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

Multi-Criteria Decision Analysis (MCDA) for sustainability assessment in food sector. A systematic literature review on methods, indicators and tools

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

Multiple criteria decision analysis to support the design of safe and sustainable chemicals and materials

The development of safe and sustainable chemicals and materials is essential to achieve the Zero-Pollution Ambition for a Toxic Free Environment stated in the EU Green Deal. For that, criteria need to be defined and considered since early stage of development. A Safe and Sustainable by Design (SSbD) framework is proposed in an EU Recommendation suggesting the assessment of multiple safety and sustainability aspects of chemicals and materials leaving open how the evaluation and selection of the preferable option should be done. This paper presents a proposal with different options for the use of multiattribute aggregation in an evaluation procedure for the SSbD assessment of chemicals and materials. This proposal is based on i) a review of the literature focusing on Multi-Criteria Decision Analysis (MCDA) application in the SSbD context (i.e. applications considering simultaneously safety and sustainability attributes) and ii) the definition of requisites for MCDA to be applied to the SSBD framework. In the latter, an absolute rather than a relative assessment is preferred as it should be possible for an organization developing a new chemical or material to assess if it is SSbD, without needing to obtain data on all of its possible competitors. Moreover, rank-reversals caused by the introduction of other options are avoided, i.e., assessments of one alternative that depends on other alternatives being assessed simultaneously are not the most adequate. Different options for the aggregation of attributes at different levels are discussed as well as for the consideration of data quality in the evaluation procedure. Regardless the approach selected, the use of multiattribute aggregation does not rule out a richer dashboard presenting not only the overall aggregate result, but also the results obtained in other levels of the hierarchy. Such complementary information is important to understand the strengths and weaknesses that an aggregate result might hide.

A multi-criteria decision framework for circular wastewater systems in emerging megacities of the Global South

Lima faces increasing water stress due to demographic growth, climate change and outdated water management infrastructure. Moreover, its highly centralized wastewater management system is currently unable to recover water or other resources. Hence, the primary aim of this study is to identify suitable wastewater treatment alternatives for both eutrophication mitigation and indirect potable reuse (IPR). For eutrophication mitigation, we examined MLE, Bardenpho, Step-feed, HF-MBR, and FS-MBR. For IPR, we considered secondary treatment+UF + RO + AOP or MBR + RO + AOP. These alternatives form part of a WWTP network at a district level, aiding Lima's pursuit of a circular economy approach. This perspective allows reducing environmental impacts through resource recovery, making the system more resilient to disasters and future water shortages. The methods used to assess these scenarios were Life Cycle Assessment for the environmental dimension; Life Cycle Costing for the economic perspective; and Multi-Criteria Decision Analysis to integrate both the quantitative tools aforementioned and qualitative criteria for social and techno-operational dimensions, which combined, strengthen the decision-making process. The decision-making steered towards Bardenpho for eutrophication abatement when environmental and economic criteria were prioritized or when the four criteria were equally weighted, while HF-MBR was the preferred option when techno-operational and social aspects were emphasized. In this scenario, global warming (GW) impacts ranged from 0.23 to 0.27 kg CO2eq, eutrophication mitigation varied from 6.44 to 7.29 g PO4- equivalent, and costs ranged between 0.12 and 0.17 €/m3. Conversely, HF-MBR + RO + AOP showed the best performance when IPR was sought from the outset. In the IPR scenario, GW impacts were significantly higher, at 0.46-0.51 kg CO2eq, eutrophication abatement was above 98 % and costs increased to ca. 0.44 €/m3.

Selection of appropriate on-site household sanitation options for rural communities of Zimbabwe - case of Mbire district, Zimbabwe

Selecting an appropriate sanitation option involves multiple stakeholders with often conflicting objectives. A multiple criteria decision analysis (MCDA) framework was developed to inform decision makers on selecting appropriate sanitation options for rural communities. Criteria established from literature were evaluated and weighted on-line by stakeholders. A performance matrix was developed by assigning weights to criteria and scoring alternatives. Selection of alternatives was based on a composite appropriateness index from a rank using the simple multi-attribute ranking technique. The framework was evaluated by verification, validation and sensitivity analysis. Five alternatives were evaluated on 14 decision criteria. The first preferred alternative was the urine diverting dry toilet (72.54) then the Blair ventilated improved pit latrine (67.10). The framework was commented as reasonable and robust. A simple and transparent MCDA framework was developed considering local conditions in a participatory manner to select appropriate alternatives for rural sanitation where a single option is encouraged.

Experimental Research on the Use of a Selected Multi-Criteria Method for the Cutting of Titanium Alloy with an Abrasive Water Jet

The use of selected multi-criteria decision methods for the optimization of cutting processes by abrasive water jet methods is increasingly being used in industrial processes. This is due to the complexity of the processes and the need to reduce operating costs. Process optimization methods are available to support organizational processes including the design phase, quality assurance, production automation, and many more. This article presents the current state of research on the water-abrasive cutting process and the use of multi-criteria methods in optimizing this process. This article presents a detailed methodological study of the VIKOR approach to optimization, indicating the applicability conditions, assumptions, and limitations on the example of high-pressure abrasive water jet cutting of elements made of titanium alloy utilizing HPX garnet abrasive. As a result of the research conducted, the best input parameters of the cutting process for abrasive flow rate, pressure, and the traverse speed of the cutting process were determined. The achieved result is consistent with the assumption that the most favorable output parameters are the highest cutting depth and the lowest level of roughness.

Modeling Opportunity Indicators Fostering Social Entrepreneurship: A Hybrid Delphi and Best-Worst Approach

Opportunity as a construct has been widely examined in for-profit entrepreneurship research, but it is scarcely studied in the context of social entrepreneurship. It is being observed that many entrepreneurs venture into social enterprise because they perceive it as an opportunity. This study aims to address this phenomenon by extensively identifying the opportunity indicators that promote entrepreneurs to pursue social entrepreneurship. We accomplish this by employing a mixed-methods approach wherein we used both quantitative and qualitative data from experts and analysed it using a hybrid approach of Delphi rounds and the best-worst method. We identified 13 opportunity indicators from the literature, and in the first round of Delphi, four new indicators were added to the list by a panel of 24 experts drawn from industry and academia across India. In the second round of the Delphi method, 18 of the 24 experts took part and rated the importance of each indicator on a 5-point Likert scale. Depending on the availability of the experts, both rounds of Delphi were held in person and virtually. Based on the cut-off levels for standard deviation, interquartile range, and probability of occurrence, experts agreed on 16 indicators. Furthermore, a best-worst method approach was used to prioritise these indicators based on the opinions of industry and academic experts. The study used a theoretical lens of entrepreneurial opportunity and its two different views: objectively discovered and subjectively perceived. The results revealed a consensus among academicians and practitioners for objectively discovered opportunity indicators, which gave the highest priority to "institutional support" and "funding opportunities."

Acceptability of cognitive remediation for schizophrenia: a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Acceptability is an important factor for predicting intervention use and potential treatment outcomes in psychosocial interventions. Cognitive remediation (CR) improves cognition and functioning in people with a diagnosis of schizophrenia, but its acceptability, and the impact of participants and treatment characteristics, remain to be investigated. Few studies provide a direct measure of acceptability, but treatment drop-out rates are often available and represent a valid surrogate.

METHOD

The systematic search conducted for the most comprehensive CR outcomes database for schizophrenia was updated in December 2020. Eligible studies were randomized clinical trials comparing CR with any other control condition in patients diagnosed with schizophrenia spectrum disorders and that also reported drop-out in treatment and control arms separately. Acceptability was measured as odd-ratios (OR) of drop-out.

RESULTS

Of 2119 identified reports, 151 studies, reporting 169 comparisons between CR and control interventions with 10 477 participants were included in the analyses. The overall rate of drop-out was 16.58% for CR programs and 15.21% for control conditions. In the meta-analysis, no difference emerged between CR interventions and controls [OR 1.10, 95% confidence interval (CI) 0.96-1.25, p = 0.177]. Factors improving acceptability were: inpatient only recruitment, participants with fewer years of education and lower premorbid IQ, the presence of all CR core elements, and the presence of techniques to transfer cognitive gains into real-world functioning.

CONCLUSIONS

CR for people diagnosed with schizophrenia is effective and has a good acceptability profile, similar to that of other evidence-based psychosocial interventions.

Feasibility of a Hospital Information System for a Military Public Organization in the Light of the Multi-Criteria Analysis

The healthcare environment presents a large volume of personal and sensitive patient data that needs to be available and secure. Information and communication technology brings a new reality to healthcare, promoting improvements, agility and integration. Regarding high-level and complex decision-making scenarios, the Brazilian Navy (BN), concerning its healthcare field, is seeking to provide better management of its respective processes in its hospital facilities, allowing accurate control of preventive and curative medicine to members who work or have served there in past years. The study addresses the understanding, structure and clarifying variables related to the feasibility of technological updating and installing of a Hospital Information System (HIS) for BN. In this scenario, through interviews and analysis of military organization business processes, criteria and alternatives were established based on multi-criteria methodology as a decision aid. As methodological support for research and data processing, THOR 2 and PROMETHEE-SAPEVO-M1 methods were approached, both based on the scenarios of outranking alternatives based on the preferences established by the stakeholders in the problem. As a result of the methodological implementation, we compare the two implemented methods in this context, exposing the Commercial Software Purchase and Adoption of Free Software, integrated into Customization by the Marine Studies Foundation, as favorable actions to be adopted concerning HIS feasibility. This finding generates a comprehensive discussion regarding the BN perspective and changes in internal development in the military environment, prospecting alignment to the culture of private organizations in Information Technology for healthcare management. In the end, we present some conclusions concerning the study, exploring the main points of the decision-making analysis and for future research.

Similarity of TOPSIS results based on criterion variability: Case study on public economic

In the real world, acceptance of a decision is conditional on the availability of a great volume of data. Selection of a suitable solution on the basis of this data represents a problem that multi-criterial methods (MCDM) are applied to. The issue of which of these should be favoured during their use involves a specification of the importance of the assessed criteria. The goal of the presented research is to quantify the differences (symmetry) in assessment using selected MCDM methods (Technique for Order of Preference by Similarity to Ideal Solution–TOPSIS), while applying an absolute and relative variability of the assessed criteria to a determination of their importance. The obtained results indicate that the order of the assessed subject (alternative) is not directly influenced by the method of determining the variability of the assessed criteria. We can also state that the degree of concurrence in the order of application of the TOPSIS technique, in combination with both approaches expressed by the Jaccard index, is relatively low.

A multi-criteria assessment of policies to achieve the objectives of the EU marine litter strategy

This paper proposes and assesses policy options to achieve the objectives of the EU marine litter strategy, based on the existing EU legislation. A group of experts and stakeholders was involved through a multi-staged workshop organized to generate the information to assess the contribution of the policies to the set of objectives, as well as the relative importance of the objectives, on qualitative scales. The ELECTRE TRI multi-criteria decision analysis method was used to rate the policies, which were subsequently ranked. Per the results, all policies deserve to be considered, even when the more pessimistic assessments (33rd percentile) are used. Revising the Urban Wastewater Treatment Directive, setting legislative targets on marine litter and ensure they are fully monitored, and funding proven clean-up technologies were deemed to be the most potentially impactful policies. The remaining policies assessed can nevertheless play an important role in complementing the higher-ranked policies.

A Systematic Review of the Applications of Multi-Criteria Decision Aid Methods (1977–2022)

Multicriteria methods have gained traction in academia and industry practices for effective decision-making. This systematic review investigates and presents an overview of multi-criteria approaches research conducted over forty-four years. The Web of Science (WoS) and Scopus databases were searched for papers on multi-criteria methods with titles, abstracts, keywords, and articles from January 1977 to 29 April 2022. Using the R Bibliometrix tool, the bibliographic data was evaluated. According to this bibliometric analysis, in 131 countries over the past forty-four years, 33,201 authors have written 23,494 documents on multi-criteria methods. This area’s scientific output increases by 14.18 percent every year. China has the highest percentage of publications at 18.50 percent, followed by India at 10.62 percent and Iran at 7.75 percent. Islamic Azad University has the most publications with 504, followed by Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. Expert Systems With Applications, Sustainability, and the Journal of Cleaner Production are the top journals, accounting for over 4.67 percent of all indexed works. In addition, E. Zavadskas and J. Wang have the most papers in the multi-criteria approaches sector. AHP, followed by TOPSIS, VIKOR, PROMETHEE, and ANP, is the most popular multi-criteria decision-making method among the ten nations with the most publications in this field. The bibliometric literature review method enables researchers to investigate the multi-criteria research area in greater depth than the conventional literature review method. It allows a vast dataset of bibliographic records to be statistically and systematically evaluated, producing insightful insights. This bibliometric study is helpful because it provides an overview of the issue of multi-criteria techniques from the past forty-four years, allowing other academics to use this research as a starting point for their studies.

Investigation on Current and Prospective Energy Transition Scenarios in Indian Landscape Using Integrated SWOT-MCDA Methodology

India has ambitious goals to increase renewable energy penetration, and significant progress has been made since 2017. However, the Indian energy mix is highly dominated by fossil fuels. To set India on the pathway of the energy transition, a comprehensive analysis of the complex factors influencing the Indian energy sector is required. This study is put forward to delineate the current energy transition scenario in India and to direct the energy sector towards a prospective scenario for accomplishing a smooth energy transition. A hybrid quantitative-qualitative SWOT-integrated MCDA methodology is employed to accomplish the objective of this study. An extensive literature review is performed to understand and sort the various factors under each SWOT category. Fuzzy AHP methodology is utilized to convert the qualitative significance of each SWOT factor into quantitative scores, through which the crucial influencing factor in the current energy transition scenario is obtained. The top three highest-influence factors include utilizing the cost-competitiveness of solar and wind energy technologies over fossil fuels, the inadequacy of manpower having specialized skillsets, and connecting households to electricity and electrifying the transportation sector. The recommendation strategies are framed and presented for prospective energy transition scenarios. These strategies are assessed against the SWOT factors by using the PROMETHEE II methodology. The assessment results highlight that developing robust regulatory and policy frameworks, increasing the contribution of local energy resources, and promoting the distributed generation and grid infrastructure development are the highest-scoring strategies that have a synergic effect on multiple dimensions of energy transition, including political, financial, and techno-economic aspects. The proposed study will be conducive to framing effective policy in the upcoming years to assist the energy transition in India.

A Rapid Literature Review of Multi-Criteria Decision Support Methods in the Context of One Health for All-Hazards Threat Prioritization

Background

Multi-Criteria Decision Analysis (MCDA) is a decision support tool that can be used in public health emergency management. The use of a One Health lens in MCDA can support the prioritization of threats and interventions which cut across the human, animal, and environmental domains. Previous literature reviews have focused on creating a snapshot of MCDA methodological trends. Our study provides an update to the MCDA methods literature with key considerations from a One Health perspective and addresses the application of MCDA in an all-hazards decision-making context.

Methods

We conducted a literature search on MEDLINE, EMBASE, SCOPUS, the CAB database, and a limited online gray literature search in partnership with a librarian from Health Canada. Articles were limited to those published in the year 2010 or later in a high-income setting (OECD member countries).

Results

Sixty-two articles were included for synthesis. Of these articles, most were Canadian studies (20%); and prioritized health risks, threats, and interventions in the human domain (69%). Six commonly used prioritization criteria were identified: threat, health, intervention, strategic, social, and economic impact. Stakeholders were engaged in 85% of studies and commonly consisted of government groups, non-governmental groups, subject matter experts, and the public. While most articles (65%) included elements of One Health based on our definition, only 5 studies (9%) explicitly acknowledged One Health as a guiding principle for the study. Forty seven percentage of studies noted that MCDA was beneficial in supporting the decision-making process.

Conclusion

Current literature on health prioritization presents some variability in the depth of integration of the One Health framework and on the use of various MCDA methodologies given prioritization objectives. Studies which applied a comprehensive One Health approach, prioritized disparate threats, or conducted cyclical prioritizations for governing bodies were broad in scope, but sparse. The results of our review indicate the need for better guidance on the integration of a One Health approach and the use of various MCDA methods given the main prioritization objectives.

Waste Classification of Spent Refractory Materials to Achieve Sustainable Development Goals Exploiting Multiple Criteria Decision Aiding Approach

The recycling of used refractory materials in the heavy industry constitutes one of the significant environmental problems in the industry related to environmental and financial issues. This study proposes a multicriteria methodological frame to characterize the refractory material waste and identify the recycling capabilities. Considering the chemical and physical analysis of the refractory material wastes, the proposed methodological frame progresses into a two-phase procedure. The first phase includes an on/off approach that allows discretizing the refractory material wastes to compatible or not compatible as far as their recycling prospects. Then, an additive value model is utilized, including (a) the marginal value functions used for every criterion related to critical environmental factors, and (b) the weight vector reflecting the relative importance of the criteria used. A group of experts concerning the environment and the refractory materials was employed to estimate the additive value model. The assessment of the marginal value function is achieved using the module of the Multicriteria Interactive Intelligence Decision Aiding System (MIIDAS), which is based on a modification of the mid-value split point technique incorporating focused dialogues, artificial intelligence, and visual techniques. The weight vector was assessed using the weight assessment through prioritization method (WAP), which concludes with the estimation of the weights based on the criteria ranking and the pairwise expression of the strength of preferences for the consecutive criteria according to their ranking. The outcome of this approach is to introduce an environmental appropriateness index for refractory materials based on their chemical composition and the judgement of an expert group. The main findings of this research may be useful for engineers, decision-makers, and scientists in the field of circular economy and waste management.

Assessment of Clean Energy Transition Potential in Major Power-Producing States of India Using Multi-Criteria Decision Analysis

India has an ambitious target to promote clean energy penetration, but as of 2021, the electricity mix of India is dominated by coal to about 71%. Therefore, analyzing the clean energy potential and the ability of the individual states to entrench energy transition in the upcoming years will be supportive for policymakers. This study is propounded to assess the clean energy transition potential with a focused analysis on seven major power-producing states of India. These states include Maharashtra, Gujarat, Tamil Nadu, Uttar Pradesh, Karnataka, Madhya Pradesh, and Andhra Pradesh. The clean energy transition potential assessment is performed by utilizing multi-criteria decision analysis methodologies such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization Method by Ratio Analysis (MOORA). Further, the analysis is performed against four major criteria that include high carbon energy resource dependency, low carbon energy resource dependency, clean energy potential, and policy support. Altogether, the assessment criteria include four primary level criteria and fourteen secondary level parameters. In order to reflect the significance of each parameter and criterion to the characteristics of clean energy transition potential, appropriate weightage is provided using the Fuzzy Analytic Hierarchy Process (AHP). The results indicate that Gujarat has the highest clean energy transition potential in both the multi-criteria decision analysis methods. On the other hand, Uttar Pradesh exhibited the least performance, and a complete energy transition to clean energy resources is less likely in this state. The rest of the states obtained intermediate ranking, and a comparative analysis between the two methods was also accomplished. This study suggests that India should focus on the clean energy policy with vigorous efforts on top-performing states which will effectively accelerate the power sector decarbonization.

On the Assessment of e-Banking Websites Supporting Sustainable Development Goals

The main aim of this article was to test the authors’ proprietary method (i.e., the conversion method applied to evaluate e-banking services that support sustainable development goals in households, communities, and society). The authors’ conversion method can be applied with the aim of maintaining a balance between households, producers, and public administration services in line with the principles of sustainable development of the information society in Poland. To achieve this goal, the authors identified the differences between the results obtained using the conversion method and the results produced by other methods such as TOPSIS, Promethee II, and PROSA involving the same group of respondents. A hypothesis was made about the existence of significant differences in the results obtained as part of the studies. The research was carried out on a sample of nearly 830 ratings concerning the 27 most popular electronic banks in Poland. As part of the survey, the respondents assessed 18 characteristics (attributes) of the selected banks using a simplified Likert scale. The study was conducted during the pandemic in Poland in 2020. The authors compared the results achieved in the case of the TOPSIS, Promethee II, and PROSA methods and the ones obtained with the application of the conversion method. Then, the ratings of the e-banking websites were arranged in descending order, and the distances between the positions in the rankings obtained by the conversion method and other methods were calculated. In addition, the R2 correlation coefficients were calculated for all combinations of the results received using individual methods. The results showed the greatest differences both in the absolute distances between the positions obtained in the ranking and the lowest value of the R2 correlation coefficient in the case of the conversion method in relation to the other methods. The limitation of the present research resulted from the fact that the study sample included respondents who were all members of the academic environment. The students analyzed in the study were part of a group supporting globalization processes where e-business solutions are widely used. However, the purchases of goods and services both local and foreign made by this group were often limited in scope and value due to a lack of funds. The research results indicate a potential need for improvement of the conversion method.

Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method

Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. However, in light of the choosing of fault diagnosis sensors, there is no MCDM analysis, and Fuel Cell Stack companies also urgently need a solution. Therefore, in this paper, we will use MCDM methods to analysis the fault-diagnosis sensor selection problem for the first time. The main contribution of this paper is to proposed a fault-diagnosis sensor selection methodology, which combines the rank reversal resisted AHP and TOPSIS and supports Fuel Cell Stack companies to select the optimal fault-diagnosis sensors. Apart from that, through the analysis, among all sensor alternatives, the acquisition of the optimal solution can be regarded as solving the symmetric or asymmetric problem of the optimal solution, which just maps to the TOPSIS method. Therefore, after apply the proposed fault-diagnosis sensor selection methodology, the Fuel Cell Stack system fault-diagnosis process will be more efficient, economical, and safe.

Behavioral Decision Making in Normative and Descriptive Views: A Critical Review of Literature

Recent studies on decision analytics frequently refer to the topic of behavioral decision making (BDM), which focuses on behavioral components of decision analytics. This paper provides a critical review of literature for re-examining the relations between BDM and classical decision theories in both normative and descriptive reviews. We attempt to capture several milestones in theoretical models, elaborate on how the normative and descriptive theories blend into each other, thus motivating the mostly prescriptive models in decision analytics and eventually promoting the theoretical progress of BDM—an emerging and interdisciplinary field. We pay particular attention to the decision under uncertainty, including ambiguity aversion and models. Finally, we discuss the research directions for future studies by underpinning the theoretical linkages of BDM with fast-evolving research areas, including loss aversion, reference dependence, inequality aversion, and models of quasi-maximization mistakes. This paper helps to understand various behavioral biases and psychological factors when making decisions, for example, investment decisions. We expect that the results of this research can inspire studies on BDM and provide proposals for mechanisms for the development of D-TEA (decision—theory, experiments, and applications).

Supporting contaminated sites management with Multiple Criteria Decision Analysis: Demonstration of a regulation-consistent approach

This study proposes a set of key decision-making features of the contaminated site remediation process to assist in selecting the most appropriate decision support method(s). Using a case study consistent with the requirements of the U.S. regulation for contaminated sites management, this article shows that suitable Multiple Criteria Decision Analysis methods can be selected based on a dynamic and evolving problem structuring. The selected methods belong to the family of PROMETHEE methods and can provide ranking recommendations of the considered alternatives using variable structures of the criteria, evaluation of the alternatives and exploitation of the preference model. It was found that in order to support a quick and up-to-date application of powerful decision support techniques in the process of remediation of contaminated sites, decision analysts and stakeholders should interact and co-develop the process. This research also displays how such interactions can guarantee a transparent and traceable decision recommendation so that stakeholders can better understand why some alternatives perform comprehensively better than others when a multitude of inputs is used in the decision-making process.

Recycling of low-value packaging films in bitumen blends: A grey-based multi criteria decision making approach considering a set of laboratory performance and environmental impact indicators

Many road construction and maintenance projects are increasingly using recycled material as pavement material. Most of the times, generic sustainability evaluations are ascribed to recycled products without fully considering their performance. The potential environmental benefits of various alternatives can be analytically evaluated with Life Cycle Assessment while many performance indicators can be found through laboratory and field tests. However, it is highly uncommon for these two approaches to be combined in the same assessment methodology and most of the analyses rely on one or the other. Trading off between environmental advantages and performance and durability in the field is considered of utmost importance when evaluating construction alternatives, especially on large projects. This study utilizes recycled plastic packaging films for bitumen modification. The recycled polyolefin blend is a combination of linear low-density polyethylene and low-density polyethylene (LLDPE/LDPE). LLDPE/LDPE was added in bitumen at various dosages (i.e., from 3% to 12% by weight of the bitumen) to assess the effect of recycled LLDPE/LDPE on the binder physio-chemical, rheological and thermal performance. In addition to the various laboratory performance tests, the environmental sustainability of the alternatives was evaluated through an LCA study. Finally, the outcomes from the two approaches (laboratory performance and environmental impact assessment) were combined via grey relational analysis to identify the best overall alternative. It was found that the storage stability of LLDPE/LDPE modified blends varied from 6 °C to 57 °C whereas the storage stability value of A35P was 2 °C. Softening point of bitumen was 44.1 °C which improved to 55.7-104.1 °C at different content of LLDPE/LDPE. The melting temperature of LLDPE/LDPE modified blends was 100.22, 101.44, 101.87 and 102.49 for LLDPE/LDPE-3%, LLDPE/LDPE-6%, LLDPE/LDPE-9% and LLDPE/LDPE-12%. The methodology highlighted in the paper can be easily adapted to other scenarios, hence facilitating multi-attribute decision-making processes when incorporating recycled materials in roads and leading to better informed decisions.

Upgrading current multi-attribute decision-making with a 3-dimensional decision matrix for future-based decisions

Two shortcomings of existing Multi-Attribute Decision-Making (MADM) approaches are presented in this paper. The problems were decision makers' (experts') dynamic level of experience in certain areas, as well as the difficulties of forecasting the future with the existing MADM techniques. A solution is also proposed to overcome the issues.•Two critical shortcomings of existing multi-attribute decision-making (MADM) approaches are presented with this work.•As a solution for the shortcomings, a 3-dimensional decision matrix is introduced.

PROMETHEE-SAPEVO-M1 a Hybrid Approach Based on Ordinal and Cardinal Inputs: Multi-Criteria Evaluation of Helicopters to Support Brazilian Navy Operations

This paper presents a new approach based on Multi-Criteria Decision Analysis (MCDA), named PROMETHEE-SAPEVO-M1, through its implementation and feasibility related to the decision-making process regarding the evaluation of helicopters of attack of the Brazilian Navy. The proposed methodology aims to present an integration of ordinal evaluation into the cardinal procedure from the PROMETHEE method, enabling to perform qualitative and quantitative data and generate the criteria weights by pairwise evaluation, transparently. The modeling provides three models of preference analysis, as partial, complete, and outranking by intervals, along with an intra-criterion analysis by veto threshold, enabling the analysis of the performance of an alternative in a specific criterion. As a demonstration of the application, is carried out a case study by the PROMETHEE-SAPEVO-M1 web platform, addressing a strategic analysis of attack helicopters to be acquired by the Brazilian Navy, from the need to be evaluating multiple specifications with different levels of importance within the context problem. The modeling implementation in the case study is made in detail, first performing the alternatives in each criterion and then presenting the results by three different models of preference analysis, along with the intra-criterion analysis and a rank reversal procedure. Moreover, is realized a comparison analysis to the PROMETHEE method, exploring the main features of the PROMETHEE-SAPEVO-M1. Moreover, a section of discussion is presented, exposing some features and main points of the proposal. Therefore, this paper provides a valuable contribution to academia and society since it represents the application of an MCDA method in the state of the art, contributing to the decision-making resolution of the most diverse real problems.

Multi-Criteria Seed Selection for Targeting Multi-Attribute Nodes in Complex Networks

Online environments have evolved from the early-stage technical systems to social platforms with social communication mechanisms resembling the interactions which can be found in the real world. Online marketers are using the close relations between the users of social networks to more easily propagate the marketing contents in their advertising campaigns. Such viral marketing campaigns have proven to provide better results than traditional online marketing, hence the increasing research interest in the topic. While the majority of the up-to-date research focuses on maximizing the global coverage and influence in the complete network, some studies have been conducted in the area of budget-constrained conditions as well as in the area of targeting particular groups of nodes. In this paper, a novel approach to targeting multi-attribute nodes in complex networks is presented, in which an MCDA method with various preference weights for all criteria is used to select the initial seeds to best reach the targeted nodes in the network. The proposed approach shows some symmetric characteristics—while the global coverage in the network is decreased, the coverage amongst the targeted nodes grows.

Uptake and Dissemination of Multi-Criteria Decision Support Methods in Civil Engineering—Lessons from the Literature

The SCOPUS and Wed of Science bibliometric databases were searched for papers related to the use of multi-criteria methods in civil engineering related disciplines. The results were analyzed for information on the reported geographical distribution of usage, the methods used, the application areas with most usage and the software tools used. There was a wide geographical distribution of usage with all northern hemisphere continents well represented. However, of the very many methods available, a small number seemed to dominate usage, with the Analytic Hierarchy Process being the most frequently used. The application areas represented in the documents found was not widely spread and mainly seemed to be focused on issues such as sustainability, environment, risk, safety and to some extent project management, with less usage on other areas. This may be due to individual engineer’s choices in relation to if and how to disseminate the results of their work and to their choice of keywords and titles that determine if their publications are selected in bibliographic searches and thus more visible to a wider readership. A comparison with more topic focused searches, relating to Bridge Design, Earthquake Engineering, Cladding, Sewage Treatment, Foundation design, Truss design, Water Supply, Building Energy, Route selection and Transport mode showed very different results. Analysis of the papers in this area indicated that the full range of supporting software available for multi-criteria decision analysis (many listed in this paper) may not be fully appreciated by potential users.

Fuzzy and Interval AHP Approaches in Sustainable Management for the Architectural Heritage in Smart Cities

For the past four decades, the methodology of fuzzy analytic hierarchy process based on fuzzy trapezoidal or triangular numbers with the linear type of membership functions has witnessed an expanding development with applicability to a wide variety of areas, such as industry, environment, education, government, economics, engineering, health, and smart city leadership. On the other hand, the interval gray analytic hierarchy process is a more practical method when a significant number of professionals have large variations in preferences and interests in complex decisions. The paper examines the management of architectural heritage in smart cities, using methods of multi-criteria decision making. Two appropriate methods generally recommended by the scientific literature have been applied: fuzzy and interval grey analytic hierarchy process. By using both techniques, there is an opportunity to analyze the consensual results from the aspect of two different stakeholder groups: architectural heritage experts and smart city development experts. Trapezoidal fuzzy analytical hierarchical process shows better stability than a triangular one. Both approaches assign priority to the strategy, but the interval approach gives a more significant rank to architectural heritage factors. The similarity of the proposed methods has been tested, and the similarity factor in the ranking indicates a high degree of similarity in comparing the reference rankings.

Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study

The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the analyzes, both the positions in the final rankings, as well as the corresponding values of utility functions of the decision variants were studied. As a result of the detailed analysis of the obtained results, recommendations were presented in the field of reference criteria set for the considered decision problem, thus demonstrating the practical usefulness of the authors’ proposed approach. It should be pointed out that the presented study of criteria relevance is an important factor for objectification of the multi-criteria decision support processes.

On the Geometric Mean Method for Incomplete Pairwise Comparisons

One of the most popular methods of calculating priorities based on the pairwise comparisons matrices (PCM) is the geometric mean method (GMM). It is equivalent to the logarithmic least squares method (LLSM), so some use both names interchangeably, treating it as the same approach. The main difference, however, is in the way the calculations are done. It turns out, however, that a similar relationship holds for incomplete matrices. Based on Harker’s method for the incomplete PCM, and using the same substitution for the missing entries, it is possible to construct the geometric mean solution for the incomplete PCM, which is fully compatible with the existing LLSM for the incomplete PCM. Again, both approaches lead to the same results, but the difference is how the final solution is computed. The aim of this work is to present in a concise form, the computational method behind the geometric mean method (GMM) for an incomplete PCM. The computational method is presented to emphasize the relationship between the original GMM and the proposed solution. Hence, everyone who knows the GMM for a complete PCM should easily understand its proposed extension. Theoretical considerations are accompanied by a numerical example, allowing the reader to follow the calculations step by step.

Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors’ approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods.

Fuzzy Model Identification Using Monolithic and Structured Approaches in Decision Problems with Partially Incomplete Data

A significant challenge in the current trend in decision-making methods is the problem’s class in which the decision-maker makes decisions based on partially incomplete data. Classic methods of multicriteria decision analysis are used to analyze alternatives described by using numerical values. At the same time, fuzzy set modifications are usually used to include uncertain data in the decision-making process. However, data incompleteness is something else. In this paper, we show two approaches to identify fuzzy models with partially incomplete data. The monolithic approach assumes creating one model that requires many queries to the expert. In the structured approach, the problem is decomposed into several interrelated models. The main aim of the work is to compare their accuracy empirically and to determine the sensitivity of the obtained model to the used criteria. For this purpose, a study case will be presented. In order to compare the proposed approaches and analyze the significance of the decision criteria, we use two ranking similarity coefficients, i.e., symmetric rw and asymmetric WS. In this work, the limitations of each approach are presented, and the results show great similarity despite the use of two structurally different approaches. Finally, we show an example of calculations performed for alternatives with partially incomplete data.

MCDM Evaluation of Asset-Based Road Freight Transport Companies Using Key Drivers That Influence the Enterprise Value

Business owners are trying to enhance company value by developing growth strategies. Besides, they need to know what supports and drives the attractiveness to potential investors. Previously to determine company value, only financial drivers were used. These are essential drivers; however, even they do not reflect the overall situation. This paper proposes a novel approach for the solution of the problem of business valuation by taking into account both financial and non-financial drivers and by using several MCDM (multiple criteria decision making) methods simultaneously both for establishing weights and for the evaluation itself. World-leading road freight transport companies were selected for a case study. MCDM methods were used for determining the weights of the drivers and comparing the listed companies. Key drivers were identified, and the ranking of companies is provided.

Location Selection of a Manufacturing Facility from the Perspective of Supply Chain Sustainability

When threatened with catastrophic political or economic fluctuations, a firm might be forced to consider relocating their supply chain to reduce the risk. Such a relocation necessitates a series of changes, so making the right decision is crucial for sustainable development of the company. In the past, various models have been developed to help managers to select the optimal location. However, most of these considered the factors independently but in the real world, these factors have a mutually influential relationship. This study purposes a hybrid multiple criteria decision making (MCDM) model to provide decision makers with a comprehensive framework to evaluate the best strategies to solve relocation problems, which also considers the interdependency between criteria. The model incorporates the DANP (Decision Making Trial and Evaluation Laboratory-based Analytic Network Process) model (subjective weight) and entropy method (objective weight) to determine the weights of the criteria. Then, the modified VIKOR (VIšekriterijumsko Kompromisno Rangiranje) method is applied to select the optimal alternative for relocation. The usefulness of the model is demonstrated by taking an electronics manufacturing company with a global supply chain as an example. The results indicate that the proposed hybrid model can assist companies in choosing the best locations for their supply chains for sustained development.