In the last decades, several studies have highlighted the significant impacts of the food sector. Therefore, enhancing sustainability within this sector has become of paramount importance. A crucial step towards achieving this goal involves the definition and implementation of effective sustainability metric and measurements. In this regard, the adoption of multi-criteria decision analysis (MCDA) methods can be seen as one of the most suitable and promising approach to comprehensively capture the complex and broad-ranging effects of agricultural practices and food supply chains. In such context, a systematic review of the scientific literature on multi-criteria approaches and tools for measuring the sustainability of food supply chains (harvest and post-harvest stages) has been carried out, resulting in the selection and analysis of 42 articles. To delve into the selected articles, three main areas of focus have been identified. The first about MCDA methods and their features, revealing the most adopted methods for sustainability assessments of food supply chains. The second, focusing on the participatory approach, led to the definition of a stakeholder\'s engagement map, highlighting the typology of stakeholders involved, the reasons of their involvement and engagement methods. Lastly, the third focus is related to the analysis and classification of indicators adopted in each study and the sustainability dimensions to which they refer to. The results of the present review study provide a comprehensive overview of the essential aspects to be considered when developing a MCDA for sustainability assessment in the food sector, serving as a valuable resource for both scholars and practitioners.

The study introduces a hybrid model that integrates system dynamics modeling and multi-criteria analysis. Through the system dynamics model, the study examines energy, economic, and environmental indicators of a District Heating (DH) company, assessing its dynamics until 2050. Various decarbonization scenarios are explored, involving the transition of the DH system to a 4th generation DH (4GDH) system based on four strategies: utilizing at least (a) 50% Renewable Energy Sources (RES), (b) 50% waste heat, (c) 75% cogenerated heat, or (d) 50% of the combined aforementioned energy and heat. Additionally, development scenarios incorporate measures to enhance energy efficiency on the consumer side and within the heating networks. The sustainability of each scenario is evaluated using the multi-criteria analysis method TOPSIS. The hybrid model establishes a ranking of the transition pathways based on their sustainability scores and benchmarks the results of the developed scenarios against a carbon-neutral DH system. This model serves as a valuable guide for DH system developers and decision-makers. The study focuses on Riga as a practical case study.

Beekeeping management is greatly influenced by spatial factors (e.g., land use/land cover, roads, or electrical energy networks), so GIS are a powerful tool to overlap and relate a variety of spatial data levels and, consequently, a very useful tool for beekeeping activity planning. This study was developed within the intervention area of three controlled zones managed by Portuguese Beekeepers Associations. The methodology, based on multi-criteria decision analysis, integrates several criteria, such as hydrographic networks, road networks, soil occupation, solar radiation, and electromagnetic radiation sources. These criteria were proposed and evaluated through online questionnaires carried out with beekeepers. Concerning the selected criteria and the respective geographical data, the most relevant were land use/land cover and water availability, with a significance of 44% and 24%, respectively. The beekeeping suitability map enabled us to evaluate the degree of compliance for the actual location of apiaries, with 60% of the apiaries being installed in high potential areas. In the context of beekeeping planning, the potential of the techniques applied seems to be an important tool for optimizing the location of apiaries and the profitability of beekeeping.

In the present study we have presented the notion of FUZZY BAYESIAN DECISION TECHNIQUE and combined the idea of the Fuzzy TOPSIS technique and entropy. We define the new ideas of fuzzy TOPSIS technique and entropy. So, we introduce the TOPSIS method and entropy, and the weights of the DMs are used. We proposed an MCDM technique based on TOPSIS and entropy. We focus on parameter different solutions of Fuzzy TOPSIS Positive ideal and Negative ideal solutions efficient decision making. Also, we provide a numerical example to elucidate the proposed technique stage by stage. Lastly, we compare the explanations of the current problem with the many existing MCGDM approaches to deliver the skills and rationality of the offered technique. We also provide a sensitivity study by shifting the entropy to establish the weights of the criteria underneath the dominant entropy measure meaning.

Construction and Demolition Waste Management (CDWM) includes collecting, transporting, processing, and disposing construction and demolition (C&D) waste, where collection and transportation of bulky and voluminous C&D waste contribute significantly to economic and environmental impacts. Transfer station (TS) being a link between various waste management (WM) facilities plays a significant role in collection and transportation of waste. Thus, locating TS at suitable site can help in reducing the overall impacts. Employment of Geographic Information System (GIS) analysis tools in CDWM is a powerful strategy for site suitability study. A case study in Coimbatore, India, is presented in this study using GIS-based multi-criteria analysis for locating C&D waste TS. The criteria for site suitability analysis are chosen based on literature review, regulations, and experts\' opinions. Weights of the chosen criteria are estimated using analytic hierarchy process (AHP), and the final suitability map is created by weighted overlay analysis (WOA) in GIS environment. Results provide first-hand information for local decision makers to locate C&D waste transfer station in the chosen study region and report that 12% of the entire area is \"highly suitable\" for transfer station location.

In this paper, we discuss the use of multi-criteria analysis for investment alternatives as a rational, transparent, and systematic approach that reveals the decision-making process during a study of influences and relationships in complex organizational systems. It is shown that this approach considers not only quantitative but also qualitative influences, statistical and individual properties of the object, and expert objective evaluation. We define the criteria for evaluating startup investment prerogatives, which are organized in thematic clusters (types of potential). To compare the investment alternatives, Saaty\'s hierarchy method is used. As an example, the analysis of three startups is carried out based on the phase mechanism and Saaty\'s analytic hierarchy process to identify investment appeal of startups according to their specific features. As a result, it is possible to diversify the risks of an investor through the allocation of resources between several projects, in accordance with the received vector of global priorities.

Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aerial vehicles (UAV) to map smallholder farms and applied multi-criteria analysis to data generated from orthomosaics, to provide a set of sustainability indicators for the farms. Images were acquired from a UAV, with structure from motion (SfM) photogrammetry then used to produce orthomosaics and digital elevation models of the farm areas. Some of the inherent problems using high spatial resolution imagery for land cover classification were overcome by using texture analysis and geographic object-based image analysis (OBIA). Six spatially explicit environmental metrics were developed using multi-criteria analysis and used to generate sustainability indicator layers from the UAV data. The SfM and OBIA approach provided an accurate, high-resolution (~5 cm) image-based reconstruction of smallholder farm landscapes, with an overall classification accuracy of 89%. The multi-criteria analysis highlighted areas with lower sustainability values, which should be considered targets for adoption of sustainable management practices. The results of this work suggest that UAVs are a cost-effective tool for sustainability assessments of oil palm plantations, but there remains the need to plan surveys and image processing workflows carefully. Future work can build on our proposed approach, including the use of additional and/or alternative indicators developed through consultation with the oil palm industry stakeholders, to support certification schemes such as the Roundtable on Sustainable Palm Oil (RSPO).

A shared personal mobility device (PMD) is a transportation model that rents personal transportation devices, such as bicycles and kickboards, through a sharing platform. The use of shared PMD has increased, but related complaints and traffic accidents are doubling with it every year. This study applied an analytic network process (ANP) methodology for the multi-criteria analysis. A survey including normal citizens was conducted to evaluate the importance of safety regarding shared PMD experience. The evaluation factors differ according to the experience of using the shared PMD device, although \'driving continuity\' and \'separation of sidewalks and roadways\' were the most important. PMD users gave greater priority to \'removal of the road gap\', \'traffic safety signs\', \'dedicated parking area\' and \'management of obstacles\' compared to non-users. On the other hand, for non-PMD users, \'bicycle lane width\', \'strengthening enforcement\', and \'user safety education\' were more important. The results showed that importance differed depending on the participant\'s experience of using a shared PMD or the lack of it. In the case of users, factors that have a direct effect on driving were prioritised, and in the case of non-users, auxiliary operations and management, such as crackdowns and education, were prioritised.

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

Water transfer is an effective measure to enhance hydrodynamic and water quality in highly urbanized areas. The effect of water transfer in highly urbanized areas is affected by strong artificial interventions, and it is difficult to evaluate the improvement of multiple indicators of many sections after water transfer. At present, there is no analysis framework directly evaluates the improvement of water environment under strong artificial interventions, making it difficult to determine the optimal scheduling of hydraulic projects. This study constructed a multi-criteria analysis framework for evaluating the improvement of water environment including index layers of water quality improvement, hydrodynamic improvement and economic cost, and designed corresponding element layers for each index layer. The weights of each element were determined based on fuzzy analytical hierarchy process, and the fuzzy comprehensive evaluation method was used for comprehensive evaluation. The framework was applied in Xishan District in highly urbanized Taihu Lake Basin, and the results showed that the proposed framework could effectively determine the optimal scheduling of hydraulic projects. Water quality compliance rate for the optimal water transfer scheme achieved in Xishan District was 82%, average rate of water quality improvement was 31%, and proportion of cross-sections meeting the Class III water quality standard was 61%. Average flow velocity was 0.10 m/s, proportion of the optimal velocity was 39%, and proportion of stagnant sections was 32%. Furthermore, the impact of regional control projects on the effect of water transfer was much greater than local projects, consequently, the best scheduling mode for regional control projects should be first determined, and then the scheduling combination for local projects. This study can provide a new framework for the assessment of water transfers to improve the water environments and a scientific basis for the dispatching of hydraulic projects in Taihu Lake Basin.