Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.7
3.3
Journals
Sustainability
Special Issues
Sustainable Logistics and Supply Chain Operations in the Digital Era
sustainability-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainable Logistics and Supply Chain Operations in the Digital Era

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

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2201

Special Issue Editors

Dr. Susana Duarte

E-Mail Website
Guest Editor
1. UNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
2. Laboratório Associado de Sistemas Inteligentes, LASI, 4800-058 Guimarães, Portugal
Interests: lean manufacturing; green management; sustainable supply chain management; business performance; Industry 4.0; intelligent production systems
Special Issues, Collections and Topics in MDPI journals
Dr. Inês Ferreira

E-Mail Website
Guest Editor
1. UNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
2. Laboratório Associado de Sistemas Inteligentes, LASI, 4800-058 Guimarães, Portugal
Interests: circular economy; industrial symbiosis; sustainability; additive symbiotic networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Logistics and supply chain management are critical processes for the global economy, ensuring the efficient flow of goods and services. However, these operations also generate significant environmental and social impacts, which have brought sustainability to the forefront of both academic research and industrial practice. In the era of Industry 4.0, the integration of digital technologies presents new opportunities to rethink logistics operations through the lens of the triple bottom line, namely economic, environmental, and social sustainability. This Special Issue intends to explore how logistics and supply chains can evolve to become more sustainable by leveraging intelligent systems, digital platforms, and collaborative ecosystems.

The Special Issue welcomes analytical, empirical, conceptual, quantitative and qualitative research studies, and focuses on, but is not limited to, the following themes:

  • LARG Supply chain 4.0.
  • Green and reverse logistics.
  • Sustainable urban logistics, smart cities, and last-mile delivery optimization.
  • Impacts and assessments of circular economy strategies and supply chain collaboration.
  • Role of digital technologies, solutions or strategies to promote sustainable maritime logistics operations.
  • Innovative methodologies or approaches to assess the environmental impact of logistics operations.
  • Case studies.

By fostering a multidisciplinary dialogue, this Special Issue seeks to advance theoretical insights and practical solutions for reducing the environmental and social footprint of logistics and supply chain operations in the digital era.

Dr. Susana Duarte
Dr. Inês Ferreira
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 250 words) can be sent to the Editorial Office for assessment.

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 supply chains
  • sustainable and green logistics
  • Industry 4.0
  • digital systems and platforms
  • environmental assessment
  • smart cities
  • maritime logistics

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 662 KB  
Article
Slowing for Sustainability: A Hybrid Optimization and Sensitivity Analysis Framework for Taiwan’s Cross-Border E-Commerce
by Yu-Feng Lin and Kang-Lin Chiang
Sustainability 2026, 18(1), 531; https://doi.org/10.3390/su18010531 - 5 Jan 2026
Viewed by 848
Abstract
Cross-border e-commerce logistics has long prioritized delivery speed; however, the trade-offs between cost-effectiveness, carbon emissions, risk, and financial performance have received relatively little attention. To address this deficiency, this study constructs a fuzzy nonlinear multi-objective optimization framework that integrates the particle swarm optimization [...] Read more.
Cross-border e-commerce logistics has long prioritized delivery speed; however, the trade-offs between cost-effectiveness, carbon emissions, risk, and financial performance have received relatively little attention. To address this deficiency, this study constructs a fuzzy nonlinear multi-objective optimization framework that integrates the particle swarm optimization (PSO) algorithm and the Sobol sensitivity analysis to capture the uncertainty and nonlinear dynamics of logistics systems. Using operational data from a Taiwanese cross-border e-commerce exporter from 2023 to 2024, empirical results show that extending the standard 25-day delivery time to an acceptable maximum of 32–37 days (i.e., an extension of 7–12 days) can reduce logistics costs per order by 22–38%, carbon emissions by 18–31%, and increase financial returns. Sobol sensitivity analysis further demonstrates that extended delivery time (T) is a significant controllable factor (S1=0.62, ST1=0.75). This study empirically verifies the profitability and sustainability of moderately T, challenges the current “speed-first” model, and provides a transparent, replicable, and scalable decision-making framework for promoting low-carbon, economically viable cross-border e-commerce supply chains. Full article
(This article belongs to the Special Issue Sustainable Logistics and Supply Chain Operations in the Digital Era)
►▼ Show Figures

Figure 1

24 pages, 745 KB  
Article
Multi-Objective Optimization for Sustainable Food Delivery in Taiwan
by Kang-Lin Chiang
Sustainability 2026, 18(1), 330; https://doi.org/10.3390/su18010330 - 29 Dec 2025
Viewed by 777
Abstract
This study develops a fuzzy linear multi-objective programming (FLMOP) model to optimize Taiwan’s online food delivery (OFD) systems by jointly considering time, cost, quality, and carbon emissions (TCQCE) under strict Hazard Analysis and Critical Control Point (HACCP) safety constraints. By integrating fuzzy set [...] Read more.
This study develops a fuzzy linear multi-objective programming (FLMOP) model to optimize Taiwan’s online food delivery (OFD) systems by jointly considering time, cost, quality, and carbon emissions (TCQCE) under strict Hazard Analysis and Critical Control Point (HACCP) safety constraints. By integrating fuzzy set theory with triangular fuzzy numbers (TFN) and employing centroid defuzzification, this model effectively addresses uncertainties in delivery time, cost, and quality. Empirical results demonstrate that controlled delivery-time extension and order batching reduce carbon emissions by 20%, maintain food quality at 89.3%, and lower delivery costs by 15% under large-scale operations. Statistical validation (p = 0.002) and sensitivity analysis confirm robustness and low variability. Comparative benchmarking highlights FLMOP’s superiority over mixed-integer linear programming (MILP) and genetic algorithms/non-dominated sorting genetic algorithm II (GA/NSGA-II), achieving higher hypervolume (0.904 vs. 0.836 and 0.743) and near-optimal solutions within 11 s, making it suitable for real-time decision-making. This study establishes a benchmark for sustainable last-mile OFD and offers practical guidelines for Taiwan’s OFD platforms. Full article
(This article belongs to the Special Issue Sustainable Logistics and Supply Chain Operations in the Digital Era)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop