Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.9
4.1
Journals
Sustainability
Special Issues
Sustainable Management Framework and Operations in the Era of Industry...
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 Management Framework and Operations in the Era of Industry 4.0 with Generative AI

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 1 February 2027 | Viewed by 1598

Editors

Dr. Rupal Mandania

E-Mail Website
Guest Editor
Loughborough Business School, Loughborough University, Loughborough, UK
Interests: optimization; GenAI; sustainability; dynamic pricing
Prof. Dr. Jiyin Liu

E-Mail Website
Guest Editor
Loughborough Business School, Loughborough University, Loughborough, UK
Interests: logistics; manufacturing; modeling; optimization; heuristics
Dr. Grammatoula Papaioannou

E-Mail Website
Guest Editor
Loughborough Business School, Loughborough University, Loughborough, UK
Interests: efficiency and productivity analysis of firms; logistics and supply chains; optimisation and meta-heuristics

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to a forthcoming Special Issue focused on how organizations can build sustainable management frameworks and, in particular, sustainable operational practices in the Industry 4.0 era. As firms adopt IoT, advanced analytics, and digital infrastructures, the frontier is increasingly defined by generative AI (GenAI)-enabled decision-making that supports operational planning, execution, and continuous improvement. At the same time, the primary objective of organizations is to enhance productivity and resilience while delivering measurable environmental and social performance. This Special Issue addresses the scientific and practical challenge of translating digital and GenAI capabilities into verifiable sustainability outcomes through better operations.

This Special Issue aims to advance research that connects day-to-day operational decisions across manufacturing, supply chains, and logistics to measurable sustainability outcomes. The topic aligns with the journal’s scope by emphasizing rigorous, operations-oriented contributions that develop and test frameworks, methods, and applications for sustainable management in Industry 4.0 contexts.

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

  • GenAI-enabled operations: AI assistant for production planning, scheduling, procurement, maintenance, compliance, and decision support.
  • Automation of operational documentation and reporting: ESG reporting workflows, audit trails, quality and compliance documentation, and sustainability disclosures.
  • GenAI integrated with analytics: GenAI with digital twins, simulation, and optimization for operational sustainability and resilience.
  • Sustainable supply chain and logistics operations: planning, execution, visibility, and coordination for lower emissions and higher resilience.
  • Energy and resource efficiency in operations: operational strategies for energy management, resource productivity, and efficiency improvement.
  • Governance and risk in operational GenAI: AI governance, transparency, ethics, accountability, and managing misinformation risks in operational and sustainability contexts.

We look forward to receiving your contributions.

Dr. Rupal Mandania
Prof. Dr. Jiyin Liu
Dr. Grammatoula Papaioannou
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-anonymized 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 operations management
  • Industry 4.0
  • generative analytics integration
  • sustainable supply chain and 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

33 pages, 2763 KB  
Article
Sustainable Inventory Management for Perishable Dairy Products: A Circular-Economy Approach Integrating Environmental Costs
by Olena Pavlova, Maryna Nagara, Oksana Liashenko, Kostiantyn Pavlov, Rafał Rumin, Viktoriia Marhasova, Oksana Drebot and Karolina Jakóbik
Sustainability 2026, 18(8), 3975; https://doi.org/10.3390/su18083975 - 16 Apr 2026
Viewed by 840
Abstract
The transition toward sustainable food systems requires innovative approaches to managing perishable products, where inefficient inventory practices contribute significantly to global food loss and environmental degradation. This study develops a circular-economy-oriented inventory optimisation framework for dairy supply chains that integrates environmental externalities and [...] Read more.
The transition toward sustainable food systems requires innovative approaches to managing perishable products, where inefficient inventory practices contribute significantly to global food loss and environmental degradation. This study develops a circular-economy-oriented inventory optimisation framework for dairy supply chains that integrates environmental externalities and waste valorisation pathways into operational decision-making. Departing from traditional linear “produce–consume–dispose” models, this study embeds three core sustainability mechanisms into a stochastic dynamic-programming framework: (1) progressive environmental cost internalisation aligned with EU Emissions-Trading System carbon pricing, capturing both waste-related emissions and cold-chain energy footprints; (2) circular-economy value-recovery channels that redirect near-expiry products to secondary applications (animal feed, biogas production, industrial processing) rather than disposal; and (3) deterioration-aware demand management that minimises resource throughput while maintaining service levels. Empirical calibration using Ukrainian dairy industry data demonstrates that sustainability-integrated inventory policies reduce waste generation by 4.8–10% relative to conventional approaches, with high-deterioration products showing the greatest potential for improvement. The authors identify a critical threshold in the circular economy: when salvage recovery rates exceed 35%, waste becomes an economic and ecological asset, fundamentally altering the sustainability calculus of inventory decisions. Environmental costs account for 4.6% of total operating expenses at current carbon prices, a share projected to increase substantially as climate regulations tighten. The findings provide actionable guidance for dairy supply chain stakeholders pursuing the Sustainable Development Goals (SDGs 2, 12, 13): processors should establish circular-economy partnerships that achieve salvage rates above 35%, implement product-specific policies for high-deterioration items, and proactively integrate carbon pricing into inventory optimisation. The framework bridges sustainable operations theory and circular economy practice, offering a replicable model for transitioning perishable food supply chains toward closed-loop, low-waste configurations that simultaneously reduce environmental impact and enhance economic performance. Full article
(This article belongs to the Special Issue Sustainable Management Framework and Operations in the Era of Industry 4.0 with Generative AI)
►▼ Show Figures

Figure 1

24 pages, 1672 KB  
Article
An Incentive-Based Decision-Support System for Sustainable Delivery Scheduling with GenAI-Assisted Interpretation
by Yizi Zhou, Rupal Mandania, Jiyin Liu and Cihan Butun
Sustainability 2026, 18(6), 2901; https://doi.org/10.3390/su18062901 - 16 Mar 2026
Viewed by 390
Abstract
Companies are under increasing legal and societal pressure to reduce CO2 emissions from their delivery vehicles, while maximizing profit remains their prime objective. We study a problem where a company sends engineers with vehicles to customer sites to provide services. Customers request [...] Read more.
Companies are under increasing legal and societal pressure to reduce CO2 emissions from their delivery vehicles, while maximizing profit remains their prime objective. We study a problem where a company sends engineers with vehicles to customer sites to provide services. Customers request the service at their preferred time windows through a website or by calling a call center, and the company needs to allocate these service tasks to time windows and decide on how to schedule these tasks among its vehicles. We propose an approach to this problem that applies low-emission vehicle-scheduling techniques with dynamic pricing to reduce CO2 emissions and maximize profit. When a customer requests a service with a preferred time window, the company will provide the customer with different service time window options and their corresponding prices. Incentives are included in the prices to influence the customers to reduce CO2 emissions. Our approach solves the problem in two phases: the first phase solves time-dependent vehicle scheduling models with the objective of minimizing CO2 emissions, and the second phase solves a dynamic pricing model to maximize profit. Results show that our approach significantly reduces CO2 emissions and increases profits. A GenAI-based interpretation tool is used to translate the optimization outputs into actionable guidance for planners. Full article
(This article belongs to the Special Issue Sustainable Management Framework and Operations in the Era of Industry 4.0 with Generative AI)
►▼ 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