Multi-criteria Decision Analysis Approach Research Articles

Complex sensitivity analysis in Multi-Criteria Decision Analysis: An application to the selection of an electric car

Sustainability research and practice decisions are the fields that address one of the most important challenges of today’s world, which is frugal resource management. More people are adopting ethical, less polluting lifestyles and, thus, are seeking out companies that share their values. Multi-Criteria Decision Analysis (MCDA) is a suitable tool for comprehensively analyzing the available decision variants. However, the currently used frameworks are frequently based on crisp values, so the resulting ranking and ratings can only be regarded as initial recommendations. On the other hand, tools for solutions based on uncertain data are limited in practical usability, scalability, and flexibility for solutions based on uncertain data. In this paper, we propose a new comprehensive framework for sensitivity analysis based on interval arithmetic and the MCDA approach. The primary assessment gives initial recommendations, but only after thorough analysis can the ranking of alternatives be reliably treated. It means that thresholds for each criterion should be obtained, which informs us about the robustness of obtained alternative’s order. It is very important information that allows accepting or rejecting the ranking received. The framework’s performance is verified in sustainable development, where we evaluate the group of electric cars. The TOPSIS method for crisp and interval numbers is involved as the selected MCDA method. The results show that the proposed framework can be effectively used as a recommendation system for multi-criteria problems where input data can fluctuate.

Assessing the sustainability of the city-port transformations: Multi-Criteria Decision Analysis (MCDA) for alternatives portfolio selection

In recent years, the EU has sought to define sustainable transition pathways towards more equitable, prosperous, and inclusive urban and territorial models, capable of responding to the rapid degradation of ecosystems, and improving quality of life of citizens. In this context, ports have been recognised as key strategic hubs not only for economic and logistical competitiveness, but also to generate employment and investment opportunities, and to address the challenges of the climate change. The research presents a multi-scale, multi-dimensional and multi- group methodological framework to support decision-making processes related to the development of sustainable transformations of port cities, capturing the complexity of interactions and conflicts. Integrating Multi-Criteria Decision Analysis (MCDA) approaches and Problem Structuring Methods (PSM), the proposed methodology aims to address the following gaps identified in the literature: (i) a scattered application of multi-group methods; (ii) the lack of social instances within the decision problem; (iii) a weak sustainability perspective; (iv) the use of one-dimensional scale assessment in sectoral studies. The case study of the city-port of Gela in Sicily (Italy) provided an opportunity to test the proposed methodology and to integrate multi-dimensional sustainability issues into feasibility studies, promoting a more balanced relationship between city and port. The interdependencies between environment, society and economy allowed MCDA to be identified as a suitable approach to address complex decision-making and support the sustainability assessment of port areas transformation. Two multi-criteria and multi-group evaluation methods guided the decision-making process to select a portfolio of preferred alternatives by assessing technical, environmental, and economic impacts and analysing stakeholder conflicts and coalitions. The process was carried out as follows: on the one hand, a multidimensional impact matrix integrating Key Performance Indicators (KPIs) divided into technical, financial-economic, and environmental categories through the application of the multi-criteria method EVAMIX; on the other hand, a social assessment with a dendrogram of coalitions derived from the application of the multi-group method NAIADE by modelling stakeholders’ preferences regarding a portfolio of alternatives related to the decision problem.

Site selection for landfills using GIS-based multi-criteria decision analysis – a case study of National Capital Territory of Delhi, India

Landfill site selection in an urban area like National Capital Territory (NCT) of Delhi is a challenging task due to shortage of suitable land and other environmental, economic and social parameters. This study focusses on the utilisation of geographic information system, open-source libraries and remote sensing for identification of potential landfill sites in Delhi NCT. Multi-criteria decision analysis (MCDA) and other GIS-based approaches are used for analysing various natural parameters derived using remote sensing satellite data products. Resourcesat LISS-III and Sentinel-2 multispectral satellite data is used for deriving the required parametric layers. Zones in the vicinity of monuments, transport, canals, drainages, lineaments are avoided altogether. Results reveal overall, most suitable places for landfill site in study area is around 4.05 sq. km (0.27%), moderately suitable places are 14.68 sq. km (0.98%), least suitable places are 25.46 sq. km (1.71%) and not suitable places is 1,419.11 sq. km (95.62%).

Insights of Bioeconomy: Biopolymer Evaluation Based on Sustainability Criteria

Abstract Sustainable development in the agriculture sector can be boosted by integrating a sustainable bioeconomy and transforming renewable resources into added-value products. There are various methods to determine, measure, and compare the extent of sustainability. We promote the bioeconomy concept by utilizing agricultural waste in biopolymers considering the sustainable development in the agriculture sector. This research aims to evaluate biopolymer alternatives based on sustainability criteria and indicators using the integrated multi-criteria decision analysis approach under the sustainability umbrella. We evaluated the PLA, PHA/PHB, starch, protein, and cellulose-based biopolymers. As a result, the cellulose-based biopolymer shows the best performance. The research findings provide valuable information to establish a sustainable pathway for biopolymer production for industries.

Assessment of flood susceptibility in coastal peri-urban areas: an alternative MCDA approach for ungauged catchments

ABSTRACT The sustainable development of coastal peri-urban areas is associated with the awareness of the local vulnerability to natural disasters, such as flood hazards. In ungauged basins, statistical and modelling approaches combined with geographic information systems have been widely used for the evaluation of different scenarios. In the current study, a multicriteria decision analysis (MCDA) simulated the response of the floodplains to the variations of the most dominant criteria, which affected the flood susceptibility of the area. An index of flood susceptibility is proposed to compare the simulated outcomes of the different scenarios. We provide a thorough discussion about improving the accuracy of the MCDA method through calibration and validation procedures, in association with the HEC-RAS 2D model. Observed and simulated inundation depths were compared for the validation process. The derived maps effectively revealed the flood susceptibility of the area upon the criteria variation, particularly the elevation and the rainfall.

A q-rung orthopair fuzzy combined compromise solution approach for selecting sustainable third-party reverse logistics provider

PurposeReverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.Design/methodology/approachWith the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.FindingsTo exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.Originality/valueThus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

AN ANALYSIS FOR OUTSOURCING BASED RISKS AND PROBLEMS IN LOGISTICS ENTERPRISES

Nowadays businesses transform into the faster, less costly, more flexible, and qualified structure because of developing world economy and fierce competition environment with each passing day. Outsourcing as one of the most essential concepts related to strategic management is considered to meet all the aforementioned conditions. In fact, logistics enterprises composing the main theme of this study tend to the outsourcing like other businesses and prefer it to increase the competitive power and specialized in main area of activity. Despite outsourcing in logistics enterprises provide numerous opportunity and advantage, some risks and problems emerge in case of not achieving the desired accordance and coordination. In this context risks and problems caused by the outsourcing for enterprises operated in international logistics activities in Giresun province are determined and ranked via the q-rung orthopair fuzzy subjective weighting as one of the multi-criteria decision analysis approaches. According to the results, essential risks and problems caused by the outsourcing for logistics enterprises were found as “Loss of control over the outsourcing firm”, “Inaccurate sales pitches”, “Layoffs” and “Unfulfilled contract provisions” respectively.

Fusion of Multispectral Remote-Sensing Data through GIS-Based Overlay Method for Revealing Potential Areas of Hydrothermal Mineral Resources

Revealing prospective locations of hydrothermal alteration zones (HAZs) is an important technique for mineral prospecting. In this study, we used multiple criteria inferred from Landsat-8 OLI, Sentinel-2, and ASTER data using a GIS-based weighted overlay multi-criteria decision analysis approach to build a model for the delineating of hydrothermal mineral deposits in the Khnaiguiyah district, Saudi Arabia. The utilized algorithms revealed argillic, phyllic, and propylitic alteration characteristics. The HAZs map resulted in the identification of six zones based on their mineralization potential, providing a basis for potential hydrothermal mineral deposit assessment exploration, which was created by the fusion of mineral bands indicators designated very low, low, moderate, good, very good, and excellent and covers 31.36, 28.22, 20.49, 10.99, 6.35, and 2.59%. Based on their potential for hydrothermal mineral potentiality, the discovered zones match gossans related to sulfide mineral alteration zones, as demonstrated by previous studies.

Use of Data Envelopment Analysis (DEA) to assess management alternatives in the presence of multiple objectives

Marine ecosystem-based management often aims to satisfy a wide range of economic, social and environmental objectives. These are often measured in non-commensurable units, making identification of a preferred option difficult when outcomes and measures vary considerably. In this paper, we examine the potential for data envelopment analysis (DEA) as an alternative approach to traditional multi-criteria decision analysis (MCDA). We derive multi-output composite indicator scores for three case study examples. The management alternatives are assessed both with and without exogenously determined objective preference weights. The frontier-based analysis does not require weights to be assigned to each objective, instead generating flexible “benefit of the doubt” weights that allow for different objectives to be influencing each management option. Applying stakeholder objective importance weights allows the assessment of the objective alignment of the different stakeholder groups, providing additional information on management option performance. The DEA results were found to be consistent with those from an earlier study that used a more traditional MCDA approach. DEA has the additional advantage of not requiring measures to be commensurable and can also directly incorporate undesirable outcomes into the analysis.

Estimation of the effectiveness of multi-criteria decision analysis and machine learning approaches for agricultural land capability in Gangarampur Subdivision, Eastern India

Land suitability analysis (LSA) is an evaluation method that measures the degree to which land is suitable for certain land use. The primary aims of this study are to identify potentially viable agricultural land in the Gangarampur subdivision (West Bengal) using Multiple Criteria Decision Making (MCDM) and machine learning procedures and to evaluate the efficacy of the employed methodologies. The Analytic Hierarchy Process (AHP) model was used to assign relative weights to the fifteen various criteria in this suitability analysis, and then the Fuzzy Complex Proportional Assessment (FCOPRAS) model was applied using the AHP's normalised pairwise comparison matrix, whereas the Waikato Environment for Knowledge Analysis (Weka) Software was used to apply machine learning algorithms to the field data. The Random Forest (RF) model, on the other hand, is a better fit for the locational study of soil potential. According to the RF findings, areas of 14.67 per cent (15368.46 ha) are excellent (ZONE V) for growing crops, approximately 22.30 per cent (23367.9 ha) are highly suitable (ZONE IV), and 23.63 per cent (24762.12 ha) are moderately suitable (ZONE III) for cultivation, respectively. The numbers for FCOPRAS are roughly 15.39% (16130.52 ha), 22.54% (23620.65 ha), and 19.79% (20733.26 ha). The Receiver Operating Characteristic (ROC) curve and accuracy measurements of the results indicate the high accuracy of the applied models, with Random Forest and FCOPRAS being the most popular and effective techniques. This study will make an important contribution to evaluations of soil fertility and site suitability. This will help local government officials, academics, and farmers scientifically use the land.

A GIS-based multi-criteria decision analysis approach using AHP for rural settlement site selection and eco-village design in Erzincan, Turkey

In recent years, natural resource depletion, rapid population growth, and increasing urbanization have all reached new heights. All of these ecological problems that exceed the planet's absorbing capacity, have begun to imperil both human life and nature itself. Rural settlement plans aim to optimize the use of natural resources. Agricultural lands are used for non-agricultural purposes as a result of proper placement planning of rural settlements. The suitability of land for a specific purpose is determined via suitability analysis. Therefore, it is extremely important to use technological innovations in the selection of rural settlement areas in addition to considering the technical, economic, and social factors in determining the most suitable locations. With the advancement of computer technology, Geographical Information System (GIS) has become an important tool for more effective use of rural areas. In this study, the most suitable rural settlement area was determined by using GIS in Erzincan Province. Technical, social, cultural, and economic criteria were developed for the selection of the location. Alternative locations were analyzed using the GIS, Multi-Criteria Decision Analysis and the Analytical Hierarchy Process method based on the criteria and site data. The most suitable areas for rural settlements were chosen as the Merkez, Tercan, Kemaliye, and Kemah districts in Erzincan Province. Çağlayan town in the Merkez district has been determined as the most suitable region for an eco-village and a cost calculation and 3D eco-village design were carried out in Çağlayan.

Identification of Suitable Sites Using GIS for Rainwater Harvesting Structures to Meet Irrigation Demand

This study uses a multi-criteria decision analysis approach based on geographic information system (GIS) to identify suitable sites for rainwater harvesting (RWH) structures (such as farm dam, check dam and contour bund) to meet irrigation demand in Greater Western Sydney region, New South Wales, Australia. Data on satellite image, soil, climate, and digital elevation model (DEM) were stored in GIS layers and merged to create a ranking system, which were then used to identify suitable RWH (rainwater harvesting) areas. The resulting thematic layers (such as rainfall, land use/land cover, soil type, slope, runoff depth, drainage density, stream order and distance from road) were combined into one overlay to produce map of RWH suitability. The results showed that 9% of the study region is ‘very highly suitable’ and 25% is ‘highly suitable’. On the other hand, 36% of the area, distributed in the north-west, west and south-west of the study region, is ‘moderately suitable’. While 21% of the region, distributed in east and south-east part of the region, has ‘low suitability’ and 9% is found as ‘unsuitable area’. The findings of this research will contribute towards wider adoption of RWH in Greater Western Sydney region to meet irrigation demand. The developed methodology can be adapted to any other region/country.

An improved multi-criteria decision analysis approach for watershed soil erosion susceptibility assessment

Soil erosion within watersheds is a common phenomenon worldwide, and many scientific efforts have been made to address this problem. The Revised Universal Soil Loss Equation (RUSLE) model has been widely employed in soil erosion estimation. However, several studies have highlighted its limitations and the need to account for some key aspects of soil erosion which are not considered in the model. This study explores the potential of utilizing locally dominant soil erosion driving factors alongside the RUSLE model for soil erosion susceptibility assessment within the OIO watershed. Landsat 8 OLI image for the year 2020, DEM, soil data, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets coupled with field observed datasets were employed to derive these factors. They include soil loss, sediment yield, sediment transport index, and runoff. Numerical rankings that represent the level of contribution of each factor and their attributes to soil erosion within the watershed were generated using the Fuzzy Analytical Hierarchy Process (FAHP). Each factor was reclassified according to these rankings and overlaid using the GIS-based weighted overlay technique to model soil erosion within the OIO watershed. Finally, we employed a statistical combination of the modelled soil erosion map and Hydrological Response Unit (HRU) to assess erosion susceptibility within the watershed. Initial results from the study highlighted the variabilities in annual soil loss (min: < 6.0 t ha−1 yr−1, max: ≥ 58.0 t ha−1 yr−1, mean: 13.55 t ha−1 yr−1) and identified areas with high predispositions to soil loss within the OIO watershed. The annual sediment yield of the entire OIO watershed ranged between ≤ 14.04 to 715.10 t ha−1yr−1 with an annual average of 14.88 t ha−1yr−1. In addition, the sediment transport index and runoff volume for the OIO watershed range between 0.00–69.07 and 0.00–70.00 mm, respectively. Five erosion susceptibility levels were delineated: very slight, slight, moderate, severe, and severe. They occupied 65.00%, 24.43%, 7.69%, 2.63%, and 0.23% of the watershed, respectively. Accuracy assessment conducted using the Receiver Operating Curve (ROC) showed that the soil erosion susceptibility map has an AUC value of 0.86, indicating acceptable results. Our methodological approach improves the RUSLE model, especially regarding preliminary soil susceptibility assessment for watershed development under typical data-scarce conditions.

Stakeholder perception of pharmaceutical value: A multicriteria decision analysis pilot case study for value assessment in the United States.

BACKGROUND: Recent attention to value frameworks has highlighted limitations of current conventional value and health technology assessment (V/HTA) methods (eg, cost-effectiveness). Multicriteria decision analysis (MCDA) has potential as a supplemental tool to incorporate additional value criteria into conventional value assessment. OBJECTIVE: To conduct a pilot study to illustrate the impact of an MCDA approach on the value perceptions of hypothetical treatment profiles from a multistakeholder panel. METHODS: Participants voted on value perceptions of 2 hypothetical treatments with similar cost-effectiveness evidence: Treatment A for aggressive B-cell non-Hodgkin lymphoma in adults and treatment B for episodic migraine in adults. Participants voted treatments A and B as low, intermediate, or high value before and after a weighting exercise on prespecified, additional value criteria. Weights from participants were used to calculate treatment-specific MCDA scores from 0 (least favorable) to 100 (most favorable) and were presented to participants for a second value-perception vote. Analyses compared changes in value perceptions within treatments A and B post-MCDA exercise. RESULTS: Before considering MCDA scores for treatment A, 0% of participants considered it to be low, 52% intermediate, and 48% high value. After considering MCDA scores for treatment A, 4% considered it low, 29% intermediate, and 67% high value. Both before and after considering MCDA scores for treatment B, 13%, considered it low, 57% intermediate, and 30% high value. Mean MCDA scores for treatments A and B were 67 and 63, respectively. Of all stakeholders, 41% altered their perception of value for treatment A (9% negatively and 32% positively) and, separately, 45% for treatment B (23% both negatively and positively) after considering MCDA scores. CONCLUSIONS: With nearly half of participants altering their perception of value after consideration of additional value criteria, findings support the need for a more inclusive and flexible value assessment process. DISCLOSURES: This study was funded by The National Pharmaceutical Council. Dr Perfetto was employed by the National Health Council (NHC) at the time this work was completed, and all honoraria and consulting and travel fees were paid to the NHC. The NHC is a not-for-profit, membership organization. It is supported through membership dues and sponsorship funds. The complete list of members and sponsors is located on the NHC's website at www.nationalhealthcouncil.org. She is also an advisor for the Brain Injury Association of America, Dan Lewis Foundation, and Canter for Medical Technology Policy.

An Interactive WebGIS Integrating Environmental Susceptibility Mapping in a Self-Burning Waste Pile Using a Multi-Criteria Decision Analysis Approach

Mining activities promote resulting wastes, so coal mines are prone to release contaminants to the environment, namely to the soil and water. Therefore, the analysis of this type of risk is crucial in waste pile management. The São Pedro da Cova (Porto, Portugal) coal waste pile has been studied in recent years, with several data acquired from 2019–2021 under a research project using distinct methodologies. These results are now combined in a multi-approach method to estimate the environmental impacts of the waste pile and identify the contamination. With the integration of all the data in a Geographical Information System (GIS) environment, and to fulfill a scientific gap, this study aims: (i) to create a susceptibility map of contamination in the areas surrounding the self-burning coal waste pile in São Pedro da Cova, using Analytical Hierarchy Process (AHP) and Fuzzy AHP approaches; and (ii) to develop a webGIS application incorporating all the information acquired that can be useful for the residents of São Pedro da Cova and also to the decision-making public entities and researchers. The results obtained show that the contamination susceptibility is higher surrounding the abandoned mine, particularly along the waste piles and the corresponding runoff areas, which can be especially sensitive.

A Multi Criteria Decision Analysis Approach for Regional Climate Model Selection and Future Climate Assessment in the Mono River Basin, Benin and Togo

Regional climate models (RCMs) are key in the current context of global warming, and they are increasingly used to support decision-making and to identify adaptation measures in response to climate change. However, considering the wide range of available RCMs, it is important to identify the most suitable ones prior to climate impact studies, especially at small scales like catchments. In this study, a multicriteria decision analysis approach, namely the technique for order preferences by similarity to an ideal solution (TOPSIS) was applied to select the best performing RCMs in the Mono River Basin of Benin and Togo (West Africa). The TOPSIS method was used to systematically rank 15 RCMs accessed from the coordinated regional downscaling experiment (CORDEX) database. Six RCMs were finally selected and averaged into an ensemble to assess the future climate in the Mono River Basin until 2070 compared to the period 1966–2015. Two climate change scenarios, RCP 4.5 and RCP 8.5, were considered. The results show that under both climate change scenarios, the annual temperature has an increasing trend during the period 1966–2070, whereas annual rainfall for the next 50 years presents high variability and no statistically significant trend. Furthermore, seasonal cycles of rainfall are expected to change in the different parts of the catchment with delayed onset of rainfall, longer dry seasons, and rainfall intensification. In response to the projected changes, impact studies and risk assessments need to be carried out to evaluate potential implications for human security in the Mono River Basin and to provide adequate adaptation measures.

Land Evaluation of Recreation and Ecotourism Services Using Multi-Criteria Evaluation Process

Land suitability of Recreation and Ecotourism (RE) is the process of predicting the potential use of land on the basis of its attributes. Decisions on land use have always been part of the evolution of human society. The integration of this GIS using the multicriteria decision analysis approach provides an environment to the decision-makers in citing areas using land suitability analysis procedures. The present study aims at evaluating the land use suitability for Recreation and Ecotourism development in the rural–urban in Aswan city-Egypt. This is achieved by using the GIS-based Multi Criteria Decision Analysis (GIS-MCDA) on twelve various economic, environmental and urban criteria This study was carried out within the framework of an Analytic Hierarchy Process (AHP) as a multi-criteria evaluation approach by integrating it with the Geographic Information System (GIS). Hence, based on the analysis and findings made in this research, finding suitable locations using the land suitability model for future recreation and ecotourism development is highly helpful. Results can be useful in the planning of public facilities and future land use planning in Aswan city.

Assessing decarbonisation pathways in the food and beverage sector: A multi-criteria decision analysis approach

Decarbonisation pathways for the food and beverage sector are focused at a national, regional, or sectoral level. There is a lack of literature which assesses decarbonisation pathways at a facility level and which compares pathways using Multi-Criteria Decision Analysis (MCDA). This work assesses the economic and environmental performance of 21 decarbonisation pathways which could be implemented at a facility in the food and beverage sector using 5 MCDA methods. Four sets of criteria weights (equal criteria weights, economic focus, environmental focus, and subjective weights of facility management) are applied to compare the results obtained.The best pathway (Pathway no. 15: Boiler–combined heat and power, organic Rankine cycle (CHP ORC) – mechanical vapour recompression (MVR)) for equal criteria weights or an economic focus achieves the best net present value, reduces emissions by 43%, has the shortest payback period, and the lowest levelised cost of abatement. Pathway no. 14 (38 kV – MVR – biogas) (recommended for an environmental focus) enables a 100% reduction in GHG emissions but achieves the third worst net present value. Pathway no. 20 (Boiler – CHP ORC – MVR – Biogas) is recommended when using subjective weights and has the best levelised cost of abatement for any pathway that reduces emissions by 100%. However, pathway no. 20 has a negative net present value, a payback period greater than 20 years, and a high CAPEX spend per mass of tCO2eq saved. To achieve GHG emissions savings greater than 67%, biogas from the anaerobic digestion of distillery feed products is required.

Sustainable cities and communities assessment using the DARIA-TOPSIS method

Effective evaluation of cities’ and communities’ sustainability is important for sustainable development. From a methodological point of view, Multi-Criteria Decision Analysis (MCDA) methods proved their usability in the sustainability evaluation domain. Nevertheless, the process of building a model in the classical MCDA paradigm is based on a single set of input data. Therefore, it may lead to oversimplification, especially in the domain of sustainability. Moreover, in addition to the current assessment, it is also important to know the dynamics of sustainability change over time. Therefore, this paper proposes an innovative sustainability assessment method that integrates the MCDA approach with the variability of the alternatives’ performance measurement called Data vARIability Assessment Technique for Order of Preference by Similarity to Ideal Solution (the DARIA-TOPSIS method). This method was used to assess sustainable cities and communities in 26 European countries. Time-based analyses conducted using the DARIA-TOPSIS method for aggregated data (countries), individual sustainability dimensions, and alternatives proved our new approach’s usefulness, suitability, and effectiveness in sustainable cities and society domain. • A new MCDA method named the DARIA-TOPSIS. • A DARIA-TOPSIS based framework for sustainable cities and communities assessment. • The practical problem of sustainable cities and communities assessment.

Spatial Characterization of Groundwater Potential in the Complex Basement Zone (Dabakala Department, North-Central Côte d’Ivoire): A Multi-Criteria Decision Analysis (MCD) Approach

The present hydrogeological study was carried out in the complex basement zone (Dabakala department, North-Central Côte d'Ivoire). Indeed, in this area, the population faces a real problem with the drinking water supply during the dry season. The aim of this study is to carry out a spatial characterization of groundwater potentialities in order to establish productive boreholes in the division. Ten decision criteria were developed and then aggregated. The methodology consisted in building a database based on these criteria, using remote sensing and GIS techniques. These criteria applied multi-criteria decision analysis (MCDA) using the Hierarchical Analytical Process (HAP) for their weighting. The resulting groundwater potential map was validated using the sensitivity trend curve technique. Ultimately, the results indicate that approximately 35% of the division’s area has strong to very strong groundwater potential.