Decision-making paradox

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The decision-making paradox is a phenomenon related to decision-making and the quest for determining reliable decision-making methods. It was first described by Triantaphyllou, and has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA), multi-criteria decision making (MCDM) and decision analysis since then.

Contents

Description

The decision-making paradox was first described in 1989, [1] and further elaborated in the 2000 book by Triantaphyllou on multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM). [2] It arises from the observation that different decision-making methods, both normative and descriptive, yield different results, when fed with exactly the same decision problem and data.[ citation needed ] It has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM), and decision analysis since then. [3] [4] [5] [6] [7] [8] [ better source needed ]

In a study reported in International Journal of Decision Support Systems [1] and Multi-Criteria Decision Making: A Comparative Study, [2] the following investigation was undertaken. Since in the beginning it was assumed that the best method is not known, the problem of selecting the best method was solved by successively using different methods. The methods used in that study were the weighted sum model (WSM), the weighted product model (WPM), and two variants of the analytic hierarchy process (AHP). It was found that when a method was used, say method X (which is one of the previous four methods), the conclusion was that another method was best (say, method Y). When method Y was used, then another method, say method Z, was suggested as being the best one, and so on.

Two evaluative criteria were used to formulate the previous decision-making problem, which is actually an MCDM problem. The first criterion was based on the premise that a method which claims to be accurate in multi-dimensional problems (for which different units of measurement are used to describe the alternatives), should also be accurate in single-dimensional problems. For such problems, the weighted sum model (WSM) is the widely accepted approach, thus, their results were compared with the ones derived from the WSM. The second evaluative criterion was based on the situation: alternative A, is evaluated as the best alternative, compared to the non-optimal alternative B. If B is replaced by a worse one, one should expect that alternative A remains the best alternative, under normal conditions where the weights of the two evaluative criteria in all possible combinations always add equal to 1. If not it is known as a ranking reversal. [2]

Methods affected

The following multi-criteria decision-making methods have been confirmed to exhibit this paradox:The analytic hierarchy process (AHP) and some of its variants, the weighted product model (WPM), the ELECTRE (outranking) method and its variants and the TOPSIS method. [1] [2]

Other methods

Other methods that have not been tested yet but may exhibit the same phenomenon include the following:

A key role in this quest is played by the study of rank reversals in decision making.

Related Research Articles

<span class="mw-page-title-main">Multiple-criteria decision analysis</span> Operations research that evaluates multiple conflicting criteria in decision making

Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making. Conflicting criteria are typical in evaluating options: cost or price is usually one of the main criteria, and some measure of quality is typically another criterion, easily in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider – it is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, managers are interested in getting high returns while simultaneously reducing risks; however, the stocks that have the potential of bringing high returns typically carry high risk of losing money. In a service industry, customer satisfaction and the cost of providing service are fundamental conflicting criteria.

<span class="mw-page-title-main">Analytic hierarchy process</span> Structured technique for organizing and analyzing complex decisions

In the theory of decision making, the analytic hierarchy process (AHP), also analytical hierarchy process, is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. It was developed by Thomas L. Saaty in the 1970s; Saaty partnered with Ernest Forman to develop Expert Choice software in 1983, and AHP has been extensively studied and refined since then. It represents an accurate approach to quantifying the weights of decision criteria. Individual experts’ experiences are utilized to estimate the relative magnitudes of factors through pair-wise comparisons. Each of the respondents compares the relative importance of each pair of items using a specially designed questionnaire. The relative importance of the criteria can be determined with the help of the AHP by comparing the criteria and, if applicable, the sub-criteria in pairs by experts or decision-makers. On this basis, the best alternative can be found.

A decision matrix is a list of values in rows and columns that allows an analyst to systematically identify, analyze, and rate the performance of relationships between sets of values and information. Elements of a decision matrix show decisions based on certain decision criteria. The matrix is useful for looking at large masses of decision factors and assessing each factor's relative significance by weighting them by importance.

The analytic network process (ANP) is a more general form of the analytic hierarchy process (AHP) used in multi-criteria decision analysis.

ÉLECTRE is a family of multi-criteria decision analysis (MCDA) methods that originated in Europe in the mid-1960s. The acronym ÉLECTRE stands for: ÉLimination Et Choix Traduisant la REalité.

The superiority and inferiority ranking method is a multi-criteria decision making model (MCDA) which can handle real data and provides six different preference structures for the system user. MCDM is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making, both in daily life and in settings such as business, government and medicine.

Decision-making software is software for computer applications that help individuals and organisations make choices and take decisions, typically by ranking, prioritizing or choosing from a number of options.

In decision theory, the weighted sum model (WSM), also called weighted linear combination (WLC) or simple additive weighting (SAW), is the best known and simplest multi-criteria decision analysis (MCDA) / multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.

The weighted product model (WPM) is a popular multi-criteria decision analysis (MCDA) / multi-criteria decision making (MCDM) method. It is similar to the weighted sum model (WSM). The main difference is that instead of addition in the main mathematical operation, there is multiplication.

In decision-making, a rank reversal is a change in the rank ordering of the preferability of alternative possible decisions when, for example, the method of choosing changes or the set of other available alternatives changes. The issue of rank reversals lies at the heart of many debates in decision-making and multi-criteria decision-making, in particular.

<span class="mw-page-title-main">European Working Group on Multiple Criteria Decision Aiding</span>

The European Working Group on Multiple Criteria Decision Aiding is a working group whose objective is to promote original research in the field of multicriteria decision aiding at the European level.

In multiple criteria decision aiding (MCDA), multicriteria classification involves problems where a finite set of alternative actions should be assigned into a predefined set of preferentially ordered categories (classes). For example, credit analysts classify loan applications into risk categories, customers rate products and classify them into attractiveness groups, candidates for a job position are evaluated and their applications are approved or rejected, technical systems are prioritized for inspection on the basis of their failure risk, clinicians classify patients according to the extent to which they have a complex disease or not, etc.

Hiview3 is decision-making software that is based on multi-criteria decision making (MCDM).

Expert Choice is decision-making software that is based on multi-criteria decision making.

DecideIT is a decision-making software for the Microsoft Windows operating system. It is based on multi-criteria decision making (MCDM) and the multi-attribute value theory (MAVT). It supports both value tree analysis for multi-attribute decision problems as well as decision tree analysis for evaluating decisions under risk and can combine these structures in a common model.

The VIKOR method is a multi-criteria decision making (MCDM) or multi-criteria decision analysis method. It was originally developed by Serafim Opricovic to solve decision problems with conflicting and noncommensurable criteria, assuming that compromise is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. VIKOR ranks alternatives and determines the solution named compromise that is the closest to the ideal.

D-Sight is a company that specializes in decision support software and associated services in the domains of project prioritization, supplier selection and collaborative decision-making. It was founded in 2010 as a spin-off from the Université Libre de Bruxelles (ULB). Their headquarters are located in Brussels, Belgium.

DEX is a qualitative multi-criteria decision analysis (MCDA) method for decision making and is implemented in DEX software. This method was developed by a research team led by Bohanec, Bratko, and Rajkovič. The method supports decision makers in making complex decisions based on multiple, possibly conflicting, attributes. In DEX, all attributes are qualitative and can take values represented by words, such as “low” or “excellent”. Attributes are generally organized in a hierarchy. The evaluation of decision alternatives is carried out by utility functions, which are represented in the form of decision rules. All attributes are assumed to be discrete. Additionally, they can be preferentially ordered, so that a higher ordinal value represents a better preference.

Valerie Belton, commonly known as Val Belton, is a retired professor of management science at University of Strathclyde. She is a researcher who has worked on the design and application of multi-criteria decision making (MCDM) approaches for over 30 years. She co-authored a book on this field Multicriteria Decision Analysis: An Integrated Approach, that was released in 2002. She has attempted to incorporate multi-criteria decision analysis with problem structuring techniques, system dynamics, and other analytical approaches. She has a number of scholarly articles to her name and served as the editor of the journal Multi-Criteria Decision Analysis.

A sensitivity analysis may reveal surprising insights in multi-criteria decision making (MCDM) studies aimed to select the best alternative among a number of competing alternatives.

References

  1. 1 2 3 Triantaphyllou, E.; S.H. Mann (1989). "An Examination of the Effectiveness of Multi-Dimensional Decision-Making Methods: A Decision-Making Paradox". International Journal of Decision Support Systems. 5 (3): 303–312. doi:10.1016/0167-9236(89)90037-7 . Retrieved 2010-06-25.
  2. 1 2 3 4 Triantaphyllou, E. (2000). Multi-Criteria Decision Making: A Comparative Study. Dordrecht, The Netherlands: Kluwer Academic Publishers (now Springer). p. 320. ISBN   0-7923-6607-7.
  3. Bernroider, E.W.N.; V. Stix (2006). "On The Applicability of Data Envelopment Analysis for Multiple Attribute Decision Making in the Context of Information Systems Appraisals". Data Envelopment Analysis for Multiple Attribute Decision Making, Communications of the IIMA 107. 6 (2): 107–118.
  4. Caterino, N.; I. Iervolino; G. Manfredi; E. Cosenza (2009). "A Comparative Analysis of Multi-Criteria Decision-Making Methods for Seismic Structural Retrofitting". Computer-Aided Civil and Infrastructure Engineering. 24 (6): 1–14. doi:10.1111/j.1467-8667.2009.00599.x. S2CID   18689305.
  5. Fitz-Gerald, A.; M. Tracy (2008). "Developing a Decision-Making Model for Security Sector Development in Uncertain Situations". Journal of Security Sector Management: 1–37.
  6. Bernroider, E.W.N.; S J. Mitlöhner. "Social Choice Aggregation Methods for Multiple Attribute Business Information System Selection". Vienna University of Economics and Business Administration, Augasse 2–6, 1090 Vienna, Austria.
  7. Mysiak, J. "Development of transferable multicriteria decision tools for water resource management". UFZ Centre for Environmental Research, Permoserstraße 15; 04318 Leipzig, Germany: 1–6.
  8. Falessi, D.; Tutor: Prof. Giovanni Cantone; Coordinatore: Prof. Daniel P. Bovet. "A Toolbox for Software Architecture Design (a Doctoral Dissertation)". Universita Degli Studi di Roma Tor Vergata, Rome, Italy, Facoltà di Ingegneria, Dottorato di Ricerca in Informatica e Ingegneria, dell'Automazione, XX Ciclo: 1–203.