This study surveys the ordered weighted averaging OWA operator literature using a citation network analysis. The main goals are the historical reconstruction of scientific development of the OWA field, the identification of the dominant direction of knowledge accumulation that emerged since the publication of the first OWA paper, and to discover the most active lines of research. The results suggest, as expected, that Yager's paperIEEE Trans. Systems Man Cybernet, 181, 183-190, 1988 is the most influential paper and the starting point of all other research using OWA. Starting from his contribution, other lines of research developed and we describe them.

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Ordered Weighted Averaging Operators 1988-2014: A Citation-Based Literature Survey

Originally published in Contemporary Psychology: APA Review of Books, 1993, Vol 38(9), 1000. Reviews the book, Quasi-Rational Economics by Richard H. Thaler (1992). Thaler presents 16 chapters (some written with collaborators) about “quasirational” behavior and how it affects the validity of traditional economic theories. He presents a variety of research on topics that investigate consumer choice and financial markets, and he proposes some alternate models of economic theory to suggest ways of incorporating quasi-rational thinking into the economic forecast. Although this book draws on some psychological research, Thaler advocates economists developing models for quasirational economics rather than closing up shop and leaving the job to psychoeconomists. (PsycINFO Database Record (c) 2006 APA, all rights reserved)

Quasi-rational Economics

The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, based on the assumption of normality of the principal component scores, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into account the dependence among curves. Results on simulated and real datasets show the efficiency of the proposed method.

Model-based clustering for multivariate functional data

Determination of parameters of a functional relation by factor analysis : a technical report

This study was aimed at identifying effective leadership abilities as appreciated by soldiers in the Lithuanian armed forces Leader behavior was measured using an adapted version of the Leader Behavior Description Questionnaire (LBDQ), which was originally developed by Andrew W Halpin from Ohio State University Data were collected from soldiers holding different ranks and doing professional military service in all units of the Lithuanian armed forces and were analyzed using the IBM SPSS version 20 software application For our data analysis, the Chi-square Automatic Interaction Detector (CHAID) decision tree growing method was used with three class dependent variables The CHAID algorithm helped in specifying the best splits for each of twelve potential predictors and then select the predictors whose splits presented the most serious differences in the sub-populations of the sample In the Chi-squared significance test, the lowest p-value was achieved The model structures obtained after analysis are presented

Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators

The aim of this paper is to present a methodology to generate a partially subadditive (respectively superadditive) discount function starting from an entirely subadditive (respectively superadditive) discount model. To do this, we are going to use the concept of deformation of time in a discount function, focusing on Stevens' power law. A deformation of time is a function that mathematically represents the perception from an individual or a group of individuals about how the calendar time evolves. This approach will be important when describing the treatment of addictions and other diseases in patients who show a certain degree of impulsivity in their intertemporal choice.

Deforming Time in a Nonadditive Discount Function

A model for multi-expert multi-criteria decision making (ME-MCDM) is proposed and defined in a consensus-reaching process. A decision problem is considered, in which a group of experts are involved in the evaluation of the performances of a set of alternatives with respect to a predefined set of criteria. The main novelty of the present consensus model is that of being guided by both consensus and false consensus effects. One finding in studies examining intuitive predictions of the preference is the false consensus effect, which represents the tendency to overestimate consensus for one's attitudes and behaviors. The purpose is to evaluate a consensual judgement whether the consensus degree is partly due to expert's failure to recognize that their choices not only depend on the “objective” response alternatives but also on their subjective structure. In this context, expert's own beliefs, values, and habits tend to bias their perception of how widely they are shared. Our study contributes by investigating the impact of the description of the choice option and the form of the judgement task on the magnitude of the agreement in the case of the presence of the false consensus effect. The consensus reaching process is modeled within fuzzy set theory by ordered weighted averaging operators. Our study contributes by investigating the magnitude of the presence of the false consensus effect. © 2010 Wiley Periodicals, Inc.

Assessing false consensus effect in a consensus enhancing procedure

We consider the problem of group decisions, in which decision-makers have different opinions or interests. This study proposes various metric spaces for representing the movements of decision-makers for reaching consensus. We also introduce the concept of fuzzy coalition for developing an algorithm for building a feasible fuzzy coalition, which is defined as the union of winning maximum coalitions which solve the issue of consensus among decision-makers.

Consensus in Multiperson Decision Making Using Fuzzy Coalitions

Hyperbolic discounting refers to the tendency for people to increasingly choose a smaller-sooner reward over a larger-later reward as the delay occurs sooner rather than later in time. When offered a larger reward in exchange for waiting a set amount of time, people act less impulsively (i.e., choose to wait) as the rewards happen further in the future. Put another way, people avoid waiting more as the wait nears the present time.

https://cab.unime.it/journals/index.php/AAPP/article/download/AAPP.90S1C3/pdf

The intertemporal choice behaviour: classical and alternative delay discounting models and control techniques

The aim of this paper is to obtain the family of the so-called generalized Weibull discount functions, introduced by Takeuchi (Game Econ Behav 71:456–478, 2011), by deforming the q-exponential discount function by means of the Stevens’ “power” law. The obtained discount functions exhibit different degrees of inconsistency and so they can be classified according to the value of their characteristic deforming parameters. Moreover, we extend the construction of the generalized Weibull discount function starting from any discount function instead of the q-exponential discounting. In any case, the value of the parameter $$\theta $$
 of these new discount functions is extended from (0, 1] to the union of the intervals $$(-\,\infty ,0) \cup (0,+\,\infty )$$
 .

Viviana Ventre

Papers

Deforming Time in a Nonadditive Discount Function

Assessing false consensus effect in a consensus enhancing procedure

Consensus in Multiperson Decision Making Using Fuzzy Coalitions

The intertemporal choice behaviour: classical and alternative delay discounting models and control techniques

Modeling the inconsistency in intertemporal choice: the generalized Weibull discount function and its extension