Measuring Attractiveness By A Categorical Based Evaluation Technique Research Articles

Digitalization and tender evaluation in construction projects: a BIM-integrated MCDA approach supported by Macbeth

The tender evaluation process in the procurement for construction works, aligned with regulations such as the European Directive 2014/24/EU, faces various constraints, increasingly acknowledging the impact of digitalization, particularly through Building Information Modeling (BIM). Therefore, a thorough BIM-integrated multi-criteria decision analysis approach is vital to fairly select the best contractor for the job and ensure project success. Despite its significance, the literature remains scarce, particularly in addressing BIM-related and value-focused constraints for construction tender evaluation. This research introduces a comprehensive and value-focused method integrating BIM criteria through Multicriteria Decision Analysis (MCDA) supported by the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), which is applicable to both the public and private sectors, serving as a reference guide for contracting authorities to assess and select the best tender for BIM-based construction works contracts. For this purpose, the following methodology was adopted: 1) conducting an extensive literature review; 2) carrying out interviews with construction experts to identify BIM-integrated evaluation criteria and performance descriptors; 3) creating an adapted MCDA construction tender evaluation framework supported by MACBETH; 4) performing a real-world case study to demonstrate the proposed evaluation framework; 5) discussing its application and limitations, along with considerations for future research. The study demonstrated the practicality of the proposed framework through a case study, showing that a value-based approach can significantly improve project outcomes compared to traditional methods. While acknowledging the potential of the BIM methodology, the impact of BIM-specific criteria on contractor selection was found to be less significant than expected. In conclusion, this work addresses current limitations, such as the absence of BIM-integrated assessment guidelines in the European Directive 2014/24/EU and ISO 19650. It outlines a value-focused MCDA approach for evaluating tenders for construction works contracts, supported by MACBETH for structuring the decision problem and building the evaluation model. The contribution to the body of knowledge lies in providing a robust framework that enhances the evaluation process in BIM-based construction works contracts and offers practical insights for contracting authorities.

Multicriteria Model to Support the Hiring of Road Freight Transport Services in Brazil

The transportation of goods plays a fundamental role in the global economy. In Brazil, specifically, a significant portion of what is transported goes through highways, and the provision of this service is carried out through the hiring of specialized companies or independent drivers, who end up serving companies from various sectors. This study successfully constructed a decision model to support the hiring of road freight transport services in Brazil. To achieve this, the multicriteria decision analysis (MCDA) approach was used, employing the Measuring Attractiveness By a Categorical-Based Evaluation Technique (MACBETH) method. The development of this model was informed by a comprehensive literature review, interviews with three transportation professionals, and a simulation involving eight anonymous Brazilian companies. This initiative aims to create a practical framework for effectively selecting logistics operators in the road transport sector to meet the needs of companies dependent on these services.

Evaluating the Onshore Wind Farms based on Multi-Criteria Decision-Making Model under Neutrosophic Set

This work comprehensively evaluates onshore wind farms, focusing on their technological efficiency, environmental impact, economic viability, and societal implications. Onshore wind energy has emerged as a prominent renewable energy source, leveraging the kinetic power of wind to generate electricity on a substantial scale. The evaluation encompasses a detailed analysis of wind resource assessment, turbine technology, grid integration, environmental considerations, economic feasibility, and stakeholder engagement. Findings reveal that onshore wind farms exhibit commendable technological advancements, with modern turbines showcasing higher efficiency and capacity. Environmental assessments highlight their lower carbon footprint compared to conventional energy sources, albeit with considerations for land use and wildlife impacts. Economic evaluations emphasize the decreasing costs of wind energy, yet challenges persist concerning upfront investment and intermittency. Stakeholder engagement emerges as a crucial aspect, stressing the importance of community acceptance and regulatory compliance. The assessment illuminates the multifaceted aspects of onshore wind farms, underscoring their potential as a sustainable energy source while acknowledging the need to address technological, economic, and social barriers to widespread adoption. We used the multi-criteria decision-making (MCDM) model for evaluating the onshore wind farms. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method is used to rank the alternatives. The MCDM method used under single valued neutrosophic set (SVNS). The SVNS is used to overcoming the uncertainty in the evaluation process.

Entropy weighted WASPAS and MACBETH approaches for optimizing the performance of solar water heating system

In this work, multi-criteria decision-making (MCDM) techniques namely the weighted aggregated sum product assessment (WASPAS) method and the measuring attractiveness by a categorical based evaluation technique (MACBETH) are applied for predicting the optimum performance of a solar water heating system (SWHS) equipped with perforated delta-shaped obstacles. In total fifteen SWHS design alternatives based on the variation of pitch ratio (0.5, 1, 1.5, 2.0), angle of attack (15°, 30°, 45°), and Reynolds number (400, 800, 1200) were selected. The Nusselt number, friction factor, and thermohydraulic efficiency were fixed as the selection criteria in evaluating SWHS alternatives. By the entropy method, the importance of the identified criteria is quantified as weight, whereas the ranking of SWHS alternatives is determined by the WASPAS and MACBETH methods. The results show that the SWHS design alternative with a Reynolds number of 1200, pitch ratio of 1, and 45° angle of attack exhibits the optimal performance in selected criteria. Sensitivity analysis was used to demonstrate the robustness of the acquired ranking findings, which were further, validated using ten popular decision-making models.

Health and sustainability impacts of scenarios of replacement of beef by pulses in two EU countries

Abstract Background High consumption of red meat is an important cause of burden of disease and environmental degradation globally. To motivate changes in food consumption and production, policymakers need evidence on the overall impact of such changes on the health of citizens, and on all aspects of sustainability: environment, socioeconomics, and culture. Methods Using three different approaches, we compared the impact of four scenarios of replacement of beef consumption with pulses (a well-established plant protein source) in two EU countries, Portugal and Denmark. First, health impacts were quantified in disability-adjusted life years (DALY); second, sustainability impact was measured using various social, economic and environmental indicators. Finally, we used MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique), an interactive, iterative, multicriteria decision analysis approach, to create a quantitative value model. Results We estimated positive health impacts for all substitution scenarios in the two populations. Positive impacts were larger for Denmark and ranged from 5,9 DALYs (25% substitution of beef by pulses in Portugal) to 39,7 DALYs averted/100,000 people (100% substitution, Denmark). The two countries had positive economic impacts, but beef production was more resilient than pulses. Environmental and social impacts of beef production were consistently higher than pulses. The MCDA model included a set of 15 criteria within the four dimensions of analysis to assess the overall value of implementing each scenario. Conclusions Individually, each approach allowed us to compare health, sustainability and integrated impacts of different options for food substitutions relevant to the sustainability agenda. Together, they allowed us to create a platform for discussing the co-benefits of dietary changes in different contexts. Expanding this work to other dietary changes and countries will support further development of public health policies. Key messages • Different possible scenarios of substitution of beef consumption by pulses, an alternative plant-based protein source, will lead to overall positive health and sustainability impacts. • Quantitative measurements of the integrated health, environmental and socioeconomic impacts of dietary transitions will support development of public health policies towards sustainable diets.

Analytic hierarchy process and data envelopment analysis: A match made in heaven

Analytic hierarchy process (AHP) and data envelopment analysis (DEA) are two popular decision science methods with many business, science, and engineering applications. AHP is a Multi-Attribute Decision-Making (MADM) method for prioritizing alternatives, and DEA is a non-parametric method for estimating production frontiers. Each method has known strengths and weaknesses, and the strengths in one method can overcome the weaknesses in the other. We study several strategies to diminish the weaknesses of DEA with the strengths of pairwise comparisons in AHP. We tackle the low discrimination power inherent to conventional DEA methods. AHP, with its pairwise comparison capability, has been consistently used to increase the discrimination power and accuracy in DEA. We propose and evaluate several new hybrid MADM-DEA models of different computational complexity and consistency, including combinations of the best-worst method (BWM) and its variants with DEA as well as a novel method composed of Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and DEA. We further develop a new technique for evaluating the similarity among multiple ranking results in MADM. The new simple but powerful technique is called Rank Absolute Deviation (RAD) and is inspired by the mean absolute deviation method. Several numerical examples and a real-world problem are used to demonstrate the applicability and efficacy of the new BWM-DEA, MACBETH-DEA, and RAD methods proposed in this study. We illustrate how less computationally demanding MADM-DEA techniques provide rankings that are highly correlated with the benchmark DEA-AHP and different consensus ranking models.

Fuzzy-MACBETH Hybrid Method: Mathematical Treatment of a Qualitative Scale Using the Fuzzy Theory

This paper describes the research procedures adopted in developing a triangular fuzzy number scale based on the semantic scale of MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). The objective was to mathematically treat the uncertainty and subjectivity of linguistic variables used to assess a decision problem. A matrix was initially obtained based on a decision maker’s assessment of a given context analysis. This decision matrix was then fuzzified based on a triangular Fuzzy numbers scale. Next, the inference process was performed using F-LP-MACBETH linear programming problem proposed here, resulting in a Fuzzy scale. This scale was then defuzzified using the centroid method, from which a crisp basic scale emerged, which was then cardinalized. The results show that the MACBETH Fuzzy method proposed here can overcome the classical method’s cardinal inconsistency problem, which facilitates its application in complex contexts. Hence, the MACBETH Fuzzy Hybrid method generated numerical values based on the decision makers’ semantically consistent assessments in a decision matrix, which by the classical method presents cardinal inconsistency. Therefore, the advantage of the proposed method consists in the possibility of obtaining a cardinal scale aligned to the decision makers’ preferences without the need to reassess the context.

MACBETH Tabanlı Bulanık MARCOS Yöntemi ile Bir Tekstil İşletmesi için Ürün Grubu Seçimi

Tekstil işletmeleri hızlı değişen sektör dinamizminde ve artan rekabet ortamında hayatta kalabilmek için hem üretecekleri ürünlere doğru karar vermeli hem de üretimlerini gerçekleştirirken maliyet, hammadde temini, kapasite doluluk ve hata oranı kriterlerini optimum şartlarda sağlayabilmelidir. Bu çalışmada, Çok Kriterli Karar Verme (ÇKKV) yöntemlerinden MACBETH (Measuring Attractiveness by a Categorical Based Evaluation TecHnique) ve bulanık MARCOS (Measurement of Alternatives and Ranking according to the COmpromise Solution) yöntemleri birlikte kullanılarak bir tekstil işletmesi için üretilecek ideal ürün grubu belirlenmeye çalışılmıştır. Üretilecek ideal ürün grubu seçiminde dikkate alınan maliyet, hammadde temini, kapasite doluluk ve hata oranı kriterlerinin ağırlıklarının belirlenmesinde MACBETH yönteminden yararlanılmıştır. İşletmenin yoğun olarak en fazla ürettiği dört ürün grubu alternatifinin değerlendirilmesinde bulanık MARCOS yöntemi kullanılmış ve tekstil işletmesinde üretim parametrelerinin optimal şekilde yönetilebilmesi için en uygun ürün grubu belirlenmiştir.

Evaluation of Retrofitting Techniques for Historical Adobe Constructions Using a multi-criteria Decision Analysis: The Case Study of Chile

ABSTRACT The evaluation of retrofitting techniques against multiple (often conflicting) criteria requires an expert-driven approach with in-depth context-based knowledge. This research evaluates the expected performance of retrofitting techniques for historical adobe constructions by integrating literature-data and expert assessment. Consideration is given to performance-based criteria (structural behaviour, material compatibility), values around cultural built heritage (degree of intrusion, retreatability), and local constraints (cost-effectiveness). A multi-criteria decision analysis using MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation TecHnique) is undertaken in this study in order to facilitate the selection process for retrofitting techniques within distinct damage scenarios. The MACBETH model is applied to three historical adobe buildings in Chile using a weighted criteria matrix, while a sensitivity analysis is conducted to determine the stability of interventions. The best-scoring options for each damage pattern are then compared with national guidelines and the current practice. Among the best-ranking solutions obtained from MACBETH models, the use of wooden corner keys makes it possible to effectively counteract flexural cracks or mid-height cracks, damage at intersections of perpendicular walls, corner-damage vertical cracks, and in-plane damage. Wooden tie beams are effective solutions for corner-damage vertical cracks. Geo-mesh also obtains a high score yet is limited by its cost and low reversibility.

A novel rough numbers based extended MACBETH method for the prioritization of the connected autonomous vehicles in real-time traffic management

Digital transformation can help to make better use of existing transportation networks that are congested. One solution to the road congestion problem is real-time traffic management, which focuses on enhancing traffic flow conditions. The advantages of real-time traffic management systems have developed significantly as a result of connected autonomous vehicle (CAV) innovations. CAVs can act as enforcers for managing the traffic. This study aims to propose a novel rough numbers-based extended Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method for prioritizing real-time traffic management systems. Furthermore, a new approach for defining rough numbers is proposed, based on an improved methodology for defining rough numbers' lower and upper limits. This allows consideration of mutual relations between a set of objects and flexible representation of rough boundary interval depending on the dynamic environmental conditions. In this study, three main alternatives are defined for real-time traffic management systems: real-time traffic management, real-time traffic management integrated with CAVs, and real-time traffic management by using CAVs. For these alternatives, 5 main criteria and 18 sub-criteria are defined and then prioritized using the fuzzy multi-criteria decision-making (MCDM) approach. The proposed method's performance is validated through scenario analysis. The findings demonstrate that the proposed method is effective and applicable to real-world conditions. According to the study's findings, real-time traffic management with CAVs is the most advantageous alternative, while real-time traffic management integrated with CAVs is the least advantageous

Recovery center selection for end-of-life automotive lithium-ion batteries using an integrated fuzzy WASPAS approach

With the emergence of battery-based electric vehicles, transportation systems gradually leave using fossil fuel-based combustion engines. Due to their reasonable performance, Lithium-ion batteries have become one of the major batteries used for electric vehicles. Although these batteries are being used in most companies, their high production cost, rare raw material, and short life cycle have raised important incentives for their recovery process. However, locating a recovery center for end-of-life Lithium-ion batteries is a multi-aspect decision making problem influenced by many criteria. For this purpose, a novel integrated decision-making model is developed based on Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH) for calculating the criteria weights and Weight Aggregated Sum Product ASsessment (WASPAS) methods under the fuzzy environment with Dombi norms for evaluating the alternatives to address recovery center location selection problem considering technical as well as environmental, economic, and social aspects. To show the reliability and applicability of the developed method, a real-world case study in Istanbul is investigated. The developed method is used to evaluate six potential locations for the possible establishment of a recovery center. Results showed that Tuzla district is the most suitable location for opening a recovery center for end-of-life Lithium-ion batteries. Tuzla is in a very good position in terms of proximity to suppliers, transportation and location. To illustrate the robustness of the obtained results, extensive sensitivity analysis tests are performed.

The assessment of a smart system in hydroponic vertical farming via fuzzy MCDM methods

By 2050, the global population is estimated to rise to over 9 billion people, and the global food need is expected to ascend 50%. Moreover, by cause of climate change, agricultural production may decrease by 10%. Since cultivable land is constant, multi-layered farms are feasible alternatives to yield extra food from the unit land. Smart systems are logical options to assist production in these factory-like farms. When the amount of food grown per season is assessed, a single indoor hectare of a vertical farm could deliver yield equal to more than 30 hectares of land consuming 70% less water with nearly zero usage of pesticides. In this study, we evaluated technology selection for three vertical farm alternatives via MCDM methods. Even though commercial vertical farms are set up in several countries, area is still fresh and acquiring precise data is difficult. Therefore, we employed fuzzy logic as much as possible to overcome related uncertainties. WEDBA (Weighted Euclidean Distance Based Approximation) and MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) methods are employed to evaluate alternatives.

EMBEDDED REMOTE GROUP ENVIRONMENT THROUGH MODIFICATION IN MACBETH – AN APPLICATION OF CONTRACTOR’S SELECTION IN CONSTRUCTION

A group decision environment has profound roots in MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) analysis which indeed has plentiful advantages; however, many researchers envisage the embedded group decision system as an impediment in actual implementation. The accessibility of explicit interaction of decision makers at a single platform in the form of embedded group decision environment is a great impediment to the researchers. Accordingly, this research aims to tailor a novel alternative system of dealing with the embedded group decision under a remote group decision environment via integrating MACBETH and Exploratory Factor Analysis. The study finds that an embedded remote group decision making system could serve as an alternative system of group decision making which has plentiful perks in group decision applications. This system could help researchers to carry out research without confusing in embedded group decision environment but including all decision-makers in the model. The implication of proposed system is not only limited to MACBETH; however, due to system’s versatility, a similar approach could be fruitful for other group-related environments involving collective decisions.

Environmental analysis for the selection of long-distance natural gas pipeline routes using MACBETH

PurposeReliable operation of natural gas pipeline (NGP) is a critical factor in Iran’s economic development. NGP projects go through different ecosystems and considerably affect the environment. Environmental analysis is an essential step toward sustainable development. Tackling the challenges, this paper aims to develop a framework to systematically assess the environmental impact of NGPs.Design/methodology/approachThis study proposes a comprehensive framework for environmental impact analysis of NGPs using Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH). MACBETH protocol is used to calculate the overall environmental scores of projects.FindingsThe results indicate that the impact of implementing NGPs on protected areas is of the highest priority, while the impact on vegetation covers is of least priority for assessing the environmental impact of NGP.Practical implicationsThe practicality and validity of the model in the case of three candidate routes for the Polkale-Neizar project in Iran are examined. According to the results, the third alternative is selected based on its non-interference in protected areas and less environmental impacts. The proposed model can be modified and applied to perform environment appraisal of other linear projects such as energy, road and railway networks.Originality/valueThis model addresses a range of environmental impacts of implementing NGPs at two levels, with the second level being non-additive. The novelty of this study translates into considering the qualitative and quantitative features of each evaluation criterion applied to linear projects simultaneously using a multi-criteria value measurement.

Using a Multi-Criteria Model to Assess the Suitability of Potential Sites to Implement Off-Grid Solar PV Projects in South America

The role of the private sector is essential in providing energy access to all by 2030. However, private investors often face the decision problem of deciding where to implement off-grid projects. This selection process can be considered a multifactorial task because it requires accounting not only for local conditions, technical constraints, and economic-financial feasibility but also for socio-cultural dynamics and environmental consequences. In this paper, we implemented a multi-criteria decision-making (MCDM) method based on the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) to assist in the selection of the most suitable location to implement off-grid solar PV projects in South America. Following a participatory process with the input of a decision-maker representing the private sector, we combined 13 criteria, within 5 dimensions, to evaluate the performance of three potential sites, namely Bolivia, Peru and Colombia. Based on an overall score associated with each alternative, we grouped them into three categories: highly sustainable, sustainable, and unsustainable. As a result, Colombia represents the highest sustainable option for a potential private investor. This methodology provides guidance not only to investors but also to local utility companies and policymakers assessing off-grid locations with electricity access deficits, in developing countries.

Dynamic Portfolio Selection in Gas Transmission Projects Considering Sustainable Strategic Alignment and Project Interdependencies through Value Analysis

Selecting a sustainable cross-country natural gas pipeline project portfolio plays a vital role in enhancing energy security and national self-reliance. The interdependencies between projects augment the complexity of project portfolio selection. Hence, the selection must be done with sustainable strategic alignment and adjustment of ongoing projects to determine the most suitable project portfolio. This is while they have barely been addressed simultaneously in the literature. The aim of the present study is to fill in the mentioned gap by establishing an integrated framework incorporating the organization strategies, project interdependencies, and ongoing projects in the project portfolio selection problem. This presented framework uses network mapping to visualize project interdependencies and improve the quality of the resulting decision. The decision-aid approach of Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) was employed to tackle multi-criteria value measurement in project portfolio selection. Applicability and validity of the proposed framework were tested using the case study of the Iranian Gas Engineering and Development Company (IGEDC). The pipeline project portfolios were analyzed on the basis of experts’ opinions with regard to technical and sustainability strategic criteria (economic, environmental, and social pillars).

Developing a Fuzzy TOPSIS Model Combining MACBETH and Fuzzy Shannon Entropy to Select a Gamification App

Due to the important advantages it offers, gamification is one of the fastest-growing industries in the world, and interest from the market and from users continues to grow. This has led to the development of more and more applications aimed at different fields, and in particular the education sector. Choosing the most suitable application is increasingly difficult, and so to solve this problem, our study designed a model which is an innovative combination of fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and Shannon entropy theory, to choose the most suitable gamification application for the Industrial Manufacturing and Organisation Systems course in the degree programmes for Electrical Engineering and Industrial and Automatic Electronics at the Higher Technical School of Industrial Engineering of Ciudad Real, part of the University of Castilla-La Mancha. There is no precedent in the literature that combines MACBETH and fuzzy Shannon entropy to simultaneously consider the subjective and objective weights of criteria to achieve a more accurate model. The objective weights computed from fuzzy Shannon entropy were compared with those calculated from De Luca and Termini entropy and exponential entropy. The validity of the proposed method is tested through the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) II, ELimination and Choice Expressing REality (ELECTRE) III, and fuzzy VIKOR method (VIsekriterijumska optimizacija i KOmpromisno Resenje). The results show that Quizizz is the best option for this course, and it was used in two academic years. There are no precedents in the literature using fuzzy multicriteria decision analysis techniques to select the most suitable gamification application for a degree-level university course.

Automated two-stage continuous decision support model using exploratory factor analysis-MACBETH-SMART: an application of contractor selection in public sector construction

Public sector client marks contractor selection decisions on technical and financial bid considerations where efficient use of public resources is never unheeded. A plethora of past studies has developed two-stage models; however, continuous assessment of contractors is disregarded, and the models compromise on the discontinuous progression that partially recognizes the prominence of the technical stage in the selection process. This research aims to develop a novel automated two-stage continuous decision model for contractors’ assessment and selection where each contractor would be assessed on corresponding performance assessment grading levels. Exploratory Factor Analysis (EFA) assimilated with MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) employed to assess the model criteria, whereas, criteria assessment stage is developed using a novel hybrid combination of SMART (Simple Multi-Attribute Rating Technique), which in turn entails the EFA-MACBETH-SMART triplet-combination. The model encompasses extensive model criteria; thus, 76 model criteria were investigated and evaluated. Final selection of a contractor is proposed on technical bid/financial bid ratio mechanisms based on performance levels such as RT/F: 80/20; 75/25; 70/30; 65/35; and 60/40. A hypothetical case is encompassed to portray the operational mechanism of the automated assessment system. Findings from the model unveil that continuous progression of technical assessment stage in final selection make justice with the highly qualified contractors, and the likelihood of project success increases. The developed model further conclude that technically highest bidders may be awarded the contract if additionally offers a feasible bid. The developed model preserves the concept of efficient use of public resources alongside supporting the technically highest bidders.

PND103 Patient Preferences for Multiple Sclerosis Treatment during a Phase 3 Trial

To quantify patients’ preferences for multiple sclerosis (MS) treatment attributes and how they may be impacted by treatment experience. In a double-blind, active-controlled, randomized controlled clinical trial, OPTIMUM (NCT02425644), subjects completed a questionnaire at screening, baseline and follow-up (FU1; 15 days after end of treatment). The questionnaire aimed to elicit preferences for 7 MS treatment attributes (number of relapses in 2 years, years until MS worsens, disability due to disease progression, likelihood of liver failure within 10 years, likelihood of serious infection leading to disability within 10 years, likelihood of developing cancer within 10 years and time spent in hospital (for monitoring of the heart) using the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH). Dirichlet regression models were used to analyse observable preference heterogeneity. In total, 293 (63% female, mean age 38 ± 8 years) subjects with relapsing MS completed the preference questionnaire. At all times, subjects most valued decreasing ‘disability due to disease progression’ (screening=0.218; baseline=0.220; FU1=0.222), followed by increasing ‘time until your MS disease gets worse’ (screening= 0.176; baseline=0.172; FU1=0.170) and decreasing ‘number of relapses in two years’ (screening= 0.165; baseline= 0.165; FU1= 0.164). Subjects in the ponesimod treatment arm cared significantly less about disability due to disease progression at FU1 (p-value=0.024) compared to those in the teriflunomide treatment arm. Patients who had experienced >1 relapses in the past 12 months cared significantly more about ‘disability due to disease progression’ at screening (p-value=0.041) and ‘time until MS gets worse’ at FU1 (p-value=0.029) compared to those who had ≤1 relapse in the past 12 months. Trial subjects cared most about disability due to disease progression and their preferences were stable throughout the trial. MACBETH technique was able to capture treatment preferences accurately and Dirichlet regression was appropriate for quantifying observable preference heterogeneity.

Multi-Criteria Model for Evaluating Drugs to Prevent Deep Venous Thrombosis Associated With Orthopedic Surgery: A Hospital-Based Case Study

BackgroundIt's estimated that 40% to 60% of patients undergoing major orthopedic surgery of the hip or knee who do not receive thromboprophylaxis will develop deep venous thrombosis Instituto Nacional de Traumatologia e Ortopedia has established a guideline to prevent DVT with the administration of the Enoxaparin. Recently, institute stakeholders have been questioning this guideline as new oral anticoagulants that offer more comfort and efficacy, but present higher risk of bleeding, have been appearing in the market for treating deep venous thrombosis. ObjectiveThis study aims to validate the application of a multicriteria decision analysis in a real-world problem, the use of rivaroxaban and enoxaparin to prevent deep venous thrombosis. MethodsThe multicriteria method MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) was used in a decision conferencing process to develop an evaluation model for measuring the relative value of the drugs on each evaluation criterion, separately and globally. The model-building process was informed by a literature review and meta-analysis of randomized clinical trials with a critical appraisal of the evidence. ResultsWe report a model-structure with eight criteria, each one associated with a weighting coefficient and value function. Following a simple additive aggregation process, the model-outputs showed that Rivaroxaban was considered a robust option for DVT. Sensitivity analysis and robustness analysis were performed and testify the consistency of the results. ConclusionThis article contributes to literature by showing how MACBETH method can be combined with scientific evidence and participatory group processes, for health technology assessment in hospitals.