Multi-criteria Decision Research Articles

Establishment of a value assessment framework for orphan medicinal products in China

BackgroundThis study aimed to establish a suitable value assessment framework for orphan medicinal products in China based on the multi-criteria decision analysis (MCDA) method.MethodsFirst, a draft framework of the MCDA criteria was built based on a systematic literature evaluation and the EVIDEM framework tools. Second, stakeholder groups were formed and expert opinions were collected through the brainstorming and expert consultation methods. Third, from the perspective of stakeholders, the five-point weighting method and a two-step percentile distribution method were employed to weigh the quantitative criteria in the framework for orphan drug value evaluation. Meanwhile, from the public perspective, a survey was conducted on a sample of 71 people to obtain the scoring scale of the framework for orphan drugs through a two-step percentile distribution method. Finally, based on the synthetization and comparison of all evidence and methods, we developed the framework criteria and scoring scale for the orphan medicinal products.ResultsCombined with the stakeholder selection and suggestions in the stakeholder workshop, the framework criteria for the evaluation were constructed based on China’s national conditions, which included 11 quantitative and 8 qualitative criteria. The two-step percentile distribution method was selected as the weighting method.ConclusionsMCDA is feasible for the value assessment of orphan drugs in China and can be used as a supplementary tool for drug access decisions in medical insurance. It is suggested to further improve the value assessment framework of orphan medicinal products, scientifically evaluate the MCDA framework weighting method, explore a framework system suitable for China’s national conditions.

Novel Multi-Criteria Decision Analysis Based on Performance Indicators for Urban Energy System Planning

Urban energy systems planning presents significant challenges, requiring the integration of multiple objectives such as economic feasibility, technical reliability, and environmental sustainability. Although previous studies have focused on optimizing renewable energy systems, many lack comprehensive decision frameworks that address the complex trade-offs between these objectives in urban settings. Addressing these challenges, this study introduces a novel Multi-Criteria Decision Analysis (MCDA) framework tailored for the evaluation and prioritization of energy scenarios in urban contexts, with a specific application to the city of Bozen-Bolzano. The proposed framework integrates various performance indicators to provide a comprehensive assessment tool, enabling urban planners to make informed decisions that balance different strategic priorities. At the core of this framework is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is employed to systematically rank energy scenarios based on their proximity to an ideal solution. This method allows for a clear, quantifiable comparison of diverse energy strategies, facilitating the identification of scenarios that best align with the city’s overall objectives. The flexibility of the MCDA framework, particularly through the adjustable criteria weights in TOPSIS, allows it to accommodate the shifting priorities of urban planners, whether they emphasize economic, environmental, or technical outcomes. The study’s findings underscore the importance of a holistic approach to energy planning, where trade-offs are inevitable but can be managed effectively through a structured decision-making process. Finally, the study addresses key gaps in the literature by providing a flexible and adaptable tool that can be replicated in different urban contexts to support the transition toward 100% renewable energy systems.

Wind Power Plant Location Selection with Fuzzy Logic and Multi-Criteria Decision-Making Methods

This study aims to examine the effectiveness of the fuzzy multi-criteria decision-making methods, especially Fuzzy Weight by Envelope and Slope (F-WENSLO) and Fuzzy Ranking Alternatives with Weights of Criterion (F-RAWEC) for evaluating the potential locations for wind power plants. The study's objective is to provide a solid framework for deciding which locations are most suitable for wind energy projects, taking into account various criteria and expert opinion. The study includes the evaluation of five potential places including Gürün, Kangal, Divriği, Ulaş and Zara in Sivas province of Turkey. The evaluation criteria include wind speed and direction, altitude, land use, environmental impacts, infrastructure proximity, social acceptance, economic costs, security and risk factors, climatic conditions and legal and permit requirements. Scores from experts from various fields and weights of criteria were determined. The analysis revealed that Ulaş and Kangal got the highest point for the wind power plant installation. As Ulaş gets the highest point due to favorable wind conditions, favorable altitude and advantageous land use; Kangal stood out as a strong candidate because of its acceptable wind speed, positive social acceptance and low economic costs. The study highlights the importance of integrating multiple criteria and expert assessments in the decision-making process. The findings suggest that fuzzy multi-criteria decision-making methods can be effectively supportive of wind power plant site selection. The study provides valuable information for project managers and policy makers, emphasizing the importance of criteria such as security in the choice of location, legal requirements and social acceptance. Future research may expand these findings to examine the integration of additional criteria, alternative locations, and other multi-criteria decision-making techniques.

Aerodynamic performance characteristics of low Re airfoils: A parametric and multi criteria decision study

This research aims at investigating the aerodynamic performance of 51 low Re airfoils and applying a Multi Criteria Decision Making (MCDM) approach for selecting airfoils that align with the specific requirements of small wind turbines (SWTs). The study was carried out by varying the Re from 5 × 104 to 5 × 105; angle of attack (AOA) from −10° to 20°, thickness to chord ratio (0.1–0.9), camber ratio (0.1–0.9), and camber position (10 %–80 %) to evaluate the impact of these parameters on the airfoils’ performance. Furthermore, MCDM approach was applied to identify suitable airfoils optimized for their average lift to drag ratio, stall angle, operating range of AOA, strength, manufacturability, and material cost. The findings showed that of the teste parameters, the AOA and airfoil profile have the most pronounced effects on the airfoil performance. Among the tested airfoils, the E63 provided superior performance at 105 Re with LDR of 76.32, a 37.7 % improvement over that of NACA 4412 which is commonly used for wind turbine blade design. Furthermore, the MCDM results revealed that SG6043, FX63-137, E216 and E62 airfoils were the top-ranked airfoils suitable for SWTs application. These findings can help to produce optimized airfoil designs for increased performance and efficiency of SWTs.

Assessing the holistic value of Danhong injection for chronic stable angina: a multi-criteria decision analysis in China

IntroductionThis study aimed to assess the holistic value of Danhong injection (DHI) for treating chronic stable angina (CSA) and to identify the therapeutic characteristics of DHI. MethodsThe holistic value of DHI was assessed using a well-established evaluation index system including 34 criteria based on the Multi-criteria decision analysis (MCDA) model. Each criterion was rated by seven experts based on an evidence matrix comprising a literature review on DHI for treating CSA. The overall value of DHI for the treatment of CSA was evaluated by aggregating these performance scores and predetermined weights. Additionally, the contributions of each domain and criterion to the overall value estimate were calculated. Uncertainty was explored using an online retest and intra-rater correlation coefficient (ICC). ResultsWe found that the comprehensive value estimate of DHI for treating CSA was 80.18 points. The domain of “safety and risk management” was the strongest contributor to the final estimated value (30.37), followed by “effectiveness” (23.75). The criteria “size of population affected by disease” (3.79), “risk control of toxic medicinal materials” (4.38), “comparative non-medical costs” (1.14), “clarity of the mechanism of drug action” (0.6), “sustainability of medicinal materials resources” (1.91) and “patient compliance” (4.59) were found to be the most significant contributors to the overall value estimate across the 6 evaluation domains. The initial scores for DHI over the two rounds showed good consistency across panelists (ICC=0.886 [0.858–0.909]). ConclusionCompared with standard treatment alone, DHI was perceived as being at a “good level” intervention.

Performance Analysis of Indian Railway Zones using MCDM Approaches

The study aims to enhance the efficiency and effectiveness of Indian Railways (IR), a public sector infrastructural organization, through a performance analysis using various Multi-Criteria Decision-Making (MCDM) methods. Analyzing the Indian Railway’s open data, the study optimizes and ranks the zones of IR, offering insights for targeted investments to boost future performance. This research holds value by furnishing managerial perspectives, formulating strategies, and elevating the performance of different zones within Indian Railways. Through the identification of improvement areas, the analysis empowers decision-making, facilitating overall enhanced performance. MCDM, Indian Railways, Supply and demand, Data analysis.

Multiple-Criteria Decision Analysis for Assessments of Chemical Alternatives (MCDA-ACA).

A comprehensive assessment of chemical alternatives (ACA) is necessary to avoid regrettable substitution. In a preceding study, an analysis of six hazard assessment methods found that none of them are fully aligned with the hazard assessment criteria of Article 57 of the European REACH regulation, indicating a need for a method better reflecting hazard assessment schemes in European chemical regulations. This paper presents a multiple-criteria decision analysis (MCDA) method for the ACA that takes the criteria of Article 57 of REACH into account. Investigated and presented are objective hierarchies, the aggregation of objectives, the curvature of the value functions, weights, and the introduction of a classification threshold. The MCDA-ACA method allows for the aggregation of hazards in such a way that poor performance in one hazard cannot be compensated for by good performance in another hazard. The method parameters were developed and tested using two data sets with the aim to classify chemical alternatives into acceptable (nonregrettable) and unacceptable (regrettable) alternatives according to the regulations set in Europe. The flexibility of the general method was explored by adapting the method to align with two hazard assessment schemes, Article 57 of REACH and GreenScreen. The results show that MCDA-ACA is so flexible and transparent that it can easily be adapted to various hazard assessment schemes.

Multi-Criteria Decision-Making Approach for Optimal Energy Storage System Selection and Applications in Oman

This research aims to support the goals of Oman Vision 2040 by reducing the dependency on non-renewable energy resources and increasing the utilization of the national natural renewable energy resources. Selecting appropriate energy storage systems (ESSs) will play a key role in achieving this vision by enabling a greater integration of solar and other renewable energy. ESSs allow for solar power generated during daylight hours to be stored for use during peak demand periods. Additionally, the proposed framework provides guidance for large-scale ESS infrastructure planning and investments to support Oman’s renewable energy goals. As the global renewable energy market grows rapidly and Oman implements economic reforms, the ESS market is expected to flourish in Oman. In the near future, ESS is expected to contribute to lower electricity costs and enhance stability compared to traditional energy systems. While ESS technologies have been studied broadly, there is a lack of comprehensive analysis for optimal ESS selection tailored to Oman’s unique geographical, technical, and policy context. The main objective of this study is to provide a comprehensive evaluation of ESS options and identify the type(s) most suitable for integration with Oman’s national grid using a multi-criteria decision-making (MCDM) methodology. This study addresses this gap by applying the Hesitate Fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitate Fuzzy VIKOR methods to assess alternative ESS technologies based on technical, economic, environmental, and social criteria specifically for Oman’s context. The analysis reveals pumped hydro energy storage (PHES) and compressed air energy storage (CAES) as the most appropriate solutions. The tailored selection framework aims to guide policy and infrastructure planning to determine investments for large-scale ESSs and provide a model for comprehensive ESS assessment in energy transition planning for countries with similar challenges.

MCDM Method for Managing the Water Resources Based on Possibility Theory under Bipolar Fuzzy Environment

Background: Uncertainty is a common factor in every real-life decision-making problem. Possibility theory is one uncertainty theory in Fuzzy sets (FS). The possibility-based decision-making under a fuzzy environment is a significant multi-criteria decision-making (MCDM) method. Methods: A bipolar FS is an extension of a fuzzy set. With the bipolarity concept, we can handle both positive and negative thoughts. In this study, we have provided a possibility mean of a bipolar fuzzy number. We have developed a ranking method for bipolar fuzzy numbers using this pos-sibility concept. A novel possibility MCDM method is suggested for solving the water resources management (WRM) in the Nagpur area, Maharashtra State, India. Results: The MCDM technique is an effective tool for solving WRM problems in an area. Many uncertainties and bipolarities occur together in Nagpur water resources. WRM technique with fuzzy is one approach that can be used to solve the area's water problem. We have used the pro-posed MCDM to address the water-related issues of this district. With this proposed MCDM method, numerically, we employed water resource problems under a bipolar fuzzy environ-ment. Conclusion: The Nagpur area is covered by Basaltic rock and faces water shortage. The district is experiencing severe water shortages. Groundwater, surface water, and rainfall are three water resources considered as alternatives. According to the proposed MCDM technique in Nagpur district, Groundwater is the best water source from three flanks: quality of water, affordability, and availability.

Participatory multi-criteria decision making for optimal siting of multipurpose artificial reservoirs

Water resources management is a crucial activity due to climate change concerns and increasing water scarcity. The increase of water storage by building new artificial reservoirs is one of the most common solutions to fulfill the community’s needs for potable water, energy, irrigation, and prevention of flood risk. The siting of the reservoirs is usually assessed based on topographical and hydrological considerations. However, there are additional crucial factors, often disregarded in common engineering top-down design approaches, that should be considered to determine suitable locations, such as bio-physical, socio-economic, regulatory, and environmental factors, especially where there are competing interests in the use of territory. Involving the communities in the initial stages of the decision-making process is therefore crucial. In this work, we present a methodology, based on multi-criteria decision-making analysis (MCDA), for identifying the optimal locations for new reservoirs while simultaneously addressing all the aforementioned factors through community engagement. The presented method aims at overcoming two major challenges in existing works, i.e., retrieving quantitative information from the participatory approach and going beyond standard hydro-morphological suitability of a dam site. In a first step, an algorithm assesses a large number of sites using a Digital Elevation Model (DEM). Then, MCDA is conducted to rank all potential locations. The selection criteria are defined quantitatively, based on a territorial analysis combined with hydrological modelling. The criteria include: geometric and morphological aspects (reservoir volume, etc.), hydrological indicators (water balance, potential flood mitigation), anthropization (population, infrastructures, etc.), landscape, archaeological heritage, ecology, environmental components and natural hazards. A web-based survey tool based on the pairwise comparison is developed to engage the community in the decision-making process, allowing them to express their perspectives on the relative significance of each criterion. The application of this methodology is demonstrated through a case study in the Pesa river watershed, Italy, showcasing its effectiveness in identifying the most suitable reservoir locations while targeting the highest environmental preservation and community acceptance. The results show that sole engineering criteria might not reflect the sensibility of the community and that variations of the size of the dam can lead to distinct trade-offs between costs and benefits where interference with impact elements occurs.

A quantum probability theory-based method for heterogeneous multi-criteria group decision making with incomplete probabilistic linguistic preference relations considering the interference effect among decision makers

Quantum probability theory (QPT) reveals that decision makers (DMs) can interfere with each other and thus affect the decision result. However, existing methods of heterogeneous multi-criteria group decision making (HMCGDM) seldom consider the interference effect among DMs. This paper defines an interference degree based on the phase angle difference obtained by QPT to address HMCGDM problems in which the alternative and criteria sets provided by DMs may be different. In addition, the incomplete probabilistic linguistic preference relations (InPLPRs) are introduced to express the evaluation information of DMs. Considering that the same linguistic term may has different meanings for DMs, we construct a consistency-driven optimization model based on the personalized individual semantics (PISs) to estimate the missing information in InPLPR on each criterion provided by DMs and the corresponding complete PLPR (CPLPR). Then, for each DM, the individual weights of criteria and the comprehensive CPLPR on all criteria in the individual criteria set can be obtained by an optimization model. Subsequently, a novel QPT-based model is erected to derive the weights of DMs and the ranking order of alternatives. Finally, an example of tourism evaluation and several sensitivity and comparative analyses are offered to examine the applicability of the proposed method.

The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS

The current study introduced Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance landslide susceptibility. It determines the relative distance of each alternative from the ideal best and ideal worst value. The ArcGIS environment was used to prepare eleven landslide conditioning factors, while raster values were extracted for the decision matrix preparation. We utilized subjective expert judgment to create a weighted matrix that considers the roles of each conditioning component. In addition, a Euclidean distance was measured from each alternative to the ideal best and worst values. The relative closeness value (Ri) has been used to prepare the landslide susceptibility index by the inverse distance weighting (IDW) interpolation. Furthermore, the precision of the landslide susceptibility was justified by area under curve-receiver operating characteristic (AUC-ROC) which was 0.987. Hence, multi-criteria decision-making (MCDM) techniques like the TOPSIS method are very useful for natural hazard mapping.•The simplified TOPSIS approach described by Hwang and Yoon (1981) is applied in this study. The criteria have been categorized and assigned weights based on expert judgment and previously published material.•The TOPSIS approach and GIS integration has significantly enhanced the creation of a landslide susceptibility map for a sensitive area.•The method is easiest and suitable for short term operation research.

Skewness impact through distributional evaluation (SITDE) method: a new method in multi-criteria decision making

In this article, we propose the Skewness Impact Through Distributional Evaluation (SITDE) method for multi-criteria decision-making. Unlike traditional methods ignoring criteria distribution asymmetry, SITDE enhances the decision quality. We use a case-study on electric vehicle selection to illustrate the efficiency of SITDE relative to conventional methods. The comprehensive decision support with SITDE across multiple thresholds is an important aspect of a detailed and balanced decision-making virtue as our results show in case the skewness effects are included. Theoretical backgrounds, typologies practical applications and statistical justifications to confirm the accuracy of SITDE in regarding to limit complexities MCDM scenarios are explained this paper. SITDE enhances a robust decision-making process by accounting for the inherent biases of symmetric assumption models. Moreover, SITDE proves to be extremely useful in cases for dealing with asymmetrical data distributions and skewed datasets humanitarian cause as infected situations are always overwhelming. This broad applicability indicates the potential for wider use with respect to different domains, such as in environmental management and financial risk assessment. Future studies should investigate the adequacy or insufficiency of its fusion with different MCDM methods and explore if this approach would apply a more efficient and valid insight that might enhance decision making in multiple sectors.

Multi-Criteria Decision Analysis of Wireless Technologies in WPANs for IoT-Enabled Smart Buildings in Tourism

The increasing demand for energy-efficient and interconnected smart buildings, particularly in the tourism sector, has driven the adoption of advanced wireless technologies. IoT technologies are crucial in this evolution, improving modern buildings’ functionality and operational efficiency. This study investigates the utilization of various wireless technologies within Wireless Personal Area Networks (WPANs), including Bluetooth BLE 4.2, Bluetooth BLE 5.0, ZigBee, and Z-Wave, in smart buildings. A multiple-criteria decision-making (MCDM) approach, specifically the PIPRECIA-S model, was applied to evaluate these technologies based on criteria such as device connectivity, mobility, low energy consumption, scalability, flexibility, and interoperability. Simulations using the PIPRECIA-S model were conducted to assess technology performance across various real-world scenarios. The results indicate that ZigBee (0.2942) and Bluetooth BLE 5.0 (0.2602) provide superior performance in terms of energy efficiency and scalability, followed by Z-Wave (0.2550) and Bluetooth BLE 4.2 (0.1906). These findings provide decision-makers with data-driven recommendations for selecting the most suitable wireless technologies for smart buildings.

Methodology of Multiple-Criteria Decision Making for Selecting a Refrigerant to Be Used in Commercial Refrigeration Equipment

This paper presents the application of the multiple-criteria decision-making (SAW) method for selecting the optimum refrigerant for the refrigeration systems of commercial cooling equipment used in gastronomy furniture, which is paramount in storing food under optimal conditions. The analysis focused on comparing different refrigerants, including natural refrigerants such as R744 (carbon dioxide) and R290 (propane) and synthetic refrigerants such as R455A, R449A, and R452A. As a result of the analysis using the SAW method, the refrigerant R455A was found to be the best solution. This choice resulted from the consideration of various decision criteria, such as energy efficiency, environmental impact, operating costs, and technology availability. R455A stands out as a synthetic refrigerant that provides high energy efficiency with minimal environmental impact. Its use supports sustainability goals by reducing greenhouse gas emissions and electricity consumption, which is crucial given the modern regulatory requirements and environmental standards. This study offers a practical decision-making tool for commercial refrigeration equipment designers and manufacturers, supporting them while selecting the optimal technological solutions. The choice of refrigerant R455A addresses the need to integrate energy efficiency, environmental protection, and cost-effectiveness in the process of designing modern refrigeration systems for catering furniture.

Application of multi-criteria decision making (MCDM) model for solar plant location selection

This study aims to systematically evaluate and identify the most suitable locations for establishing solar farms in the United Kingdom. It employs a comprehensive Multi-Criteria Decision-Making (MCDM) model that incorporates the Fuzzy Analytic Hierarchy Process (FAHP) method. Eight potential locations have been identified and selected for their climatic conditions and other pertinent parameters. These potential locations underwent additional assessment considering several factors including temperature, annual hours of sunshine, absolute humidity, proximity to major roads, distance from the power network, and potential demand. The data was normalized to eliminate scale effects and improve comparability. A MATLAB program has been developed with universality and user-friendliness in mind. Its purpose is to establish location selection factors graphs according to application-specific criteria and generate the matrix representation of these graphs for each potential candidate location. The permanent matrix, a composite metric synthesizing six criteria, identifies Torquay as the optimal location with a permanent value of 18.16. This quantitative approach, intersected with qualitative assessments, presents a clear hierarchy of site suitability. The model's simplicity, scalability, and proven accuracy make it a valuable tool for assessing renewable energy project viability in diverse regions.

Optimizing marine vehicles industry: a hybrid analytical hierarchy process and additive ratio assessment approach for evaluating and selecting IoT-based marine vehicles

Rapid developments in the Internet of Things (IoT) have opened the door for game-changing applications in numerous sectors, especially the vehicle industry. There is a rising demand for efficient assessment and decision-making methodologies to pinpoint the most promising choices for the vehicle sector with the introduction of IoT-based maritime vehicles. To overcome this issue, the integrated multi-criteria decision-making analysis (MCDA) paradigm proposed in this research combines the additive ratio assessment (ARAS) and analytic hierarchy process (AHP) approaches to evaluate and choose IoT-based maritime vehicles based on their performance- and authenticity-related criteria in the vehicle sector. The selection issue is hierarchically organized, and the assessment criteria are prioritized using the AHP approach. There are seven performance and authentication related criteria are selected that might aid in the selection procedure. Using the AHP, we are assigned these criteria proportionate weights that reflect their respective significance and interrelationships. AHP, however, falls short of offering a thorough analysis of the alternatives that exist. To overcome these restrictions, this research presents the integration of AHP with the ARAS approach for the ranking of alternatives according to how well they perform against the set criteria. By using the ARAS technique, it is possible to get over the restrictions of AHP and achieve a more thorough assessment of maritime IoT-based vehicles. The efficiency of the framework is proven using empirical data and professional judgment. The findings show that the hybrid method successfully encapsulates the intricate relationships between the factors being evaluated and objectively appraises the potential of IoT-based maritime vehicles for the automotive sector. This study extends to the area by providing an organized and thorough method for assessing and choosing IoT-based maritime vehicles. Considering several factors and their mutual dependence, the hybrid AHP and ARAS technique gives decision-makers a powerful tool for evaluating the potential of IoT-based maritime vehicles in the automotive sector. Smart decisions on the deployment of IoT-based marine vehicles and maximizing the potential they present may be made by beneficiaries in the automotive sector using the study’s results.

Decision making techniques in mass gathering medicine during the COVID-19 pandemia: a scoping review.

The COVID-19 pandemic has profoundly affected mass gatherings (MGs) worldwide, necessitating the implementation of advanced decision support techniques. These techniques, including mathematical models and risk assessment tools, have played a critical role in ensuring the safe conduct of events by mitigating the spread of SARS-CoV-2. This mini-review aims to explore and synthesize the decision support methodologies employed in managing MGs during the COVID-19 pandemic. A scoping review was conducted following the PRISMA guidelines covering the period from 2020 to 2024. Studies were categorized by event type (e.g., academic, religious, political, sports) and decision-making tools applied. The review identified a range of decision support techniques, with risk assessment and simulation tools being the most commonly employed across various event types. A total of 199 studies were initially identified, with 10 selected finally for inclusion based on relevance to decision support techniques. Case studies included the successful risk mitigation strategies during the 2020 Hajj, the 2021 Tokyo Olympics, and the 2022 FIFA World Cup in Qatar. Techniques such as fuzzy logic, Bayesian analysis, and multi-criteria decision-making were also highlighted, particularly in complex scenarios. These tools significantly contributed to reducing COVID-19 transmission risks at large-scale events. The review underscores the importance of decision support systems in the safe management of MGs during the pandemic. Further research should focus on the integration of emerging technologies and the long-term impacts of decision support tools on public health management.

Techno economic analysis of electrolytic hydrogen production by alkaline and PEM electrolysers using MCDM methods

Hydrogen, a crucial clean and renewable energy source, addresses pressing challenges of energy security and environmental pollution. Water electrolysis for hydrogen production is a promising approach to satisfy the growing demand for sustainable energy. This study uniquely performs a comprehensive techno-economic analysis of hydrogen production using both Alkaline and Proton Exchange Membrane (PEM) electrolyzers, a first in the field to evaluate their performance comprehensively with advanced Multi-Criteria Decision-Making (MCDM) techniques. Leveraging TOPSIS, WASPAS interval methods, and the Best Worst Method (BWM) with fuzzy logic, this research introduces a novel evaluation framework that incorporates a wide-ranging set of factors, including environmental, technical, technological, economic, and social aspects, divided into 30 sub-criteria. These insights offer a comprehensive understanding of each electrolyser's strengths and weaknesses, helping stakeholders make informed decisions about cost reduction in hydrogen production technologies. This has not been done before. Although cost results favour Alkaline electrolysers, PEM electrolysers are attractive for specific applications where their benefits justify the higher initial cost, choosing between Alkaline and PEM electrolysers dependent on a given hydrogen production project's requirements.

Application of Multicriteria Decision Analysis Approach Managing Solar Prosumer Choices: Implications for Households, Regulatory Authorities, and Contractors

Application of Multicriteria Decision Analysis Approach Managing Solar Prosumer Choices: Implications for Households, Regulatory Authorities, and Contractors