Analytical Hierarchical Process Research Articles

Assessment of concentrated solar power (CSP) generation potential in Cameroon using a Multi-Criteria Analysis Method and Geographic Information System (GIS).

This research aims to identify wet-cooled CSP (Concentrated Solar Power) solar power plants connected to the existing electricity grid in Cameroon. This study uses a hybrid approach which combines an MDCM-AHP method (Multi-Criteria Analysis Method - Hierarchical Analysis Process) and a GIS (Geographic Information System). The elements studied are the climate (Direct Normal Irradiance (DNI), temperature), orography (slope and elevation) and location (proximity to the electricity network, proximity to roads and railways, proximity to homes), in order to determine the weight of these different factors and combine them to obtain the final map. The method was used to map and visualize unsuitable areas, as well as to rank suitable sites. According to the results, over 42.35% of the country's nland is unsuitable for the construction of CSP solar plants, mainly due to excessive land use. According to the results, 0,001% of Cameroon's land is considered "Less suitable", 44% "Suitable", 13.46% "Highly suitable" and 0.01% "Most suitable".The sensitivity study includes three different situations, namely the technical scenario (high consideration of technical factors such as DNI, temperature, elevation, and slope). The economic scenario (where economic factors such as proximity to electricity grids, roads, residential areas and watercourses are taken into account) and the equal-weight scenario (where all factors are equal) clearly demonstrate that we can find very suitable areas for the installation of CSP solar plants in Cameroon, particularly in the Far North region. A detailed analysis by region shows that the theoretical potential for CSP solar energy in regions with "Less Suitable", "Suitable", "Highly Suitable" and "Most Suitable" suitability is approximately 4242.25TWh/year, 29328.658TWh/year, 3965.25TWh/year and 5.794TWh/year. The overall potential amounts to approximately 37536.159TWh/year for all ten Canadian regions. Thanks to the model, it has been possible to identify the most suitable regions for CSP investment and offers opportunities to carry out more in-depth studies in order to choose the right site.

Data-driven methodology for identifying the best influencers for a brand: A case study on Anemonia

This study aims to develop a new data-driven methodology for identifying suitable influencers for a brand using data from social media. The increasing presence of such figures in these communication channels makes it challenging to select consistent and influential influencers for a specific audience. This paper introduces an innovative approach to defining these figures based on the analysis of relationships within the brand's network. Specifically, this methodology will be applied to the case study of a brand named “Anemonia”. The approach relies on the sequential application of various steps, including the use of tools such as Social Network Analysis (SNA) centrality, Sentiment Analysis (SA), and Analytical Hierarchical Process (AHP). Through the application of this methodology, the brand has been able to identify influencers consistent with its aesthetics and vision.

Evaluation of Material Selection for Small Wind Turbine Blades Using the TOPSIS Method

When creating a wind turbine blade, the material choice is crucial. Small wind turbine blades can be made out of a variety of materials, including wood, metals, carbon fibre reinforced polymers, natural fibre reinforced polymers, glass fibre reinforced polymers, and nanocomposites. Low density, high strength, and a long fatigue life are three attributes that must be present in the material used to create turbine blades. The substance is additionally made to tolerate high aerodynamic drag, fatigue loads, and impacts from the environment including dust particulate collecting and humidity. The material used to make the turbine blades should have the aforementioned essential qualities, including low density, high strength, and long fatigue life. Additionally, the material is made to endure high aerodynamic drag, fatigue loads, and environmental effects including dust particle collection and moisture materials. In order to capture energy from moving air masses, rotor blade designs rely on the principles of lift or drag. The lift blade design generates a force that lifts the object perpendicular to the plane of motion using the same principle that allows aeroplanes, kites, and birds to fly. Low density, high strength, fatigue resistance, and damage tolerance are requirements for materials used to make wind turbine blades. Composite materials, or materials with an elevated component content, are used extensively in the construction of the blades. Top Rank by Similarity to the Ideal Solution (TOPSIS), a multi-criteria evaluation technique, makes use of numerous factors. The alternative must be the furthest away of the beneficial ideal solution (BIS) & the negative ideal solution (NIS) in order to be chosen. Topsis is built on this principle. The geometric gap between each choice and the most favourable option—that is, the option with the greatest score for each criterion—is calculated after a collection of alternatives is evaluated and the scores for all criteria are normalised. An analytical hierarchical process, the direct prioritisation approach, and other techniques can be utilised to calculate the value requirements according to the TOPSIS method. By using TOPSIS, parameters are thought to be steadily rising or decreasing. Alternate Parameters taken as Wood, Aluminium, epoxy based Carbon FRP (CFRPEP), epoxy based Glass FRP (GFRPEP), polypropylene based Glass FRP with (GFRPPP), epoxy based Cotton-Glass FRP (CGFRPEP), polypropylene based Cotton-Glass FRP (CGFRPPP), epoxy based FlaxGlass FRP (FGFRPEP), and epoxy based Sisal-Glass FRP with (SGFRPEP), plastic. Evaluation Parameters taken a Tensile Strength (MPa), Production Rate, Flexural Strength (MPa), Corrosion resistance, Blade Cost (USD), Setup Cost (USD), Density (kg/m^ {3}). From the result it is seen that epoxy based Carbon FRP (CFRPEP) got the first rank and Aluminium has the lowest rank. The first ranking epoxy based Carbon FRP (CFRPEP) is obtained with the lowest quality of Aluminium

Análise Multicritério para Seleção de Técnicas Compensatórias de Drenagem Urbana e Recomendação de sua Distribuição Espacial para a Cidade de Itajubá – MG

Objective - This study evaluated the applicability of the integration of multicriteria analysis methods with Geographic Information System tools to identify suitable locations for the implementation of sustainable drainage measures. Methodology – The multicriteria analysis method known as Analytical Hierarchical Process (AHP) was employed alongside QGIS software to evaluate bioretention, detention basins, permeable pavements, individual reservoirs, and green/storage roofs in a case study conducted in the city of Itajubá, MG. Originality/relevance – Decision-makers continue to face challenges in identifying optimal locations for implementing sustainable urban drainage techniques that account for technical and spatial constraints, posing a persistent barrier to their widespread adoption. Results – It was observed that detention basins are more suitable for peripheral areas and individual reservoirs and green/storage roofs systems for urban areas. Bioretention was not very suitable for urban areas, due to space restrictions. The most influential criterion overall was “solid input”, except for the green/storage roof system, which prioritized the resident population. Social and environmental contributions - This work provides a consolidated methodology for creating maps that can be used by decision makers to choose the most suitable locations for the application of sustainable urban drainage techniques, contributing to the reduction of flooding and diffuse pollution in urban centers.

Evaluation and improvement of nursing undergraduates’ informatics competencies using a hybrid multi-criteria decision-making model

BackgroundNursing staff need to be constantly exposed to information systems at work and encounter patients who share medical data obtained from the internet; this was widely observed during the coronavirus disease 2019 (COVID-19) pandemic. Hence, nursing staff should have the necessary skills and education that can help them develop nursing students’ informatics competencies. However, research on assessing and improving nursing students’ informatics competencies remains scarce.ObjectiveThis study aimed to provide nursing educators with a refined evaluation model and targeted improvement strategies tailored to enhance undergraduate students’ informatics competencies.DesignA cross-sectional study.MethodsThis study constructed a hybrid multiple-criteria decision-making model. The analytical hierarchical process was applied to obtain criteria weights; thereafter, the Visekriterijumska Optimizacija I Kompromisno Resenje with Aspiration-level (VIKOR-AS) method was used to assess undergraduate nursing students’ informatics competencies of in the case hospital.ParticipantsData were obtained from 22 clinically experienced nurses with experience in supervising undergraduate nursing students at a secondary public hospital in Zhejiang Province, China.ResultsAccording to the weighted results, “Skill (C2)” is an important dimension with the highest weight ranking. The corresponding highest-ranking criteria for each dimension are “Knowing how to explain the information management strategies to ensure patient safety (C12),” “Applying information technology tools to support patient safety management (wristband scanning to identify patients, patients’ electronic orders, etc.) (C21),” and “Paying attention to the importance of information technology in clinical decision-making and preventing errors or facilitating patient care coordination (C32).” In the case of the undergraduate nursing students’ performance assessment, Student E was the best overall performer from the perspective of overall utility value. The remaining students ranked as follows: Student C ≻ Student D ≻ Student F ≻ Student A ≻ Student B.ConclusionsThis study model remedies the shortcomings of previous studies on evaluating undergraduate students’ informatics competency dimensions, provides a reference for nursing colleges to develop nursing informatics-related curriculum content, and helps train nursing instructors to assess and train specific students. The results indicate that information skills are an important factor in the development of nursing students’ informatics competencies; hence, nursing educators should prioritize the development of nursing students’ informatics competencies, followed by information knowledge and attitudes.

Assessing avalanche susceptibility using the analytic hierarchical process and multi-criteria weighted overlay: a case study of the Leh-Parthapur road axis

Purpose This paper aims to focus on devising a comprehensive approach for avalanche susceptibility mapping leveraging the analytic hierarchical process (AHP) coupled with multi-criteria weighted overlay (MCWO) technique and further prioritizing based on ASSI and flow modeling. Design/methodology/approach The research methodology comprises four main stages. Initially, relevant spatial data sets, including terrain attributes and meteorological factors, are collected, processed and reclassified. The AHP with MCWO is then applied to establish hierarchical criteria and determine the relative importance of each criterion, resulting in a composite avalanche susceptibility map (ASM). Avalanche sites identified and vectorized from ASM, prioritized using avalanche site susceptibility index (ASSI). Final prioritization is based on RAMMS flow modeling for three sites with the highest ASSI. Finally, a Web-based application, AvalSAFE-LPR, is created using Google Earth Engine for visualization and dissemination of results. Findings The final analysis of the study area shows that 28.5% is classified as low susceptibility, 56.6% as moderate susceptibility and 14.9% as high susceptibility zones. Additionally, 28 avalanche sites were identified along the LPR, and the three sites with the highest ASSI were modeled using the RAMMS: Avalanche Module. Originality/value This research represents a novel approach to identify, vectorize and prioritize the avalanche prone sites by integrating AHP with RAMMS: Avalanche Module and ASSI.

Selection of Best Suitable Titanium Alloy for Biomedical Applications Using Analytical Hierarchical Process

Selection of Best Suitable Titanium Alloy for Biomedical Applications Using Analytical Hierarchical Process

Novel LCA-centric mix design approach for alkali-activated EAF slag with hybrid optimization techniques.

This study presents an innovative life cycle assessment (LCA)-centric approach for optimizing the mix design of alkali-activated materials (AAMs) as sustainable alternatives to ordinary portland cement (OPC). The AAMs are developed using electric arc furnace slag (EAFS) and fly ash as precursors. The environmental performance is evaluated using the ReCiPe midpoint methodology, considering both mass and economic allocation methods. The results indicate that global warming potential and terrestrial ecotoxicity are the primary environmental impact categories across all mixes and allocation scenarios. A Taguchi-based hybrid optimization technique, integrating gray relational analysis (GRA) and analytical hierarchical process (AHP)-weighted GRA, is employed to determine the optimal mix design based on fresh properties, mechanical performance, durability, and sustainability indices. The AHP-GRA analysis reveals that mixes containing at least 50% EAFS perform better than OPC in terms of overall sustainability. A blend of 75% EAFS and 25% fly ash is recommended for achieving the best balance between performance and environmental impact, offering a promising alternative for sustainable construction practices.

Land Suitability Evaluation for Agroforestry Using Geospatial Techniques in Genale Sub-basin Oromia, Ethiopia

Agroforestry is a sustainable agricultural method that integrates trees, crops, and/or livestock within a unified land space, promoting ecological balance and resource efficiency which has been widely used for centuries due to its social, economic, and environmental advantages, despite its numerous advantages, it has not achieved substantial global acknowledgment. This research investigates the land units within the Genale sub-basin to assess their suitability for agroforestry practices, focusing on the factors that significantly impact tree and crop growth as well as productivity. Conducting a land suitability analysis is essential for designating particular areas for specific agricultural purposes. The study employs an integrated approach utilizing Geographic Information Systems (GIS), Remote Sensing (RS), and the Analytical Hierarchical Process (AHP) model, along with a weighting function, to assign suitability weights to the criteria and sub-criteria influencing plant growth, ultimately producing a predictive map of agroforestry cultivation suitability. Soil fertility parameters (soil nitrogen (N), potassium (K), organic carbon (C), phosphorus (P) and pH), Climatic (rainfall) and Topographic (Elevation and Slope) were considered in the model as a significantly determinant of agroforestry factors. Each of criteria/factor layers were classified (not suitable, less suitable, suitable and highly suitable) based on reviewed literature and expert level judgement. The Analytical Hierarchical Process indicated that the most influential variable determining agroforestry practice were, Soil nutrient availability, Slope, The Normalized Difference Water Index (NDWI), Mean annual rainfall and Elevation, respectively with 5% consistency index. The model results showed that approximately 0.6% (19,072.80 ha) of sub-basin area has optimal growth conditions, 67.83% (2,193,368 ha) suitable, 30.8% (995,382 ha) less suitable and 0.77% (24,841.60 ha) Not suitable conditions for agroforestry practice. The findings indicate that the integration of Geographic Information Systems (GIS) and Remote Sensing (RS) with the Analytic Hierarchy Process (AHP) model, incorporating a weight function, proves to be effective in identifying and assessing land units suitable for agroforestry practices aimed at optimizing production yields. This study's outcomes provide valuable insights for land-use policymakers and farmers, facilitating informed decision-making concerning agroforestry cultivation in the Genale sub-basin and similar watershed regions.

Groundwater potential zones delineation in Oued Zdin basin using GIS, RS and hierarchical analysis process

Water scarcity poses a significant challenge, particularly in regions with limited rainfall such as Algeria, where groundwater plays a crucial role in supporting both daily life and economic activities. This research aims to evaluate the groundwater potential in the Oued Zdin basin in northern Algeria by utilizing advanced geomatics methods, particularly the Analytic Hierarchy Process (AHP). Through the integration of Remote Sensing (RS) and Geographic Information Systems (GIS), the study incorporates multiple datasets, including rainfall patterns, topography, geology, drainage networks, land use, and hydrological data to assess areas with high groundwater potential. By applying AHP, the study assigns relative importance to these factors, creating a groundwater potential map that classifies the region into very high, high, low, and poor potential zones. The results indicate that 7% of the basin has very high potential for groundwater recharge, 33% has high potential, while 56% is categorized as low potential, and 4% falls under poor potential. The accuracy of the results is validated through comparison with existing well data, which aligns with the identified high-potential zones. The research demonstrates that combining GIS, RS, and AHP is an effective approach for mapping groundwater potential, offering valuable insights for sustainable water resource management in areas experiencing water scarcity. This methodology presents a scalable model that can be applied to similar regions facing groundwater challenges.

Resilient and Sustainable Green Technology Strategies: A Study of Morocco's Path Toward Sustainable Development

This study proposes a strategic framework to develop resilient green technology strategies for sustainable development in Morocco. The fuzzy Delphi method was applied to finalize and categorize the indicators. Twenty-three indicators were identified and grouped into five categories. Furthermore, the fuzzy analytical hierarchical process was used to compute and rank the green technology indicators. The findings indicate that the environmental capital foundation and output efficiency rank the highest among the major categories, with the regulatory measure subindicator being the most important among the twenty-three subindicators. Finally, this study assessed resilient green technology strategies to promote economic and environmental sustainability in Morocco.

Groundwater potential assessment in the Eastern Cape, South Africa, using analytical hierarchical process (AHP) technique

Groundwater is crucial for the growth of any country. It is a vital resource for drinking water, agriculture, industry, and economic development. However, delineating the groundwater potential zones requires a systematic approach. This study assessed the groundwater potential zones (GWPZ) in the Ntabankulu municipality using remote sensing, geographic information systems, and analytical hierarchical process (AHP) techniques. Six groundwater controlling parameters were integrated to assess groundwater potential zones, including lithology, slope, lineaments density, land use/land cover, drainage density, and rainfall. The AHP pairwise comparison matrix was utilized to determine the normalized weight of the parameters. The parameters and their classes were assigned ranks, taking into account their influence on groundwater accumulation. The resultant GWPZ map was generated by integrating the parameters and their assigned weights in ArcGIS 10.8 software. The final map from the AHP technique showed five GWPZ, including very poor (13.06%), poor (25.36%), moderate (26.93%), good (22.72%), and very good (11.93%). Validation was done by using the existing 242 boreholes in the study area. Furthermore, the receiver operating characteristics (ROC) curve was plotted, and the area under the curve (AUC) analysis indicated a satisfactory accuracy prediction (AUC = 61%). The results of this study will assist in developing a proper plan for sustainable utilization of groundwater resources within the Ntabankulu municipality.

Multi-criteria decision-making optimization of a two-staged solar power plant for low radiation zone through the social decision units

The effective use of renewable energy has been the most common problem of the last few years. The optimal designs of renewable energy systems are the most crucial issue among these problems. However, the optimal points can differ according to the perspectives. In this study, the effects of the different social aspects were investigated on the optimal design of the two-staged solar power plant operating under low solar radiation. In this regard, three social perspectives were handled to optimize the design parameters, including investor, engineering and consumer sights. Thus, different system designs were formed considering different thermodynamical parameters, solar radiation values, and working fluids. The formed designs were then thermodynamically analyzed through energy and exergy methods and economically analyzed through the net present value (NPV) method to obtain the input and output values to determine the optimal points. Finally, the efficiency analysis technique with output satisficing (EATWOS) analysis was handled for three different social aspects to make a decision on the optimal system. The social aspects were included in the optimization through the analytical hierarchic process (AHP) for inputs and outputs. The results show that the social perspectives have essential effects on the optimal designs of the energy systems. As a result, the system’s energy and exergy efficiency for the investor basis were determined as 20.88 % and 22.42 %, respectively. This system can produce 93.55 MW of power generation with a profit of 103 million US$ at the end of 20 years. The system’s energy and exergy efficiency for the engineering basis were determined as 20.56 % and 22.08 %, respectively. This system can produce 71.17 MW of power generation with a profit of 80 million US$. The system’s energy and exergy efficiency for the consumer basis were determined as 19.65 % and 21.09 %, respectively. This system can produce 88.03 MW of power generation with a profit of 92 million US$.

Low-carbon agricultural technologies improve forage and feed production in the Caatinga biome, Brazil: Characteristics, comparison, effects of climate change, resilience, local development, and food security

Adjustments in Brazilian livestock are necessary to minimize greenhouse gas (GHG) emissions, since the largest source of methane comes from ruminants’ enteric fermentation, and of carbon from deforestation. Low-carbon agriculture technologies (LCAT) contribute to mitigating these emissions and this study evaluates the role of these technologies on ruminant forage production in Caatinga. A Strength, Weakness, Opportunity, and Threats analysis was used to elucidate the main features, followed by an Analytic Hierarchical Process, ranking the LCAT, and a risk analysis. Integrated Crop-Livestock-Forest System (ICLFS) is the most recommended technology, followed by Sustainable Forest Management (SFM) and Recovery of Degraded Areas with Pastures (RDA-P). The results can aid in the choice of the LCAT to be implemented by the smallholder in Caatinga, demonstrating the need to strengthen rural technical assistance, so that there is a real benefit to the producer and the environment.

An analytical hierarchical process approach to assessing local food preferences among foreign tourists

PurposeThis study evaluates the relative preference for local foods among foreign tourists. It also assessed how the sociodemographic profiles of tourists influence their local food preferences.Design/methodology/approachThis research utilized a mixed-methods approach. The initial qualitative analysis phase involved semi-structured, in-depth interviews with stakeholders in Fiji’s local food sector, providing feedback on tourists’ preferred dishes. In the second phase, 204 foreign tourists were surveyed through the location intercept approach at various local restaurants, street food joints and eateries across Fiji. The preferences of these foreign tourists for the local food were subsequently analyzed utilizing the analytical hierarchical process (AHP) model and Chi-square statistics.FindingsThis research identified 25 local food dishes most preferred by foreign tourists. A pairwise comparison matrix revealed that “Kokoda” was most preferred, while “Tuna Ika Vakalolo” was the least preferred, and the normalized matrix presented the estimated overall priorities of the local foods based on taste and flavor. Among all the factors analyzed for their potential influence on the local food preferences of foreign tourists, “education attainment” and “marital status” were found to have no significant influence.Originality/valueThis study highlights the varied local dishes preferred by tourists, assessed through the AHP model, and provides the sociodemographic factors influencing these preferences. By identifying and presenting local Fijian dishes across regions and examining sociodemographics’ impact on food preference, this research provides invaluable implications for significantly benefiting the local food vending sector.

An Integrated Approach to Constraints Theory and Fuzzy Analytical Hierarchy Process (FAHP) in Construction Projects (Case Study)

The research endeavors to harness the benefits stemming from the integration of constraint theory into construction project management, with the primary goal of mitigating project completion delays. Additionally, it employs fuzzy analysis to determine the relative significance of fundamental constraints within projects by assigning them appropriate weights. The research problem primarily revolves around two key issues. Firstly, the persistent utilization of outdated methodologies and a heavy reliance on workforce experience without embracing modern computerized technologies. Secondly, the recurring problem of project delivery delays. Construction projects typically encompass five fundamental constraint types: cost restrictions, time constraints, administrative and legal limitations, technical and design constraints, and environmental constraints. To address these issues, a field study was conducted, focusing on the development of a housing complex in Qa'imaqamiya, Al-Mada'in district, Bismayah. The researchers propose a three-stage methodology to tackle these challenges. In the initial stage, the theory of accelerated activities is applied to all concurrent implementable tasks. Subsequently, the second stage introduces a hierarchical analysis process, known as FAHP, to quantify the importance of each constraint. Finally, in the third phase, fuzzy logic is employed to calculate the projected duration and associated costs for each activity, ensuring project execution and delivery within agreed-upon timeframes. After applying the proposed methodology, there is a reduction in completion time by up to (23%). Research Type: Research Paper

Application of analytical hierarchical process in assessing the suitability of land for growing grain crops

Application of analytical hierarchical process in assessing the suitability of land for growing grain crops

Developing a composite index of conservation value to determine the conservation status of protected areas: The case of the Krau Wildlife Reserve and Tasek Bera Ramsar Site, Peninsular Malaysia

In Peninsular Malaysia, the various forms and contexts of assessing the conservation status of a protected area has led to inconsistent results, causing misunderstanding and uncertainty among protected area managers. Furthermore, these assessments rely heavily on the conservation value inside the protected area, despite the fact that its value is also influenced by the external environment. In this regard, using a composite index of conservation value (CICV) provides the opportunity for a more practical assessment of conservation status. Therefore, the objective of this study was to develop a CICV to determine the conservation status of two protected areas in Peninsular Malaysia, i.e., the Krau Wildlife Reserve and Tasek Bera Ramsar Site. Land use/land cover maps inside and outside the protected areas, developed using Landsat images from 2014, were the basis for the conservation value assessment, which employed three landscape scale indicators, i.e., naturalness, fragmentation, and connectivity. Through an analytical hierarchical process, the indicators were combined to develop a CICV inside and outside each protected area. Acceptable robustness values obtained through sensitivity analysis enabled the calculation of the CICV scores. For each protected area, the internal and external sites were then merged to calculate a net CICV. The inside, outside, and net CICV scores were used to determine the area’s conservation status on a critical value scale with the markers ‘very critical’, ‘critical’, ‘moderate’, ‘good’, and ‘excellent’. Inside the Krau Wildlife Reserve, the CICV was 88.4 %, indicating an ‘excellent’ conservation status, while its outside status is ‘critical’ with a CICV of 35 %. The net CICV of this area was 64.29 %, yielding a ‘good’ net conservation status. The CICV inside and outside Tasek Bera Ramsar Site were 35 % and 21.34 % respectively, both of which represent a ‘critical’ conservation status. The net CICV was found to be 22.52 %, suggesting that the net conservation status is ‘critical’. The results show that the external landscape of protected areas is a threat that influences the areas’ net conservation status. Therefore, a comprehensive conservation status assessment requires a composite index that integrates conservation values from the outside to help protected area managers easily understand and interpret findings, and thus, effectively coordinate conservation planning.

Prediction of eco sustainability component using fuzzy Z numbers based ratio analysis and interval type 3 fuzzy logic system

Amid rapid global urbanization, understanding eco-sustainability challenges in megacities like Delhi is crucial both locally and globally. This study introduces a novel multi-criteria group decision-making approach, the Z-Fuzzy Step-Wise Weight Assessment Ratio Analysis (SWARA), to address these complex challenges. This method prioritizes key eco-sustainability components like air quality index (AQI), water quality index (WQI), Temperature, and Precipitation, based on their impact, aiming to enhance resource allocation and environmental quality. Criteria weights are determined using fuzzy analytical hierarchical processing with Z-numbers, which manage decision-makers' uncertainty through a reliability function, illustrating their confidence levels and supporting the adaptability and effectiveness of eco-sustainability measures. A case study is conducted on seven sub-cities in Delhi examining their unique environmental impacts and urban sustainability challenges. Moreover, the most effective component of eco-sustainability say AQI is also dependent on some factors like PM10, PM2.5, SO2, O3, NO2, and CO. Considering these factors as inputs, an interval type-3 fuzzy logic system (IT3FLS) has been constructed to predict AQI, supporting timely interventions and improvements in eco-sustainability management. The IT3FLS model demonstrated exceptional precision across all Delhi sub-cities, with low root means square error (<0.05), and high R2 values (>0.94), affirming its effectiveness. To validate the Z-Fuzzy SWARA rankings, we compared them with existing Z-Fuzzy methods, consistently ranking AQI first. The IT3FLS's AQI predictions were also compared with those from fuzzy logic and advanced machine learning algorithms, demonstrating superior performance. Finally, the study underscores the managerial implications, emphasizing their role in guiding decision-making and strategy implementation.

Retraction Note: Assessment of green economic efficiency in China using analytical hierarchical process (AHP)

Retraction Note: Assessment of green economic efficiency in China using analytical hierarchical process (AHP)