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Applied Sciences
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Data-Driven Supply Chain Management and Logistics Engineering
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Data-Driven Supply Chain Management and Logistics Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 23 November 2025 | Viewed by 1191

Special Issue Editors

Prof. Dr. Dimitrios Vlachos

E-Mail Website
Guest Editor
Department of Industrial Management , Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: supply chain management; digital supply chains; circular economy; educational technology; logistics
Special Issues, Collections and Topics in MDPI journals
Dr. Dimitrios Bechtsis

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, International Hellenic University, 54124 Thessaloniki, Greece
Interests: digital supply chains; autonomous vehicles; Internet of Things; industrial informatics; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Nikos Tsotsolas

E-Mail Website
Guest Editor
Department of Business Administration, School of Administrative, Economics and Social Sciences, University of West Attica, 12243 Egaleo, Greece
Interests: IoT; smart farming, agricultural logistics; digital supply chains; logistics

Special Issue Information

Dear Colleagues,

Modern global supply chains are experiencing disruptions due to economic, environmental, societal and technological challanges. Therefore, the digital transformation of supply chains can lead to a higher level of operational excellence.

Alongside the Industry 5.0 ecosystem, Digital Supply Chains (DSCs) incorporate state-of-the-art technologies (cloud computing, blockchain technology, IoT networks and 5G communications, Artificial Intelligence (AI) applications) while focusing on the dimensions of sustainability and resilience.

Sophisticated sensor networks collect critical data using communication protocols (for example LoRa and 5G networks) in order to feed cloud computing services. Cloud applications are employed to handle data streams and AI technologies are used for vetting, classifying potential SC stakeholders, analyzing SC streams, and facilitating decision-making. Thus, Generative AI and Large Language Models (LLMs) offer promising solutions for real-time data management.

It is evident that although these technologies are important, their ability to address SC disruptions has not been fully investigated. Moreover, we lack holistic data-driven frameworks that capture all the emerging major challenges that SCs will face (including security, sustainability and resilience) in the coming years.

This Special Issue will facilitate the effective collection of data sources and the implementation of a technology-enabled auditing process (i.e., data collection, management, sharing, analysis, and decision-making process) that can enhance the veracity, visibility and transparency of DSCs.

DSC entities (retailer, distributor, wholesaler, manufacturer, supplier) should focus on automating processes, sharing information and coordinating in order to overcome these challenges. For example, it is critical to (i) monitor the charging levels, the condition and scheduling of electric vehicles; (ii) monitor agricultural supply chains and agro-logistics processes; (iii) safeguard the quality of products using traceability standards in supply chains; and (iv) ballance the utilization and maintenance of SC equipment in order to ensure 24/7 operations.

Prof. Dr. Dimitrios Vlachos
Dr. Dimitrios Bechtsis
Dr. Nikos Tsotsolas
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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • data-driven supply chains
  • digital supply chains
  • smart logistics
  • sustainability
  • resilience
  • artificial intelligence
  • traceability
  • Internet of Things (IoT)
  • asset management in SCs
  • Maintenance 5.0 in SCs

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Published Papers (3 papers)

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Research

17 pages, 2080 KiB  
Article
IoT Services for Monitoring Food Supply Chains
by Loucas Protopappas, Dimitrios Bechtsis and Nikolaos Tsotsolas
Appl. Sci. 2025, 15(13), 7602; https://doi.org/10.3390/app15137602 - 7 Jul 2025
Viewed by 121
Abstract
Ensuring the safety and quality of perishable agrifood products throughout the supply chain is essential. Key parameters, such as temperature and humidity, must be consistently monitored to prevent spoilage, maintain nutritional value, and minimise health risks. Fluctuations in transportation conditions can compromise product [...] Read more.
Ensuring the safety and quality of perishable agrifood products throughout the supply chain is essential. Key parameters, such as temperature and humidity, must be consistently monitored to prevent spoilage, maintain nutritional value, and minimise health risks. Fluctuations in transportation conditions can compromise product integrity, leading to deterioration and an increased risk of foodborne illness. Monitoring agrifood supply chains is essential, from packaging to last-mile delivery. Distribution methods that rely on non-automated monitoring systems, such as manual temperature measurements, are error-prone due to the failure of manual treatments and increase the likelihood of product deterioration. Emerging sensor technologies and the rapid development of Information and Communication Technologies offer new possibilities for real-time tracking, enabling stakeholders to maintain optimal conditions and monitor aesthetic, physicochemical, and nutritional quality. This paper proposes a cost-effective temperature and humidity traceability system that utilises wireless sensor networks (WSN) and Internet of Things (IoΤ) services to monitor perishable products within the agrifood supply chain ecosystem. It also provides an overview of recent innovations in sensor technologies, along with food quality indicators relevant to real-time monitoring of food quality. The proposed research examines the available sensor technologies and methodologies that enable continuous monitoring of agrifood supply chains. Moreover, the paper presents a pilot full-scale project from both functional and technological perspectives. Full article
(This article belongs to the Special Issue Data-Driven Supply Chain Management and Logistics Engineering)
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25 pages, 4207 KiB  
Article
Supplier Risk in Supply Chain Risk Management: An Updated Conceptual Framework
by Ciro Rodrigues dos Santos, Ualison Rébula de Oliveira and Vicente Aprigliano
Appl. Sci. 2025, 15(13), 7128; https://doi.org/10.3390/app15137128 - 25 Jun 2025
Viewed by 335
Abstract
Disruptions in a single supplier’s operations can trigger cascading effects across the entire supply chain, highlighting the critical importance of effective supplier-focused risk management. While supply chain risk management (SCRM) frameworks encompass diverse dimensions—such as supply, products, demand, and information—risks specifically related to [...] Read more.
Disruptions in a single supplier’s operations can trigger cascading effects across the entire supply chain, highlighting the critical importance of effective supplier-focused risk management. While supply chain risk management (SCRM) frameworks encompass diverse dimensions—such as supply, products, demand, and information—risks specifically related to suppliers demand tailored strategies and analytical focus. Despite the growing volume of publications on this topic, the literature still lacks updated conceptual guidance on how to manage these risks, particularly in light of emerging challenges and practices. This study addresses this gap, with the primary objective of developing a contemporary conceptual framework for supplier risk management, reflecting recent academic and practical advances. The research methodology combines bibliometric analysis, the PRISMA systematic review protocol, and visualization tools including CiteSpace and CitNet Explorer. Key findings include the evolution of thematic clusters over time, with “supplier selection” identified as the most dominant theme, and simulation as the prevailing research method. The automotive industry emerges as the most frequently studied empirical context. Moreover, the study expands existing frameworks by introducing two emerging dimensions—environmental, social, and governance (ESG) and information technology (IT)—as key factors in supplier risk management. This framework contributes to theory and practice by offering an updated lens for understanding supplier-related risks and providing decision-makers with structured insights to enhance resilience in complex supply networks. Full article
(This article belongs to the Special Issue Data-Driven Supply Chain Management and Logistics Engineering)
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28 pages, 838 KiB  
Article
Assessment of Sustainability and Risk Indicators in an Urban Logistics Network Analysis Considering a Business Continuity Plan
by Mehmet Erdem, Akın Özdemir, Selahattin Kosunalp and Teodor Iliev
Appl. Sci. 2025, 15(9), 5145; https://doi.org/10.3390/app15095145 - 6 May 2025
Viewed by 504
Abstract
A business-continuity plan is crucial in providing an organization with the ability to maintain operations against possible risks. Therefore, companies should consider holistic risk management to sustain their activities and enhance their capabilities. Also, sustainability is able to eliminate the number of adverse [...] Read more.
A business-continuity plan is crucial in providing an organization with the ability to maintain operations against possible risks. Therefore, companies should consider holistic risk management to sustain their activities and enhance their capabilities. Also, sustainability is able to eliminate the number of adverse environmental effects and increase the financial and social performance of a company. The purpose of this paper is to evaluate the sustainability and risk performance pillars for logistics networks, including a business-continuity plan. For this particular aim, this study considers the ten main criteria and sixty-six sub-criteria to evaluate sustainability and risk performances in logistics operations when dealing with a business-continuity plan under uncertainty. A novel and innovative four-phased integrated procedure involving a fuzzy-based AHP method with novel linguistic scales and operators is proposed. The TOPSIS technique, part of the integrated technique, is also presented to rank the alternative cities for an urban logistics network analysis. Moreover, the criteria of transportation and information infrastructures are analyzed for logistics operations. A case study of the thirty metropolitan cities in Türkiye is conducted to determine the best logistics center for a logistics firm. Several scenario analyses are performed, and a comparison study is also carried out from the literature. This study comprehensively analyzes the problem, including sustainability, risks, renewable energy and social aspects. Based on the results from the fuzzy-based AHP method, economic, safety and hazard risk are the top three main criteria. Moreover, Istanbul, Konya and Ankara are the top three alternatives for logistic networks from the results of the TOPSIS technique. Finally, managerial and policy implications are presented for policy-makers who should pay attention to the main criteria and sub-criteria in this paper for successful logistics operations dealing with the business-continuity plan when achieving Sustainable Development Goals. Full article
(This article belongs to the Special Issue Data-Driven Supply Chain Management and Logistics Engineering)
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