MCDA Approach Research Articles

Deploying the ELECTRE III and MACBETH multicriteria ranking methods for SMEs tactical performance improvements

Purpose – Industrial companies are continuously looking to improve their business turn-over and choose improvement actions to achieve this objective. Legitimating this choice by only a strategic financial point of view currently has some limits, because additional ones such as quality, delay, resources needs have also to be taken into account. The multicriteria decision aid (MCDA) approaches have been developed to deal with problems such as ranking, sorting or quantification. The purpose of this paper is to describe the operational aspects in MCDA deployment through a case study submitted by the SME Fournier Company. Design/methodology/approach – This paper concerns analytical overall performance models to allow the decision-makers (DMs) to select potential actions to launch regarding given decision criteria. The principles of the main MCDA approaches, outranking and aggregation, are presented. Then representative MCDA methods, ELECTREIII and MACBETH, are successively deployed to a tactical decision problem of business turn-over increase. From the building of their respective preference modelling, decision aid is provided in the form of preference relation or performance function. Findings – A formal framework supplying information to the industrial DMs in order to legitimate the action selection is described. In addition, the DMs feedback highlights the required expertise for the preference modelling. Practical implications – The article gives a guideline for industrial practitioners to carry out ELECTREIII and MACBETH for their improvement action selection. Originality/value – SMEs can find an adapted framework for their improvement actions choice dealing with financial and non-financial criteria. It is also enriched by practical considerations concerning the methods deployment for tactical decision problems.

Land Suitability Evaluation for Sorghum Based on Boolean and Fuzzy-Multi-Criteria Decision AnalysisMethods

The objective of this paper was to compare two approaches to land suitability evaluations, Fuzzy MCDA and Boolean, to model the opportunities for sorghum production in the north-western region of Jeffara Plain, Libya. In this paper a number of soil and landscape and climate criteria were identified and their weights specified as a result of discussions with local experts. The Fuzzy MCDA approach was found to be better than the Boolean approach. Boolean logic indicted that the study area has only four suitability classes (highly suitable, moderately suitable, marginally suitable and currently not suitable). In contrast, the results obtained by adopting the Fuzzy MCDA approach showed that the area of study has a greater degree of subdivision in land suitability classes for sorghum. The richer overall picture provides an alternative type of land suitability evaluation to Boolean approaches and allows subtle variations in land suitability to be explored.

An MCDA approach for the selection of bike projects based on structuring and appraising activities

This paper presents an MCDA approach for the structuring and appraising activities of a large and complex decision problem. More specifically, the paper makes use of the three-step structuring process for decision analysis proposed by von Winterfeldt and Edwards: (1) identifying the problem; (2) selecting an appropriate analytic approach; and (3) developing a detailed analytic structure. For illustration of the approach a case study dealing with the assessment task of prioritising and selecting initiatives and projects from a public pool with limited funds is examined throughout the paper. The process is embedded in a Decision Support System (DSS) making use of the REMBRANDT technique for pair wise comparisons to determine project rankings. A procedure for limiting the number of pair wise comparisons to be made in the process is in this connection presented. Finally, strengths and weaknesses in the approach are discussed and conclusions are made.

Strategic performance measurement in a healthcare organisation: A multiple criteria approach based on balanced scorecard

The Balanced Scorecard (BSC) methodology focuses on major critical issues of modern business organisations: the effective measurement of corporate performance and the evaluation of the successful implementation of corporate strategy. Despite the increased adoption of the BSC methodology by numerous business organisations during the last decade, limited case studies concern non-profit organisations (e.g. public sector, educational institutions, healthcare organisations, etc.). The main aim of this study is to present the development of a performance measurement system for public health care organisations, in the context of BSC methodology. The proposed approach considers the distinguished characteristics of the aforementioned sector (e.g. lack of competition, social character of organisations, etc.). The proposed measurement system contains the most important financial performance indicators, as well as non-financial performance indicators that are able to examine the quality of the provided services, the satisfaction of internal and external customers, the self-improvement system of the organisation and the ability of the organisation to adapt and change. These indicators play the role of Key Performance Indicators (KPIs), in the context of BSC methodology. The presented analysis is based on a MCDA approach, where the UTASTAR method is used in order to aggregate the marginal performance of KPIs. This approach is able to take into account the preferences of the management of the organisation regarding the achievement of the defined strategic objectives. The main results of the proposed approach refer to the evaluation of the overall scores for each one of the main dimensions of the BSC methodology (i.e. financial, customer, internal business process, and innovation-learning). These results are able to help the organisation to evaluate and revise its strategy, and generally to adopt modern management approaches in every day practise.

Exploratory MCDA for handling deep uncertainties: the case of intelligent speed adaptation implementation

AbstractSometimes experts, decisionmakers, and analysts are confronted with policy problems that involve deep uncertainty. Such policy problems occur when (1) the future is not known well enough to predict future changes to the system, (2) there is not enough knowledge regarding the appropriate model to use to estimate the outcomes, and/or (3) there is not enough knowledge regarding the weights stakeholders currently assign to the various criteria or will assign in the future. This paper presents an MCDA approach developed to deal with conditions of deep uncertainty, which is called Exploratory Multi‐Criteria Decision Analysis (EMCDA). EMCDA is based on exploratory modelling, which is a modelling approach that allows policy analysts to explore multiple hypotheses about the future world (using different consequence models, different scenarios, and different weights). An example of a policy problem that can benefit from this methodology is decision making on innovations for improving traffic safety. In order to improve traffic safety, much is expected from Intelligent Speed Adaptation (ISA), an in‐vehicle system that supports the driver in keeping an appropriate speed. However, different MCDA studies on ISA give different results in terms of the estimates of real‐world safety benefits of ISA and the willingness of stakeholders (e.g. the automotive industry) to supply ISA. The application of EMCDA to the implementation of ISA shows that it is possible to perform an MCDA in situations of deep uncertainty. A full analysis taking into account the complete uncertainty space shows that the best policy is to make mandatory an ISA system for young drivers (less than 24 years of age) that restricts them from driving faster than the speed limit. Based on different assumptions, the analysis also shows that ISA policies should not target older drivers. Copyright © 2010 John Wiley & Sons, Ltd.

Ranking and selection of power expansion alternatives for multiple objectives under uncertainty

Strategic planning in the electricity supply industry is a complex task due to the multiple and often conflicting objectives of the decision makers, as well as the inherent technical and valuation uncertainties involved. As such, a transparent decision support framework is needed, for guiding information management throughout the decision process, in a way which shapes decision outcomes, and enables confident choices to be made. This paper outlines a methodology for the ranking of power expansion alternatives given multiple objectives and uncertainty, and demonstrates this using the South African electricity supply industry. This methodology uses a value function MCDA approach that is augmented with scenario analysis to yield information relating to both the relative performance and credibility of power expansion alternatives. A portfolio of preferred alternatives is then identified based on performance and confidence criteria. Finally a more detailed analysis of the reduced solution set examines short-term technology investment details alongside attribute performance information, so as to gain insight into the decision problem and relate it back to real life actions.

Improving pluralism in Multi Criteria Decision Aid approach through Focus Group technique and Content Analysis

Various economic valuation techniques and Multi Criteria Decision Aid (henceforth MCDA) methods seek to identify and evaluate the environmental impacts in aquatic ecosystems for the improvement of the decision making process. Despite the latter's ability to respond more effectively to the task of confronting environmental problems thanks to its multidimensional structure, strong criticism is levelled against the obscurity prevalent in the way the social preferences are elicited and certain criteria and weights are adopted. In the present paper, the Focus Group technique, complemented by Content Analysis, are applied in order to strengthen the pluralistic concept of MCDA approach and enhance the social learning in decision making processes. The analysis was accomplished within the framework of the EUROCAT project (European Catchments: Catchments Changes and their impacts on the coast), and was applied to the delta area of the Axios transboundary river in Northern Greece.

A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.