Multi-criteria Decision-making Approach Research Articles

Evaluation of carbon sink and photovoltaic system carbon reduction along roadside space

As China's photovoltaic (PV) sector experiences rapid growth, the availability of land resources has become a pivotal policy focus, driving the need for comprehensive research and strategic planning for roadside PV initiatives. Utilizing a fuzzy multi-criteria decision-making approach, combined with GIS spatial analysis and a modular design framework, our study quantitatively compared the carbon reduction capabilities of PV systems against the carbon sequestration potential of various vegetative arrangements along the roadside space. The roadside space analysis modular considers a range of factors including topography, meteorology, and construction costs. We examined the spatial distribution of suitability for PV installation and vegetation establishment along the provincial expressway network in China. The results revealed that Inner Mongolia stood out as the frontrunner in carbon reduction potential within high-suitability zones for PV construction, achieving an impressive 4.845 million tons of carbon reduction—nearly four times greater than that of Shaanxi Province. In contrast, the carbon sequestration attributed to vegetation greening in areas less suited for PV development revealed a higher propensity in the southeastern provinces. Guangdong led the charge with an impressive annual carbon sequestration of 2.89 million tons. This was closely followed by Yunnan, Sichuan, Hebei, Guizhou, and Henan, each achieving carbon sequestration amounts exceeding 2 million tons. These results offer valuable quantitative support and practical recommendations for achieving low-carbon objectives in the construction of China's expressways.

Assessing the Challenges to Leverage Carbon Markets for Renewable Energy in Developing Countries: A Multi-Criteria Decision-Making Approach

Assessing the Challenges to Leverage Carbon Markets for Renewable Energy in Developing Countries: A Multi-Criteria Decision-Making Approach

Assessing Southeast Asia countries’ potential in the semiconductor supply chain: an objectively weighting multi-criteria decision-making approach

The semiconductor industry serves as a key enabler of technological progress and economic growth on a global scale. With Southeast Asia emerging as a region of increasing importance in the global supply chain landscape, understanding the potential for its countries to participate in the semiconductor supply chain becomes crucial. Despite extensive research on global supply chain dynamics, a focused analysis on the role of Southeast Asia within this crucial industry has been notably absent, particularly considering recent geopolitical and economic shifts. This gap has been filled by employing a rigorously designed Multi-Criteria Decision Making (MCDM) approach that integrates the Criteria Importance Through Intercriteria Correlation (CRITIC) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Data on fifteen indicators, including economic stability, technological innovation capacity, and infrastructural capabilities, were collected and identified through an extensive literature review and consultations with stakeholders. These indicators were weighted using the CRITIC method to reflect their relative importance, and each country’s position relative to an ideal solution was assessed using the TOPSIS method. It was revealed that countries such as Singapore and Malaysia possess significant potential due to their advanced technological infrastructure and stable economic environments. Other countries, like Vietnam and Indonesia, were also found to exhibit promising capabilities, albeit with certain limitations. The study highlights the varying strengths and strategic areas that should be considered by policymakers and investors to enhance integration into the global semiconductor supply chain. Significant contributions to the strategic decision-making process have been made by providing a nuanced analysis of the region’s readiness and identifying specific areas for investment and policy intervention. By offering a methodological framework that can be adapted to other regions and sectors, not only has an existing research void been filled, but the practical understanding of effectively leveraging Southeast Asia’s potential in the semiconductor industry has also been enhanced.

A hybrid multi-criteria decision-making approach for hospital sustainability performance assessment

PurposeNowadays, the sustainability of healthcare services is of increasing importance. In particular, hospitals have ceased to be only treatment-oriented institutions and have begun to operate on the principles of sustainability in their environmental, economic and social dimensions. In this context, a comprehensive method is required to evaluate and improve the performance of hospitals.Design/methodology/approachIn this study, it is recommended to combine D-DEMATEL (D number theory and decision-making trial and evaluation laboratory methods) and objectives matrix (OMAX) methods, which are two important methods in determining hospital performance. D-DEMATEL is a technique used to analyze complex relationships and interactions that reduces subjective judgments because it is based on the opinions of many decision-makers and can be applied even in cases of incomplete information. OMAX, on the other hand, provides a comprehensive framework for measuring performance and allows different performance indicators to be evaluated together.FindingsThe novel performance assessment model is applied to a hospital in real life. Its performance value, according to 36 determined performance indicators, is calculated at 56.91%. The indicators of the hospital that need improvement are defined by the traffic light system method. The performance indicator importance ranking of D-DEMATEL is compared to the ranking obtained by the fuzzy DEMATEL method.Originality/value Important indicators to be used in later sustainable hospital performance evaluation studies were determined. Also, an integrated D-DEMATEL and OMAX method for evaluating sustainable hospital performance is presented.

A comprehensive assessment of working fluids selection in heat pipe-assisted battery thermal management systems: An integrated Multi-criteria decision-making approach

A comprehensive assessment of working fluids selection in heat pipe-assisted battery thermal management systems: An integrated Multi-criteria decision-making approach

Prioritization of investment order in Brazil among renewable energy sources: an analysis using the SWARA-MOORA-3NAG method

Purpose This paper aims to comprehensively analyze renewable energy alternatives in Brazil, focusing on identifying the most suitable option for investment in the country’s sustainable development. Design/methodology/approach The study adopts the step-wise weight assessment ratio analysis-multiobjective optimization by ratio analysis −3NAG (a combination of three normalization methods) methodology, a multicriteria decision-making approach, to evaluate and rank renewable energy sources based on key criteria such as resource availability, cost-effectiveness, job creation potential and environmental impact. Findings The analysis reveals that solar energy emerges as the preferred choice for Brazil, offering significant advantages over other alternatives such as hydroelectric, wind and biomass energy. Solar energy’s distributed generation capability, cost reduction trends and positive environmental impact contribute to its favorable position in meeting Brazil’s energy needs. Research limitations/implications While the study provides valuable insights into renewable energy selection, there are limitations regarding the criteria’ scope and the exclusion of specific renewable energy options. Future research could explore sensitivity analyses and incorporate additional criteria to enhance the study’s comprehensiveness. Originality/value This research contributes to the existing literature by thoroughly analyzing renewable energy alternatives in Brazil using a robust multicriteria decision-making methodology. The study’s findings provide actionable guidance for policymakers, businesses and stakeholders seeking to promote sustainable energy development in the country.

Traditional and Integrated MCDM Approaches for Assessment and Ranking of Laser Cutting Conditions

Multiple benefits and advantages that offer laser cutting technology are difficult to achieve if the laser cutting parameter conditions are not adequately set. Determining laser cutting conditions is not trivial task considering large number of controllable inputs, existence of multiple process performances which are often mutually opposed as well as effects of noise factors. Different scientific methods and engineering approaches represent more sophisticated approaches which aid assessment and determination of the most favourable (optimized) cutting conditions. This study is focused assessment and ranking of laser cutting conditions in CO2 laser cutting of AISI 316L stainless steel. Based on kerf width and surface roughness experimental data and estimation of material removal rate (MRR) and total variable costs, four criteria in the multi-criteria decision making (MCDM) model were considered. For solving the developed model, six well-known MCDM methods were applied, and in addition, in order to overcome ranking inconsistency, robust decision-making rule was developed upon which final ranking was obtained.

Technical feasibility and modeling of enzymatic pre-treatments of organic fraction of municipal solid waste to improve anaerobic digestion

The study explored the combined effects of enzymatic pre-treatment and anaerobic digestion (AD) on the organic fraction of municipal solid wastes (OFMSW) through experimental and multicriteria decision-making approaches. Five enzymes (UPP2, MPCS, USC4, USE2, and A. niger) and their dosages were studied. AD parameters included two inoculum origins (waste active sludge - WAS - and cow-agricultural sludge - CAS), the substrate: inoculum (SI) ratio, and inoculum incubation time (INOC). Desirability functions were used to optimize the multiple experimental responses simultaneously by converting each of them into values from 0 (unacceptable) to 1 (completely acceptable) and then combining these into a global desirability (D). D highlighted that higher enzyme dosages, INOC, and SI, improved AD performances, with optimal DOSE (at the highest level adopted for each enzyme) and INOC (5–10 d). AD tests with the five enzymes increased CH4 production by 10–13%v/v compared to untreated OFMSW. For UPP2 and MPCS, increasing DOSE boosted the biogas production, while increasing INOC enhanced the CH4 content. MPCS reached the highest efficiency (478. 43 NL CH4/kg VS with CAS, SI = 2:1, INOC = 10 d), followed by UPP2. Furthermore, higher INOC reduced A. niger doses, increasing CH4 production by 9%v/v compared to literature, with 5–10 d INOC (452.86 NL s/kg VS with WAS, SI = 2:1).

Integrated analytic hierarchy process and multi-criteria decision-making approach: An Application for Unmanned Underwater Vehicle Control Method Selection

Using Multi-Criteria Decision Analysis (MCDA) techniques, it is possible to thoroughly examine all available options and determine the most desirable ones. However, the prevalence of these methods, which employ various computational changes, can result in disparate outcomes. Therefore, the final rankings should be as dependable and consistent as possible. In this study, the consistency of the findings obtained from the TOPSIS, COPRAS, MAUT, and MOOSRA methodologies was investigated in the real-world problem of Unmanned Underwater Vehicle Control Method Selection by forming decision matrices through simulations.

An integrated multi-criteria decision-making approach for life cycle approach in road construction projects

An integrated multi-criteria decision-making approach for life cycle approach in road construction projects

Ranking and Challenges of Supply Chain Companies Using MCDM Methodology

Background: Supply chain companies have merits and demerits regarding operational and economic transactional policies. The effectiveness of supply chain companies corresponds to a cumulative score on a multi-criteria and perspectives-based evaluation. In this paper, we analyse the performances and challenges of several celebrated e-commerce companies to perceive their overall impression of supply chain management. Method: A mathematical model is framed as a multi-criteria decision-making (MCDM) problem with challenges as criteria and companies as alternatives. The criteria importance through inter-criteria correlation (CRITIC) method is used in this paper to adjust weights representing the available data. The ranking of e-commerce companies is evaluated using multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method. Results: This model investigates the most dependent criteria and sub-criteria for the adaptation challenges of supply chain companies (SCCs). Furthermore, the SCCs are prioritized based on various conflicting criteria. Conclusion: Various challenges of SCCs, like logistics constraints, disruptions in supply chains, issues with technology, ethical sourcing and inconsistency between the products’ availability and the pace of consumption, are considered and analysed. We amassed the difficulties as criteria and sub-criteria in a numerical process using the MCDM approach. Additionally, the sensitivity and comparative of several optimal phenomena are analysed based on distinctive combinations of challenges in the ranking arena.

Analyzing the role of social media in addressing public health development in india through a multi-criteria decision-making approach

Nowadays, social media plays a vital role in managing public health developments. This research study has analyzed the factors of social media enhancing public health development. The analytic hierarchy process (AHP) is used to rank the factors, and the Decision-making trial and evaluation laboratory (DEMATEL) is used to find out the network relationship map of the role of social media in public health development. Results of AHP revealed that social media enhances public engagement and participation, collaboration of health professionals worldwide, and helps in remote monitoring of patients. Results of DEMATEL show that the development of health policies, repository of public health-related information, and prevention of health-related misinformation and fake news are classified as the topmost causal factors. Real-time monitoring of health conditions is the factor with the most significant impact on other factors. Policymakers and stakeholders should focus on improving public health through social media. Social media enhances collaboration among health professionals worldwide, and various stakeholders use it to address public health issues in the case of COVID-19.

Beyond tradition: charting a greener future for cassava starch industry using multi-criteria decision-making

Cassava, a staple food crop, is widely used for starch production, but its inconsistent supply, price volatility, and substantial waste generation pose challenges to the cassava industrial market's growth. This study aims to identify a sustainable biorefinery pathway by optimizing conventional cassava starch plants (business-as-usual, BAU) for economic and environmental benefits. Four scenarios were evaluated: animal feed from peel waste (Scenario 1), fungal protein from thippi waste (Scenario 2), fish feed from digested wastewater (Scenario 3), and conversion of all waste streams into animal feed, fish feed, and fungal protein (Scenario 4). Scenario 4 emerged as the best pathway using the multi-criteria decision-making (MCDM) approach, with a performance score of 0.282. Despite the highest energy consumption (18.91 MWh), Scenario 4 was favored for producing four value-added products alongside starch, yielding the highest profit at USD 8.85 million. In contrast, profits for BAU, Scenario 1, Scenario 2, and Scenario 3 were 1.91, 2.30, 5.01, and USD 8.79 million, respectively. Waste valorization in Scenarios 1, 2, 3, and 4 resulted in CO2 avoidance of 36.5., 42.6., 21.7, and 57.45 t CO2eq., respectively. However, producing value-added products increased energy consumption by 13, 73, 7, and 74% compared to BAU (4.58 MWh). The global warming potential analysis showed negative values for scenarios 2 and 4, at -436 and -434 kg CO2eq./t root, respectively. This study highlights the potential of a biorefinery approach for sustainable cassava starch production, providing insights for future research and policy development.

Assessing Climate Transition Risks in the Colombian Processed Food Sector: A Fuzzy Logic and Multi-Criteria Decision-Making Approach

Climate risk assessment is critical for organisations, especially in sectors such as the processed food sector in Colombia. This study addresses the identification and assessment of the main climate transition risks using an approach that combines fuzzy logic with several multi-criteria decision-making methods. This approach makes it possible to handle the inherent imprecision of these risks and to use linguistic expressions to better describe them. The results indicate that the most critical risks are price volatility and availability of raw materials, the shift towards less carbon-intensive production models, increased carbon taxes, technological advances, and associated development or implementation costs. These risks are the most significant for the organisation studied and underline the need for investments to meet regulatory requirements, which are the main financial drivers for organisations. This analysis highlights the importance of a robust framework to anticipate and mitigate the impacts of the climate transition.

Humanitarian logistics: A multicriteria decision approach for venezuelan refugee resettlement process

Humanitarian logistics: A multicriteria decision approach for venezuelan refugee resettlement process

Unveiling the optimal configuration of impulsive buying behavior using fuzzy set qualitative comparative analysis and multi-criteria decision approach

Sudden and unplanned purchasing behavior is considered impulsive buying behavior. With the increasing popularity of social commerce platforms and shopping automation, people's tendency towards impulsive purchases has grown significantly. In this connection, the role of marketing influencers has crucially impacted the customers' purchasing decisions over the last decade. This study aims to investigate the effect of marketing influencers on impulsive buying behavior. In addition, the current study addresses a critical methodological problem by highlighting the optimal configuration provided by fuzzy set qualitative comparative analysis (fsQCA) using a multi-criteria decision approach (MCDM). Based on a survey of 672 users of live streaming commerce platforms in Malaysia, we examined impulsive buying behavior from the perspective of influencer marketing, cognitive trust, and affective trust in influencer. Partial Least Squares Structural Equation Modeling (PLS-SEM) results confirmed the influence of parasocial relationship, authenticity, expertise, trustworthiness, attractiveness, and influencer–follower congruence on impulsive buying behavior through cognitive trust in influencer, affective trust in influencer, and behavioral inertia. The fsQCA results provided 15 different configurations confirming the role of marketing influencers' characteristics in impulsive buying behavior. However, fsQCA analysis is unable to determine the optimal solution or configuration. To this end, the MCDM analysis complemented the fsQCA analysis by unveiling the optimal configuration, which was the ninth configuration. Furthermore, the combination of authenticity, expertise, trustworthiness, cognitive trust, affective trust is considered a key concept to increase impulsive buying behaviour regardless of the presence of a parasocial relationship.

A novel dual-level multi-source information fusion approach for multicriteria decision making applications

A novel dual-level multi-source information fusion approach for multicriteria decision making applications

An Integrated Pythagorean Neutrosophic DEMATEL- Grey Relational Analysis Framework for Assessing Recent Technological Advancements in Maternal Healthcare

This study proposes a novel methodology that integrates the Decision making trial and evolution laboratory (DEMATEL) technique and Grey relational analysis (GRA) in a Pythagorean neutrosophic environment. This multi-criteria decision-making approach uses the DEMATEL technique to analyze the weights of the criteria and Grey relational analysis to prioritize the alternatives. The proposed approach is utilized to evaluate the most recent technological advancements in maternity healthcare, along with a pertinent numerical example.

New robust multi-criteria decision-making framework for thermal insulation of buildings under conflicting stakeholder interests

The choice of thermal insulation technology for existing building retrofit can be a complex multi-criteria decision-making (MCDM) problem characterized by multiple stakeholders with conflicting interests. The conflicting interests of the building owners and the policymakers could negatively influence the adoption of low-carbon energy retrofit measures by building possessors, slowing down the progress toward sustainable development. The investigation of this issue is, therefore, crucial to support more informed decisions and offer policymakers useful insights to develop future economic incentives for energy refurbishment of buildings. Most of the existing MCDM studies on the subject do not emphasize the differences among different stakeholders nor consider the outcomes' robustness. To overcome this gap, this paper integrates multi-stakeholder analyses and robustness assessments to provide broad-spectrum and reliable results. An innovative robust MCDM framework for building thermal insulation under conflicting stakeholder interests is proposed and tested on a real case study building (located in Southern Italy) using building dynamic energy simulation. Several alternatives of thermal insulation are evaluated under environmental, energy, and economic key performance indicators (KPIs). The Analytic Hierarchy Process is used to define criteria weights for conflicting decision-makers representing collectivity (policymakers) and private interests. TOPSIS, VIKOR, WASPAS, and MULTIMOORA methods are integrated to perform initial rankings of the alternatives. A rank similarity analysis is performed to evaluate the consensus between MCDM methods, and an ensemble ranking is obtained for each decision-maker using an approach based on the half-quadratic theory. A Confidence Index and a Trust Level are used to evaluate the agreement among the MCDM approaches, verifying the reliability of the final ensemble ranking. The robustness of the framework is attained by complying with well-established literature guidance. The hybrid MCDM analysis showed that porous materials like expanded clay and expanded perlite lead to better results under the KPIs investigated. The worst performances are attained by vacuum insulation panels and aerogel, mainly due to high values of embodied CO2 emissions and long payback periods. Insights upon the performance of different thermal insulating alternatives are also highlighted by the study and a stakeholder comparative analysis demonstrates that global rankings obtained for the different decision-makers show some similarities, but also important deviations, and a full compromise solution is not achieved.

Assessment of the betterness of a battery electric vehicle: A multi-criteria decision-making approach

Despite the advantages and benefits of a battery electric vehicle, its adoption rate remains low. Previous studies have explored factors that influence the adoption of electric vehicles. However, studies investigating whether an electric car outperforms a gasoline car are still limited. Therefore, this study aims to assess the betterness of an electric vehicle compared with a gasoline vehicle in helping customers perform their jobs to be done. A multi-criteria decision-making approach using the analytic hierarchy process is built on two main criteria, namely, customer pains and customer gains, where customer pains are divided into cost pains and non-cost pains, and customer gains are divided into functional gains and emotional gains. Using the most affordable battery electric vehicle in the Indonesian market, interviewees who live in the greater Jakarta and drive to work were invited to perform the pairwise comparison processes. The finding of this study shows that with respect to helping customers perform their jobs to be done, a battery electric vehicle is equally to moderately worse than a gasoline vehicle with a worse score of 0.5946 compared with a better score of 0.4054. This finding comes from interviewees who prioritize customer gains with a priority score of 0.6993 over customer pains with a priority score of 0.3007. Considering that the analytic hierarchy process allows a small number of interviewees, the result obtained should be limited as an early prediction about the betterness of an electric car compared with a gasoline car from a certain group of persons.