Tackling Disruptions in Supply Chain Networks Through Resilient, Sustainable and Innovative Methods and Practices

A special issue of Logistics (ISSN 2305-6290).

Deadline for manuscript submissions: 28 February 2026 | Viewed by 3037

Special Issue Editors


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Guest Editor
Department of Financial & Management Engineering, School of Engineering, University of the Aegean, 82100 Chios, Greece
Interests: freight transportation; city logistics; last-mile delivery; warehouse optimization; logistics 4.0; digital twin; logistics information systems; sustainable logistics
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Guest Editor
Department of Applied Informatics, School of Information Sciences, Information Systems and e-Business Laboratory (ISeB), University of Macedonia, 54636 Thessaloniki, Greece
Interests: transportation; terminal operations; city logistics; sustainable logistics; operational research applications in transport and logistics; emerging technologies and ICT applications in logistics and supply chain management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid growth of e-commerce, accelerated by the COVID-19 pandemic, has placed substantial pressure on supply chain operations and transportation infrastructure, often leading to failures or disruptions. The supply chain is not only disrupted by seasonal fluctuations such as demand spikes during events (e.g., Black Friday, Cyber Monday) but also by unpredictable incidents like climate change, cyberattacks, or global crises, which critically undermine supply chain resilience. In response to these challenges, companies tend to adopt emerging technologies as well as innovative practices and business models to enhance their efficiency and tackle these challenges. Interestingly, recent developments in artificial intelligence (AI), machine learning (ML), Internet of Things (IoT) applications, and blockchain technology have enabled innovative solutions that can potentially improve the efficiency of different processes within a supply chain (e.g., inventory management, demand forecasting, transportation planning, warehouse optimization, data security, dynamic vehicle/robot/drone routing). The industry leaders often uptake innovative solutions and apply practices to tackle or mitigate disruptions in supply chains (e.g., predictive analytics, optimizing inventory location, anticipatory shipping). Apart from the implementation of innovative solutions, the adoption of new, sustainable, and smart business models is crucial for companies enhancing their resilience. For example, collaborative business models support a paradigm of resources and operations sharing between multiple stakeholders which promotes resilience and flexibility towards disruptions and changing market conditions and networks.

This Special Issue aims to investigate the integration of resilient, sustainable, and innovative practices within supply chains to enhance operational efficiency and infrastructure robustness. We invite contributions from scholars and practitioners interested to explore beyond the traditional supply chain management approaches to tackle these challenges through technological advancements and collaborative strategies by addressing one or more of the following topics:

  • Global supply chain crisis management;
  • blockchain for secure supply chains;
  • disruption management in supply chains;
  • weather-related disruptions in supply chain operations and infrastructure;
  • resilient global supply strategies;
  • supply chain disaster recovery;
  • IoT supply chain monitoring;
  • multi-stakeholder supply partnerships;
  • designing and assessing supply chain resilience;
  • cloud-based supply collaboration;
  • AI in demand forecasting;
  • smart inventory control;
  • warehouse robotics and automation;
  • smart crew scheduling and rostering;
  • resource planning for disruption management;
  • predictive logistics maintenance;
  • green logistics innovations;
  • AI-driven logistics optimization;
  • collaborative logistics models;
  • combined freight transport planning;
  • dynamic routing optimization;
  • omni-channel supply resilience;
  • predictive shipping analytics;
  • physical internet and sustainability;
  • energy-efficient freight transport solutions;
  • circular economy in supply chains;
  • innovative approaches towards supply chain resilience and sustainability;
  • Logistics 4.0 for agile supply chains.

We look forward to receiving your contributions.

Dr. Vasilis Zeimpekis
Dr. Michael A. Madas
Guest Editors

Manuscript Submission Information

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Keywords

  • supply chain
  • disruption management
  • resilience
  • sustainability
  • disaster recovery
  • crisis management

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Published Papers (2 papers)

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32 pages, 1168 KiB  
Article
Effect of Social Sustainability on Supply Chain Resilience Before, During, and After the COVID-19 Pandemic in Mexico: A Partial Least Squares Structural Equation Modeling and Evolutionary Fuzzy Knowledge Transfer Approach
by Miguel Reyna-Castillo, Alejandro Santiago, Ana Xóchitl Barrios-del-Ángel, Francisco Manuel García-Reyes, Fausto Balderas and José Ignacio Anchondo-Pérez
Logistics 2025, 9(2), 50; https://doi.org/10.3390/logistics9020050 - 2 Apr 2025
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Abstract
Recent disruptions have led to a growing interest in studying the social dimension of sustainability and its relationship to resilience within supply chains. Social sustainability is characterized as complex, often offering anomalous data and confounding variables that are impossible to categorically define as [...] Read more.
Recent disruptions have led to a growing interest in studying the social dimension of sustainability and its relationship to resilience within supply chains. Social sustainability is characterized as complex, often offering anomalous data and confounding variables that are impossible to categorically define as true or false axioms. This work starts from an epistemological premise, in which non-parametric statistical methodologies and mathematical analytics are complementary perspectives to comprehensively understand the same social phenomenon. Second-generation predictive statistics, such as the PLS-SEM algorithm, have demonstrated robustness in treating multivariate social information, making it feasible to prepare data for knowledge transfer with mathematical techniques specialized for fuzzy data. This research aimed to analyze evolutionary fuzzy knowledge transfer pre-, during-, and post-pandemic COVID-19, and its effect on the relationship between social sustainability and supply chain resilience in representative cases from Mexico. Based on empirical data collected from supply chain managers in 2019 (n = 153), 2021 (n = 159), and 2023 (n = 119), the methodological technique involved three phases: (1) PLS-SEM modeling, (2) fuzzy-evolutionary predictive evaluation based on knowledge transfer between latent data, and (3) comparative analysis of the predictive effects of social attributes (labor rights, health and safety, inclusion, and social responsibility) on supply chain resilience. The results found a moderate significant variance in the pre-in-post-COVID-19 effect of social dimensions on supply chain resilience. Social and management implications are presented. Full article
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28 pages, 6444 KiB  
Systematic Review
Weather-Related Disruptions in Transportation and Logistics: A Systematic Literature Review and a Policy Implementation Roadmap
by Dimos Touloumidis, Michael Madas, Vasileios Zeimpekis and Georgia Ayfantopoulou
Logistics 2025, 9(1), 32; https://doi.org/10.3390/logistics9010032 - 20 Feb 2025
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Abstract
Background: The increasing frequency and severity of extreme weather events (EWEs) as a consequence of climate change pose critical challenges on the transport and logistics sector, hence requiring systematic evaluation and strategic adaptation. Methods: This study conducts a comprehensive systematic literature [...] Read more.
Background: The increasing frequency and severity of extreme weather events (EWEs) as a consequence of climate change pose critical challenges on the transport and logistics sector, hence requiring systematic evaluation and strategic adaptation. Methods: This study conducts a comprehensive systematic literature review (SLR) of 147 peer-reviewed articles and reports through a PRISMA framework to comprehensively identify key weather-induced challenges, quantify their operational, infrastructural and economic impacts, and explore alternative mitigation strategies. Results: With a greater focus on rainfall, flooding and snowfall, this study highlights their notable impacts causing reductions in transport efficiency, increased maintenance costs and substantial financial losses. Also, it emphasizes the role of advanced technologies, resilient infrastructure, and adaptive policy frameworks as critical enablers for enhancing sector resilience while simultaneously formulating a robust roadmap for cities and companies with actions ranging from direct operational adjustments to long-term transformational changes in policy and infrastructure. Conclusions: This work underscores the importance of using a data-driven approach to safeguard transport and logistics systems against evolving climate risks contributing to the broader goal of sustainable urban resilience and operational continuity. Full article
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