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The Sustainable Development Goals (SDGs) of the United Nations represent a crucial worldwide initiative aimed at advancing development and fostering a more favorable future. However, the advancement made towards achieving these objectives has been insufficient, and the allocation of research endeavors has been uneven. As a way to address this concern, the present study aimed to conduct an evaluation of the SDGs through examining their research-friendly characteristics. By conducting a systematic review of scholarly works and employing diverse evaluation criteria, the research employed a multi-criteria decision-making approach to rank the SDGs. The results of the study indicate that SDG 3, which pertains to health and well-being, was rated the most research-friendly, whereas SDG 4, which emphasizes quality education, and SDG 16, which concerns peace, justice, and strong institutions, received the lowest ratings. Besides, some of the research obstacles linked with every SDG have been outlined by this paper. The present investigation underscores the research-oriented character of the SDGs and emphasizes the significance of comprehending research agendas to formulate efficacious and sustainable resolutions to worldwide predicaments. The outcomes of this study offer a significant asset for individuals responsible for making decisions, the academic community, and other interested parties who are involved in the allocation of resources towards the SDGs. The current investigation provides an important contribution to the scholarly dialogue by creating a framework that can direct expected research efforts and aid policymakers in modifying existing or creating new goals that are more favorable to research and development. [ABSTRACT FROM AUTHOR]

In recent years, sustainable digital economy development goals have received increasing attention because of the serious influence environment with the development of the rapid economy. Meanwhile, Multiple Criteria Decision-Making (MCDM) methods are efficient ways to measure sustainable developments, which can controls environmental pollution and protects sustainability improvement. However, assessment results are unconvincing by using the common MCDM methods because various areas that caused pollution conditions are inconsistent. Therefore, the purpose of this paper is to design an interpretable MCDM method with uncertain weights for various areas evaluation. In particular, MCDM can be used to evaluate environmental sustainability development efficiently, and deep neural networks can supply credible weights to MCDM. Interpretability is used to understand key factors in the decision-making process. Referring to the national policy and urgent areas from central areas in China, six areas are conducted to assess the sustainable digital economy problem, which could be interpreted as demonstrating the effectiveness and feasibility of the proposed approach. Besides, the experimental results demonstrate that the sustainable developmental level of Hubei is the best in the latest year. [ABSTRACT FROM AUTHOR]

Sustainability assessment provides essential information to facilitate informed decision-making, enabling the selecting of the best option among various projects. This research paper considers the decision-making problem in the context of marginalised and isolated communities, introducing a groupal model for evaluating the sustainability of small-scale power supply projects. The proposed model incorporates a comprehensive set of five indicators and 25 criteria. The analysis presented in this study prioritises these indicators and criteria, introducing new criteria based on several stakeholders' participation and offering guidance on measuring the identified criteria. Furthermore, the proposal provides fundamental thresholds for evaluating the projects' sustainability and proposes a model based on aggregated indicators to assess the available alternatives. It encompasses all stages of the decision-making process, employing multiple indicators to evaluate the sustainability of power supply projects. The effectiveness of the proposed model was validated in a real case study conducted in a marginalised community facing isolation challenges in La Guajira, Colombia. The evaluation showcased the model's contribution to decision-making processes regarding power supply projects in isolated communities. Finally, the results demonstrated the suitability of this strategy for immediate application, highlighting its potential impact on decision-making for sustainable development within marginalised areas. • The multi-criteria-based decision-making model maximises projects' sustainability. • The model evaluates the projects' sustainability, incorporating innovative criteria. • The model implementation in a study case confirms its efficacy for decision-making. • The study case findings suggest adopting cooperative or community-based governance. [ABSTRACT FROM AUTHOR]

Water, which is predicted to be one of the most critical resources for the near future, also plays a vital role in society's sustainable development. Wastewater treatment is a critical part of the circular water management system and offers various technological alternatives. Taking appropriate decision for the technology selection is, therefore, essential for a long-term perspective. A complex yet imperative process is the sustainable selection of the wastewater treatment process. This paper presents the use of multi-criteria decision-making (MCDM) in the sustainability assessment of wastewater treatment technologies that may be very relevant to the growing sector with many emerging options. A comparison of six wastewater treatment technologies based on four sustainability parameters using three MCDM techniques, namely FSWARA, FMOORA and FTOPSIS is presented in detail. FSWARA is used for weighting criteria and the other two for technology ranking. The detailed step-by-step comparison study is presented and the results were somewhat predictable for the study, and this confirms the reliability of the methodology. This paper's primary objective is to propose a well-defined increscent practice for making sustainable wastewater treatment decisions among state-of-the-art technologies. • Sustainability ranking of wastewater treatment technologies using multi-criteria decision making methods. • Combined Fuzzy SWARA-MOORA and fuzzy SWARA-TOPSIS methods. • While weighing the criteria, most significance is given to environmental factors. • Inclusion of both conventional and non-conventional technologies. [ABSTRACT FROM AUTHOR]

• The score function is proposed for hesitant Fermatean fuzzy set. • Unify the framework of Regional Green Development Level Evaluation. • Improve MULTIMOORA method is proposed with hesitant Fermatean fuzzy information. • Level Difference Maximization Method to combine subjective and objective weights. • Case study of RGDL is presented to show the potentiality of the developed method. Economic green development has received increase attention. However, the uncertainty decision processes in the development of green economic growth has brought challenges to the evaluation, which leads to the evaluation index system has not yet reached a consensus. In order to solve the above problems, this paper, based on the established and developed regional green development level evaluation (RGDLE) system in existing literature, employed improved MULTIMOORA group decision model under the hesitant fuzzy Fermatean environment (HFFS-MULTIMOORA) and an innovative weighting method to develop the RGDLE process. This evaluation framework describes the complexity of the RGDLE process. The Level Difference Maximization Method to combine the average-based subjective weight-determining method and the Shannon-entropy-based objective weight-determining method is developed to fit RGDLE problems with cognitive complex information. This innovative index system and HFFS-MULTIMOORA method based group decision-making framework is further applied to evaluate the green development level of five provinces and municipalities along the Yangtze River Economic Zone, China. Results showed the optimal green development levels ranking of the five alternative provinces and municipalities of the Yangtze River Economic Zone, China. Moreover, the effectiveness and feasibility of the model framework was verified by robustness and comparative analysis between the existing method. This paper contributes not only to the literature on RGDLE but also to giving decision-makers and researchers inside and outside China valuable inspiration and references for improving the evaluation efficiency and giving policy suggestions. [ABSTRACT FROM AUTHOR]

Increasing water-use efficiency across all sectors has been set as a key target for sustainable water management within the framework of the United Nations Sustainable Development Goals. Agriculture stands out as a key sector where opportunities for sustainable transformation arise, due to its dominant position in water use. The aim of this study is to propose a risk- and robustness-based multi-objective decision support model (RARB-MODSM) tool to help explore water-efficient agricultural development schemes and to enable inclusion of their associated environmental impacts into a stringent assessment of the risks. This tool allows for integration of economic growth and water use objectives with stringent pollution control requirements to help gain insights into the trade-offs between resource efficiency and environmental impact. This paper provides a case study of the application of this decision support tool in a prefectural-level city in China as an example of demonstrating how the tool could help reduce the water usage from the agricultural sector while enabling a higher economic productivity. The results show that expanding agricultural production in two regions of the city may help promote efficiency-oriented water management and improve the entire agricultural system's economic productivity. The results also indicate that this agricultural system is more sensitive to the control over phosphorus discharge and imposing more stringent total phosphorus (TP) control requirements within local agricultural system may help achieve better results on the system-wide pollution control. Overall, this tool demonstrates the applicability of using the systems analysis approach to help navigate the agricultural transition toward a water-efficient and low-impact growth path. [Display omitted] • This study proposes a novel decision support model tool to help reshape urban agricultural systems toward water efficiency. • This tool allows for integration of economic growth and water use objectives with stringent pollution control requirements. • This tool enables decision makers to gain insights into the trade-offs between resource efficiency and environmental impact. • This tool helps to explore viable paths forward for economic restructuring in urban agricultural systems. [ABSTRACT FROM AUTHOR]

Since the different matching schemes between manufacturing tasks and services have a great influence on the life cycle sustainability of complex product system (CoPS), the strategy used to find cost-effective, environmentally friendly, and socially acceptable matching results is essential for sustainable development. This paper proposed a novel two-sided matching model for CoPS based on life-cycle sustainability assessment (TSMM-CoPS-LCSA). First, the two-sided matching model based on the life-cycle sustainability assessment of manufacturing tasks and services for CoPS is presented. Then, a bi-level decision-making method is proposed, where learning and synergy effect are considered to ensure stability in the matching process. Sequentially, to facilitate the optimization solution, the Karush-Kuhn-Tucker (KKT) conditions are adopted to convert the bi-level model to a single model which aims to minimize the total cost, environmental impact, and social impact. Subsequently, for solving this nonlinear and complex multi-objective decision-making model, an improved hybrid algorithm that integrated Tabu Search and non-dominated sorting genetic algorithm II (TS-NSGA-II) is applied to solve the above model. Finally, a case study of CoPS manufacturing project is illustrated to demonstrate the effectiveness and superiority of the proposed TSMM-CoPS-LCSA model. The results indicate that the proposed method can find a better services scheme in line with actual demand, which provides a guiding significance for promoting the sustainable development of the manufacturing industry. [ABSTRACT FROM AUTHOR]

Farmers in Europe act within guidelines set by agricultural programs, market demands and biophysical constraints. At the same time, they are social actors embedded in their respective family structures and individual lifestyles and preferences. We here present the socio-ecological land-use model SECLAND that provides an improved representation of the versatility in farmer's characteristics and subsequently its impact on land-use decision making. The model combines (1) an agent-based module (ABM) with farmers as agents whose intrinsic behavioural characteristics are represented via farming styles with (2) a probabilistic GIS-based forest regrowth module. We apply the model for the LTSER Eisenwurzen region in northern Austria to explore land-use patterns until the year 2050 under three different scenarios. Our results show the relevance of explicitly considering differences between the responses of individual farmers to changing framework conditions. In order to devise sustainable development paths for future agriculture, it is important to focus on farmers' well-being and recognize it as being equally important as economic success. • This paper provides the description of the bimodular SECLAND land-use model. • We depict the effect of intrinsic factors on farms decision-making. • We investigate the impact of socio-economic and climatic framework changes on land-use patterns. • We analyse intensity shifts, crop and forest type changes as well as forest transition. [ABSTRACT FROM AUTHOR]

• The positional TOPSIS, combined with different optimal tail selection methods of the variable distribution, is proposed to assess the sustainable development of territorial units. • The cluster compactness measure is proposed to evaluate the classification results of the positional TOPSIS with the optimal tail selection of variable distribution. • The automated Eye-Ball method and the Guillou and Hall's method enable correct identification of extreme values of variables describing the economic, social, and environmental development of municipalities. • The positional TOPSIS with selected optimal tail selection methods enable correct classification of the municipalities and assessment of their sustainable development in terms of levels and statuses. In the face of accelerating climate change, economic instability and limited resources, it is essential to find indicators that better measure the sustainable development of territorial units. Despite ambiguous definitions of sustainable development, numerous studies describe quantitative indicators of sustainable development. Main methodological problems include data availability and their use, spatial and time scales, selection of indicators, and their aggregation. Usually, analysts and decision-makers apply well known conventional methods that have numerous limitations. These methods in many cases cause excessive simplification of the real phenomena and relations between their determinants. Moreover, variables describing the development of territorial units (especially the environmental pillar) are often characterized by strong asymmetry or extreme observations. Even a single outlier for a given territorial unit may significantly affect the analysis and the resulting conclusions. The objective of this paper is to present the application potential of a Multi-Criteria Decision Making (MCDM) approach with an optimal tail selection to assess the sustainable development of territorial units. The proposed approach is based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and different methods of optimal tail selection of variable distribution. The Oja's spatial median and the optimal tail selection methods are used to reduce the impact of strong asymmetry and extreme values of variables. Moreover, the measure of cluster compactness is proposed for the evaluation of the proposed method. The proposed approach was used to assess the sustainable development of municipalities in Poland in 2018. We found that the automated Eye-Ball method and the Guillou and Hall's method enabled correct identification of extreme values of variables describing the economic, social, and environmental development of municipalities. This made it possible to distinguish the types of sustainable development level and its pillars and enabled to provide the statuses of the sustainable development level of the examined municipalities with respect to other municipalities in Poland. [Display omitted] [ABSTRACT FROM AUTHOR]