Multicriteria Decision Aid Model Research Articles

Using the constructivist multi-criteria decision aid model (MCDA-C) to supporting the planning of the creation of a quality seal for cargo handling for ports of Santa Catarina

Using the constructivist multi-criteria decision aid model (MCDA-C) to supporting the planning of the creation of a quality seal for cargo handling for ports of Santa Catarina

Using the constructivist multi-criteria decision aid model (MCDA-C) to supporting the planning of the creation of a quality seal for cargo handling for ports of Santa Catarina

Using the constructivist multi-criteria decision aid model (MCDA-C) to supporting the planning of the creation of a quality seal for cargo handling for ports of Santa Catarina

Using a Constructivist Multi-Criteria Decision Aid Model (MCDA-C) to Develop a Novel Approach to Self-Manage Motivation in Organizations

The Brazilian Federal Highway Patrol is an organ of public administration with the constitutional mission to carry out the extensive patrolling of federal highways. Stress and physical and emotional exhaustion are constant, causing illnesses along with frustration, demotivation, and depression. The objective of this research is the development of a self-evaluation model of performance for the Federal Highway Patrols, using their perceptions to enhance their motivation at work considering the factors under their control. The constructivist multi-criteria decision aid (MCDA-C) methodology was used to elaborate the model. The proposed model identifies, establishes, and structures a process to measure the performance of patrol officers on the relevant aspects that they can manage, to guide their decisions toward the desired consequences, thus regulating their stress levels.

Measuring the Attractiveness of Cities to Receive Investments in Regional Airport Infrastructure

The vast Brazilian territory and the accelerated economic growth of the cities of the country’s interior in recent years have created a favourable environment for the expansion of regional aviation. In 2015, the Brazilian Government launched a program of investments in regional airports equipping them to receive commercial flights. However, the economic crisis and the scarcity of resources drive the prioritisation of projects with a greater economic and social return. This article aims to present a multicriteria decision aid (MCDA) model to measure cities’ attractiveness to receive investments in regional airports. The MCDA approach can deal with multiple indicators and different points of view and provide systematised steps for supporting decision-makers. For this purpose, we selected 12 criteria among the evaluation parameters identified in the literature, which led to the construction of the evaluation model and elaborating the ranking of the localities participating in the investment program. This study can contribute scientifically by proposing the use of an MCDA approach to support decisions related to logistics and infrastructure. It can help managers and practitioners provide a structured and systematised model to address decisions related to airport investments.

Combining diversification practices to enhance the sustainability of conventional cropping systems

A major path helping agriculture achieve the dual challenges of production and environmental preservation, consists of transitioning from the current, external input-based, conventional farming systems to a biodiversity-based agricultural system that rely more on ecosystem services. One lever of this transition consists of diversifying agri-food systems using practices such as rotation extension, intercropping (IC), multiple cropping or multi-services cover crops (MSCC) implementation. Here, we investigated to what extent the combination of diversification practices could contribute to the enhancement of the sustainability of current conventional cropping systems through an ex ante evaluation.We compared the sustainability performances of five diversified (DIV) cropping systems from five major arable crop production regions of France to their local less diversified reference (REF) systems by calculating various criteria and implementing a multi-criteria decision aid model. 76 criteria assessing the three dimensions of sustainability were calculated (10, 17 and 49 criteria for the economic, social and environmental dimensions respectively).Our analysis showed that the combination of diversification practices could improve the environmental performances while maintaining a priori economic and social performances at satisfactory levels according to the local expert working group. The DIV systems always had lower greenhouse gas (GHG) emissions compared to their REF systems and often improved air and water quality and above- and belowground biodiversity. However, diversification may also cause drawbacks for some indicators, as negative impacts were observed from, gross margin, NO3 lixiviation, NH3 volatilization or pesticide use, in some cases. Our analysis also suggested that the effect of a combination of diversification practices on an indicator can be either positive or negative according to the pedo-climatic context, the level of performance of the reference and compromises in the management of diversification practices in response to local objectives of performance.

Using MCDA-C to assess the organizational performance of industries operating at Brazilian maritime port terminals

This article describes the use of the constructivist multicriteria decision aid (MCDA-C) model as an intervention instrument, using a case study of a fertilizer industry located at a Brazilian maritime port terminal, with the goal of developing a customized performance evaluation model to help its management process. The sequence of steps created to develop the model occurred interactively through interviews with the decision maker. The developed model allowed the decision maker to incorporate the unique aspects of the company and environment, thereby widening the performance evaluation possibilities and enhancing organizational management.

Combining the functional unit concept and the analytic hierarchy process method for performance assessment of public transport options

This paper presents a case study covering the operational and functional performances of the Bus Rapid Transit (BRT), Light Rail Transit (LRT), and Monorail (MNT) modes in the São Paulo City, Brazil. The innovative multicriteria decision aid model (MCDAM) combine the use of a Functional Unit with the Analytic Hierarchy Process (AHP) method to access objective and subjective preferences of stakeholders and performances of alternatives of three transport options. The case study shows that the MCDAM has proven to be the most effective. The Functional Unit provided a common set of requirements to guide the performance assessment of the modal options. In addition, the evaluated stakeholders’ preferences were combined with the performance assessment resulting into global priority indexes based on a linear additive function algorithm.

Development of a web graphic model with fuzzy-decision-making Trial and Evaluation Laboratory/Multi-criteria-Spatial Decision Support System (F-DEMATEL/MC-SDSS) for sustainable planning and construction of rural housings

There is often a complicated process for planning and constructing rural housings under the influence of (mass)-tourism in reservoir areas, involving multiple evaluation criteria use and geographical information analysis. With some methodologies within a unique framework considering current increasing construction sprawls and ecological consequences, these approaches will overcome existing shortcomings, especially spatial decision and visual impact problems on sustainable rural housing planning and construction. This paper presents a distinct web-based graphic model of sustainable rural housing planning and construction with a Fuzzy-DEcision-MAking Trial and Evaluation Laboratory/Multi-Criteria-Spatial Decision Support System (F-DEMATEL/MC-SDSS) method in a Geographic Information System (GIS) environment applied to Alange, Spain as a case study. The aim of this methodology is to optimally eco-design rural housings under (mass)-tourism in reservoir areas, as for their sensitivity and effect. The methodology presents herein the combined method of GIS and Multi-Criteria Decision Aid (MCDA) together with F-DEMATEL method. Because of the technological improvements in the area of information systems, it has a great necessity to study in what way to combine GIS, MCDA, Weighted Linear Combination (WLC), sensitivity analysis, the Internet, modeling, and database, targeting to generate MC-SDSS based on a web-based platform. A methodological framework named as web-based F-DEMATEL/MC-SDSS is suggested by means of a totally united GIS and definite MCDA model by programed in ArcGIS software’s Visual Basic for Applications (VBA) and Model View Controller (MVC) to be an object-oriented system. These program languages interact on an algorithmic web server that processing the MCDA products. The model consists of four main modules: the general overview module, the F-DEMATEL/MC-SDSS module, the sensitivity analysis module, and, finally, the final result module especially with the buildings suitability option, which users can access consecutively. Through the web graphic model developed, seven rural housings constructed in the area can be checked their suitability based on the selected criteria of decision-makers. Therefore, the results can be used to verify sustainable housings’ sites and designs differentiated parts of space as the asynchronous process of decision-makings. Thus, this model can be a channel to collaborate and communicate the spatial design and visual impact strategies of sustainable housings for decision-makers, who have practical and specific purposes.

Accounting for asymmetry between strengths, weaknesses, opportunities and threats in outranking methods

PurposeThe purpose of this paper consists in discussing and modeling the asymmetrical nature of evaluation criteria that are notably relevant in strategic planning, project portfolio management and complex systems management.Design/methodology/approachThe author guarantees the theoretic validity of the proposed approach, by showing that it possesses desirable properties such as monotonicity. This allows for a reduced implementation time and thus a real-time use of the model.FindingsThe author conducts a comparative study with two other multicriteria decision aid models on a set of real data regarding a power plant sitting problem and highlights some of the limitations of previous models compared to the proposed approach.Originality/valueThis paper describes a novel multicriteria decision aid model, entitled SPADE (which is an acronym for Structuring Preferences to Aid DEcisions). It aims at consolidating SWOT analysis with sound decision-theoretic techniques, and making use of its results to support decision-making.

Risk assessment of ship-to-ship transfer operations based on stochastic criteria evaluation and intervally scaled importance weights

Ship-to-ship (STS) transfer of cargo operations suffers inherently from risks that can compromise the success of such operations, leading to an accident with adverse effects on human lives and the environment. A feasible way to tackle the risks of STS transfers is through the use of multicriteria decision aid (MCDA) methodologies. This paper aims to develop an MCDA model to evaluate risks of an STS transfer based on the outranking relation concept. The proposed methodology uses confidence indices to compare alternative risk scenarios on stochastic risk criteria evaluation. To do so, a team of experts evaluate the scenarios regarding three risk factors; the likelihood of a scenario to occur, the severity of the scenario and the ability to detect the risk on time. Next, fuzzy domination relation is applied to complete the ranking of the risks. Finally, robustness analysis is performed to control the model's stability.

Risk assessment of ship-to-ship transfer operations based on stochastic criteria evaluation and intervally scaled importance weights

Ship-to-ship (STS) transfer of cargo operations suffers inherently from risks that can compromise the success of such operations, leading to an accident with adverse effects on human lives and the environment. A feasible way to tackle the risks of STS transfers is through the use of multicriteria decision aid (MCDA) methodologies. This paper aims to develop an MCDA model to evaluate risks of an STS transfer based on the outranking relation concept. The proposed methodology uses confidence indices to compare alternative risk scenarios on stochastic risk criteria evaluation. To do so, a team of experts evaluate the scenarios regarding three risk factors; the likelihood of a scenario to occur, the severity of the scenario and the ability to detect the risk on time. Next, fuzzy domination relation is applied to complete the ranking of the risks. Finally, robustness analysis is performed to control the model's stability.

Goal programming model for management accounting and auditing: a new typology

In practice, generally the accountants are facing complex decision-making situations where they aggregate simultaneously several conflicting and incommensurable factors (dimensions). They look for the decision of the best compromise. The goal programming (GP) is one of the multi-criteria decision aid models that have been applied to the field of accounting. The aim of this paper is to provide an exhaustive literature review of the GP application within the field of accounting and to propose a new typology which serves as a guideline for the accountants to identify the most appropriate variant of GP to deal with specific accounting related decision making situation.

Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases.

From mono-criterion to multi-criteria decision aid: a necessary but unfinished evolution in operational research

The aim of this paper is to discuss the evolution process from the mono-criteria decision making paradigm to the multi-criteria decision aid paradigm. This process is based on the fact; in general, the decision-maker desires to consider simultaneously several heterogeneous and conflicting dimensions instead of optimising one single objective such as minimising the cost or maximising the profit. This paradigm shift has led to a different way of using mathematical reasoning and tools within the discipline of operational research. Basically, a shift that has meant a return to the roots of the decision making process in order to develop models that attempt to integrate explicitly the decision-maker’s preferences where he/she will be playing the main role during the decision-making process. In this paper we will look at some epistemological aspects of this evolution and point out that this mission of integrating explicitly the decision-makers preferences within the multi-criteria decision aid models remains unfinished.

Multicriteria decision aid models for the prediction of securities class actions: evidence from the banking sector

In recent years, there has been an increase in the number and value of securities class actions (SCAs), attracting the attention of various stakeholders such as investors, managers, policy makers, lawyers, etc. The present study extends the literature, by investigating for the first time the development of a classification model to forecast SCAs filed against US banks. Our results show that the proposed multicriteria decision aid model achieves a satisfactory accuracy, by classifying correct around 80 % of the banks in an out-of-sample testing. We obtain similar results when we use a walk-forward approach, instead of a tenfold cross-validation technique, for the estimation and testing of the model. Further analysis indicates that the classification accuracies can improve further by the inclusion of a corporate governance indicator that relates to executive and director compensation and ownership.

Modelling of linguistic variables in multicriteria energy policy support

The climate change and the increasing complexity of the energy sector along with the prerequisite for sustainability have broadened the energy policy shaping field by bringing out new challenges. Decision support tools and methods, such as Multicriteria Decision Aid (MCDA), are necessary for energy policy, in the pursuit of appropriate approaches necessary to support the restructuring of the energy sector, concerning patterns of energy extraction, generation, transformation and use, from unsustainable to sustainable forms of development. Papers devoted to the investigation of MCDA models using linguistic variables for energy policy support seem to be not available in the international literature. The scope of this paper is to explore different linguistic representation and computational models in MCDA that are or can be applied to energy policy support and to establish a clear linkage between them. This paper argues that MCDA methodologies with direct computation on linguistic variables can support energy policy frameworks, bridging the gap between energy policy makers thinking, reasoning, representation and computing. Finally, current trends, open questions and prospects in this topic are pointed out.

An application of multicriteria decision aid models in the prediction of open market share repurchases

This study presents the first attempt to develop classification models for the prediction of share repurchase announcements using multicriteria decision aid (MCDA) techniques. We use three samples consisting of 434 UK firms, 330 French firms, and 296 German firms, to develop country-specific models. The MCDA techniques that are applied for the development of the models are the UTilités Additives DIScriminantes (UTADIS) and the ELimination and Choice Expressing REality (ELECTRE) TRI. We adopt a 10-fold cross validation approach, a re-sampling technique that allows us to split the datasets in training and validation sub-samples. Thus, at the first stage of the analysis the aim is the development of a model capable of reproducing the classification of the firms considered in the training samples. Once this stage is completed, the model can be used for the classification of new firms not included in the training samples (i.e. validation stage). The results show that both MCDA models achieve quite satisfactory classification accuracies in the validation sample and they outperform both logistic regression and chance predictions. The developed models could provide the basis for a decision tool for various stakeholders such as managers, shareholders, and investment analysts.

Developing Multicriteria Decision Aid Models for the Prediction of Share Repurchases

This study presents the first attempt to develop classification models for the prediction of share repurchases using multicriteria decision aid (MCDA) methods. The MCDA models are developed using two methods namely UTilites Additives DIScriminantes (UTADIS) and ELimination and Choice Expressing REality (ELECTRE) TRI, through a ten-fold cross-validation approach. The sample consists of 1060 firms from France, Germany and the UK. We find that both MCDA models achieve quite satisfactory classification accuracies in the validation sample and they outperform both logistic regression and chance predictions.

A Dynamic Multi-criteria Aid for Process Driving Using Case-based Reasoning

The evolution that knew the driving since the nineties concludes on the necessity to consider the driving as a system of multi-criteria decision aid. It is not an easy task for process decision-makers to acquire, to integrate and to understand all the increasing amount of data obtained from a process and to get meaningful knowledge from it. Thus, it is necessary to use automatic knowledge acquisition to build consistent and robust decisions taken in a process. Case-based reasoning (CBR) is a technique to solve new problems based on previous experience. This paper introduces a new multi-criteria decision aid model for process driving like an answer to the intervening changes in the enterprise and its environment. The objective of this model is to help the decision-maker to adopt the best action facing a new situation. The application of the proposed model has been done in the operational process of the Packing Techniques in Cardboard Mayr-Melnhof Packaging society.

Predicting business failure: an application of multicriteria decision aid techniques in the case of small UK manufacturing firms

Small firms play an important role in most modern economies. Nevertheless, they are not without their problems. Therefore, the development of business failure prediction models for small firms is quite important. In the present study we employ three multicriteria decision aid (MCDA) techniques for the development of failure prediction models for small UK firms. The MCDA models are developed using a ten-fold cross validation and benchmarked against models developed with discriminant analysis and logit analysis. All models achieve satisfactory classification accuracies while including only a small number of input variables, hence avoiding the commonly encountered problem of data availability when dealing with small firms. Also we examine two non-financial variables – the age of the firm and auditors' opinion – but the classification results are only marginally affected.