Multi-criteria Decision Support Tool Research Articles

Multicriteria assessment of technology pathways to produce renewable and sustainable biofuels: case study in eastern Canada

AbstractOne of the key pathways that can contribute to net‐zero goals is to enhance the use of renewable and sustainable biofuels. However, uncertainties remain owing to critical challenges to selecting the right sustainable biofuels technology most suitable for the longer term. These uncertainties can be partly addressed using a multidisciplinary perspective for scenarios and multicriteria decision‐making analysis. Multicriteria decision support tools (DSTs) are a powerful means to conduct the comparison of technology pathways at different technology readiness levels (TRLs). For this case study, a multidimensional DST was used to compare two technology pathways: (1) gasification combined with Fischer–Tropsch; and (2) hydrothermal liquefaction (HTL) to produce biofuels. The metrics available in the DST were examined, and five metrics related to evaluating profitability, robustness and capital efficiency as well as socio‐economic performance were selected. HTL was found to have a higher yield for renewable gasoline and diesel, largely due to higher economic performance and reduced environmental footprint as compared with the integrated gasification Fischer–Tropsch process. However, the TRL of 8–9 of biomass gasification was higher than that of HTL, which was still at 5–6, reflecting that the gasification process is essentially proven at a pre‐commercial scale. Based on sensitivity and scenario analyses, the importance of government support for capital cost and of biofuel price production incentives was identified as critical. From this comparison, HTL emerges as an attractive process for the future because of its outperformance from technical and environmental perspectives, but further demonstration efforts are still needed at the commercial scale. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

An operations research approach to automated patient scheduling for eye care using a multi-criteria decision support tool

Inefficient management of resources and waiting lists for high-risk ophthalmology patients can contribute to sight loss. The aim was to develop a decision support tool which determines an optimal patient schedule for ophthalmology patients. Our approach considers available booking slots as well as patient-specific factors. Using standard software (Microsoft Excel and OpenSolver), an operations research approach was used to formulate a mathematical model. Given a set of patients and clinic capacities, the model objective was to schedule patients efficiently depending on eyecare measure risk factors, referral-to-treatment times and targets, patient locations and slot availabilities over a pre-defined planning horizon. Our decision support tool can feedback whether or not a patient is scheduled. If a patient is scheduled, the tool determines the optimal date and location to book the patients’ appointments, with a score provided to show the associated value of the decisions made. Our dataset from 519 patients showed optimal prioritization based on location, risk of serious vision loss/damage and the referral-to-treatment time. Given the constraints of available slots, managers can input hospital-specific parameters such as demand and capacity into our model. The model can be applied and implemented immediately, without the need for additional software, to generate an optimized patient schedule.

Analysis of the relevance of the location of quarrying surfaces by using a multi-criteria decision support tool taking into account the sustainable territorial development (Case of Settat – Morocco)

The cohabitation between the material extraction activity and its receiving environment requires a conciliation between the three dimensions of sustainable development, namely the economic, social and environmental aspects. Given that the reasons for the existence of this extractive industry are economic, it feeds the pillar sectors of the economy (civil engineering, buildings ...) or, social it creates employment and contributes significantly to the revenue of local communities through taxes but it has disadvantages on the receiving ecosystem. The problem is to know how to make this sector a vector of economic development without compromising the environment in order to guarantee and ensure simultaneously economic growth and social equity and environmental protection and to make the territory more attractive and sustainable to investments in this field. Therefore, it has become necessary to take into account these three pillars when locating this activity. The said location is an essential decision, the fact of favoring one of the three aspects over the other aspects will undoubtedly have consequences on the environment where the activity is hosted (either more positive or more negative, conditioned by its choice). Indeed, the choice of quarry sites is a multi-criteria issue since we must reconcile the three imperatives of sustainable development which are often contradictory. In this sense this work has opted for a decision-making approach designed from a decision-making tool process of hierarchical analysis (AHP), said approach is based on the three axes of sustainable development (economic, social and environmental) which are subdivided into 16 criteria and apply on options (15 careers). The choice of criteria families, criteria and options was made while respecting the imperatives of sustainable development and according to their distributions and typologies at the level of the study area. Once these decision elements were identified, the attractiveness of the options on each criterion was evaluated, weighted according to the concerns and preferences presented by the decisionmakers and then aggregated by the AHP method in order to produce a hierarchy of the criteria and options. The implementation of this method allows for the evaluation of existing quarry operations in the study area and the forecasting of future optimization of quarry facilities

MCDM Filter with Pareto Parallel Implementation in Shared Memory Environment

Nowadays, multi-criteria decision-making (MCDM) methods are often used to solve problems involving large data sets, especially with the advent of the big data age. In such a context, the multi-criteria decision-making methods theoretically can be used but technically are not effificient in terms of the treatment time. Indeed, the majority of commercial or even experimental multi-criteria decision support tools always have limits in terms of the number of alternatives and the number of criteria to be retained in the decision-making process, which presents a computational challenge to relieve. This present paper discusses the application of parallel computation to meet this challenge and make the application of MCDM methods possible in the presence of a big number of alternatives and criteria. More precisely, the main objective of this work is to provide a parallel fifiltering mechanism that can be executed even on accessible personal computers and offering a short and reasonable response time. The introduction of a fifilter as a fifirst step in the decision-making process consists in retaining, as alternatives to be treated by the MCDM method, and by parallel processing only the Pareto solutions. To achieve this objective, we propose a parallel computing approach deploying the Open MP (Open Multi-Processing) paradigm on a shared memory environment to fifind Pareto solutions. To prove the effectiveness of the proposed approach for problems with large dimensionality, several numerical examples with different dimensions will be examined.

Perceptions of and needs for e‐Health solutions for elderly people with cognitive impairment, their caregivers and health care providers: A qualitative exploration

AbstractBackgroundThe prevalence of mild cognitive impairment (MCI) and mild neurocognitive disorder (mNCD) are steadily increasing in Canada. Information and communication technologies (ICTs) in health represent an innovation to promote home care and autonomy for people with various degrees of cognitive impairment. The objective of this study is to develop a web‐based multicriteria decision support tool adapted to older adults with MCI or mNCD, their informal caregivers, and health care providers (HCPs) to support the development and implementation of ICTs adapted to the needs and preferences of people with cognitive impairments and their caregivers.MethodsWe used a participatory research strategy to develop of a decision support tool for the use of ICTs focused on the needs of patients, their caregivers, and HCPs. Data collection consisted of semi‐structured interviews with elderly people with MCI (N = 10) and caregivers of people with mNCD (N= 7) to explore their current knowledge and perceptions of various ICTs as well as their needs and preferences for such interventions and a focus group with HCPs to understand their perceptions of the needs of seniors with MCI and caregivers of people with mNCD.ResultsICTs are seen as a beneficial solution to promote home care and autonomy for people with cognitive disorders. ICTs provide a sense of security and peace of mind, especially for caregivers of people with mNCD. However, the complexity and high cost of ICTs as well as the lack of support appear to be major limits to their use. HCP recognize the value of e‐Health but claim to lack reliable information and were therefore highly unsure to recommend its use.ConclusionsPeople suffering from cognitive disorders and their caregivers are generally open to technological developments and favour the use of ICTs. For health professionals, continuous training on ICTs would make them more comfortable to recommend them to patients and their families. Although the use of ICTs is promising for maintaining elderly people with cognitive disorders at home, our study shows that it will be necessary to find ways to make them accessible to promote their use.

Development of an ecodesign framework for food manufacturing including process flowsheeting and multiple-criteria decision-making: Application to milk evaporation

The food industry urgently needs to design sustainability into its processes. Here we develop a methodological framework for the ecodesign of food processes. The framework combines process flowsheeting (using a process simulation tool) and multiobjective optimization with life-cycle and cost-cycle analysis tools embedded in a multicriteria decision support tool. The framework developed is illustrated by the example of milk evaporation, which is one of the most energy-intensive processes in the dairy industry and has huge potential for optimization. The commercial process simulator was first adapted to modeling milk evaporators. Economic and environmental criteria were then computed from inventories of both the production and cleaning phases, and we went on to apply multiobjective optimization (with a genetic algorithm) and multicriteria decision-making either independently or in combination. The potential of the framework was demonstrated first through analysis of three evaporator design solutions, and second as a support for the strategic choice of a fuel for the purpose of on-site energy production. This work provides a pathway to ecodesigning the entire milk powder production chain.

A conceptual framework for a multi-criteria decision support tool to select technologies for resource recovery from urban wastewater

In the context of circular economy, wastewater can be used to address some of the 21st century's challenges regarding the transition to renewable resources for water, energy, and nutrients. Despite all the research, development, and experience with resource recovery from urban wastewater, its implementation is still limited. The transition from treatment to resource recovery is complex due to the difficulty of selecting unit processes from a large number of candidate processes considering the operational limitations of each process, and sustainability objectives. Presently, a multi-criteria decision support tool that deals with the difficulty of unit process selection for resource recovery from wastewater has not been developed. Therefore, this paper presents the conceptual framework of a decision support tool to find the optimum treatment train consisting of compatible unit processes which can recover water, energy and/or nutrients from a specified influent composition. The framework presents the relationship between the user input, the knowledge library of technologies and a weighted multi-objective nonlinear programming model to aid process selection. The model presented here shows, not only how the processes are selected, but also the four-dimensional sustainability impact of the generated treatment train while considering the weight provided by the user. Thus, this study presents a reproducible framework which can support private and public decision-makers in transparent evidence-based decision making and eventually the systematic implementation of resource recovery from urban wastewater.

Land Suitability Assessment for Olive Mill Wastewater Disposal by Integrating Multicriteria Decision Support Tools

Many on-site waste disposal systems fail regularly due to problems concerning suitable location and management. A potential environmental threat is inevitably propagated through on-site, off-site, downstream, soil surface and ground water pollution. Soil is a key component of land suitability for waste disposal. This paper presents a Geographic Information Systems (GIS) – based integrated multicriteria decision support system for evaluating the land suitability for olive mill wastewater (OMWW) disposal in the Mediterranean region. Two-scaled classification schemes are developed, the global scheme for Central and South Greece (scale: 1:30.000) and the local scheme for the study area in Xiromero, Aetolia-Acarnania Prefecture, Western Greece, scale 1:10.000. Constrains and factors are included into the spatial decision-making framework, where geostatistical and fuzzy set theory techniques, as well as Analytical Hierarchy Process (AHP) are appropriately integrated. Physical, chemical, and socioeconomic variables adapted to the Mediterranean soil conditions are incorporated as driving forces for the land suitability assessment and the produced maps reveal valuable results for final end-users, such as municipal authorities, agriculturalists, farmers and other national and local stakeholders.

Metamodeling and multicriteria analysis for sustainable and passive residential building refurbishment: A case study of French housing stock

For the energy-related issues that the world is facing nowadays, the renovation of the building stock is one of the major challenges. The objective of this study is to present an approach that helps to develop a multi-criteria decision support tool dedicated to the rehabilitation of sustainable and passive energy housing by integrating heating energy needs, economic, social and environmental criteria throughout the life cycle stages of the building. The methodology consists of developing metamodels to predict heating energy needs from polynomial regression, design of experiments method and thermo-aeraulic simulations of building behavior. This metamodel is used to carry out a combinatorial study of real technical solutions. The methodology was applied to a real-life existing building located in La Rochelle city (France) based on an in-situ energy diagnosis. Three multicriteria analysis methods were studied and compared: weighted sum, Min-Max and Pareto concept. Furthermore, technical constraints as well as owner preferences and performance constraints have been studied. Optimal technical solutions have been obtained in order to meet the various criteria studied. In addition, window shading and natural ventilation have been proposed to reduce the thermal discomfort rate in summer. This study was extended to all French regions. Finally, this method can be transformed into a decision support tool which will be useful for architects, engineers and stockholders.

SUSTAINABILITY-ORIENTED INNOVATION, TECHNOLOGIES & FINANCE IN CONSTRUCTION: A MULTI-CRITERIA METHODOLOGY

Considering the efforts to adjust the great demand of the civil construction in the developing countries and the economic interests of the sector, in line with current sustainable trends, this article presents a methodology to support the planning and decision making of construction companies. An analysis of the elements involved in the process, their interaction and proposed application priorities are evaluated using the AHP (Analytic Hierarchy Process) method as a multi-criteria decision support tool. The results obtained allow us to observe the parameters that guide the decision-making of the managers in the construction sites, the impact of low productivity and limited investments in innovation and processes, which still adopts the traditional methods of construction. However, exists a margin that is sustainable, without major financial impact, through the management and encouragement of the environmental awareness of investors, entrepreneurs and construction workers. The actions that interfere with the process and its application priorities in construction are related, within the context of innovation, technology and finance oriented to sustainability. Supported by the concepts of management and SOI (Sustainability-oriented innovation) topics, a discussion of the civil construction scenario in Brazil is carried out through the economic, social, technological and managerial issues typical of developing countries, guided by the strong trends in the macro-economics adjustments and rational use of natural resources in the coming decades. It highlights the main challenges of the sector and presents a analysis, planning, decision-making approach and collective impact actions that could support the development actions of the sector, in order to reduce the distance from the concepts of environmental awareness and attitudes existing in developed countries.

A new multicriteria decision support tool based on Fuzzy SWARA and TOPSIS

The problem of selecting 3PL (Third Party Logistics) suppliers is a major issue in the management of the supply chain and the improvement of the production management of a manufacturing company. A 3PL supplier can be defined as a company that provides contract logistics services to a manufacturer, supplier or main user of a product or service. It is called a third party because the logistics provider does not own the products but participates in the supply chain between the manufacturer and the user of a given product. In actual cases, several decision-makers intervene in the selection of 3PL suppliers and each one has his own points of view and wishes to take into account criteria which are not generally the same for all the decision-makers. Furthermore, the criteria have different weights. In this study, we propose a method to solve this problem. It consists of a combination of the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The objective is to optimize the decision-making process and have another, more dynamic model and satisfy the needs of the decision-maker. Fuzzy SWARA is one of the new methods being used for ranking evaluation criteria based on decision makers’ expected degree of importance to determine the weights of evaluation criteria (Selçuk, 2019). This method can be used to facilitate estimation of decision makers’ preferences regarding the meaning of attributes in the weight determination process. TOPSIS is a multi-criteria method for identifying solutions from a finite set of alternatives (Behzadian et al., 2012). To the best of our knowledge, this combination has not been developed in the literature, especially in the third-party logistic problems. The proposed model will be implemented to solve a 3PL problem of a company selling steel products. Keywords: multicriteria decision support, 3PL suppliers, Fuzzy SWARA, TOPSIS

Multicriteria Decision Support Would Avoid Overdiagnosis and Overtreatment.

Population-level studies confirm the existence of significant rates of overdiagnosis and overtreatment in a number of conditions, particularly those for which the screening of asymptomatic individuals is routine. The implication is that the possibility of being overdiagnosed and/or overtreated must be mentioned as a possible harm in generating informed consent and participation from the individual invited to be screened. But how should the rates of such preference-insensitive population-level phenomena be introduced into preference-sensitive individual decision making? Three possible strategies are rejected, including the currently dominant one that involves presenting the rates relevant to overdiagnosis and overtreatment as discrete pieces of information about a single criterion (typically condition-specific mortality). Extensive quotation from a review of cancer decision aids confirms that processing this complex and isolated information is not a practical approach. However, the task is unnecessary, since an outcome-focused multicriteria decision support tool will incorporate the effects of overdiagnosis and overtreatment - along with the effects of any underdiagnosis and undertreatment.

WEB-BASED DECISION SUPPORT TOOL FOR BUILDING-INTEGRATED SOLAR PHOTOVOLTAIC SYSTEMS

Abstract. A web-based multi-criteria decision support tool is designed to support the planning, control and deployment of building-integrated photovoltaic (BIPV) in the City of Cape Town, South Africa. Solar energy is one of the renewable sources for generating electricity by means of photovoltaic systems, and it offers a viable and expedient means of generating electricity within a short period of time. Nevertheless, there are some impediments to the extensive deployment of solar photovoltaic systems. The most prominent among these are generation potential and the high capital cost of initial set-up. Hence, the location, design and yield of building-integrated photovoltaic systems have to be well thought-out before their deployment. The interactive web-based tool designed utilises JavaScript and Hypertext Mark-up Language (HTML) to implement a map mashup, which can be queried to retrieve vital information about the solar photovoltaic potential of a building roof. From results generated and the system developed, it becomes possible to remotely and sufficiently evaluate buildings in the city in order to make decisions about solar photovoltaic potentials, designs and installations.

Are Clinical Decision Support Systems Compatible with Patient-Centred Care?

Few, if any, of the Clinical Decision Support Systems developed and reported within the informatics literature incorporate patient preferences in the formal and quantitatively analytic way adopted for evidence. Preferences are assumed to be 'taken into account' by the clinician in the associated clinical encounter. Many CDSS produce management recommendations on the basis of embedded algorithms or expert rules. These are often focused on a single criterion, and the preference trade-offs involved have no empirical basis outside an expert panel. After illustrating these points with the Osteoporosis Adviser CDSS from Iceland, we review an ambitious attempt to address both the monocriterial bias and lack of empirical preference-sensitivity, in the context of Early Rheumatoid Arthritis. It brings together the preference data from a Discrete Choice Experiment and the best available evidence data, to arrive at the percentage of patients who would prefer particular treatments from those in the listed options. It is suggested that these percentages could assist a GRADE panel determine whether to produce a strong or weak recommendation. However, any such group average preference-based recommendations are arguably in breach of both the reasonable patient legal standard for informed consent and simple ethical principles. The answer is not to localise, but personalise, decisions through the use of preference-sensitive multi-criteria decision support tools engaged with at the point of care.

Energy, carbon, and cost analysis of rural housing retrofit in different climates

A large portion of rural residential buildings in developing countries neglecting climate and the low construction quality has resulted in high-energy consumption in this sector. Besides, low economic power and awareness make it difficult to invest in energy upgrades in rural areas. Therefore, low-cost energy retrofit strategies are required to reduce energy levels and improve occupants living conditions while minimizing adverse environmental effects. This study aims to define optimum retrofit strategies for rural buildings based on their economic viability, environmental impact, and comfort benefits in the form of a multi-criteria decision support tool for retrofit projects in four represented climates of Iran.Three groups of retrofit strategies (architectural, constructional, and renewable) are modelled in four actual rural buildings in different climates. Environmental, economic, and comfort performance of each strategy is calculated via different indices by dynamic simulations. Energy consumption, carbon emission and cost (ECC) analysis are carried out. Different active and passive retrofit measures are evaluated via ECC.The main result of this study is a multi-criteria decision making tool for prioritizing retrofitting strategies in rural houses in different climates. According to results, the primary energy demand is reduced between 46 and 55%, the carbon emission is reduced between 40 and 51%, and thermal comfort levels are improved up to 23% in different climate zones.In line with the current market prices of Iran (high construction costs and low energy prices due to energy subsidies), the payback time for retrofit actions is not very appealing for the building owners. Thus, subsidizing should be dedicated to refurbishment strategies instead of energy. Also, widespread governmental supported programs should be administrated to educate and improve awareness, especially in low-income areas.

Multicriteria decision-support system to assess the potential of exclosure-based conservation in Ethiopia

AbstractLand degradation is a global challenge that affects lives and livelihoods in many communities. Since 1950, about 65% of Africa's cropland, on which millions of people depend, has been affected by land degradation caused by mining, poor farming practices and illegal logging. One-quarter of the land area of Ethiopia is severely degraded. As part of interventions to restore ecosystem services, exclosures have been implemented in Ethiopia since the 1980s. But the lack of tools to support prioritization and more efficient targeting of areas for large-scale exclosure-based interventions remains a challenge. Within that perspective, the overarching objectives of the current study were: (i) to develop a Geographic Information System-based multicriteria decision-support tool that would help in the identification of suitable areas for exclosure initiatives; (ii) to provide spatially explicit information, aggregated by river basin and agroecology, on potential areas for exclosure interventions and (iii) to conduct ex-ante analysis of the potential of exclosure areas for improving ecosystem services in terms of increase in above-ground biomass (AGB) production and carbon storage. The results of this study demonstrated that as much as 10% of Ethiopia's land area is suitable for establishing exclosures. This amounts to 11 million hectares (ha) of land depending on the criteria used to define suitability for exclosure. Of this total, a significant proportion (0.5–0.6 million ha) is currently under agricultural land-use systems. In terms of propriety river basins, we found that the largest amount of suitable area for exclosures falls in the Abay (2.6 million ha) and Tekeze (2.2 million ha) river basins, which are hosts to water infrastructure such as hydropower dams and are threatened by siltation. Ex-ante analysis of ecosystem services indicated that about 418 million tons of carbon can be stored in the AGB through exclosure land use. Ethiopia has voluntarily committed to the Bonn Challenge to restore 15 million ha of degraded land by 2025. The decision-support tool developed by the current study and the information so generated go toward supporting the planning, implementation and monitoring of these kinds of local and regional initiatives.

A multicriteria decision support tool for modelling bank credit ratings

We introduce an application of the SMAA-Fuzzy-FlowSort approach to the case of modelling bank credit ratings. Its stochastic nature allows for imprecisions and uncertainty that naturally surround a decision-making exercise to be embedded into the proposed framework, whilst its output complements the ordinal nature of a crisp classification with cardinal information that shows the degree of membership to each rating category. Combined with the SMAA variant of GAIA that offers a visual of a bank’s judgmental analysis, both recent approaches provide a holistic multicriteria decision support tool in the hands of a credit analyst and enable a rich inferential procedure to be conducted. To illustrate the assets of this framework, we provide a case study evaluating the credit risk of 55 EU banks according to their financial fundamentals.

A multi-criteria decision support tool for biorefinery siting: Using economic, environmental, and social metrics for a refined siting analysis

Facility siting has traditionally been performed using economic metrics alone to determine suitable locations for a new facility. In this era of climate change concerns and political discord, a more holistic approach to biorefinery siting may yield alternative locations that meet stakeholder goals for community acceptance and reduced environmental impacts. A multi-criteria decision support tool (DST) that incorporates economic, environmental, and social metrics concurrently is introduced to assess the repurpose potential of existing facilities as a wood-based biorefinery. Economic siting criteria are represented by biorefinery operational cost components that vary geospatially. The environmental criterion is the Global Warming Potential of the supply chain, as measured through greenhouse gases emitted from the feedstock procurement, preprocessing, and transport equipment. Social criteria are represented by 1) the number of regional jobs created through the installation of a biofuel supply chain, and 2) county-level social assets that may influence biorefinery project success. Weights and scale values are derived for each set of metrics. An overall facility score is produced by summing the three metric scores. Additionally, overall user-defined metric weights are used to adjust the importance of the three metrics, thus altering the overall facility scores. The DST is applied to a case study in Western Oregon and Western Washington to refine a list of candidate pulp mills down to a select few for further investigation. It was found that the mills scored differently when overall metric weights were adjusted. Therefore, different stakeholder preferences may yield a different priority list of facilities.

Temporal sustainability efficiency analysis of urban areas via Data Envelopment Analysis and the hypervolume indicator: Application to London boroughs

Abstract Transitioning towards a more sustainable society calls for systematic tools to assess the sustainability performance of urban systems. To perform this task effectively, this work introduces a novel method based on the combined use of Data Envelopment Analysis (DEA) and the hypervolume indicator. In essence, DEA is applied to (i) distinguish between efficient and inefficient urban systems through the identification of best practices; and to (ii) establish improvement targets for the inefficient urban systems that, if attained, would make them efficient. Meanwhile, the hypervolume indicator is employed in conjunction with DEA to evaluate how urban systems evolve with time. The capabilities of this approach are illustrated through its application to the sustainability assessment of London boroughs between 2012–2014. Results reveal that most boroughs tend to perform well in terms of the indicators selected, with 20–25 of the 32 boroughs found efficient depending on the year. Regarding the temporal assessment, a global improvement in sustainability performance was found, with a strong relationship between the boroughs’ performances and their locations. The method proposed opens new pathways of social and environmental research for the application of advanced multi-criteria decision-support tools in the assessment and optimisation of urban systems.

Social sustainable supplier evaluation and selection: a group decision-support approach

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.