scholarly journals AHP-Like Matrices and Structures—Absolute and Relative Preferences

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 813 ◽  
Author(s):  
David Koloseni ◽  
Tove Helldin ◽  
Vicenç Torra
Keyword(s):  
Choquet Integral ◽  
Pairwise Comparisons ◽  
Weighted Mean ◽  
Relative Preference ◽  
Aggregation Functions ◽  
Decision Making Processes ◽  
Available Information ◽  
Hierarchy Process ◽  
Relative Preferences ◽  
Preference Matrix

Aggregation functions are extensively used in decision making processes to combine available information. Arithmetic mean and weighted mean are some of the most used ones. In order to use a weighted mean, we need to define its weights. The Analytical Hierarchy Process (AHP) is a well known technique used to obtain weights based on interviews with experts. From the interviews we define a matrix of pairwise comparisons of the importance of the weights. We call these AHP-like matrices absolute preferences of weights. We propose another type of matrix that we call a relative preference matrix. We define this matrix with the same goal—to find the weights for weighted aggregators. We discuss how it can be used for eliciting the weights for the weighted mean and define a similar approach for the Choquet integral.

scholarly journals Two Proofs and One Algorithm Related to the Analytic Hierarchy Process

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Miron Pavluš ◽  
Rostislav Tomeš ◽  
Lukáš Malec
Keyword(s):  
Analytic Hierarchy Process ◽  
Pairwise Comparisons ◽  
Problem Solution ◽  
Maximal Eigenvalue ◽  
Analytic Hierarchy ◽  
Solution Vector ◽  
Decision Making Processes ◽  
Hierarchy Process ◽  
Activity Areas

36 years ago, Thomas Saaty introduced a new mathematical methodology, called Analytic Hierarchy Process (AHP), regarding the decision-making processes. The methodology was widely applied by Saaty and by other authors in the different human activity areas, like planning, business, education, healthcare, etc. but, in general, in the area of management. In this paper, we provide two new proofs for well-known statement that the maximal eigenvalue λmax is equal to n for the eigenvector problem Aw=λw, where A is, so-called, the consistent matrix of pairwise comparisons of type n×n (n≥ 2) with the solution vector w that represents the probability components of disjoint events. Moreover, we suggest an algorithm for the determination of the eigenvalue problem solution Aw=nw as well as the corresponding flowchart. The algorithm for arbitrary consistent matrix A can be simply programmed and used.

scholarly journals Possibilities of Utilizing the Method of Analytical Hierarchy Process Within the Strategy of Corporate Social Business

2010 ◽  
Vol 18 (29) ◽  
pp. 63-70 ◽  
Author(s):  
Katarína Drieniková ◽  
Gabriela Hrdinová ◽  
Tomáš Naňo ◽  
Peter Sakál
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Analytical Hierarchy Process ◽  
Environmental Risks ◽  
Social Business ◽  
Major Benefit ◽  
Decision Making Processes ◽  
Strategic Goals ◽  
Corporate Social ◽  
Hierarchy Process

Possibilities of Utilizing the Method of Analytical Hierarchy Process Within the Strategy of Corporate Social Business The paper deals with the analysis of the theory of corporate social responsibility, risk management and the exact method of analytic hierarchic process that is used in the decision-making processes. The Chapters 2 and 3 focus on presentation of the experience with the application of the method in formulating the stakeholders' strategic goals within the Corporate Social Responsibility (CSR) and simultaneously its utilization in minimizing the environmental risks. The major benefit of this paper is the application of Analytical Hierarchy Process (AHP).

scholarly journals A decision support method for evaluating database designs

2012 ◽  
Vol 9 (1) ◽  
pp. 81-106 ◽  
Author(s):  
Erki Eessaar ◽  
Marek Soobik
Keyword(s):  
Decision Support ◽  
Data Model ◽  
Processing System ◽  
Transaction Processing ◽  
Database Management System ◽  
Pairwise Comparisons ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Decision Support Method

It is possible to produce different database designs based on the same set of requirements to a database. In this paper, we present a decision support method for comparing different database designs and for selecting one of them as the best design. Each data model is an abstract language that can be used to create many different databases. The proposed method is flexible in the sense that it can be used in case of different data models, criteria, and designs. The method is based on the Analytic Hierarchy Process and uses pairwise comparisons. We also present a case study about comparing four designs of SQL databases in case of PostgreSQL? database management system. The results depend on the context where the designs will be used. Hence, we evaluate the designs in case of two different contexts - management of measurements data and an online transaction processing system.

scholarly journals Hesitation and Refusal Factors in Individuals' Decision-Making Processes Regarding a Coronavirus Disease 2019 Vaccination

2021 ◽  
Vol 9 ◽  
Author(s):  
Arcadio A. Cerda ◽  
Leidy Y. García
Keyword(s):  
Side Effects ◽  
Multinomial Logistic Regression ◽  
Health Belief ◽  
Hygiene Measures ◽  
Logistic Regression Method ◽  
Decision Making Processes ◽  
The Government ◽  
Using Data ◽  
Belief Model ◽  
Available Information

Introduction: Considering the global prevalence of coronavirus disease 2019 (COVID-19), a vaccine is being developed to control the disease as a complementary solution to hygiene measures—and better, in social terms, than social distancing. Given that a vaccine will eventually be produced, information will be needed to support a potential campaign to promote vaccination.Objective: The aim of this study was to determine the variables affecting the likelihood of refusal and indecision toward a vaccine against COVID-19 and to determine the acceptance of the vaccine for different scenarios of effectiveness and side effects.Materials and Methods: A multinomial logistic regression method based on the Health Belief Model was used to estimate the current methodology, using data obtained by an online anonymous survey of 370 respondents in Chile.Results: The results indicate that 49% of respondents were willing to be vaccinated, with 28% undecided or 77% of individuals who would potentially be willing to be inoculated. The main variables that explained the probability of rejection or indecision were associated with the severity of COVID-19, such as, the side effects and effectiveness of the vaccine; perceived benefits, including immunity, decreased fear of contagion, and the protection of oneself and the environment; action signals, such as, responses from ones' family and the government, available information, and specialists' recommendations; and susceptibility, including the contagion rate per 1,000 inhabitants and relatives with COVID-19, among others. Our analysis of hypothetical vaccine scenarios revealed that individuals preferred less risky vaccines in terms of fewer side effects, rather than effectiveness. Additionally, the variables that explained the indecision toward or rejection of a potential COVID-19 vaccine could be used in designing public health policies.Conclusions: We discovered that it is necessary to formulate specific, differentiated vaccination-promotion strategies for the anti-vaccine and undecided groups based on the factors that explain the probability of individuals refusing or expressing hesitation toward vaccination.

GENERATION OF WEIGHTING TRIANGLES ASSOCIATED WITH AGGREGATION FUNCTIONS

2000 ◽  
Vol 08 (04) ◽  
pp. 417-451 ◽  
Author(s):  
T. CALVO ◽  
G. MAYOR ◽  
J. TORRENS ◽  
J. SUÑER ◽  
M. MAS ◽  
...  
Keyword(s):  
Aggregation Function ◽  
Weighted Averaging ◽  
Fractal Structures ◽  
Weighted Mean ◽  
Averaging Operators ◽  
Ordered Weighted Averaging ◽  
Aggregation Functions ◽  
Different Types ◽  
Ordered Weighted Averaging Operators

In this work, we present several ways to obtain different types of weighting triangles, due to these types characterize some interesting properties of Extended Ordered Weighted Averaging operators, EOWA, and Extended Quasi-linear Weighted Mean, EQLWM, as well as of their reverse functions. We show that any quantifier determines an EOWA operator which is also an Extended Aggregation Function, EAF, i.e., the weighting triangle generated by a quantifier is always regular. Moreover, we present different results about generation of weighting triangles by means of sequences and fractal structures. Finally, we introduce a degree of orness of a weighting triangle associated with an EOWA operator. After that, we mention some results on each class of triangle, considering each one of these triangles as triangles associated with their corresponding EOWA operator, and we calculate the ornessof some interesting examples.

FAIR CONSISTENCY EVALUATION FOR RECIPROCAL RELATIONS AND IN GROUP DECISION MAKING

2009 ◽  
Vol 05 (02) ◽  
pp. 407-420 ◽  
Author(s):  
MICHELE FEDRIZZI ◽  
MATTEO BRUNELLI
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Evaluation Method ◽  
Group Decision ◽  
Pairwise Comparison ◽  
Pairwise Comparisons ◽  
Reciprocal Relations ◽  
Decision Making Processes ◽  
Consistency Evaluation

In decision-making processes, it often occurs that the decision maker is asked to pairwise compare alternatives. His/her judgements over a set of pairs of alternatives can be collected into a matrix and some relevant properties, for instance, consistency, can be estimated. Consistency is a desirable property which implies that all the pairwise comparisons respect a principle of transitivity. So far, many indices have been proposed to estimate consistency. Nevertheless, in this paper we argue that most of these indices do not fairly evaluate this property. Then, we introduce a new consistency evaluation method and we propose to use it in group decision making problems in order to fairly weigh the decision maker's preferences according to their consistency. In our analysis, we consider two families of pairwise comparison matrices: additively reciprocal pairwise comparison matrices and multiplicatively reciprocal pairwise comparison matrices.

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