Combinative Distance-based Assessment Research Articles

Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

This paper delves into the development and validation of the RAMDOE method, a pioneering approach in multi-criteria decision making (MCDM) that seamlessly integrates the root assessment method (RAM) and design of experiments (DOE) techniques, addressing the inflexibility of traditional MCDM methods in accommodating adjustments in criteria ranges and the addition of new alternatives without necessitating a complete overhaul of the decision framework. Through empirical analysis, the study demonstrates the RAMDOE method's remarkable efficacy in precisely ranking alternatives, as illustrated through a practical case study focused on the selection of a supplier from a pool of seven candidates. One of the most notable aspects of the RAMDOE method lies in its capacity to formulate a regression equation that accurately captures the intricate relationship between alternative scores and criteria values, enabling decision-makers to seamlessly integrate new alternatives into the decision-making process without the cumbersome task of recalibration, thereby distinguishing it from conventional MCDM techniques such as TOPSIS (technique for order of preference by similarity to ideal solution), COPRAS (complex proportional assessment), MOORA (multiobjective optimization on the basis of ratio analysis), EDAS (evaluation based on distance from average solution) and CODAS (combinative distance-based assessment). The practical implications of these findings are profound, offering decision-makers across various domains a more efficient and adaptable framework to navigate complex decision scenarios. Particularly in contexts like supplier selection, where criteria ranges may vary significantly, the RAMDOE method provides decision-makers with a robust toolset to make informed decisions, presenting a promising avenue for addressing the dynamic nature of decision-making environments and enhancing the overall robustness and flexibility of MCDM processes in real-world applications

Proportional intuitionistic fuzzy CODAS method: Cloud service provider selection application

Intuitionistic fuzzy sets aims at taking the hesitancy of an expert into account in assigning a membership degree or a non-membership degree. The direct assignment of decimal numbers for membership and non-membership degrees of an element in intuitionistic fuzzy sets is not practical. Besides, the assigned degrees are generally composed of one digit or at most two digits after dot. This problem has not been addressed as much as it deserves in the literature. The hypothesis of the paper is that the determination of proportional relationships between membership and non-membership degrees is more appropriate than the direct assignment to obtain the degrees. Proportional intuitionistic fuzzy (PIF) sets require only the proportion relations between an intuitionistic fuzzy set’s parameters. The accuracy of the results obtained with multi-criteria decision-making models definitely depends on how accurately the membership degrees are determined. In this paper, we extend Combinative distance-based assessment (CODAS) method by using single-valued proportional intuitionistic fuzzy sets. We compare the proposed PIF CODAS method with ordinary fuzzy CODAS method. A cloud service provider selection problem is handled to show the validity of the proposed PIF CODAS method. Additionally, a comparative analysis and a sensitivity analysis together with a discussion are presented.

Combinative distance-based assessment method using linguistic T-spherical fuzzy aggregation operators and its application to multi-attribute group decision-making

Clean energy has become a hot topic worldwide because of the continuous rise in the climate's temperature. Reduced air pollution is only one of the many economic and environmental advantages of clean energy. An effective contractor with experience and knowledge in clean energy projects is always required to handle the complicated process of planning, implementing, and maintaining the new clean energy infrastructure. Contractor selection for renewable energy projects (REPs) is a multi-attribute group decision-making (MAGDM) problem. Linguistic T-spherical fuzzy set (LT-SFS) can be compatible with fuzzier information, and the contractor selection problem also has a lot of fuzzy information, which makes LT-SFS very suitable for contractor selection for REPs. Hence, the present work proposes a MAGDM methodology utilizing a combinative distance-based assessment (CODAS) method within the LT-SF context. For that, the Einstein and Frank t-norm and t-conorm has been used to define new and generalized operational laws for linguistic T-spherical fuzzy numbers. Then, the linguistic T-spherical fuzzy Einstein and linguistic T-spherical fuzzy Frank aggregation operators are proposed to integrate the information data provided by experts. Moreover, the proposed aggregation operators based-CODAS approach is designed to evaluate and rank the available alternatives. A real-life decision problem of selecting the best suitable contractor for a renewable energy project is solved to verify our suggested technique. Moreover, the sensitivity analysis is also carried out by changing the parameter's value to check the consistency of the rank order. Finally, the new model is compared with existing approaches to demonstrate its strength. The comparative analysis shows that the results of the suggested technique are more feasible and beneficial than those of existing approaches.

An ideal plastic waste management system based on an enhanced MCDM technique

The Fermatean probabilistic hesitant fuzzy set (FPHFS) concept is a method that combines Fermatean fuzzy sets and PHFS to provide detailed MCDM problem solutions. The management of solid waste is facing challenges in disposing of environmentally harmful plastic products. The study primarily focuses on plastic waste from the packaging industry, as it is the primary contributor to overall waste generation. The packaging sector has proposed a concept for the recycling of waste at various levels. This study aims to assess the effectiveness of the hybrid analytic hierarchy process and the combinative distance-based assessment (AHP-CODAS) method FPHFS in determining the most suitable plastic waste collection system. The AHP analysis identified the most effective methods for collecting plastic waste for recycling, emphasizing successful segregation for efficient recycling. A deposit and refund system promotes waste collection and a circular economy by facilitating efficient waste management. The research offers valuable insights into selecting packaging waste collection (PWC) technology in uncertain environments and enhances decision-making methods in the field.

A group decision framework for core competitiveness evaluation of small and medium-sized foreign trade enterprises under probabilistic linguistic term sets

Since the reform and opening up, China’s foreign trade has developed rapidly. The import and export trade volume has doubled, and the team of foreign trade enterprises is constantly expanding. After China’s accession to the WTO and the liberalization of foreign trade management rights, a group of small and medium-sized foreign trade enterprises have grown up in recent years and are becoming a new force in the development of China’s foreign trade industry. So, how to make these enterprises grow and grow in the international market competition, and focus on cultivating the core competitiveness of small and medium-sized foreign trade enterprises, has become a strategic issue related to the overall development of foreign trade. Recently, COmbinative Distance-based ASsessment (CODAS) method computes the Euclidean distances as the primary measure and Hamming distances as the secondary measure to assess alternatives based on predetermined attribute. Moreover, the probabilistic linguistic term sets (PLTSs) are effective tool for depicting uncertainty of the multiple attribute group decision making (MAGDM) problems. The core competitiveness evaluation of small and medium-sized foreign trade enterprises is a classical MAGDM. In this paper, the CODAS method is extended to the MAGDM with PLTSs. Firstly, the definition of PLSs is introduced. Then, on the basis of the classical CODAS method, the PL-CODAS method is proposed to cope with MAGDM under PLTSs and its significant characteristic is that it can fully consider PLED and PLHD. Finally, a practical example for core competitiveness evaluation of small and medium-sized foreign trade enterprises is given to verify the developed approach and some comparative analysis was also given to verify the PL-CODAS approach.

Sustainable waste valorization process selection through AHP and advanced Interval Valued Fermatean Fuzzy with integrated CODAS

The sustainable waste valorization process selection is a complex process in real life scenarios. In this study, a comprehensive evaluation of biological and thermal valorization processes is performed. The Interval Valued Fermatean Fuzzy Set (IVFFS) methodology with the integration of the Dombi Operator (DO), is applied combining with the Analytical Hierarchy Process (AHP). This analysis considered four distinct municipal solid waste (MSW) valorization processes—anaerobic digestion (AND), gasification, pyrolysis, and hydrothermal gasification (HTG)—assessing their effectiveness based on economic, environmental, technological, and social-governance criteria through IVFFS with Dombi Operator (DO). Advanced Combinative Distance-Based Assessment (CODAS) was applied for ranking these processes based on expert opinions and existing literature on the subject. According to the IVFFS assessment results, the thermal valorization technique gasification identified as the sustainable process with assessment score (As) of 0.063, followed by pyrolysis and HTG with As of 0.009 and −0.033, respectively. The threefold validation, encompassing weights variation, rank reversal, and changing DO value, consistently supported the finding that gasification stands out as the most sustainable process. Finally, policy implications derived from this study findings offer valuable guidance for policymakers seeking to endorse and promote these sustainable waste valorization processes in developing countries.

Evaluation of the Contaminated Area Using an Integrated Multi-Attribute Decision-Making Method

Air pollution affects public health and the environment, creating great concern in developed and developing countries. In India, there are numerous reasons for air pollution, and festivals like Diwali also contribute to air contamination. Determining the polluted region using several air contaminants is significant and should be analyzed carefully. This study aims to analyze the air quality in Tamil Nadu, India, during the Diwali festival from 2019 to 2021, based on multiple air pollutants. The study models the impact of air pollution as a Multi-Attribute Decision-Making (MADM) problem. It introduces a hybrid approach, namely the Analytical Hierarchy Process-Entropy-VlseKriterijumska Optimizacija I Kompromisno Resenje (AHP-Entropy-VIKOR) model, to analyze and rank the areas based on the quality of air. A combined approach of AHP and entropy is employed to determine the weights of multiple air pollutants. The VIKOR approach ranks the areas and identifies the areas with the worst air quality during the festival. The proposed model is validated by performing the Spearman’s rank correlation with two existing MADM methods: Combinative Distance Based Assessment (CODAS) and Weighted Aggregates Sum Product Assessment (WASPAS). Sensitivity analysis is carried out to assess the effects of the priority weights and the dependency of the pollutants in ranking the regions. The highest air pollution level during the festival was seen in Cellisini Colony (2019), Rayapuram (2020), T. Nagar and Triplicane (2021) in their respective year. The results demonstrate the consistency and efficiency of the proposed approach.

Green logistics park location selection with circular intuitionistic fuzzy CODAS method: The case of Istanbul

In this study, it is aimed to integrate CODAS method with circular intuitionistic fuzzy sets as a new solution method for MCDM problems. Containing a radius notation with degrees of central membership and non-membership degrees is the main advantage of circular intuitionistic fuzzy in decision making. On the other side, Combinative Distance-based Assessment (CODAS) method contains many advantages such as basing on two types of distance calculations (Euclidean and Taxicab distances) comparing with other MCDM methods. When the advantages of circular intuitionistic fuzzy sets and CODAS method are considered, proposed circular intuitionistic fuzzy CODAS method (CIFS-CODAS) presents many superiorities compared to other MCDM techniques. By this way, an application for green logistics park location selection will be handled by using CIFS-CODAS to show the validity of the methodology. After, a comparative analysis with intuitionistic fuzzy CODAS (IFS-CODAS), intuitionistic fuzzy TOPSIS (IFS-TOPSIS) and intuitionistic fuzzy EDAS (IFS-EDAS) methods will be performed for green logistics park location selection problem to confirm the robustness of presented method. Green logistics and Green Deal are also emphasized considering environmental factors as a scope of the article. Finally, the results will be evaluated in the context of the logistics sector and green logistics.

Evaluation of trustworthy artificial intelligent healthcare applications using multi-criteria decision-making approach

The purpose of this paper is to propose a novel hybrid framework for evaluating and benchmarking trustworthy artificial intelligence (AI) applications in healthcare by using multi-criteria decision-making (MCDM) techniques under a new fuzzy environment. To develop such a framework, a new decision matrix has been built, and then integrated with q-ROF2TL-FWZIC (q‐Rung Orthopair Fuzzy 2‐Tuple Linguistic Fuzzy-Weighted Zero-Inconsistency) and q-ROF2TL-CODAS (q‐Rung Orthopair Fuzzy 2‐Tuple Linguistic Combinative Distance-Based Assessment). In this integration, q-ROF2TL-FWZIC is utilized for assigning the weights of evaluation attributes of trustworthy AI, while q-ROF2TL-CODAS is employed for benchmarking trustworthy AI applications. Findings show that the q-ROF2TL-FWZIC method effectively weights the evaluation attributes. The transparency attribute receives the highest importance weight (0.173566825), whereas the human agency and oversight criterion has the lowest weight (0.105741901). The remaining attributes are distributed in between. Moreover, alternative_4 receives the highest rank order (score of 7.370410417), while alternative_13 receives the lowest rank order (score of −4.759794397). To evaluate the validity of the proposed framework, systematic ranking and sensitivity analysis assessments were employed.

CODAS method for Pythagorean 2-tuple linguistic multiple attribute group decision making

The evaluation of the financial performance of universities is conducive to the sustainable development of universities. Based on this, we extend the traditional CODAS (COmbinative Distance-based ASsessment) method to the Pythagorean 2-tuple linguistic fuzzy environment and propose a P2TL-CODAS model to evaluate the financial management performance of universities. Firstly, we briefly describe the definition, the score function, accuracy function, operational laws and the distance calculating method of P2TLSs. Next, two aggregation operators of P2TL including Pythagorean 2-tuple linguistic weighted averaging (P2TLWA) operator and Pythagorean 2-tuple linguistic weighted geometric (P2TLWG) operator are also introduced to fuse overall Pythagorean 2-tuple linguistic evaluation information. Then the steps of CODAS method are depicted briefly. Moreover, we use linguistic Pythagorean 2-tuple linguistic fuzzy numbers to extend the CODAS method. The P2TL-CODAS model is established and all computing steps are simply presented. Furthermore, we apply the proposed method to evaluate the financial management performance about five universities. Finally, a comparison between P2TL-CODAS method and P2TL-TODIM method is made to demonstrate the stability of the new method. The results show that the proposed method has unique advantages.

Prioritizing solutions to mitigate the risks due to adoption of intermodal railroad freight transportation for achieving sustainable development goals

Multiple cleaner strategies are being devised by governments worldwide to incorporate approaches aligning with sustainable development goals (SDGs), placing particular emphasis on the modal shift from unimodal road to intermodal railroad (IRR) freight transportation. This shift is gaining traction due to its documented positive impact on environmental, economic, and social sustainability. However, adopting IRR freight transportation in emerging economies faces hurdles, primarily attributable to inherent modal shift risks (MSRs). Addressing these MSRs requires the implementation of modal shift solutions (MSSs). This study aims to prioritize the MSSs to mitigate the impact of MSRs in IRR adoption, focusing on achieving SDGs with a case study conducted in the Indian logistics sector. The study is structured into four phases. The first phase identifies 37 sub-MSRs, categorized into seven main MSRs, accompanied by the 39 MSSs for IRR freight transportation adoption. The second phase employs the spherical fuzzy Bayesian best-worst method (SF-BBWM) to assess the relative weights of main and sub-MSRs. The third phase uses the spherical fuzzy C-means clustering (SF-CMC) algorithm to identify crucial MSSs. Finally, the fourth phase utilizes the spherical fuzzy combinative distance-based assessment (SF-CODAS) to prioritize these crucial MSSs. From the identified MSSs, pivotal solutions include developing an integrated physical IRR network across the freight transport chain and fostering relationships between stakeholders through long-term contracts and strategic partnerships. The available results are discussed to facilitate logistics stakeholders’ understanding of the implementation of MSSs aligning with SDGs to mitigate the impact of MSRs.

Decision Support System Analysis of School Promotion Media Selection using MABAC, OCRA And CODAS Methods

School promotion is an activity to communicate educational products to consumers or prospective students. Promotional activities require strategic policies in order to maximize promotional results, therefore analysis of the selection of appropriate promotional media needs to be done. Multi-Attributive Border Approximation area Comparison, Operational Competitiveness Rating Analysis, COmbinative Distance-based Assessment in decision support system with case study at SMK Airlangga Balikpapan. MABAC, OCRA and CODAS are used in the calculation process that produces output in the form of promotional media ranking to be recommended to the school promotion team as a consideration for selecting the right promotional media. Alternative promotional media used in this research are brochures, posters, billboards, banners and newspaper advertisements. Based on the results of the research, the MABAC, OCRA and CODAS methods can be applied to the school promotion media selection decision support system and can produce output in the form of a priority ranking of school promotion media

A novel CODAS approach based on Heronian Minkowski distance operator for T-spherical fuzzy multiple attribute group decision-making

T-spherical fuzzy sets (TSFSs) are more flexible and efficient tools to deal with ambiguous, uncertain and vague information in complex real-world decision-making problems than various extended intuitionistic fuzzy sets. This paper aims to develop a novel T-spherical fuzzy (TSF) Combinative Distance-Based ASsessment (CODAS) based on the Heronian Minkowski distance aggregation operator, this new method can capture interrelationship between input arguments. Some TSF weighted Heronian Minkowski distance (TSFWHMD) aggregation operators with generalization are developed based on Heronian mean and Minkowski-type distance, their properties are discussed as well as their families are analyzed. Furthermore, the TSF MAGDM methodology based on the improved CODAS is designed, where the Minkowski-type distance is used to define the TSF similarity for computing the expert weights and to construct the maximizing deviation method (MDM) for determining the attribute weights, respectively. The TSF ordered weighted Heronian Hamming distance (TSFOWHHD) and TSF ordered weighted Heronian Euclidean distance (TSFOWHED) operators derived from the TSFOWHMD operator are integrated into the CODAS method, which is an improved method for both measuring the deviation of the negative ideal solution from each alternative and capturing the correlation between attributes. Finally, the feasibility and practicality of developed methodology are illustrated with an example of CAE (Computer Aided Engineering) software selection for lithium-ion power battery (LiPB) design, sensitivity analysis and method comparisons are performed to elucidate the reliability and validity of the developed methodology.

Evaluation of sustainable development and utilization-oriented renewable energy systems based on CRITIC-SWARA-CODAS method using interval valued picture fuzzy sets

Multi-criteria decision making (MCDM) methods used to overcome complex real-life problems is the process of finding the most suitable alternative among alternative options under multiple tangible or intangible criteria. In particular, the use of MCDM methods is an important tool for policy makers, managers and decision makers (DMs) to easily and effectively address today's MCDM problems such as renewable energy. However, since the classical MCDM methods are based on crisp numerical values, they are insufficient when considering insufficient information about the systems, complex environment and real-life conditions. Especially since many real-life problems within the scope of sustainability contain uncertain information, using them together with fuzzy sets is extremely important for making the right decisions. This study presents a new model based on the interval-valued picture fuzzy (IVPF)-MCDM integrated approach in an environment of uncertainty for the evaluation of sustainable development and utilization oriented renewable energy systems. In the study, firstly, renewable energy alternatives focused on sustainable development and utilization for Turkey and the criteria affecting them have been determined. Secondly, for the objective and subjective weights of the criteria, the CRiteria Importance Through Intercriteria Correlation (CIRITIC) and Stepwise Weight Assessment Ratio Analysis (SWARA) methods have been extended to interval-valued picture fuzzy sets (IVPFSs), respectively, and the weights have been obtained. Then, the weights have been combined by the coefficient parameter determined by the expert. Later, the COmbinative Distance-based ASsessment (CODAS) method has been extended to IVPFSs to rank renewable energy alternatives focused on sustainable development and use under uncertainty. A comprehensive sensitivity analysis has been conducted to confirm the stability and effectiveness of the method. Moreover, a comparative analysis has been presented with other MCDM methods in the literature showing the superiority and advantages of the developed method.

Fermatean Fuzzy Group Decision-Making Based CODAS Approach for Taxation of Public Transit Investments

The provision of public goods is always a controversial issue in many aspects. Even some additional financial resources can provide public transit systems, the tax revenues constitute a significant part of the investments in practice. Yet, governments should make an important decision regarding tax schemes. This article focuses on how to identify the best tax scheme to finance public transit investments. A three-phase Fermatean fuzzy group decision-making approach is developed to solve the highlighted problem. Qualifications and experience of experts are considered to distinct their reputations. A Fermatean fuzzy direct rating method is introduced to evaluate criteria importance. A Fermatean fuzzy combinative distance-based assessment method is formulated to assess tax schemes. The study provides valuable policy implications and decision-making guidelines using a real-life case. The results show that beneficiaries of public services should pay more, and tax collectors are encouraged to use progressive tax schemes instead of the equal distribution of the cost to the taxpayers. The sensitivity analysis to changes in the threshold parameter is given. The comparative analysis with all state-of-the-art Fermatean fuzzy set based multicriteria decision-making methods is provided. The Fermatean fuzzy group decision-making approach is highly robust and reliable. The approach can solve other public transportation problems.

Enhancing risk factor evaluation for infectious diseases using decision-making approach based on linear programming

Infectious diseases are defined as the invasion of hazardous agents into the human body that causes injury and has the potential to spread to others. These diseases cause a considerable proportion of illnesses and deaths in any given community. The criteria importance through inter-criteria correlation (CRITIC) approach is used to determine the relative importance of multiple assessment criteria, whereas combinative distance-based assessment (CODAS) is a methodology used to compare and evaluate the efficacy of numerous options. The CRITIC-CODAS method is a linear programming-based tool for estimating the risks of infectious diseases. This method takes into account a number of aspects, including the disease’s characteristics, the population at risk, and the available resources for prevention and treatment. The CRITIC-CODAS technique can provide valuable insights into the possible impact of an infectious disease outbreak and aid in improving decision-making regarding prevention and control measures by assessing these elements in a systematic and quantitative manner. The purpose of this work is to provide an overview of the CRITIC-CODAS technique, which is powered by a q-rung orthopair fuzzy set (q-ROFS), and its use in estimating the risk of infectious disease outbreaks. According to the case study, the infectious disease malaria has a greater possibility of spreading in the city under observation. According to the proposed method, the ranking of infectious cities given as ℐ3ℷ≻ℐ4ℷ≻ℐ5ℷ≻ℐ2ℷ≻ℐ1ℷ. This implies that the likelihood of an epidemic of the infectious disease ℐ3ℷ is higher in the city being observed. The study also addresses the approach’s benefits and shortcomings and makes recommendations for further research and development. Overall, the CRITIC-CODAS approach appears to be a useful tool for better understanding infectious disease risks and guiding appropriate response tactics.

Improvising CODAS method functionalized with grey numbers to improve the performance of PVD titanium carbon nitride (TiCN) thin film coating: a novel approach

This experimental study focuses on the deposition of TiCN thin film coating onto a bare p-type silicon substrate using physical vapor deposition (PVD) processes, with varying process parameters. The study employed a design of experiment in accordance with the L 16 orthogonal Array, followed by the implementation of the combinative distance-based assessment (CODAS) method functionalized with grey numbers to enhance the performance of the PVD process for the very first time in the film of thin film deposition. The study also conducted various analyses to examine the coating’s properties, including morphological, structural, microstructural, electrochemical, and mechanical properties. According to the result, the morphology of the coating was wavy in nature, with a smooth microstructure and a few agglomerated particles. The structure of the film indicated that TiCN had a single-phase FCC structure, while the mechanical and electrochemical properties improved with higher N2 flow rates. Additionally, the analysis by CODAS method functionalized with grey numbers suggested that substrate to target distance = 50 mm, N2 flow rate = 25 sccm, and bias voltage = −120 V were the most suitable condition for obtaining the best quality of TiCN thin film coating.

A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets

Reviewing and integrating decisions in the supply chain and project management is crucial. This problem is known as a project-driven supply chain problem. By the growing dependency of project-driven companies on suppliers since they prefer to concentrate on their core and subcontracting processes, the project-based organization's dependence on suppliers has increased. A project-driven supply chain (PDSC) focuses on integrating project management activities into the supply chain. In this paper, a new model is presented for the integration of supply chain and project management decisions. Firstly, a new method is proposed to determine the resilience score of suppliers. This new model consists of three parts: the weighting of criteria, the weighting of experts, and the ranking of suppliers. To give weight to the experts, a new version of the combinative distance-based assessment (CODAS) method is presented based on the average and positive ideal concepts. Also, the importance of the criteria is specified by an expanded best-worst method (BWM). Computing the resilience score of suppliers is done through a developed CODAS method that is extended by the average and positive concepts. Furthermore, in order to consider the uncertainty of project-driven supply chain problems, interval type-2 fuzzy sets (IT2FSs) are used. Secondly, a new subtraction operation is defined to avoid producing negative in recursive critical path method (CPM) calculations in the IT2F environment. Also, the criticality score of the project's activities is defined. According to the criticality and resilience indexes of activities, suggestions are made to project management to prevent delays. Finally, a case study of hospital construction is solved to illustrate the strengths of the proposed model.

Toward sustainable development: Developing a decision‐making framework for cross‐sectoral engagement in green procurement

AbstractGreen procurement plays a crucial role in mitigating emissions, promoting sustainable practices, and achieving the objectives of keeping global warming below the 2°C threshold. However, the implementation of green procurement faces significant challenges. Despite the recognized importance of sectoral collaboration, cross‐sectoral engagement (CSE) has not yet been widely acknowledged as an essential principle in green procurement implementation. This study aims to address these implementation challenges by developing a comprehensive decision‐making framework for CSE in public–private partnership projects, with a focus on advancing sustainable development goals. The research identifies and prioritizes barriers to CSE from multiple theoretical perspectives, employing an integrated approach that combines the Method Based on the Removal Effects of Criteria (MEREC) and the Combinative Distance‐Based Assessment (CODAS) method. The results reveal three primary factors hindering cross‐sectoral engagement: conflicting stakeholder interests and priorities, power imbalances, and communication gaps and language barriers. To promote effective collaboration, policymakers are urged to invest in capacity building initiatives that enhance stakeholders' understanding of green procurement principles and encourage their active participation in achieving sustainable development objectives. Theoretically, this study has, for the first time, developed a CSE framework that can be used to promote green practice implementation, integrate four theories to holistically access barriers to cross‐sectoral collaboration, and show the integration of the MEREC CODAS MCDM technique.

Six Sigma Project Prioritization and Selection Using AHP–CODAS Integration: A Case Study in Healthcare Industry

Given the complex nature of Six Sigma project (SSP) prioritization and selection processes, multicriteria decision-making (MCDM) methods may help organizations identify the most effective projects. Considering potential limitations of subjective methods and advantages of MCDM methods, this article proposes a model that integrates analytical hierarchy process (AHP) and combinative distance-based assessment (CODAS) in SSP prioritization and selection process. In the proposed approach, AHP is employed to assign criteria weights, and CODAS is performed to determine priorities of SSPs. CODAS was advanced in term of its threshold function. Differences between Euclidean distances of two alternatives were compared, based on the standard deviation of Euclidean distances of all alternatives to overcome the subjectivity. This is the first study that combines AHP and CODAS methods for SSP selection, and CODAS is used with objective threshold value computation, and developed for the healthcare industry. In this article, ten SSPs were evaluated for four key criteria groups as financial, operational, patient centric, and organizational main criteria groups. In total, 18 subcriteria were considered under these four main criteria groups. This article provides a support for executives who make implementation plans for the potential SSPs.