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Application of Data-Driven in Sustainable Logistics and Supply Chain

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 12276

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Special Issue Editor

Dr. Wen Jiang

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Guest Editor

College of Architecture and Urban-Rural Planning, Sichuan Agricultural University, Chengdu 611830, China
Interests: supply chain management; sustainable construction management; data-driven operations management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the present global landscape, where environmental pollution, short-term resource availability, and slow economic development represent increasingly severe conflicts, the field of logistics and supply chain management is facing unprecedented challenges. As such, the execution of a sustainable development model for logistics and supply chains has emerged as a shared international goal.

Data-driven technologies play a crucial role in advancing sustainable logistics and supply chains. By collecting and analyzing big data, companies can enhance their ability to respond to market fluctuations, optimize supply chain collaboration, streamline operational efficiency, and achieve cost reduction. For example, by using big data and artificial intelligence technology, companies can analyze logistics paths and find optimal solutions for transportation routes; by integrating data from all parts of the supply chain, an intelligent decision-making system can be established; by analyzing historical data, potential supply chain risks can be predicted and assessed, and contingency plans can be generated. Despite the huge scope of data-driven technologies available, there have been few attempts to apply them to sustainable logistics and supply chains.

Therefore, this Special Issue aims to explore in depth the application of data-driven technologies in sustainable logistics and supply chains. Technologies, such as the Internet of Things, blockchains, and big data technologies, are redefining how logistics and supply chain businesses operate. As the field continues to evolve, it is essential that researchers and practitioners stay abreast of the latest developments and contribute to the growing knowledge of data-driven applications in logistics and supply chains.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Sustainable logistics;
Data-driven supply chain management;
Design and application of artificial intelligence, big data, and Internet of Things in supply chain optimization;
Data-driven forecasting and analysis;
A data-driven approach to sustainable supply chains;
Big data analytics in logistics and supply chain;
Data-driven design and optimization;
Data-driven impact on all aspects of social value in logistics and supply chain management.

I look forward to receiving your submissions.

Dr. Wen Jiang
Guest Editor

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. Sustainability 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

sustainable logistic
sustainable inventory management
logistics route optimization
data-driven technology
operation management and optimization
sustainable supply chain
supply chain coordination
sustainable supply chain network design
supply chain visualization
carbon emission reduction strategy

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Published Papers (7 papers)

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Research

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18 pages, 1762 KB

Open AccessArticle

Energy Consumption of Transfer Points in Passive and Plus-Energy Warehouses—A Systemic Approach to Internal Transport

by Pawel Zajac

Sustainability 2025, 17(21), 9419; https://doi.org/10.3390/su17219419 - 23 Oct 2025

Viewed by 218

Abstract

Sustainable logistics increasingly requires energy-efficient solutions for warehousing systems. However, current energy consumption models often neglect the role of pallet transfer points that act as interfaces between various internal transport subsystems, despite their measurable impact on overall energy demand. This study addresses the energy implications of such transfer points in passive and plus-energy warehouse environments. Using the results of an operational analysis and empirical observations, we propose a dual classification of transfer nodes based on their technological characteristics (manual, semi-automated, automated, integrated) and energy profile (low, medium, high consumption). A novel Energy Performance Index (EPI) is introduced to quantify the energy efficiency of transfer nodes by combining both classification dimensions with weighted coefficients. Practical data indicate that overlooking these interfaces can lead to underestimating total energy use by up to 30%. Furthermore, the results emphasise the importance of technical integration and synchronisation between subsystems to reduce idle consumption and transfer losses. The approach presented in this paper provides a system-level modelling framework for energy assessment and supports the design of more sustainable and energy-conscious warehouse operations. The findings are relevant for logistics planners and system designers aiming to meet passive or plus-energy standards in intralogistics. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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26 pages, 902 KB

Open AccessArticle

Sustainable Financial Performance Analysis of Logistics Companies Listed on Borsa Istanbul: An Integrated Multi-Criteria Decision-Making Approach

by Hatice Handan Oztemiz, Kemal Vatansever and Tuba Bayraktar

Sustainability 2025, 17(20), 9243; https://doi.org/10.3390/su17209243 - 17 Oct 2025

Viewed by 400

Abstract

With the impact of globalization, logistics has evolved beyond mere goods transportation to become an indispensable component of international trade and a strategic force that provides a competitive advantage. Through logistics companies with strong financial performance, the sector plays a decisive role in enhancing industry efficiency and supporting global economic sustainability. In this context, measuring and improving the financial performance of logistics companies has become critically important. This study introduces an innovative approach to evaluating the financial performance of logistics companies listed on the Borsa Istanbul (BIST) Transportation Index by integrating four distinct Multi-Criteria Decision-Making (MCDM) methods. The SIWEC, MEREC, and LODECI methods, recognized for objective weighting, were used to assign weights to financial criteria for logistics companies. The obtained criteria weights were combined for each research period using the Heron mean, and then the performance rankings of logistics companies were determined using the CoCoSo method. The consistency of the results obtained was also evaluated through sensitivity analysis, and the reliability of the model was tested. It has been determined that the methods used are moderately to highly sensitive to changes in parameters. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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30 pages, 916 KB

Open AccessArticle

Two-Way Carbon Options Game Model of Construction Supply Chain with Cap-And-Trade

by Wen Jiang, Zhaoyi Tong, Yifan Yuan, Qingqing Yang, Jiangyan Wu and Ruixiang Li

Sustainability 2025, 17(17), 8089; https://doi.org/10.3390/su17178089 - 8 Sep 2025

Viewed by 1573

Abstract

As one of the main sources of global greenhouse gas emissions, the low-carbon transformation and emission reduction in the construction industry are inevitable requirements for addressing climate change. Under cap-and-trade regulations, Carbon emission rights have become a key production factor. However, the price of carbon emission rights is highly random. Taking the EU carbon market in 2024 as an example, the carbon price fluctuated by more than 35%, soaring from 65 euros per ton to 80 euros per ton and then falling back. Such sharp fluctuations not only increase the cost uncertainty of enterprises but also complicate the investment decisions for emission reduction. Therefore, enterprises can enhance the flexibility of carbon emission rights trading decisions through option strategies, helping them hedge against the risks of carbon price fluctuations, and at the same time improve market liquidity and risk management capabilities. Against this background, based on the carbon cap-and-trade policy, this paper introduces the two-way option strategy into the construction supply chain game model composed of general contractors and subcontractors, and studies to obtain the optimal carbon reduction volume, carbon option purchase volume, maximum expected profit of general contractors, subcontractors and profit distribution ratio. This study shows that two-way options play a crucial role in optimizing supply decision-making and emission reduction strategies. Under the decentralized model, emission reduction responsibilities are often shifted to subcontractors by the general contractor, resulting in a decline in overall mitigation effectiveness. Furthermore, appropriately lowering the carbon emission benchmark can strengthen enterprises’ incentives for emission reduction and significantly enhance the profitability of the supply chain. The study further suggests that general contractors should enhance their competitiveness by developing environmentally friendly technologies and improving their ability to reduce emissions on their own. Meanwhile, subcontractors need to actively participate in the collaborative efforts through revenue-sharing contracts. This study reveals the strategic value of two-way carbon options in construction supply chain carbon trading and provides theoretical support for the formulation of carbon market policies, contributing to the low-carbon transition of the construction supply chain. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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17 pages, 2351 KB

Open AccessArticle

Future Rail Signaling: Cyber and Energy Resilience Through AI Interoperability

by Pavlo Holoborodko, Darius Bazaras and Nijolė Batarlienė

Sustainability 2025, 17(10), 4643; https://doi.org/10.3390/su17104643 - 19 May 2025

Viewed by 1642

Abstract

In today’s world, everything changes at lightning speed, making what is relevant today potentially obsolete tomorrow. This author’s scientific article addresses the issues of energy resilience and cybersecurity in railway signaling. A new proposal based on artificial intelligence is made to improve the fault tolerance of rail transport signaling infrastructure by ensuring increased energy efficiency and detecting cyber-attacks in real time. A linearly coupled neural network model was designed and implemented in a railway signaling simulation to simultaneously track the energy characteristics of signaling and detect abnormal behavior. The authors’ model was validated based on MATLAB(24.2.0.2863752 (R2024b) Update 5) simulations of a real double-track railway line under normal operating conditions and in a ransomware cyber-attack scenario. The AI simulation model correctly predicted the resilience of the signaling system, achieving an average absolute error of 0.0331 in predicting the fundamental performance indicator, and successfully identified an upcoming cyber-attack 20 min before the incident. This study demonstrates the promising architecture of the AI-based signaling system, which provides a significant increase in resilience to emergency situations in relation to power supply and cyber-attacks. By optimizing the signaling infrastructure with AI, it is possible to ensure safe and continuous movement of trains, including emergency situations, representing a promising approach to improving the resilience and safety of railways. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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55 pages, 482 KB

Open AccessArticle

A Practical and Sustainable Approach to Industrial Engineering Discrete-Event Simulation with Free Mathematical and Programming Software

by Jérémie Schutz, Christophe Sauvey, Eduard Laurențiu Nițu and Ana Cornelia Gavriluță

Sustainability 2025, 17(9), 3973; https://doi.org/10.3390/su17093973 - 28 Apr 2025

Cited by 1 | Viewed by 3080

Abstract

Discrete-event simulation (DES) is a powerful tool for modeling and analyzing complex systems where state changes occur at discrete points in time. This paper presents a practical and sustainable approach to implementing DES using free mathematical and programming software, making it accessible to a wider audience including educators, students, and practitioners. This study explores the use of open-source tools, such as Python and Octave, highlighting their capabilities in building and optimizing DES models without the need for expensive and unaffordable software. In the context of Industry 4.0 and smart manufacturing, the ability to simulate and optimize discrete processes with open tools contributes to the development of digital twins, the integration of cyberphysical systems, and data-driven decision-making. Through detailed case studies in industrial fields, including manufacturing, maintenance, and logistics, this study demonstrates the effectiveness of these tools in simulating real processes and promoting their sustainability. Case studies are also re-examined to emphasize their relevance to smart manufacturing, particularly in terms of predictive maintenance, process optimization, and operational flexibility. Several challenges were encountered during the research process, such as adapting DES methodologies to the limitations of general-purpose mathematical software, ensuring accurate time management and event scheduling in environments not specifically designed for simulation, and balancing model complexity with accessibility for nonexpert users. The integration of free software not only reduces costs but also promotes collaborative learning and innovation. Additionally, the paper discusses the best practices for model validation and experimentation, providing a comprehensive guide for those new to DES. By linking open-source DES tools to the objectives of Industry 4.0, we aim to reinforce the applicability of our approach to modern, connected industrial environments. By leveraging free mathematical and programming software, this approach aims to democratize the use of DES, fostering a deeper understanding and broader application of simulation techniques across diverse fields and various regions of the world. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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29 pages, 12354 KB

Open AccessArticle

Data-Driven Order Consolidation with Vehicle Routing Optimization

by Changhee Yang, Yongjin Lee and Chulung Lee

Sustainability 2025, 17(3), 848; https://doi.org/10.3390/su17030848 - 22 Jan 2025

Cited by 3 | Viewed by 2872

Abstract

This study compares time-based and quantity-based consolidation strategies within the Vehicle Routing Problem (VRP) framework to optimize supplier profitability and logistical efficiency. The time-based model consolidates deliveries at fixed intervals, offering predictable routes, reduced customer wait times, and cost efficiency in stable markets. Conversely, the quantity-based model dynamically adjusts delivery volumes to meet fluctuating demand, providing flexibility in dynamic environments but potentially increasing long-term costs due to logistical complexity. Using a mixed-integer linear programming (MILP) model, sensitivity analyses, and scenario-based experiments, the study demonstrates that the time-based model excels in stable conditions, while the quantity-based model performs better in highly variable demand scenarios. These findings provide actionable insights for selecting consolidation strategies that optimize delivery operations and enhance supply chain performance based on market dynamics. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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Review

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24 pages, 1438 KB

Open AccessReview

Supply Chains of the Banks in Poland Based on EU Sustainability Reporting Standards: A Review of the Data-Driven Potential

by Marcin Wołek and Joanna Próchniak

Sustainability 2025, 17(18), 8442; https://doi.org/10.3390/su17188442 - 19 Sep 2025

Viewed by 621

Abstract

The disclosure of value chains—particularly supply chains—in the European Union (EU) banking sector represents an emerging area of sustainability research. Triggered by the 2024 enforcement of the Corporate Sustainability Reporting Directive (CSRD) and the European Sustainability Reporting Standards (ESRSs), EU-listed banks are now required to report on value chain impacts as part of their sustainability disclosures. This regulatory shift has positioned value chain transparency as a key element in double materiality assessments. This study explores the data-driven potential within commercial banks’ supply chains, focusing on the Polish financial sector as a case study. The methodology combines a literature review with a case study analysis supported by a comparative analysis using the Sustainability Accounting Standards Board (SASB) Materiality Navigator tool. The findings indicate that banks currently do not consider upstream supply chain issues—such as data security, privacy, or systemic risk—as material, despite their relevance. However, by extending materiality considerations to upstream processes, the analysis uncovers significant data-driven opportunities related to supply chain transparency. This research contributes early empirical insights into how banks might develop value chain disclosures to understand accountability and data-driven potential better, offering implications for both academic inquiry and practice. Full article

(This article belongs to the Special Issue Application of Data-Driven in Sustainable Logistics and Supply Chain)

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