Logistics

22 pages, 826 KB

Open AccessArticle

Integrating Machine Learning with Multi-Criteria Decision-Making Models for Sustainable Supplier Selection in Dynamic Supply Chains

by Osheyor Joachim Gidiagba, Lagouge Tartibu and Modestus Okwu

Logistics 2025, 9(4), 152; https://doi.org/10.3390/logistics9040152 - 24 Oct 2025

Abstract

Background: Supplier evaluation and selection are pivotal processes in supply chain management, profoundly influencing organisational efficiency and sustainability. This study addresses the limitations of traditional multi-criteria decision-making approaches, particularly the Technique for Order Preference by Similarity to an Ideal Solution, which often [...] Read more.

Background: Supplier evaluation and selection are pivotal processes in supply chain management, profoundly influencing organisational efficiency and sustainability. This study addresses the limitations of traditional multi-criteria decision-making approaches, particularly the Technique for Order Preference by Similarity to an Ideal Solution, which often lacks dimensional reduction capability and assumes uniform weight distribution across criteria. Methods: To overcome these challenges, a hybrid model integrating non-negative matrix factorisation, random forest, and the Technique for Order Preference by Similarity to an Ideal Solution is developed for supplier evaluation in the pharmaceutical sector. The method first applies non-negative matrix factorisation to condense twenty-four evaluation criteria into eight core dimensions, enhancing analytical efficiency and reducing complexity. Random forest is then employed to derive data-driven weights for each criterion, ensuring accurate prioritisation. Finally, the Technique for Order Preference by Similarity to an Ideal Solution ranks suppliers and provides actionable insights for decision-makers. Results: Results from real-world pharmaceutical data validate the model’s effectiveness and demonstrate superior performance over conventional evaluation methods. Conclusions: The findings confirm that integrating machine learning techniques with established decision-making frameworks enhances precision, interpretability, and sustainability in supplier selection while requiring adequate data quality and computational resources for implementation. Full article

(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics—2nd Edition)

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21 pages, 1526 KB

Open AccessArticle

A Multi-Product and Multi-Period Inventory Planning Model to Optimize the Supply of Medicines in a Pharmacy in Barranquilla, Colombia

by Katherinne Salas-Navarro, Jousua Pardo-Meza, Juan Torres-Prentt and Juan Rivera-Alvarado

Logistics 2025, 9(4), 151; https://doi.org/10.3390/logistics9040151 - 21 Oct 2025

Abstract

Background: Supply chains in pharmaceutical industry encounter constant challenges in balancing the availability of medicine with cost efficiency, particularly in developing regions with limited storage capacity, as regulatory constraints increase operational complexity. Methods: This research focuses on developing a multi-product, multi-period [...] Read more.

Background: Supply chains in pharmaceutical industry encounter constant challenges in balancing the availability of medicine with cost efficiency, particularly in developing regions with limited storage capacity, as regulatory constraints increase operational complexity. Methods: This research focuses on developing a multi-product, multi-period inventory planning model designed to optimize the supply process for a pharmacy located in Barranquilla, Colombia. The methodology involves conducting field studies within the pharmaceutical sector, which includes regular visits to pharmacies, interaction with employees, and analysis of historical data collected over a 16-month period. Results: The primary goal is to minimize costs while ensuring that products remain available to customers, considering various internal and external factors. Several scenarios will be examined to evaluate different alternatives for enhancing the supply process. Initial findings suggest that the proposed model could reduce inventory planning costs by approximately 15.78% by classifying antibiotics, which in turn leads to better resource utilization and improved order management. Conclusions: The proposed model minimizes the inventory planning costs associated with antibiotic management, ultimately leading to improved resource utilization and more accurate order management. Full article

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

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24 pages, 1993 KB

Open AccessArticle

The Downstream Supply Chain for Electricity Generated from Renewables in Egypt: A Dynamic Analysis

by Islam Hassanin, Tariq Muneer and Matjaz Knez

Logistics 2025, 9(4), 150; https://doi.org/10.3390/logistics9040150 - 21 Oct 2025

Abstract

Background: Generating electricity from renewable sources continues to receive significant attention from both scholars and professional communities. This is mainly because traditional energy use harms public health, threatens biodiversity, and increases pollution, particularly in developing countries. Meanwhile, renewable technologies are considered one of [...] Read more.

Background: Generating electricity from renewable sources continues to receive significant attention from both scholars and professional communities. This is mainly because traditional energy use harms public health, threatens biodiversity, and increases pollution, particularly in developing countries. Meanwhile, renewable technologies are considered one of the most effective solutions to enrich energy security for future usage with clean practices and affordable prices. However, planning such applications may become complex due to the convolution of many technical, economic, environmental, and social dimensions, particularly from a supply chain management viewpoint. Methods: The paper identifies the dimensions affecting the supply chain variables of downstream processes in renewable energy supply systems, especially for generating electricity in Egypt. Also, this paper investigates the relationships between the dimensions of renewable energy supply systems and the downstream supply chain variables that are closely related to the Egyptian energy sector. Results: The different relationships between these indicators and downstream supply chain variables are revealed. Conclusions: This study employed conceptual causality diagramming to organize these relationships harmoniously, which helps to analyze the behavior of the supply chain during the transitions to renewable energy applications and its implications, whether at the managerial or policy and procedural levels. Full article

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24 pages, 1066 KB

Open AccessArticle

Liner Schedule Reliability Problem: An Empirical Analysis of Disruptions and Recovery Measures in Container Shipping

by Jakov Karmelić, Marija Jović Mihanović, Ana Perić Hadžić and David Brčić

Logistics 2025, 9(4), 149; https://doi.org/10.3390/logistics9040149 - 20 Oct 2025

Abstract

Background: Schedule reliability in container liner services is essential for the efficiency of maritime and inland transport, terminal operations, and the overall supply chain. Disruptions to vessel schedules can trigger a series of disruptions at other points, generating additional operational costs for carriers, [...] Read more.

Background: Schedule reliability in container liner services is essential for the efficiency of maritime and inland transport, terminal operations, and the overall supply chain. Disruptions to vessel schedules can trigger a series of disruptions at other points, generating additional operational costs for carriers, terminal operators, inland transport providers, and ultimately, for importers, exporters, and end consumers. Methods: The research paper combines literature reviews and shipping company data. A qualitative analysis contains specific causes of vessel delays and corrective actions used to realign schedules with the pro forma plan. The analysis was expanded to include transport of cargo in containers from origin to the final inland destination. Results: Disruption factors are identified and classified by their place of occurrence: (1) inland transport, (2) anchorage, (3) ports, and (4) navigation between ports. The research produced several new disruptive factors previously not identified and published. It has been confirmed that port congestion acts as the principal cause of delay in liner service. Conclusions: The findings indicate that while the number and complexity of disruptive factors are increasing due to global and regional dynamics, the range of recovery measures remains narrow. A deeper understanding of these causes enables more effective prevention, aiming to minimize supply chain disruptions and costs and increase the reliability of door-to-door container transport. Full article

(This article belongs to the Special Issue Investment, Risk, and Sustainability in Maritime Logistics and Supply Chain)

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25 pages, 2325 KB

Open AccessArticle

The Role of Spare Parts Supply Chains in the Success of New Computer Technology Products

by Maria Sashkova Vodenicharova and Yulia Genova

Logistics 2025, 9(4), 148; https://doi.org/10.3390/logistics9040148 - 20 Oct 2025

Abstract

The purpose of this study is to examine the spare parts supply chain when introducing new computer technology products to the market. Background: Despite the growing importance of after-sales service, the supply chain for spare parts for ICT (information and communications technology) [...] Read more.

The purpose of this study is to examine the spare parts supply chain when introducing new computer technology products to the market. Background: Despite the growing importance of after-sales service, the supply chain for spare parts for ICT (information and communications technology) products often receives insufficient attention. Materials and Methods: The data was obtained from an analysis of operational service logs encompassing 149,937 warranty service requests and associated Service Level Agreements, augmented by feedback from 1572 surveyed computer equipment customers regarding their after-sales service experience. The data refers to a period of one year (1 January 2023 to 1 January 2024) and takes into account all new products launched in the computer category during this period (116 new products), primarily focusing on equipment such as servers, and the product tree for each of these products. Results: The results are related to increasing requirements for after-sales service, in particular, the supply chain for spare parts, which is of great importance for the development and success of companies producing computing equipment. Conclusions: The study contains original results obtained during scientific research conducted by the authors in the field of logistics and supply chain for spare parts. 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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17 pages, 673 KB

Open AccessArticle

Impact of Logistics on Global Economic Growth: Beta and Sigma Convergence During the Period 2007–2022

by Pablo Coto-Millán, David Paz Saavedra and Marta De la Fuente

Logistics 2025, 9(4), 147; https://doi.org/10.3390/logistics9040147 - 20 Oct 2025

Abstract

Background: Logistics plays a key role in economic performance, yet its contribution to global growth and convergence remains underexplored. This study examines how different logistics dimensions have influenced GDP per worker across countries over the period 2007–2022. Methods: Using econometric panel data [...] Read more.

Background: Logistics plays a key role in economic performance, yet its contribution to global growth and convergence remains underexplored. This study examines how different logistics dimensions have influenced GDP per worker across countries over the period 2007–2022. Methods: Using econometric panel data techniques and convergence models (β and σ), data from 86 countries are analysed by incorporating logistics performance indicators—such as infrastructure quality, customs efficiency, and shipment traceability—into an endogenous growth framework. Results: The analysis confirms the existence of both β- and σ-convergence, suggesting that lower-income countries are catching up with higher-income ones. Improvements in logistics competence and tracking systems positively affect economic growth, while inefficiencies in shipping services and delivery timeliness negatively impact convergence. Conclusions: These findings highlight the dual role logistics can play in fostering or hindering growth. Enhancing logistics infrastructure and services through targeted policies is essential to promote sustained economic development and reduce global income disparities. Full article

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24 pages, 2054 KB

Open AccessArticle

Post-Harvest Cold Chain Efficiency in Pome Fruit Operations: Analysing Time and Process Bottlenecks

by Stefan Le Roux and Leila Louise Goedhals-Gerber

Logistics 2025, 9(4), 146; https://doi.org/10.3390/logistics9040146 - 16 Oct 2025

Abstract

Background: South Africa’s pome fruit industry serves over 60 international markets, competing with Chile, New Zealand, and the United States. Inefficiencies in the beginning stages of South Africa’s pome fruit supply chain compromise competitiveness as global quality standards rise and consumers demand [...] Read more.

Background: South Africa’s pome fruit industry serves over 60 international markets, competing with Chile, New Zealand, and the United States. Inefficiencies in the beginning stages of South Africa’s pome fruit supply chain compromise competitiveness as global quality standards rise and consumers demand premium fruit with an extended shelf life. This research identifies operational bottlenecks in the post-harvest handling and processing of pome fruit, focusing on temperature control, lead times, and infrastructure constraints. Methods: A mixed-methods case study approach of Company X, combining on-site observations, semi-structured interviews, and analysis of Company X’s processing data. Findings were triangulated with Hortgro and PPECB sources for validity. Results: Prolonged ambient temperature exposure from packhouse processing bottlenecks resulted in increased fruit pulp temperatures, with congestion, inefficient practices, and poor communication exacerbating problems. Pre-cooling proved most inefficient, with pulp temperatures averaging 1.9 °C (peak season: 3.2–3.5 °C), far exceeding the −0.5 °C industry standard required for international markets and resulting in a downgrade from Class 1 to Class 2 fruit. Conclusions: This research identifies cold chain bottlenecks affecting South Africa’s global competitiveness. Recommended solutions include hydrocooling, infrastructure upgrades, and enhanced stakeholder coordination to strengthen the country’s position in international pome fruit markets. Full article

(This article belongs to the Special Issue Supply Chain Management for Reducing Food Waste)

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20 pages, 2001 KB

Open AccessArticle

Factors Influencing Courier Drivers’ Preferences and Safety Perceptions in Urban Deliveries

by Tijana Ivanišević, Aleksandar Trifunović, Larysa Neduzha and Sreten Simović

Logistics 2025, 9(4), 145; https://doi.org/10.3390/logistics9040145 - 13 Oct 2025

Abstract

Background: Urban freight transport is essential for the functioning of cities. The COVID-19 pandemic accelerated the growth of e-commerce, creating new challenges for courier services. While consumer satisfaction has been extensively studied, little attention has been paid to courier drivers’ own perceptions and [...] Read more.

Background: Urban freight transport is essential for the functioning of cities. The COVID-19 pandemic accelerated the growth of e-commerce, creating new challenges for courier services. While consumer satisfaction has been extensively studied, little attention has been paid to courier drivers’ own perceptions and preferences. This study aims to fill that gap. Methods: A questionnaire survey was conducted among 139 drivers employed in eight courier companies in Serbia. Data were analyzed using parametric statistical methods (Independent Samples T-Test, Paired-Samples T-Test, and One-way ANOVA), with additional post hoc tests to explore group differences. Results: Statistically significant differences were observed across demographic, operational, and safety-related factors (gender, age, residence, occupation, license ownership, delivery area, and type of goods). A strong preference emerged for passenger vehicles as the safest mode of delivery, highlighting a misalignment between current operational practices and drivers’ safety perceptions. Conclusions: The findings emphasize the importance of tailoring delivery strategies to demographic and operational contexts. Practical recommendations include improving transport safety, optimizing delivery zones, and addressing driver satisfaction as a determinant of service quality. The study contributes new insights into last-mile delivery by focusing on the perspectives of courier drivers rather than consumers. Full article

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25 pages, 4531 KB

Open AccessArticle

Interoperable Knowledge Graphs for Localized Supply Chains: Leveraging Graph Databases and RDF Standards

by Vishnu Kumar

Logistics 2025, 9(4), 144; https://doi.org/10.3390/logistics9040144 - 13 Oct 2025

Abstract

Background: Ongoing challenges such as geopolitical conflicts, trade disruptions, economic sanctions, and political instability have underscored the urgent need for large manufacturing enterprises to improve resilience and reduce dependence on global supply chains. Integrating regional and local Small- and Medium-Sized Enterprises (SMEs) [...] Read more.

Background: Ongoing challenges such as geopolitical conflicts, trade disruptions, economic sanctions, and political instability have underscored the urgent need for large manufacturing enterprises to improve resilience and reduce dependence on global supply chains. Integrating regional and local Small- and Medium-Sized Enterprises (SMEs) has been proposed as a strategic approach to enhance supply chain localization, yet barriers such as limited visibility, qualification hurdles, and integration difficulties persist. Methods: This study proposes a comprehensive knowledge graph driven framework for representing and discovering SMEs, implemented as a proof-of-concept in the U.S. BioPharma sector. The framework constructs a curated knowledge graph in Neo4j, converts it to Resource Description Framework (RDF) format, and aligns it with the Schema.org vocabulary to enable semantic interoperability and enhance the discoverability of SMEs. Results: The developed knowledge graph, consisting of 488 nodes and 11,520 edges, enabled accurate multi-hop SME discovery with query response times under 10 milliseconds. RDF serialization produced 16,086 triples, validated across platforms to confirm interoperability and semantic consistency. Conclusions: The proposed framework provides a scalable, adaptable, and generalizable solution for SME discovery and supply chain localization, offering a practical pathway to strengthen resilience in diverse manufacturing industries. Full article

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19 pages, 2081 KB

Open AccessArticle

Digital Twins and Augmented Reality for Humanitarian Logistics in Urban Disasters: Framework Development

by Sepehr Abrishami and Reshma Jayaram

Logistics 2025, 9(4), 143; https://doi.org/10.3390/logistics9040143 - 10 Oct 2025

Abstract

Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for [...] Read more.

Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for humanitarian logistics. Methods: A mixed methods design combined a structured literature synthesis with a practitioner survey across architecture, engineering, planning, BIM, and construction to assess perceived value and adoption conditions. Results: Findings indicate that practitioners prioritised digital twins for enhancing situational awareness (71.4%) and augmented reality for providing real-time information overlays (64.3%). A majority judged that integrating these technologies would yield substantial improvements in disaster response (67.9%), despite implementation challenges. Conclusions: The framework links live state estimation and short-horizon simulation to role-specific, in-scene AR cues, with the aim of reducing decision latency and improving coordination. Adoption depends primarily on human and organisational factors, including user accessibility, preparation needs, and clear governance. These results suggest a viable pathway to operationalise the bridge between analysis and field action and outline priorities for pilot evaluation. Full article

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

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21 pages, 420 KB

Open AccessArticle

Logistics Information Technology and Its Impact on SME Network and Distribution Performance: A Structural Equation Modelling Analysis

by Osayuwamen Omoruyi, Albert Antwi, Alfred Mwanza, Ramos E. Mabugu and Edward A. N. Dakora

Logistics 2025, 9(4), 142; https://doi.org/10.3390/logistics9040142 - 9 Oct 2025

Cited by 1

Abstract

Introduction: This study explores the impact of logistics information technology (LIT) on supply chain relationships and distribution performance in small and medium-sized enterprises (SMEs) using South Africa as a case study. Although digital supply chain solutions are increasingly important, there is limited [...] Read more.

Introduction: This study explores the impact of logistics information technology (LIT) on supply chain relationships and distribution performance in small and medium-sized enterprises (SMEs) using South Africa as a case study. Although digital supply chain solutions are increasingly important, there is limited evidence of SME efficiency in emerging markets using LIT. Methods: This study utilises a survey of 313 SMEs from four South African provinces. Bayesian structural equation modelling (Bayesian SEM) was then used to examine LIT’s effects on distribution performances in terms of timeliness, product availability, and condition. Results: The results show that the adoption of LIT strengthens buyer–seller networks (β = 0.524, CI = [0.434, 0.613]) and improves distribution by enhancing both timeliness performance (β = 0.237, CI = [0.098, 0.372]) and product condition performance (β = 0.175, CI = [0.042, 0.259], β = 0.222, p < 0.001). However, it does not directly enhance product availability performance (β = 0.085, CI = [−0.030, 0.199]), signifying that LIT adoption by itself fails to improve product availability. The results also demonstrate that SME network relationships mediate the connection between LIT adoption and distribution performance metrics. Discussion: This study’s findings contribute to the literature and offer valuable information and guidance to policymakers as they underscore the importance for SMEs to invest in LIT integration and compatibility, as well as inventory optimisation and improved supplier communication to minimise transit time variation. Policymakers should support SMEs’ digital transformation through interventions including funding and training for LIT adoption. This study confirms the essential role of LIT in SME supply chains and illustrates that technology-facilitated relationships enhance distribution performance, which enhances SME competitiveness. Full article

(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)

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20 pages, 3503 KB

Open AccessArticle

The Development, Implementation, and Application of a Probabilistic Risk Assessment Framework to Evaluate Supply Chain Shortages

by Priyanka Pandit, Arjun Earthperson and Mihai A. Diaconeasa

Logistics 2025, 9(4), 141; https://doi.org/10.3390/logistics9040141 - 6 Oct 2025

Abstract

Background: Supply chain disruptions from natural hazards, geopolitical tensions, or global events, such as the COVID-19 pandemic, can trigger widespread shortages, with particularly severe consequences in healthcare through drug supply interruptions. Existing methods to assess shortage risks include scoring, simulation, and machine [...] Read more.

Background: Supply chain disruptions from natural hazards, geopolitical tensions, or global events, such as the COVID-19 pandemic, can trigger widespread shortages, with particularly severe consequences in healthcare through drug supply interruptions. Existing methods to assess shortage risks include scoring, simulation, and machine learning, but these approaches face limitations in interpretability, scalability, or computational cost. This study explores the application of probabilistic risk assessment (PRA), a method widely used in high-reliability industries, to evaluate pharmaceutical supply chain risks. Methods: We developed the supply chain probabilistic risk assessment framework and tool, which integrates facility-level failure probabilities and flow data to construct and quantify fault trees and network graphs. Using FDA inspection data from drug manufacturing facilities, the framework generates shortage risk profiles, performs uncertainty analysis, and computes importance measures to rank facilities by risk significance. Results: SUPRA quantified 7567 supply chain models in under eight seconds, producing facility-level importance measures and shortage risk profiles that highlight critical vulnerabilities. The tool demonstrated scalability, interpretability, and efficiency compared with traditional simulation-based methods. Conclusions: PRA offers a systematic, data-driven approach for shortage risk assessment in supply chains. SUPRA enables decision-makers to anticipate vulnerabilities, prioritize mitigation strategies, and strengthen resilience in critical sectors such as healthcare. Full article

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22 pages, 445 KB

Open AccessArticle

AI Integration in Fundamental Logistics Components: Advanced Theoretical Framework for Knowledge Process Capabilities and Dynamic Capabilities Hybridization

by Zsolt Toth, Alexandru-Silviu Goga and Mircea Boșcoianu

Logistics 2025, 9(4), 140; https://doi.org/10.3390/logistics9040140 - 5 Oct 2025

Abstract

Background: Despite significant technological advances, many logistics organizations in emerging markets struggle to realize the transformative potential of artificial intelligence, with reported success rates below 65% and limited theoretical understanding of the organizational capabilities. This study develops and proposes an integrated theoretical [...] Read more.

Background: Despite significant technological advances, many logistics organizations in emerging markets struggle to realize the transformative potential of artificial intelligence, with reported success rates below 65% and limited theoretical understanding of the organizational capabilities. This study develops and proposes an integrated theoretical framework examining how knowledge process capabilities and dynamic capabilities interact to enable successful artificial intelligence adoption in logistics organizations within emerging market contexts. Methods: Through comprehensive literature review and theoretical synthesis, we propose a hybrid capability framework that integrates knowledge-based view perspectives with dynamic capabilities theory. Results: Theoretical analysis suggests that knowledge combination capabilities may be the strongest predictor of artificial intelligence implementation success, while dynamic reconfiguring capabilities could mediate the relationship between artificial intelligence adoption and performance outcomes. The proposed framework indicates that organizations with hybrid capability architecture may achieve superior implementation success compared to traditional approaches. Environmental uncertainty is theorized to strengthen the knowledge process capabilities—artificial intelligence adoption relationship. Conclusions: The framework suggests that successful artificial intelligence integration requires simultaneous development of knowledge-based and adaptive capabilities rather than sequential capability building. The hybrid capability framework provides theoretical guidance for managers in emerging markets, while highlighting the critical role of environmental context in shaping transformation strategies. Full article

(This article belongs to the Topic Sustainable Supply Chain Practices in A Digital Age)

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24 pages, 2318 KB

Open AccessArticle

From Chaos to Coherent Structure (Pattern): The Mathematical Architecture of Invisible Time—The Critical Minute Theorem in Ground Handling Operations in an Aircraft Turnaround on the Ground of an Airport

by Cornel Constantin Tuduriu, Dan Laurentiu Milici and Mihaela Paval

Logistics 2025, 9(4), 139; https://doi.org/10.3390/logistics9040139 - 1 Oct 2025

Abstract

Background: In the dynamic world of commercial aviation, the efficient management of ground handling (GH) operations in aircraft turnarounds is an increasingly complex challenge, often perceived as operational chaos. Methods: This paper introduces the “Critical Minute Theorem” (CMT), a novel framework [...] Read more.

Background: In the dynamic world of commercial aviation, the efficient management of ground handling (GH) operations in aircraft turnarounds is an increasingly complex challenge, often perceived as operational chaos. Methods: This paper introduces the “Critical Minute Theorem” (CMT), a novel framework that integrates mathematical architecture principles into the optimization of GH processes. CMT identifies singular temporal thresholds,

t_{k}^{*}

at which small local disturbances generate nonlinear, system-wide disruptions. Results: By formulating the turnaround as a set of algebraic dependencies and nonlinear differential relations, the case studies demonstrate that delays are not random but structurally determined. The practical contribution of this study lies in showing that early recognition and intervention at these critical minutes significantly reduces propagated delays. Three case analyses are presented: (i) a fueling delay initially causing 9 min of disruption, reduced to 3.7 min after applying CMT-based reordering; (ii) baggage mismatch scenarios where CMT-guided list restructuring eliminates systemic deadlock; and (iii) PRM assistance delays mitigated by up to 12–15 min through anticipatory task reorganization. Conclusions: These results highlight that CMT enables predictive, non-technological control in turnaround operations, repositioning the human analyst as an architect of time capable of restoring structure where the system tends to collapse. Full article

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17 pages, 1041 KB

Open AccessArticle

The Impact of Technological Innovations on Digital Supply Chain Management: The Mediating Role of Artificial Intelligence: An Empirical Study

by Ali F. Dalain, Mohammad Alnadi, Mahmoud Izzat Allahham and Mohammad Ali Yamin

Logistics 2025, 9(4), 138; https://doi.org/10.3390/logistics9040138 - 27 Sep 2025

Abstract

Background: This study examines the impact of technological innovations on digital supply chain management, with a focus on the mediating role of artificial intelligence. With global supply chains increasingly relying on digital platforms, the integration of advanced technologies has become essential for [...] Read more.

Background: This study examines the impact of technological innovations on digital supply chain management, with a focus on the mediating role of artificial intelligence. With global supply chains increasingly relying on digital platforms, the integration of advanced technologies has become essential for achieving efficiency and competitiveness. Methods: The research employs a mixed-methods approach, combining survey data and expert interviews with professionals from Jordan’s industrial sector. It investigates how emerging digital innovations influence supply chain performance and examines the extent to which artificial intelligence contributes to automation, predictive analytics, and data-driven decision-making. Results: The findings reveal that artificial intelligence plays a pivotal role in enhancing the effectiveness of technological innovations within digital supply chain systems. Specifically, AI improves adaptability to market fluctuations, increases operational efficiency, and strengthens strategic flexibility. These outcomes suggest that organizations adopting AI-enabled innovations are better equipped to respond to uncertainty and achieve superior supply chain performance. Conclusions: The study concludes that technological innovations significantly advance digital supply chain management when supported by artificial intelligence as a mediating factor. The integration of AI not only magnifies the value of digital innovations but also enables sustainable performance improvements and reinforces competitiveness in dynamic industrial environments. Full article

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20 pages, 745 KB

Open AccessArticle

Fuzzy–Monte Carlo-Based Assessment for Enhanced Urban Transport Planning in Amman, Jordan

by Reema Al-Dalain and Dilay Celebi

Logistics 2025, 9(4), 137; https://doi.org/10.3390/logistics9040137 - 26 Sep 2025

Abstract

Background: Cities worldwide face continuous challenges in sustainable development, particularly in transportation systems where decisions have long-lasting impacts on urban infrastructure and quality of life. The evaluation of sustainable transportation alternatives requires careful consideration of multiple indicators, making it a complex multi-criteria [...] Read more.

Background: Cities worldwide face continuous challenges in sustainable development, particularly in transportation systems where decisions have long-lasting impacts on urban infrastructure and quality of life. The evaluation of sustainable transportation alternatives requires careful consideration of multiple indicators, making it a complex multi-criteria decision-making process. Existing multi-criteria decision-making (MCDM) frameworks often overlook the dual uncertainties introduced by both fuzzy expert judgments and probabilistic performance measures, hindering robust evaluation of transportation alternatives in developing countries. Methods: In response, this study introduces a novel hybrid methodology combining fuzzy set theory and Monte Carlo simulation to evaluate transportation alternatives through 14 comprehensive sustainability indicators. Addressing the critical need for sustainable public transportation assessment in rapidly urbanizing developing countries, where existing assessment frameworks frequently prove inadequate, we present a case study from Amman, Jordan. Results: The results reveal that a Bus Rapid Transit (BRT) system outperforms both conventional automobiles and small buses in 87.06% of simulation scenarios, underscoring its robust sustainability profile. The sensitivity analysis highlights that a BRT system is highly robust, with minimal sensitivity to changes in most criteria and strong responsiveness to critical factors such as land usage. Conclusions: This research provides decision-makers with a comprehensive, evidence-based tool for evaluating public transport investment under uncertainty. The methodology’s ability to account for multiple stakeholder perspectives while handling uncertainty makes it particularly valuable for urban planners and policymakers facing complex transportation infrastructure decisions in rapidly evolving urban environments. Full article

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18 pages, 1003 KB

Open AccessArticle

Weathering the Storm: Dynamic Capabilities and Supply Chain Agility in Supply Chain Resilience

by Marie Legg, Reginald A. Silver and Sungjune Park

Logistics 2025, 9(4), 136; https://doi.org/10.3390/logistics9040136 - 25 Sep 2025

Abstract

Background: Despite growing interest in supply chain resilience (SCRes), theoretical overlap between dynamic capabilities (DC) and supply chain agility (SCA) has complicated empirical analysis of their distinct roles. Additionally, the contextual role of information asymmetry in shaping resilience remains underexplored. This study [...] Read more.

Background: Despite growing interest in supply chain resilience (SCRes), theoretical overlap between dynamic capabilities (DC) and supply chain agility (SCA) has complicated empirical analysis of their distinct roles. Additionally, the contextual role of information asymmetry in shaping resilience remains underexplored. This study addresses both issues by modeling DC hierarchically and examining IA as a moderator. Methods: Data were collected through a cross-sectional survey of 157 U.S.-based supply chain professionals. Partial least squares structural equation modeling (PLS-SEM) was used to examine the relationships among DC, SCA, IA, and SCRes. Results: SCA was a strong, direct predictor of SCRes. In contrast, DC showed no direct effect in the full model; however, in a hierarchical component model (HCM), DC, a higher-order construct, emerged as significant predictor of SCRes. IA exerted a dual negative influence: it directly weakened SCRes and negatively moderated the relationship between DC and SCRes. Conclusions: This study makes two novel contributions. First, it resolves ambiguity between DC and SCA by empirically modeling DC as a higher-order construct that encompasses but remains distinct from SCA. Second, it introduces IA as a multidimensional barrier to resilience, demonstrating its direct and interactive effects. These findings provide new insight into capability design and contextual adaptation for SCRes in uncertain, information-constrained environments. 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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37 pages, 503 KB

Open AccessArticle

A Holistic Human-Based Approach to Last-Mile Delivery: Stakeholder-Based Evaluation of Logistics Strategies

by Aleksa Maravić, Vukašin Pajić and Milan Andrejić

Logistics 2025, 9(4), 135; https://doi.org/10.3390/logistics9040135 - 23 Sep 2025

Abstract

Background: The growing complexity of last-mile logistics (LML) in urban environments has created an urgent need for sustainable, efficient, and stakeholder-inclusive solutions. This study addresses these challenges by exploring a holistic, human-centered approach to evaluating LML strategies, recognizing the diverse expectations of [...] Read more.

Background: The growing complexity of last-mile logistics (LML) in urban environments has created an urgent need for sustainable, efficient, and stakeholder-inclusive solutions. This study addresses these challenges by exploring a holistic, human-centered approach to evaluating LML strategies, recognizing the diverse expectations of logistics service providers, delivery personnel, customers, and local authorities. Methods: To capture both subjective and objective factors influencing decision-making, the study employs a Multi-Criteria Decision-Making (MCDM) framework that integrates the Fuzzy Analytic Hierarchy Process (FAHP) and Evaluation based on Distance from Average Solution (EDAS). Evaluation criteria encompass operational efficiency, environmental impact, social acceptance, and technological feasibility. Results: Six LML solutions were assessed and ranked using this approach. The results indicate that the cargo bike (A₂) emerged as the most favorable alternative, while electric freight vehicles (A₅) ranked lowest. These findings reflect significant trade-offs between stakeholder priorities and the varying performance of different delivery strategies. Conclusions: The proposed methodology offers practical guidance for designing balanced and socially responsible urban logistics systems. By emphasizing inclusivity in decision-making, this approach supports the development of LML solutions that are not only operationally effective but also environmentally sustainable and broadly accepted by stakeholders. Full article

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27 pages, 788 KB

Open AccessArticle

Extending the DBQ Framework: A Second-Order CFA of Risky Driving Behaviors Among Truck Drivers in Thailand

by Supanida Nanthawong, Panuwat Wisutwattanasak, Chinnakrit Banyong, Thanapong Champahom, Vatanavongs Ratanavaraha and Sajjakaj Jomnonkwao

Logistics 2025, 9(3), 134; https://doi.org/10.3390/logistics9030134 - 22 Sep 2025

Abstract

Background: Truck drivers are a vital workforce sustaining Thailand’s freight transport, particularly in Northeastern Thailand (Isan), a major logistics hub connecting with Laos, Vietnam, and Cambodia via Highway No. 2 and the AEC network. However, these drivers face disproportionately high risks of [...] Read more.

Background: Truck drivers are a vital workforce sustaining Thailand’s freight transport, particularly in Northeastern Thailand (Isan), a major logistics hub connecting with Laos, Vietnam, and Cambodia via Highway No. 2 and the AEC network. However, these drivers face disproportionately high risks of severe road accidents due to occupational factors such as fatigue, time pressure, and long-distance driving. Methods: This study developed and validated a second-order confirmatory factor analysis (CFA) model to examine the multidimensional structure of risky driving behavior among Thai truck drivers. Grounded in the Driver Behavior Questionnaire (DBQ), the framework was extended to include seven dimensions: traffic violations, errors, lapses, aggressive behavior, substance use, technology-related distractions, and pedestrian-related risks. Results: Data were collected from 400 truck drivers in Isan using a structured questionnaire. CFA results confirmed the model’s structural validity, with satisfactory fit indices (X²/df = 2.122, CFI = 0.913, TLI = 0.897, RMSEA = 0.053, SRMR = 0.079). Conclusions: The findings reveal that risky driving behavior in this group extends beyond traditional DBQ categories, incorporating emerging risks specific to the commercial transport environment. This framework can be effectively utilized for risk assessment, behavioral screening, and the development of targeted safety interventions for this high-risk occupational group. Full article

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

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