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

Deadline for manuscript submissions: 31 August 2026 | Viewed by 11929

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Special Issue Editors

Dr. João Miguel Lourenço

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Guest Editor

Polytechnic Institute of Setúbal—Setúbal School of Technology, 2910-761 Setúbal, Portugal
Interests: automation; optimization; simulation; decision making; multiobjective optimization; post-Pareto analysis and response surface methodology
Special Issues, Collections and Topics in MDPI journals

Dr. Nuno Costa

E-Mail Website
Guest Editor Assistant

1. Instituto Politécnico de Setúbal, ESTSetúbal, Campus do IPS, Estefanilha, 2910-761 Setúbal, Portugal
2. Centro de Investigação em Qualidade de Vida, Instituto Politécnico de Setúbal, Campus do IPS, 2910-765 Setúbal, Portugal
Interests: operations management; quality engineering; optimization; design of experiments; industry 5.0; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable business decision-making is crucial for long-term success. It entails a proactive approach where every decision, from product development to resource management, carefully weighs its environmental, social, and economic implications.

From strategic decisions such as business location to technology selection, product quality, project portfolio selection, the value of healthcare interventions and public policies, and a myriad of management decisions in (non)industrial settings require a compromise between multiple conflicting qualitative and/or quantitative criteria. To ensure long-term sustainability, these decisions must be supported by multiple criteria decision analysis and/or multiple objective decision-making methodologies, methods, procedures, and techniques that provide a scientifically robust decision-making framework while balancing economic, environmental, and social factors.

In this Special Issue, entitled “Decision-Making in Sustainable Management”, theoretical papers and practical case studies involving multiple criteria and objectives from any research field are welcome.

Dr. João Miguel Lourenço
Guest Editor

Dr. Nuno Costa
Guest Editor Assistant

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

Pareto
optimal
MADM
MCDM
sustainable
balanced solutions
resources optimization
uncertainty
robustness
resilience

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Published Papers (7 papers)

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Research

20 pages, 2350 KB

Open AccessArticle

Risk Assessment of Grid-Integrated Energy Service Projects: A Hybrid Indicator-Based Fuzzy-Entropy-BP Evaluation Framework

by Haoran Du and Yaling Sun

Sustainability 2026, 18(2), 1002; https://doi.org/10.3390/su18021002 - 19 Jan 2026

Viewed by 353

Abstract

Grid-integrated energy service (GIES) projects are characterized by strong cross-energy coupling and long investment horizons, resulting in multidimensional and nonlinear risk profiles. To address these challenges, this study develops an indicator-based risk evaluation framework by integrating an entropy–back-propagation (BP) combined weighting method with fuzzy matter-element theory. A 30-indicator system covering economic, environmental, and safety and reliability dimensions is constructed to support systematic risk assessment. The entropy–BP scheme combines data-driven objectivity with nonlinear correction, producing stable and interpretable indicator weights, as confirmed through robustness tests based on indicator removal and data perturbation. A real-world GIES project in East China is used as a case study. The results show clear risk grade differentiation among alternative scenarios and identify key risk drivers related to renewable energy integration, investment structure, and energy supply reliability. The proposed framework provides effective decision support for GIES project planning and risk management. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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19 pages, 425 KB

Open AccessArticle

A Decision-Support Model for Holistic Energy-Sustainable Fleet Transition

by Antoni Korcyl, Katarzyna Gdowska and Roger Książek

Sustainability 2026, 18(1), 62; https://doi.org/10.3390/su18010062 - 20 Dec 2025

Viewed by 531

Abstract

The transition toward sustainable transport systems requires decision-support tools that help organizations navigate strategic choices under environmental, economic, and operational constraints. This study introduces the Holistic Multi-Period Fleet Planning Problem (HMPFPP), a nonlinear optimization model designed to support long-term, sustainability-oriented fleet modernization. The model integrates investment costs, operational performance, emission limits, and dynamic demand into a unified analytical framework, enabling organizations to assess the long-term consequences of their decisions. A notable feature of the HMPFPP is the inclusion of outsourcing as a strategic option, which expands the decision space and helps maintain service performance when internal fleet capacity is constrained. An illustrative ten-year scenario demonstrates that the model generates non-uniform but cost-efficient transition pathways, in which legacy vehicles are gradually replaced by cleaner technologies, and temporary fleet downsizing can be optimal during low-demand periods. Outsourcing is activated only when joint emission and budget constraints make fully internal service provision infeasible. Across the tested instance, the HMPFPP is solved within seconds on standard hardware, confirming its computational tractability for exploratory planning. Taken together, these results indicate that data-driven optimization based on the HMPFPP can provide transparent and robust support for sustainable fleet management and transition planning. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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24 pages, 1097 KB

Open AccessArticle

Multicriteria Optimization of Nanocellulose-Reinforced Polyvinyl Alcohol and Pyrrolidone Hydrogels

by Nuno Costa, João Lourenço, Joana Cabalú, Ana Branco and Célio G. Figueiredo-Pina

Sustainability 2025, 17(21), 9905; https://doi.org/10.3390/su17219905 - 6 Nov 2025

Viewed by 683

Abstract

Developing new materials for human cartilage replacement is a hot research topic. These materials have multiple properties of interest, so selecting a new material (hydrogel) is a multi-attribute decision-making problem. A case study illustrates the application of a structured approach and tools to solve this problem type. Ten hydrogels, most of which are new formulations, were evaluated based on three attributes. The weights assigned to the attributes were identified using three methods from the literature, in addition to those previously assigned by an expert. Since the hydrogel properties showed some variability, Monte Carlo simulations were carried out using triangular distribution. Ten thousand decision matrices were built and 10,000 rankings were generated by each of the ten multicriteria decision-making methods employed in this study. Ranking similarity was evaluated through the PS index, whose values ensure consistency and reliability of the results achieved. Rank acceptability and pairwise indexes were used to identify the most promising hydrogels. Two hydrogels were identified as the most promising for further study, for any of the four sets of weights used. Both are annealed nanocellulose-reinforced polyvinyl alcohol and pyrrolidone hydrogels. The robustness of this result is supported on the values of acceptability and pairwise indexes. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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28 pages, 2302 KB

Open AccessArticle

New Energy Vehicle Decision-Making for Consumers: An IBULIQOWA Operator-Based DM Approach Considering Information Quality

by Yi Yang, Xiangjun Wang, Jingyi Chen, Jie Chen, Junfeng Yang and Chang Qi

Sustainability 2025, 17(17), 7753; https://doi.org/10.3390/su17177753 - 28 Aug 2025

Viewed by 918

Abstract

New energy vehicles (NEVs) have gained increasing favor among NEV consumers due to their dual advantages of “low cost” and “environmental friendliness.” In recent years, the share of NEVs in the global automotive market has been steadily rising. For instance, in the Chinese market, the sales of new energy vehicles in 2024 increased by 35.5% year-on-year, accounting for 70.5% of global NEV sales. However, as the diversity of NEV brands and models expands, selecting the most suitable model from a vast amount of information has become the primary challenge for NEV consumers. Although online service platforms offer extensive user reviews and rating data, the uncertainty, inconsistent quality, and sheer volume of this information pose significant challenges to decision-making for NEV consumers. Against this backdrop, leveraging the strengths of the quasi OWA (QOWA) operator in information aggregation and interval basic uncertain linguistic information (IBULI) information aggregation and two-dimensional information representation of “information + quality”, this study proposes a large-scale group data aggregation method for decision support based on the IBULIQOWA operator. This approach aims to assist consumers of new energy vehicles in making informed decisions from the perspective of information quality. Firstly, the quasi ordered weighted averaging (QOWA) operator on the unit interval is extended to the closed interval

[0, τ]

, and the extended basic uncertain information quasi ordered weighted averaging (EBUIQOWA) operator is defined. Secondly, in order to aggregate groups of IBULI, based on the EBUIQOWA operator, the basic uncertain linguistic information QOWA (BULIQOWA) operator and the IBULIQOWA operator are proposed, and the monotonicity and degeneracy of the proposed operators are discussed. Finally, for the problem of product decision making in online service platforms, considering the credibility of information, a product decision-making method based on the IBULIQOWA operator is proposed, and its effectiveness and applicability are verified through a case study of NEV product decision making in a car online service platform, providing a reference for decision support in product ranking of online service platforms. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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18 pages, 849 KB

Open AccessArticle

Decision Optimization of Manufacturing Supply Chain Based on Resilience

by Feng Lyu, Jiajie Zhang, Fen Liu and Huili Chu

Sustainability 2025, 17(14), 6519; https://doi.org/10.3390/su17146519 - 16 Jul 2025

Cited by 3 | Viewed by 3454

Abstract

Manufacturing serves as a vital indicator of a nation’s economic strength, technological advancement, and comprehensive competitiveness. In the context of the VUCA (Volatility, Uncertainty, Complexity, Ambiguity) business environment and globalization, uncertain market demand has intensified supply chain disruption risks, necessitating resilience strategies to enhance supply chain stability. This study proposes five resilience strategies—establishing an information sharing system, multi-sourcing, alternative suppliers, safety stock, and alternative transportation plans—while integrating sustainability requirements. A multi-objective mixed-integer optimization model was developed to balance cost efficiency, resilience, and environmental sustainability. Comparative analysis reveals that the resilience-embedded model outperforms traditional approaches in both cost control and risk mitigation capabilities. The impact of parameter variations on the model results was examined through sensitivity analysis. The findings demonstrate that the proposed optimization model effectively enhances supply chain resilience—mitigating cost fluctuations while maintaining robust demand fulfillment under uncertainties. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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25 pages, 2961 KB

Open AccessArticle

Procurement Optimization for Manufacturing Enterprises Considering Supply Chain Disruption Risks and Carbon Emissions

by Mengying Shi and Jinwei Zhu

Sustainability 2025, 17(8), 3532; https://doi.org/10.3390/su17083532 - 15 Apr 2025

Cited by 2 | Viewed by 2968

Abstract

This study addresses the procurement problem in mechanical manufacturing enterprises, considering both supply chain disruption risks and carbon emissions. Based on a multi-product, multi-supplier procurement planning optimization problem, a high-dimensional multi-objective optimization model is developed with procurement cost, total loss, number of quality defects, and carbon emissions as objectives. The model is solved using an improved integer-coded NSGA-III algorithm, which includes four mechanisms: heuristic population initialization, infeasible solution optimization and repair, a weight-matrix-based crossover operator, a multi-column exchange mutation operator, and Pareto simulated annealing. Through numerical experiments, the performance of this algorithm is compared with NSGA-III and NSGA-II, demonstrating its superior ability to handle multi-objective, multi-constraint optimization problems. Ablation experiments further validate the effectiveness of the four improved mechanisms. Case study results show that the optimized procurement plan balances economic and environmental benefits while considering supply chain risks. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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28 pages, 4236 KB

Open AccessArticle

Application of the Fuzzy MCDM Model for the Selection of a Multifunctional Machine for Sustainable Waste Management

by Yu Duan, Željko Stević, Boris Novarlić, Sarfaraz Hashemkhani Zolfani, Ömer Faruk Görçün and Marko Subotić

Sustainability 2025, 17(6), 2723; https://doi.org/10.3390/su17062723 - 19 Mar 2025

Cited by 6 | Viewed by 2110

Abstract

In the sustainability concept, one of the most important areas is sustainable waste management, a system that significantly impacts both economic and social well-being. The aim of this paper is to create a unique model that can contribute to better and more promising waste management in local governments in order to increase the level of sustainability. The scientific contribution and novelty of this research is reflected in developing the Fuzzy M-FullEX (Modified Fuller’s triangle approach extended) method for defining fuzzy weight coefficients of criteria and its integration with the Fuzzy ROV (range of value) method for ranking multifunctional machines. The unique model developed in this study encompasses 10 criteria and seven alternative solutions, including the two aforementioned Fuzzy MCDM (multi-criteria decision-making) methods and the Bonferroni operator for averaging expert assessments. The results of the Fuzzy M-FullEX-Fuzzy ROV model based on the preferences of three experts define the best multifunctional machine for efficient and sustainable waste management, which is the Venieri. The rankings are as follows: M1 > M3 > M2 > M4 > M5 > M6 > M7. The obtained results were confirmed through extensive analysis (sensitivity, comparative analysis, correlation coefficients, different matrix size) and discussion. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Management)

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