A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

Multi-criteria decision analysis for monitoring and evaluating soil erosion risk in forest fire-affected areas

Wildfires lead to socio-economic and environmental impacts. These impacts include hydrological instability, which can cause severe damage, especially where infrastructures are present. Post-rehabilitation measures can be useful in reducing or preventing erosion or hydrogeological risks. Decision-makers are called on to prioritize post-fire intervention areas and allocate public funds for this purpose. This work focuses on the assessment of erosion and hydrological risk potential in forested slope areas affected by wildfire using a Multi-Criteria Decision Analysis (MCDA) approach integrated with a GIS environment on a regional scale. Expert perception was considered using the pairwise comparison method as part of the Analytical Hierarchy Process (AHP). This allows expert stakeholders to rank relevant criteria, providing a quantitative metric (weight) for qualitative data. Two MCDA methods are used and compared: Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). Fire frequency, slope (gradient and length), and proximity to infrastructures were found to be the most important factors by the stakeholders. The WLC method provides evidence classified into high and moderate suitability class areas characterized by high values for fire frequency or slope gradient. Conversely, the OWA method, ranging from low to high risks, makes it possible to adapt the method and obtain a range of suitability maps. Novelties of the MCDA-GIS combined methodology adopted in this work are its application on a regional scale and the combination of vulnerability and driving-force factors (namely presence of grey infrastructures, fire frequency). The MCDA-GIS methodology can be suitable for public administrations in that it allows for mapping a regional area more quickly and thus facilitates sector planning.

Machine learning and analytic hierarchy process integration for selecting a sustainable tractor

Selecting the appropriate tractor for small-scale farms is a complex process due to the multitude of technical, environmental, and economic criteria that must be evaluated. This study addresses this challenge by integrating the Analytic Hierarchy Process (AHP) with machine learning (ML) to reduce the number of criteria and simplify the decision-making process. The research aims to determine the most relevant criteria aligned with sustainable development goals for selecting the right tractor, focusing on small farms in the Egyptian Delta. Four tractors, with horsepower ranging from 55 to 95, were evaluated based on inputs from forty-two governmental service providers in the study area. Initially, nine criteria were identified, encompassing key technical, environmental, and economic factors. These criteria were reduced to three-price, power, and maintenance costs by weights 0.142, 0.334, and 0.525, respectively-using Hierarchical Agglomerative Clustering with Euclidean distance. This reduction streamlined the selection process, making it more practical for farmers. Results show that the second tractor (T2), with a priority score of 0.326 and a normalized value of 33.4%, emerged as the optimal choice for small-scale farmers, outperforming the first tractor (T1) (28.7%) and third tractor (T3) (21%). Integrating AHP and ML simplifies tractor selection, ensuring sustainability, cost-efficiency, and operational effectiveness.

Socio-economic or environmental benefits from pondscapes? Deriving stakeholder preferences using analytic hierarchy process and compositional data analysis

Ponds occupy a large share of standing water worldwide and play an important role in providing various ecosystem services. There are concerted efforts of the European Union either to create new ponds, or to restore and preserve existing ponds as nature-based solutions to provide benefits to ecosystem and human well-being. As part of the EU PONDERFUL project, selected pondscapes (i.e. landscapes of ponds) in eight different countries - hereafter "demo-sites", are studied to comprehensively understand their characteristics and their efficiency to provide ecosystem services. In addition, the needs and knowledge of stakeholders who own, work, research, or benefit from the pondscapes are also important, because of their capabilities to create, manage and develop the pondscapes. Therefore, we established connection with stakeholders to study their preferences and visions on the pondscapes. Using the analytic hierarchy process, this study shows that in general stakeholders in the European and Turkish demo-sites prefer environmental benefits to economic benefits, while stakeholders in the Uruguayan demo-sites rank the economic benefits higher. More specifically, in the European and Turkish demo-sites, the biodiversity benefits, i.e. life-cycle maintenance, habitat and gene pool protection, receive the highest ranking among all groups. On the other hand, stakeholders at the Uruguayan demo-sites rank provisioning benefits as the most important, because many ponds in Uruguayan demo-sites are being used for agricultural purposes. Understanding those preferences helps policy makers to address the needs of stakeholders more correctly, when considering any action or policy for the pondscapes.

Analysis of wastewater reuse options using a multicriteria decision tool for Phuket, Thailand

The act of balancing between water demand and water supply in Phuket Island is facing challenges, suggesting water reuse options in various activities on the island should be properly promoted considering the potential benefits in a variety of dimensions. This research presented options to reuse effluent water from wastewater treatment plants for Phuket Municipality in 3 main activity groups, namely, domestic reuse, agricultural reuse, and raw water for water treatment plants (WTP). Water demand, additional water treatment trains, and the length of the major water distribution pipeline for each water reuse option were designed, and its cost and expenses were calculated. Multi-criteria decision analysis (MCDA) was used by 1000Minds internet-based software to prioritize the suitability of each water reuse option based on a four-dimensional scorecard, including economic, social, health, and environmental aspects. The decision algorithm for the trade-off scenario based on the government's budget allocation was proposed to obtain weighing without subjective expert opinions. The results revealed that recycling effluent water as raw water for the existing WTP was the first priority, followed by agriculture reuse for planting coconut, Phuket's economic crops, and domestic reuse. There was a significant difference in the total scores of economic and health indicators between the first- and second-priority options because of the difference in the additional treatment system in which the first-priority option applied the microfiltration and reverse osmosis system, which could effectively eliminate viruses and chemical micropollutants. In addition, the first priority option required a much smaller piping system than other water reuse options because it relied on the existing plumbing system of WTP, lowering the investment cost, which was a very important indicator for decision-making.

Digital tools for brownfield redevelopment: Stakeholder perspectives and opportunities

Brownfield redevelopment is a complex process often involving a wide range of stakeholders holding differing priorities and opinions. The use of digital systems and products for decision making, modelling, and supporting discussion has been recognised throughout literature and industry. The inclusion of stakeholder preferences is an important consideration in the design and development of impactful digital tools and decision support systems. In this study, we present findings from stakeholder consultation with professionals from the UK brownfield sector with the aim of informing the design of future digital tools and systems. Our research investigates two broad themes; digitalisation and the use of digital tools across the sector; and perceptions of key brownfield challenge areas where digital tools could help better inform decision-makers. The methodology employed for this study comprises the collection of data and information using a combination of interviews and an online questionnaire. The results from these methods were evaluated both qualitatively and quantitatively. Findings reveal a disparity in levels of digital capability between stakeholder groups including between technical stakeholder types, and that cross-discipline communication of important issues may be aided by the development of carefully designed digital tools. To this end, we present seven core principles to guide the design and implementation of future digital tools for the brownfield sector. These principles are that future digital tools should be: (1) Stakeholder driven, (2) Problem centred, (3) Visual, (4) Intuitive, (5) Interactive, (6) Interoperable, and (7) Geospatial data driven.

Proposal for an objective binary benchmarking framework that validates each other for comparing MCDM methods through data analytics

When it comes to choosing the best option among multiple alternatives with criteria of different importance, it makes sense to use multi criteria decision making (MCDM) methods with more than 200 variations. However, because the algorithms of MCDM methods are different, they do not always produce the same best option or the same hierarchical ranking. At this point, it is important how and according to which MCDM methods will be compared, and the lack of an objective evaluation framework still continues. The mathematical robustness of the computational procedures, which are the inputs of MCDM methods, is of course important. But their output dimensions, such as their capacity to generate well-established real-life relationships and rank reversal (RR) performance, must also be taken into account. In this study, we propose for the first time two criteria that confirm each other. For this purpose, the financial performance (FP) of 140 listed manufacturing companies was calculated using nine different MCDM methods integrated with step-wise weight assessment ratio analysis (SWARA). İn the next stage, the statistical relationship between the MCDM-based FP final results and the simultaneous stock returns of the same companies in the stock market was compared. Finally, for the first time, the RR performance of MCDM methods was revealed with a statistical procedure proposed in this study. According to the findings obtained entirely through data analytics, Faire Un Choix Adéquat (FUCA) and (which is a fairly new method) the compromise ranking of alternatives from distance to ideal solution (CRADIS) were determined as the most appropriate methods by the joint agreement of both criteria.

Intelligent analysis of the quality of education through teaching practices on virtual campuses

ICTs have been increasingly involved in teaching–learning processes due to the potential offered by the tools as well as to the set of demands derived from the political and health situations of the social environment. In this sense, the introduction of virtual campuses as complex systems that centralize the entire technological component that complements traditional teaching processes has meant a change of paradigm with repercussions at the teaching and pedagogical level. In this context, the purpose of this study aims to analyze students’ perception of the use of virtual campus and how to enhance the quality of the educational process using intelligent systems. For this purpose, 318 students that use virtual campus have been surveyed. The results show that there are three variables that predominantly influence the quality of teaching–learning processes using virtual campuses: frequent contact with teachers through the platform, the digital competence of the student, and the adaptation of training content to the students’ prior knowledge. This information can be useful, as it allows them to establish guidelines to guide the practices of their teaching teams in technological environments, guaranteeing the suitability of the teaching–learning process and improving the evaluation processes and the assessment of their own educational work.

Evaluation of Agricultural Machinery Using Multi-Criteria Analysis Methods

To achieve the highest possible agricultural production, it is necessary to procure the appropriate agricultural machinery. A tractor is the most useful machine in agriculture that performs various functions. Therefore, the selection of a tractor is one of the key decisions in the agriculture-production process. This study aims to evaluate heavy tractors for agricultural production in Bosnia and Herzegovina. Since this is a selection between different tractors, which are evaluated using several criteria, the methods of multi-criteria analysis (MCDA) were used in this study. Five different methods were used to determine the weight of the criteria, of which a modified standard-deviation method is a new method used in practice, while the tractor ranking was performed using the CRADIS (compromise ranking of alternatives from distance to ideal solution) method. The results showed that the best-ranked tractor is A4, while the most deviations from the ranking occur when the entropy method is used. The contribution of this study is in the systematization of the methods for the objective determination of the criteria weights and the development of new methods to facilitate decision-making in agriculture and other industries.

Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data

A major difficulty in comparing and even choosing MCDM methods is the uncertainty of information about the consistent and unique characteristics of the results produced. The objective information content of the final scores produced by MCDM methods and their relevance to real life can give us an important idea about them. In this study, first of all, seven MCDM methods with different methodologies were applied to evaluate companies’ financial performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. The first validation criterion is the relationship of a MCDM method to real-life rankings (share price). The second criterion is the standard deviation (SD) technique used to discover the objective information content of MCDM final scores. According to the results of this study, PROMETHEE and FUCA definitely outperform other methods in terms of both SD values and strength of correlation with reference real-life rankings. Also, FUCA is methodologically simpler than other methods. However, it produced nearly identical results as the sophisticated PROMETHEE method.

Incorporating local researchers' and decision makers' preferences for groundwater resources management in a spatial multi-voiced decision model

Water is a crucial and highly sensitive political issue. The overexploitation of groundwater resources and deterioration of water quality caused by pollution as well as the deficiencies of the existing infrastructure require immediate attention. The main goal of this paper is to carry out a multi-voiced multicriteria analysis that integrates the preferences of local researchers and decision makers in a process aimed at prioritizing watersheds that require the implementation of groundwater management instruments. Using the Criterium Decision Plus system, criteria and subcriteria were integrated into a spatial multi-voiced decision model for the prioritization of watersheds for groundwater resources management. The criteria chosen were Groundwater quality, Groundwater quantity, Land use with potential pollutant load, Equity and Intrinsic aquifer vulnerability. Criteria and subcriteria preferences analysis were derived from workshops with local researchers and decision makers. The spatial multi-voiced decision model identified five of the fourteen watersheds as high to very high priority and requiring groundwater resources management. Based on the local researchers' and decision makers' preferences and hierarchy scheme of the multi-voiced decision model the main criteria and subcriteria that contributed to the final model results were identified. Regarding the criteria, Groundwater quality, Equity and Groundwater quantity contributed extensively to the model. The subcriteria contributions to the groundwater resources management came mainly from High intrinsic aquifer vulnerability, Agrochemicals, Groundwater Storage and Groundwater for domestic supply. This proposed procedure showed that time and effort can be directed to using data and preferences to assist in planning and decision making for groundwater resources management.

Global greenhouse gas emissions from residential and commercial building materials and mitigation strategies to 2060

Building stock growth around the world drives extensive material consumption and environmental impacts. Future impacts will be dependent on the level and rate of socioeconomic development, along with material use and supply strategies. Here we evaluate material-related greenhouse gas (GHG) emissions for residential and commercial buildings along with their reduction potentials in 26 global regions by 2060. For a middle-of-the-road baseline scenario, building material-related emissions see an increase of 3.5 to 4.6 Gt CO2eq yr-1 between 2020-2060. Low- and lower-middle-income regions see rapid emission increase from 750 Mt (22% globally) in 2020 and 2.4 Gt (51%) in 2060, while higher-income regions shrink in both absolute and relative terms. Implementing several material efficiency strategies together in a High Efficiency (HE) scenario could almost half the baseline emissions. Yet, even in this scenario, the building material sector would require double its current proportional share of emissions to meet a 1.5 °C-compatible target.

Urban Pluvial Flood Management Part 1: Implementing an AHP-TOPSIS Multi-Criteria Decision Analysis Method for Stakeholder Integration in Urban Climate and Stormwater Adaptation

Cities are facing increasing pressures to enact adaptation measures due to climate change. While blue-green infrastructure has emerged as a focal adaptation technique for stormwater management, in order to craft adaptation policies cities must consider a multitude of emerging, complex, and competing stakeholder interests around multiple adaptation alternatives. However, accounting for these different interests, analyzing their diverse priorities, and maintaining a transparent decision-making process is not easily achieved within the existing policy frameworks. Here we define and present a combined multi-criteria decision analysis (MCDA) of the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) methods that easily integrates and quantifies stakeholder priorities while remaining accessible for non-experts engaged in the policy-making process. We demonstrate the method’s effectiveness through analyzing opinions about stormwater adaptation in New York City across several stakeholder groups. The method succeeds in integrating quantitative and qualitative judgements, indicating stakeholder preferential differences and allowing for more inclusive policy to be crafted. It can be extended beyond stormwater to many urban climate adaptation decisions facing multi-criteria considerations.

Incorporating stakeholders' preferences into a multi-criteria framework for planning large-scale Nature-Based Solutions

Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders' preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.

Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)

Evaluating the life cycle of buildings is a valuable tool for assessing sustainability and analyzing environmental consequences throughout the construction operations of buildings. In this study, in order to determine the importance of building life cycle evaluation indicators, a new combination method was used based on a quantitative-qualitative method (QQM) and a simplified best-worst method (SBWM). The SBWM method was used because it simplifies BWM calculations and does not require solving complex mathematical models. Reducing the time required to perform calculations and eliminating the need for complicated computer software are among the advantages of the proposed method. The QQM method has also been used due to its ability to evaluate quantitative and qualitative criteria simultaneously. The feasibility and applicability of the SBWM were examined using three numerical examples and a case study, and the results were evaluated. The results of the case study showed that the criteria of the estimated cost, comfort level, and basic floor area were, in order, the most important criteria among the others. The results of the numerical examples and the case study showed that the proposed method had a lower total deviation (TD) compared to the basic BWM. Sensitivity analysis results also confirmed that the proposed approach has a high degree of robustness for ranking and weighting criteria.

Indigenous Peoples, Exclusion and Precarious Work: Design of Strategies to Address Poverty in Indigenous and Peasant Populations in Ecuador through the SWOT-AHP Methodology

This research analysed the options that, following decent employment and the social economy, can allow the human development of poor, excluded and vulnerable indigenous populations in Ecuador. A set of strategies were developed which can be implemented by public authorities and by community organisations. They were designed from two types of expert consultations: the Delphi method and the analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT) combined with Analytic Hierarchy Process method (AHP) for hierarchizing the criteria collected and obtaining strategies. The proposed strategies are as follows: adopting appropriate legal frameworks, respecting peoples' rights, better distribution of public resources, implementing monitoring systems, developing solidarity markets and recognizing the participation of the poor as a subject of rights. This investigation revealed differences between the state, which identifies the poor with monetary indicators, and the indigenous peoples, who see it as the lack of community links, by conceiving the poor as a beneficiary of official assistance, despite the fact that a strong community and peasant organisation could be used. The value of an economy based on reciprocity and confidence was also recognized, identifying niches of production and consumption to create partnerships and ensure the participation of indigenous peoples in decision-making areas.

A Review of Methodological Considerations for Economic Evaluations of Gene Therapies and Their Application in Literature

OBJECTIVES

To identify methodological considerations discussed in literature addressing economic evaluations (EEs) of gene therapies (GTs). Additionally, we assessed if these considerations are applied in published GT EEs to increase understanding and explore impact.

METHODS

First a peer-reviewed literature review was performed to identify research addressing methodological considerations of GT EEs until August 2019. Identified considerations were grouped in themes using thematic content analysis. A second literature search was conducted in which we identified published evaluations. The EE quality of reporting was assessed using Consolidated Health Economic Evaluation Reporting Standards.

RESULTS

The first literature search yielded 13 articles discussing methodological considerations. The second search provided 12 EEs. Considerations identified were payment models, definition of perspectives, addressing uncertainty, data extrapolation, discount rates, novel value elements, and use of indirect and surrogate endpoints. All EEs scored satisfactory to good according to Consolidated Health Economic Evaluation Reporting Standards. Regarding methodological application, we found 1 methodological element (payment models) was applied in 2 base cases. Scenarios explored alternative perspectives, survival assumptions, and extrapolation methods in 10 EEs.

CONCLUSIONS

Although EE quality of reporting was considered good, their informativeness for health technology assessment and decision makers seemed limited owing to many uncertainties. We suggest accepted EE methods can broadly be applied to GTs, but few elements may need adjustment. Further research and multi-stakeholder consensus is needed to determine appropriateness and application of individual methodological considerations. For now, we recommend including scenario analyses to explore impact of methodological choices and (clinical) uncertainties. This study contributes to better understanding of perceived appropriate evaluation of GTs and informs best modeling practices.

COVID-19 Global Risk: Expectation vs. Reality

Background and Objective: COVID-19 has engulfed the entire world, with many countries struggling to contain the pandemic. In order to understand how each country is impacted by the virus compared with what would have been expected prior to the pandemic and the mortality risk on a global scale, a multi-factor weighted spatial analysis is presented. Method: A number of key developmental indicators across three main categories of demographics, economy, and health infrastructure were used, supplemented with a range of dynamic indicators associated with COVID-19 as independent variables. Using normalised COVID-19 mortality on 13 May 2020 as a dependent variable, a linear regression (N = 153 countries) was performed to assess the predictive power of the various indicators. Results: The results of the assessment show that when in combination, dynamic and static indicators have higher predictive power to explain risk variation in COVID-19 mortality compared with static indicators alone. Furthermore, as of 13 May 2020 most countries were at a similar or lower risk level than what would have been expected pre-COVID, with only 44/153 countries experiencing a more than 20% increase in mortality risk. The ratio of elderly emerges as a strong predictor but it would be worthwhile to consider it in light of the family makeup of individual countries. Conclusion: In conclusion, future avenues of data acquisition related to COVID-19 are suggested. The paper concludes by discussing the ability of various factors to explain COVID-19 mortality risk. The ratio of elderly in combination with the dynamic variables associated with COVID-19 emerge as more significant risk predictors in comparison to socio-economic and demographic indicators.

An Application of a Multi-Criteria Approach for the Development of a Process Reference Model for Supply Chain Operations

Nowadays, there are a plethora of business process modeling tools for use by researchers and practitioners. This paper presents the implementation of a methodological approach for the selection of such a tool in order to construct a process reference model. This reference model will support the development of a distribution system in the context of the supply chain in the phase of the system’s requirements definition, as well as in the final implementation of the system in real-life supply chain operations. The reference model is crucial for the easy and effective adoption of the system into companies’ processes. Therefore, the choice of the modeling tool can strongly support the design, development and implementation of the system. In this context, the application of a multi-criteria decision analysis (MCDA) was carried out in order to select the appropriate tool, utilizing a combination of the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) I method for the decision-making with the Analytic Hierarchy Process (AHP) method for the calculation of the weights of the evaluation criteria. The MCDA’s results showed that the Architecture of Integrated Information Systems (ARIS) Architect & Designer Tool was the one that better met the evaluation criteria. The sensitivity analysis that followed the MCDA reaffirmed its results by revealing that this tool had the highest consistency, despite the changes in the scenarios.

Developing successful environmental decision support systems: Challenges and best practices

Environmental decision support systems (EDSSs), or DSS applied in the environmental field, have been developed for over 40 years now. However, most of these tools fail to find use or fall out of use extremely quickly. In the aim of aiding in the conception and development of practical and successful decision support systems, i.e. systems that can lead to positive outcomes, this review looks over the existing literature, both EDSS-centric and from broader decision-related fields, to highlight some of the most important challenges influencing the success and usability of these systems. In all, 13 major challenges facing EDSS development were identified and over 60 recommendations and best practices were provided to address these challenges. Though this paper is mainly focused on environmental decision support systems, most of the highlighted information and conclusions are applicable to the development of decision support systems in any field.

Mass Appraisal Modeling of Real Estate in Urban Centers by Geographically and Temporally Weighted Regression: A Case Study of Beijing’s Core Area

The traditional linear regression model of mass appraisal is increasingly unable to satisfy the standard of mass appraisal with large data volumes, complex housing characteristics and high accuracy requirements. Therefore, it is essential to utilize the inherent spatial-temporal characteristics of properties to build a more effective and accurate model. In this research, we take Beijing’s core area, a typical urban center, as the study area of modeling for the first time. Thousands of real transaction data sets with a time span of 2014, 2016 and 2018 are conducted at the community level (community annual average price). Three different models, including multiple regression analysis (MRA) with ordinary least squares (OLS), geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), are adopted for comparative analysis. The result indicates that the GTWR model, with an adjusted R2 of 0.8192, performs better in the mass appraisal modeling of real estate. The comparison of different models provides a useful benchmark for policy makers regarding the mass appraisal process of urban centers. The finding also highlights the spatial characteristics of price-related parameters in high-density residential areas, providing an efficient evaluation approach for planning, land management, taxation, insurance, finance and other related fields.

Multi-Criteria Optimisation of an Experimental Complex of Single-Family Nearly Zero-Energy Buildings

The Directive 2010/31/EU on the energy performance of buildings has introduced the standard of “nearly zero-energy buildings” (NZEBs). European requirements place the obligation to reduce energy consumption on all European Union Member States, particularly in sectors with significant energy consumption indicators. Construction is one such sector, as it is responsible for around 40% of overall energy consumption. Apart from a building’s mass and its material and installation solutions, its energy consumption is also affected by its placement relative to other buildings. A proper urban layout can also lead to a reduction in project development and occupancy costs. The goal of this article is to present a method of optimising single-family house complexes that takes elements such as direct construction costs, construction site organisation, urban layout and occupancy costs into consideration in the context of sustainability. Its authors have analysed different proposals of the placement of 40 NZEBs relative to each other and have carried out a multi-criteria analysis of the complex, determining optimal solutions that are compliant with the precepts of sustainability. The results indicated that the layout composed of semi-detached houses scored the highest among the proposed layouts under the parameter weights set by the developer. This layout also scored the highest when parameter weights were uniformly distributed during a test simulation.

Identification of Priority Areas for Soil and Water Conservation Planning Based on Multi-Criteria Decision Analysis Using Choquet Integral

Soil erosion risk assessment is an essential foundation for the planning and implementation of soil and water conservation projects. The commonality among existing studies is that they considered different indicators (e.g., rainfall and slope) in order to determine the soil erosion risk; however, the majority of studies in China neglect one important indicator, namely the slope aspect. It is widely accepted that the vegetation and distribution of rainfall differs according to the different slope aspects (such as sunny slope and shady slope) and these attributes will accordingly influence the soil erosion. Thus, existing studies neglecting this indicator cannot reflect the soil erosion well. To address this problem, a flexible soil erosion risk assessment method that supports decision makers in identifying priority areas in soil and water conservation planning was developed in the present study. Firstly, in order to verify the impact of the slope aspect on soil erosion, field investigations were conducted, and its impact on the characteristics of the community in the study area was analyzed. Secondly, six assessment indicators were selected, including slope gradient, precipitation, NDVI, land use, soil texture and slope aspect. Next, a developed multi-criteria decision analysis (MCDA) method based on the Choquet integral was adopted to assess the soil erosion risk. The MCDA method, combining objective data with subjective assessment based on Choquet integral, could solve the weight problem encountered when using the quantitative method. The parameters required can be modified according to the soil erosion types, assessment scales, and data availability. The synergistic and inhibitory effects among the soil erosion parameters were also considered in the assessment. Finally, the soil erosion risk results in the Xinshui River watershed revealed that more attention should be paid to the slope of farmland and grassland during the planning and management of soil and water conservation projects. The methodology used in the current study can support decision makers in planning and implementing soil and water conservation measures in regions with different erosion types.

Sustainable Development of Ethno-Villages in Bosnia and Herzegovina—A Multi Criteria Assessment

This paper explores ethno-villages in Bosnia and Herzegovina as an important element of rural and cultural tourism. The attractiveness of natural and cultural heritage is very important for sustainable rural tourism development. In order to improve the process of decision making to enable the sustainable development of ethno-villages, a multi-criteria assessment model has been developed. The methodology is based on qualitative modeling using a multi-criteria analysis via the DEXi software. The model is based on hierarchical relations consisting of three main criteria that are the basis of sustainable tourism development: economic, social, and environmental criteria. The ultimate goal of the model in this study was to evaluate ethno-villages, namely six ethno-villages in Bosnia and Herzegovina. The results of the study show how ethno-villages contribute to sustainable development.

Real Estate Market Dynamics in the City of Naples: An Integration of a Multi-Criteria Decision Analysis and Geographical Information System

Urban development and regeneration projects produce multidimensional impacts on the city, on its environmental, economic, and social systems. An aspect that can be considerably affected by urban dynamics is linked to the real estate market. So, analysing real estate dynamics is useful to support decision-makers in the elaboration of urban regeneration plans and projects, and thus orient their choices. Focusing attention on the city of Naples (Italy), the purpose of this paper is to analyse in detail the real estate dynamics in this city through the integration of a Multi-Criteria Decision Analysis (MCDA) method and Geographical Information System (GIS). This integration allowed us to map and analyse the territory, linking a specific issue (the real estate dynamics) to the territory itself, and to analyse it according to specific criteria. This aims for a better understanding and interpretation of real estate dynamics, representing a useful tool for orienting and supporting urban planning strategies.

How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy

Decision making is a complex task that involves a multitude of perspectives, constraints, and variables. Multiple Criteria Decision Analysis (MCDA) is a process that has been used for several decades to support decision making. It includes a series of steps that systematically help Decision Maker(s) (DM(s)) and stakeholders in structuring a decision making problem, identifying their preferences, and building a decision recommendation consistent with those preferences. Over the last decades, many studies have demonstrated the conduct of the MCDA process and how to select an MCDA method. Until now, there has not been a review of these studies, nor a proposal of a unified and comprehensive high-level representation of the MCDA process characteristics (i.e., features), which is the goal of this paper. We introduce a review of the research that defines how to conduct the MCDA process, compares MCDA methods, and presents Decision Support Systems (DSSs) to recommend a relevant MCDA method or a subset of methods. We then synthesize this research into a taxonomy of characteristics of the MCDA process, grouped into three main phases, (i) problem formulation, (ii) construction of the decision recommendation, and (iii) qualitative features and technical support. Each of these phases includes a subset of the 10 characteristics that helps the analyst implementing the MCDA process, while also being aware of the implication of these choices at each step. By showing how decision making can be split into manageable and justifiable steps, we reduce the risk of overwhelming the analyst, as well as the DMs/stakeholders during the MCDA process. A questioning strategy is also proposed to demonstrate how to apply the taxonomy to map MCDA methods and select the most relevant one(s) using real case studies. Additionally, we show how the DSSs for MCDA method recommendation can be grouped into three main clusters. This proposal can enhance a traceable and categorizable development of such systems.

Integrating Sustainability into Major Infrastructure Projects: Four Perspectives on Sustainable Tunnel Development

Although sustainability is on the agenda of many countries and agencies, it is still a great challenge to properly integrate sustainability into major infrastructure projects, like tunnels. This is remarkable, as it is commonly accepted that the construction and operation of these civil infrastructures have a heavy impact on environmental, economic and social sustainability. In academia, the foregone conclusion seems to point to a lack of vision about sustainability with respect to tunnels. This article presents an empirical study that investigates sustainability ideas amongst tunnel practitioners in the Netherlands. The case was used as a practical environment to get access to tunnel practitioners, to explicitly define the meaning of a sustainable tunnel in its development phase. Perceptions of sustainable tunnels were extracted by means of a commonly accepted research methodology called Q-methodology. By applying this method, four perspectives were obtained: perspectives with a focus on energy, resilience, social or a transitional focus. Each perspective highlights distinct focal points on how to operationalize sustainability for tunnel projects. Each perspective is also accompanied by an anti-focus; how sustainability should not be approached, sometimes contrary to other perspectives. These insights help project practitioners in creating awareness for the existence of different perspectives, and subsequently help to focus project management efforts to implement sustainability in specific projects.

Prioritizing Sustainable City Indicators for Cambodia

This research is based on our previous research that developed consensus sustainable city indicators for Cambodia through three-round Delphi panel surveys. That research developed indicators in the first round based on UN sustainable development goal 11, ASEAN environmentally sustainable city, Korean case study, and domestic green and clean city indicators, and validated the developed indicators in the last two rounds. After consensus analysis, that research obtained 32 assessment indicators categorized by nine criteria. However, these indicators are not prioritized yet due to the limitation of the Delphi technique. Hence, this research aims to prioritize these indicators by applying the Analytic Hierarchy Process (AHP) technique and to confirm whether the levels of importance verified by Delphi can be used for prioritizing or ranking the indicators. This research surveyed potential respondents experienced and working in relevant fields both offline and online. Online surveys were processed through E-mail, Facebook, and LinkedIn. A total of 118 questionnaires were gathered from the surveys, and 16 were inconsistent (consistency ratio > 0.1). The results showed that the highest and lowest weights are 0.0557 and 0.086. The top ten indicators are slum population (0.0557), unemployment (0.0516), crime prevention (0.0470), water supply (0.0469), city’s migration (0.0462), low-income housing (0.0445), solid waste collection (0.0437), labor-force (0.0421), construction safety (0.0400), and traffic congestion (0.0398). The rank of all indicators based on their levels of importance is completely different from the rank of their weights. Therefore, this research confirms that the levels of importance verified by Delphi cannot be used for ranking or prioritizing the consensus indicators. The priority weights in this research would be useful to policymaking, strategic direction, and budget allocation for the development and management of sustainable cities in Cambodia.

A Novel Coordinated TOPSIS Based on Coefficient of Variation

Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS has some limitations and problems, which are listed as follows. (1) It is based on modified TOPSIS, not the original TOPSIS. (2) It is inapplicable when using vector normalization. (3) The calculation formulas of the coordination degree are incorrect. (4) The coordination level of attributes is interrelated with the weights. In this paper, the problems of the existing coordinated TOPSIS are explained and revised, and a novel coordinated TOPSIS based on coefficient of variation is proposed to avoid the limitations. Comparisons of the existing, revised, and proposed coordinated TOPSIS are carried out based on two case studies. The comparison results validate the feasibility of the proposed coordinated TOPSIS.

Developing Sustainable City Indicators for Cambodia through Delphi Processes of Panel Surveys

Currently, Cambodia does not have sustainable city indicators, and green and clean city indicators are also limited compared to UN Sustainable Development Goal 11 (SDG 11) indicators. Therefore, this research aims to develop sustainable city indicators for Cambodia and to address the questions “Are the green and clean city indicators limited in terms of sustainability?” and “Are the UN SDG 11 indicators suitable for Cambodia?” Delphi processes of panel surveys were conducted to develop the indicators in Round 1, pre-validate the indicators in Round 2, and validate the indicators in Round 3. The results showed that 69 initial indicators were obtained from Round 1; 41 pre-validated indicators were obtained from Round 2; and finally, 32 validated indicators were obtained from Round 3. All of the 32 indicators reached consensus. Based on the consensus indicators, the green and clean city indicators were found to be limited in terms of sustainability, and the UN SDG 11 has nine indicators suitable for Cambodia. These findings could be useful for applying the UN SDG 11 indicators to Cambodia and transforming the green and clean city indicators to sustainable city indicators. The 32 consensus indicators could be used as alternative sustainable city indicators for Cambodia.

Multi-Attribute Decision-Making Based on Preference Perspective with Interval Neutrosophic Sets in Venture Capital

Fuzzy information in venture capital can be well expressed by neutrosophic numbers, and TODIM method is an effective tool for multi-attribute decision-making. The distance measure is an essential step in TODIM method. The keystone of this paper is to define several new distance measures, in particular the improved interval neutrosophic Euclidean distance, and these measures are applied in the TODIM method for multi-attribute decision-making. Firstly, the normalized generalized interval neutrosophic Hausdorff distance is defined and proved to be valid in this paper. Secondly, we define a weighted parameter interval neutrosophic distance and discuss whether different weight parameters affect the decision result based on TODIM method. Thirdly, considering the preference perspective of decision-makers in behavioral economics, we define the improved interval neutrosophic Euclidean distance with the known parameter of risk preference. Finally, an application example is given to compare the effects of different parameters on the result and discuss the feasibility of these two distance measures in TODIM method.

A Fuzzy WASPAS-Based Approach to Determine Critical Information Infrastructures of EU Sustainable Development

Critical information infrastructure exists in different sectors of each country. Its loss or sustainability violation will lead to a negative impact on the supply of essential services, as well as on the social or economic well-being of the population. It also may even pose a threat to people’s health and lives. In the modern world, such infrastructure is more vulnerable and unstable than ever, due to rapid technological changes, and the emergence of a new type of threat—information threats. It is necessary to determine which infrastructure are of crucial importance when decision-makers aim to achieve the reliability of essential infrastructure. This article aims to solve the problem of ensuring the sustainable development of EU countries in terms of identifying critical information infrastructures. Integrated multi-criteria decision-making techniques based on fuzzy WASPAS and AHP methods are used to identify essential information infrastructures, which are related to a new type of potential threat to national security. The paper proposes a model for identifying critical information infrastructures, taking into account the sustainable development of countries.

An Integrated Multicriteria Analysis Tool for Evaluating Water Resource Management Strategies

Water is involved, directly or indirectly, with many activities and needs that have to be met. The large scale and importance of water projects, the investments needed, the difficulty in predicting the results, and the irreversible character of the decisions have made decision making a complex scientific process. This paper presents a multicriteria analysis (MCA) tool for evaluating water resource management (WRM) strategies and selecting the most appropriate among them, using as an example a Greek area based on agricultural economy, which faces water scarcity problems. Seven alternative strategies were evaluated under hydrological and economic criteria. Four techniques were used—multi attribute utility theory (MAUT), analytic hierarchy process (AHP), elimination and choice expressing reality (ELECTRE), and technique for order of preference by similarity to ideal solution (TOPSIS)—based on the main MCA techniques (utility theory, analytical hierarchy, outranking theory, and classification theory, respectively), to compare their performance, and to reach the most appropriate and ‘fitting’ method for the examined problem. The weightings extracted from two samples, (i) a sample of decision makers/stakeholders and (ii) a group of WRM experts, were used to compare the results. The process was carried out for each questionnaire, and thus the model shows the uncertainty of each sample group and of each method, as well as the overall uncertainty. The results illustrate the reality of the WRM problems of the watershed, enlighten their roots, and have further strengthened our conviction that the cooperation between the scientific community and the authorities is vital for more sustainable and efficient WRM.