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Systems
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Modeling and Simulation Innovations for Advanced Logistics Systems Management
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Modeling and Simulation Innovations for Advanced Logistics Systems Management

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 30 December 2025 | Viewed by 1106

Special Issue Editors

Dr. Yusheng Zhou

E-Mail Website
Guest Editor
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Hum 999077, Hong Kong
Interests: maritime cluster analysis; investment decision-making and maritime behavioral analytics
Dr. Kum Fai Yuen

E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639789, Singapore
Interests: renewable energy and sustainability; industrial engineering and design; machine-person interoperability; supply chain management; system resilience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern logistics systems have become complex, highly integrated networks requiring sophisticated management strategies to ensure seamless supply chain operations. Modeling and simulation techniques are vital for optimizing logistics systems, enabling better decision-making, efficiency, and resilience in an ever-evolving market. With the rapid advancement of digital twins, predictive analytics, and agent-based modeling technologies, logistics systems managers can now proactively address challenges like demand fluctuations, route optimization, and risk management.

This Special Issue will explore the latest advances in modeling and simulation for logistics systems management, emphasizing applications that enhance adaptability, sustainability, and strategic planning. We welcome contributions that examine innovative methodologies, case studies on real-world implementations, and research tackling the unique logistics modeling challenges. The goal is to provide theoretical insights and practical solutions that can help shape the future of logistics systems management.

Dr. Yusheng Zhou
Dr. Kum Fai Yuen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • logistics systems modeling
  • supply chain simulation
  • decision support for logistics systems
  • predictive analytics in logistics
  • risk management in logistics

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Published Papers (2 papers)

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Research

25 pages, 3203 KiB  
Article
Modeling the Growth Dynamics of Logistics Performance: Industrialization, Environmental Technology, and Economic Transformation in Manufacturing Economies
by Umar Hayyat, Li Qian, Maleeha Saeed and Wajid Nawaz
Systems 2025, 13(5), 375; https://doi.org/10.3390/systems13050375 - 13 May 2025
Viewed by 254
Abstract
Global manufacturing economies have faced logistics performance challenges in recent decades. This study investigates the influence of industrialization, environmental technology, trade openness, foreign direct investment, and economic growth on the logistics performance index in the top 20 manufacturing economies from 2007 to 2023. [...] Read more.
Global manufacturing economies have faced logistics performance challenges in recent decades. This study investigates the influence of industrialization, environmental technology, trade openness, foreign direct investment, and economic growth on the logistics performance index in the top 20 manufacturing economies from 2007 to 2023. This study used an advanced panel approach to obtain robust results, cross-section dependency, a unit root test and a panel cointegration test. The panel quantile regression (PQL) and panel quantile estimates based on income methods were employed to analyze long-run and short-run estimations. The empirical results show that industrialization accelerated across all the quantiles except at the 10th quantile, while environmental technology had a significantly positive impact on logistics performance across all quantiles (10th–90th). Moreover, our baseline model was further supported by the fact that we used Driscoll–Kraay and Prais–Winsten’s estimates and a panel causality test. Our findings reveal that in manufacturing countries, industrialization, environmental technology, and economic growth have a positive impact on logistics performance. This study proposes several recommendations to improve industrialization and environmental technology in manufacturing countries to promote logistics performance. At the same time, more resources should be allocated for industrialization as well as environmental technologies to promote logistics performance. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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22 pages, 525 KiB  
Article
Growth Mechanism in Transformation and Upgrading of Logistics Industry
by Fangzhou Li, Xiaojia Yang, Ruili Zhu, Tao Li and Jingyi Liu
Systems 2025, 13(3), 202; https://doi.org/10.3390/systems13030202 - 15 Mar 2025
Viewed by 473
Abstract
Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes [...] Read more.
Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes provincial panel data from 30 regions covering the period from 2008 to 2022. By employing an intermediary effect model and a moderation effect model, we aim to uncover the underlying mechanisms driving growth. The findings reveal that the logistics industry can be categorized into traditional and emerging logistics elements, with the integration of traditional elements forming the fundamental business model. This foundational model serves as the primary driver of the logistics industry’s growth, exerting both direct and indirect influences on its expansion. Moreover, the level of economic development positively moderates these direct and indirect effects. These insights underscore the importance of enhancing infrastructure development, fostering business innovation, and promoting region-specific differentiated growth strategies. Full article
(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)
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