant impact on optimizing operational processes and improving
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Background: Digital governance currently presents challenges in the context of ports, where efficiency and transparency are key elements for the success of operations. In ports, the effective adoption of digital governance can have a significant impact on optimizing operational processes and improving coordination between port authorities, logistics operators and customs. Method: In this context, the article proposes the use of an End-to-End Tool to analyze and evaluate digital governance in ports. This tool makes it possible to collect data from various sources, carry out a thorough analysis of the processes involved, and evaluate the satisfaction of end users. In addition, it provides an intuitive and easy-to-use interface to visualize results and make evidence-based decisions. The outcomes revealed areas of improvement in operational processes, identified bottlenecks, and presented proposals to optimize port efficiency. Results: The port currently exhibiting the best digital governance is Valencia, followed by Piraeus, Barcelona, and Algeciras, with very comparable management, and finally, Genoa. Conclusions: Efficient public–private collaboration in digital governance boosts port competitiveness. Regulatory frameworks for data security are crucial, and digital governance emerges as vital for global success.
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Open AccessArticle
The Development of Risk Assessments and Supplier Resilience Models for Military Industrial Supply Chains Considering Rare Disruptions
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Anna Urmston, Dongping Song and Andrew Lyons
Logistics 2024, 8(2), 57; https://doi.org/10.3390/logistics8020057 - 4 Jun 2024
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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
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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
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Open AccessArticle
Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit
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Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo, Oliverio Cruz-Mejia and Jose-Manuel Mejia-Muñoz
Logistics 2024, 8(2), 56; https://doi.org/10.3390/logistics8020056 - 3 Jun 2024
Abstract
Background: Efficient inventory management is critical for sustainability in supply chains. However, maintaining adequate inventory levels becomes challenging in the face of unpredictable demand patterns. Furthermore, the need to disseminate demand-related information throughout a company often relies on cloud services. However, this
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Background: Efficient inventory management is critical for sustainability in supply chains. However, maintaining adequate inventory levels becomes challenging in the face of unpredictable demand patterns. Furthermore, the need to disseminate demand-related information throughout a company often relies on cloud services. However, this method sometimes encounters issues such as limited bandwidth and increased latency. Methods: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. Our approach involves the use of an attention mechanism for accurate demand prediction. We combine it with the Newsvendor model to determine optimal inventory levels. The system is integrated with fog computing to facilitate the rapid dissemination of information throughout the company. Results: In experiments, we compare the proposed system with the conventional demand estimation approach based on historical data and observe that the proposed system consistently outperformed the conventional approach. Conclusions: This research introduces an inventory management system based on a novel deep learning architecture that integrates the attention mechanism with cloud computing to address the Newsvendor problem. Experiments demonstrate the better accuracy of this system in comparison to existing methods. More studies should be conducted to explore its applicability to other demand modeling scenarios.
Full article
(This article belongs to the Special Issue Innovative Digital Supply Chain 4.0 Transformation)
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Open AccessArticle
Make-or-Buy Policy Decision in Maintenance Planning for Mobility: A Multi-Criteria Approach
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Tommaso Ortalli, Andrea Di Martino, Michela Longo and Dario Zaninelli
Logistics 2024, 8(2), 55; https://doi.org/10.3390/logistics8020055 - 20 May 2024
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Background: The ongoing technical innovation is fully involving transportation sector, converting the usual mass-transit system toward a sustainable mobility. Make-or-buy decision are usually adopted to assess different solutions in terms of costs-benefits to put in place strategic choices regarding in-house production or
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Background: The ongoing technical innovation is fully involving transportation sector, converting the usual mass-transit system toward a sustainable mobility. Make-or-buy decision are usually adopted to assess different solutions in terms of costs-benefits to put in place strategic choices regarding in-house production or from an external supplier. This can also be reflected on maintenance operations, thus replicating a similar approach to transport companies involved. Method: A decision-making model by means of a multi-criteria analysis can lead make-or-buy choices adapted to maintenance. A brief introduction into the actual mobility context is provided, evaluating global and national trends with respect to the mobility solutions offered. Then, a focus is set on maintenance approaches in mobility sector and the need of a make-or-buy decision process is considered. The decision-making path is developed through a multi-criteria framework based on eigenvector weighing assessment, where different Key Performance Indicators (KPIs) are identified and exploited to assess the maintenance approach at stake. Results: A comparison among different scenarios considered helped in identify the solution offered to the transport operator. In particular, for the case study of interest a −35% decrease in maintenance specific cost and −44% in cost variability were found. Reliability of the fleet was kept at an acceptable level compared to the reference in-house maintenance (≥90%) while an increase in the Mean Time Between Failure was observed. Conclusions: For the purposes of a small company, the method can address the choice of outsourcing maintenance as the best. Finally, a general trend is then extrapolated from the analysis performed, in order to constitute a decision guideline. The research can benefit from further analysis to test and validate that the selected approach is effective from the perspective of transport operator.
Full article
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Open AccessReview
Closing the Gap: A Comprehensive Review of the Literature on Closed-Loop Supply Chains
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Melissa Zengin, Saman Hassanzadeh Amin and Guoqing Zhang
Logistics 2024, 8(2), 54; https://doi.org/10.3390/logistics8020054 - 13 May 2024
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Background: Sustainable closed-loop supply chains have emerged as viable answers to supply chain problems. They can handle environmental damages (e.g., waste) and related social impacts. Closed-loop supply chains (CLSCs) are forward and reverse supply chain networks that have gained popularity in recent
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Background: Sustainable closed-loop supply chains have emerged as viable answers to supply chain problems. They can handle environmental damages (e.g., waste) and related social impacts. Closed-loop supply chains (CLSCs) are forward and reverse supply chain networks that have gained popularity in recent years. Recovery options such as reusing, remanufacturing and recycling can be considered in CLSCs. Methods: This paper provides a comprehensive evaluation of CLSC journal papers published between 2020 and the present. This study examines and synthesizes 54 papers from major publications in this area, covering a wide range of themes and approaches. This paper aims to respond to the following key questions: (i) What are the current trends and challenges in CLSC research, and how have they evolved since previous literature review papers? (ii) What key variables and objectives have been studied in recent CLSC research, and how have they been operationalized? (iii) What are the gaps and limitations in current CLSC research? To our knowledge, other literature review papers in this field have covered older papers, and recent papers have been ignored in them. Another research contribution of this paper is the taxonomy of it. Results: This review article highlights some developing themes and research gaps in the CLSC literature and makes recommendations for further study. Conclusions: This paper provides a comprehensive review of papers on closed-loop supply chain networks.
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Open AccessArticle
Artificial Intelligence Capabilities for Demand Planning Process
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Claudia Aparecida de Mattos, Fernanda Caveiro Correia and Kumiko Oshio Kissimoto
Logistics 2024, 8(2), 53; https://doi.org/10.3390/logistics8020053 - 10 May 2024
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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
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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
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Open AccessArticle
Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping
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Bartosz Sawik
Logistics 2024, 8(2), 52; https://doi.org/10.3390/logistics8020052 - 8 May 2024
Cited by 1
Abstract
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
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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
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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Open AccessArticle
The Principal-Agent Theoretical Ramifications on Digital Transformation of Ports in Emerging Economies
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Benjamin Mosses Sakita, Berit Irene Helgheim and Svein Bråthen
Logistics 2024, 8(2), 51; https://doi.org/10.3390/logistics8020051 - 8 May 2024
Abstract
Background: Scholarly literature indicates a slow pace at which maritime ports fully embrace digital transformation (DT). The reasons to this are largely anecdotal and lack solid empirical grounding. This inhibits an overall understanding of DT’s tenets and the development of evidence-based policies
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Background: Scholarly literature indicates a slow pace at which maritime ports fully embrace digital transformation (DT). The reasons to this are largely anecdotal and lack solid empirical grounding. This inhibits an overall understanding of DT’s tenets and the development of evidence-based policies and targeted actions. Methods: This study deployed a qualitative case study strategy to unpack the challenges of undertaking DT through the lens of principal-agent theory (PAT). Results: Analysis of data collected through 13 semi-structured interviews from a port’s value chain stakeholders revealed five thematic challenges that contradict successful implementation of DT. These included interagency constraints and system ownership tussles; system sabotage and prevalent corruption; prevalent human agency in port operations; cultural constraints; and political influence on port governance. Conclusions: To address these challenges, the study proposes a four-stage empirically grounded DT strategy framework that guides both practitioners and policymakers through DT endeavors. The framework includes: (1) the port’s value chain mapping, (2) stakeholder engagement, (3) resource mobilization, and (4) effective monitoring. For scholars, we provide an avenue for testing statistical significance of association and causality among the identified challenges.
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(This article belongs to the Topic Global Maritime Logistics in the Era of Industry 4.0)
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Open AccessArticle
Mathematical Programming Formulations for the Berth Allocation Problems in Container Seaport Terminals
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Awad M. Aljuaid, Mayssa Koubâa, Mohamed Haykal Ammar, Karim Kammoun and Wafik Hachicha
Logistics 2024, 8(2), 50; https://doi.org/10.3390/logistics8020050 - 7 May 2024
Abstract
Background: Improving the performance of marine terminals is one of the major concerns of both researchers and decision-makers in the maritime transportation sector. The problem of container storage planning and the berth allocation problem (BAP) are the two mainstays of optimizing port operations.
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Background: Improving the performance of marine terminals is one of the major concerns of both researchers and decision-makers in the maritime transportation sector. The problem of container storage planning and the berth allocation problem (BAP) are the two mainstays of optimizing port operations. Methods: In this work, we address these two issues, proposing two mathematical models that operate sequentially and are applicable to both static and dynamic cases. The first developed model is a mixed-integer linear problem model aimed at minimizing vessel traffic time in the port. The second model developed is a multi-objective optimization model based on goal programming (GP) to minimize both container transfer time and the number of storage areas (minimizing container dispersion). Results: The robustness of the proposed models has been proven through a benchmark with tests using data from the literature and real port data, based on the IBM ILOG CPLEX 12.5 solver. Conclusions: The two developed mathematical models allowed the both minimization of the transfer time and the number of used storage areas, whatever the number of operations handling companies (OHCs) operating in the seaport and for both static and dynamic cases. We propose, as prospects for this work, the development of a heuristic model to deal with the major instances relating to the case of large ports.
Full article
(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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Open AccessArticle
Implementing Additive Manufacturing in Orthopedic Shoe Supply Chains—Cost and Lead Time Comparison
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Victor Verboeket, Harold Krikke and Mika Salmi
Logistics 2024, 8(2), 49; https://doi.org/10.3390/logistics8020049 - 7 May 2024
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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
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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.
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Open AccessArticle
A Compact Model for the Clustered Orienteering Problem
by
Roberto Montemanni and Derek H. Smith
Logistics 2024, 8(2), 48; https://doi.org/10.3390/logistics8020048 - 6 May 2024
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Background: The Clustered Orienteering Problem is an optimization problem faced in last-mile logistics. The aim is, given an available time window, to visit vertices and to collect as much profit as possible in the given time. The vertices to visit have to be
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Background: The Clustered Orienteering Problem is an optimization problem faced in last-mile logistics. The aim is, given an available time window, to visit vertices and to collect as much profit as possible in the given time. The vertices to visit have to be selected among a set of service requests. In particular, the vertices belong to clusters, the profits are associated with clusters, and the price relative to a cluster is collected only if all the vertices of a cluster are visited. Any solving methods providing better solutions also imply a new step towards sustainable logistics since companies can rely on more efficient delivery patterns, which, in turn, are associated with an improved urban environment with benefits both to the population and the administration thanks to an optimized and controlled last-mile delivery flow. Methods: In this paper, we propose a constraint programming model for the problem, and we empirically evaluate the potential of the new model by solving it with out-of-the-box software. Results: The results indicate that, when compared to the exact methods currently available in the literature, the new approach proposed stands out. Moreover, when comparing the quality of the heuristic solutions retrieved by the new model with those found by tailored methods, a good performance can be observed. In more detail, many new best-known upper bounds for the cost of the optimal solutions are reported, and several instances are solved to optimality for the first time. Conclusions: The paper provides a new practical and easy-to-implement tool to effectively deal with an optimization problem commonly faced in last-mile logistics.
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Open AccessArticle
Modelling Consumers’ Preferences for Time-Slot Based Home Delivery of Goods Bought Online: An Empirical Study in Christchurch
by
Ashu Kedia, Dana Abudayyeh, Diana Kusumastuti and Alan Nicholson
Logistics 2024, 8(2), 47; https://doi.org/10.3390/logistics8020047 - 4 May 2024
Abstract
Background: Due to the remarkable growth in online retail sales in New Zealand, a large number of parcels are needed to be delivered to consumers’ doorsteps. Home deliveries in major New Zealand cities (e.g., Christchurch) typically occur between 9 a.m. and 6
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Background: Due to the remarkable growth in online retail sales in New Zealand, a large number of parcels are needed to be delivered to consumers’ doorsteps. Home deliveries in major New Zealand cities (e.g., Christchurch) typically occur between 9 a.m. and 6 p.m. on weekdays, when many home delivery attempts fail. This leads to adverse effects, such as vehicular traffic in residential areas and greater air pollution per parcel delivered. However, home deliveries outside of typical business hours (i.e., before 9 a.m. and after 5 p.m.) might be worthwhile to help subside the above issues. Therefore, this study investigated consumers’ preferences for receiving home deliveries during various times, such as early morning, morning, afternoon, late afternoon, and evening. Methods: The data used in this study were obtained via an online survey of 355 residents of Christchurch city. Non-parametric tests, namely the Friedman test, Wilcoxon signed-rank test, and ordinal logistic regression, were carried out to examine consumer preferences for the above time slots. Results: The results showed that consumers preferred the late afternoon (3 p.m. to 6 p.m.) time slot the most for receiving home deliveries. Conclusion: It appeared that the off-peak delivery option is less likely to draw the desired consumer patronage and is thus less likely to assist in lowering the number of unsuccessful home deliveries, the transportation costs incurred by service providers, traffic congestion, and pollution in urban areas.
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(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)
Open AccessArticle
Application of Logistic Regression to Analyze The Economic Efficiency of Vehicle Operation in Terms of the Financial Security of Enterprises
by
Malgorzata Grzelak, Paulina Owczarek, Ramona-Monica Stoica, Daniela Voicu and Radu Vilău
Logistics 2024, 8(2), 46; https://doi.org/10.3390/logistics8020046 - 1 May 2024
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Background: A measurable feature of the efficiency of vehicle use in transportation companies is the revenue from transport orders, which has a significant impact on their profitability. Therefore, it is important to skillfully analyze the parameters related to the operation of vehicles
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Background: A measurable feature of the efficiency of vehicle use in transportation companies is the revenue from transport orders, which has a significant impact on their profitability. Therefore, it is important to skillfully analyze the parameters related to the operation of vehicles and their impact on the bottom line. Transportation companies, when managing their operations, take steps to reduce operating costs. The above makes a large number of studies available in the literature on the analysis of vehicle damage or wear of system components, as well as ways to predict them. However, there is a lack of studies treating the impact of the parameters of specific orders on economic efficiency, which is a research niche undertaken in the following study. Methods: The purpose of this article was to analyze the economic efficiency of vehicle operation in terms of the financial security of enterprises. The main research problem was formulated in the form of the question of how the various parameters of a transport order affect its profitability. During our study, critical analysis of the literature, mathematical modeling and inference were used. A detailed analysis of transport orders executed by SMEs (small and medium-sized enterprises), which are characterized by a fleet of light commercial vehicles with a capacity of up to 3.5 t, was carried out in the FMCG (Fast-Moving Consumer Good) industry in Poland in 2021–2022. Due to the binary variable form, a logistic regression model was elaborated. The estimated parameters of the model and the calculated odds ratios made it possible to assess the influence of the selected factors on the profitability of orders. Results: Among other things, it was shown that in the case of daily vehicle mileage, the odds quotient indicates that with each additional kilometer driven, the probability of profitability of an order increases by 1%. Taking into account the speed of travel, it is estimated that with an increase in its value by 1 km/h, the probability of profitability of an order decreases by 3%. On the other hand, an increase in cargo weight by 1 kg makes the probability of a profitable order increase by 9%. Conclusion: Through this study, the limited availability of low-cost analytical tools that can be applied during transportation fleet management in SME companies was confirmed, as was the use of simple and non-expansive mathematical models. At the same time, they are not “black boxes” and therefore enable drawing and implementing model conclusions into operations. The results obtained can help shape the overall strategy of companies in the area of vehicle operation and can support the decision-making process related to the management of subsequent orders, indicating those that will bring the highest profit. The above is very important for SME companies, which often operate on the verge of profitability.
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Open AccessArticle
Electrifying the Last-Mile Logistics (LML) in Intensive B2B Operations—An European Perspective on Integrating Innovative Platforms
by
Alejandro Sanz and Peter Meyer
Logistics 2024, 8(2), 45; https://doi.org/10.3390/logistics8020045 - 17 Apr 2024
Abstract
Background: literature on last mile logistic electrification has primarily focused either on the stakeholder interactions defining urban rules and policies for urban freight or on the technical aspects of the logistic EVs. Methods: the article incorporates energy sourcing, vehicles, logistics operation,
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Background: literature on last mile logistic electrification has primarily focused either on the stakeholder interactions defining urban rules and policies for urban freight or on the technical aspects of the logistic EVs. Methods: the article incorporates energy sourcing, vehicles, logistics operation, and digital cloud environment, aiming at economic and functional viability. Using a combination of engineering and business modeling combined with the unique opportunity of the actual insights from Europe’s largest tender in the automotive aftermarket electrification. Results: the Last Mile Logistics (LML) electrification is possible and profitable without jeopardizing the high-tempo deliveries. Critical asset identification for a viable transition to EVs leads to open new lines of research for future logistic dynamics rendered possible by the digital dimensions of the logistic ecosystem. Conclusions: beyond the unquestionable benefits for the environment, the electrification of the LML constitutes an opportunity to enhance revenue and diversify income.
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(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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