Identifying behaviour in a multiproduct oligopoly: Incumbents reaction to tariffs dismantling

The Spanish automobile market of the nineties experienced a perfectly foreseeable tariff dismantling and a strong demand downturn, with the observed result of an apparently sharpened producer competition in products and perhaps in prices. This paper is aimed at testing whether or not there really was a change in pricing behaviour, using a structural model of competition. To answer that question, we specify, estimate and test semiparametric pricing equations with panel data for 164 models belonging to the 31 firms which competed in the market. The specification includes several equilibriums as alternative estimating models, considering prominently tacit coalitions by which a group of firms sets prices, taking into account the cross effects on their demands. The statistical test selects as the best model given the data an unbroken coalition of domestic and European producers. Comparative results using tight demand side specifications show that an inadequate specification of the demand side may induce wrong inferences.behaviour; tariffs; oligopoly; coalition;

A comparative analysis between two statistical deviation–based consensus measures in group decision making problems

The mean absolute deviation and the standard deviation, two statistical measures commonly used in quantifying variability, may become an interesting tool when defining consensus measures. Two consensus indexes which obtain the level of consensus in some problems of Group Decision Making are introduced in this paper by expanding the aforementioned statistical concepts. A comparative analysis reveals that the levels of consensus derived from these indexes are close to those obtained employing distance functions when a fuzzy preference relations frame is considered, so they turn out to be a useful tool in this context. In addition, these indexes are different from each other and with the distance functions considered. Thus, they are applicable tools in the calculation of consensus in our context and are different from those commonly used

A Confusion Matrix for Evaluating Feature Attribution Methods

The increasing use of deep learning models in critical areas of computer vision and the consequent need for insights into model behaviour have led to the development of numerous feature attribution methods. However, these attributions must be both meaningful and plausible to end-users, which is not always the case. Recent research has emphasized the importance of faithfulness in attributions, as plausibility without faithfulness can result in misleading explanations and incorrect decisions. In this work., we propose a novel approach to evaluate the faithfulness of feature attribution methods by constructing an ‘Attribution Confusion Matrix’, which allows us to leverage a wide range of existing metrics from the traditional confusion matrix. This approach effectively introduces multiple evaluation measures for faithfulness in feature attribution methods in a unified and consistent framework. We demonstrate the effectiveness of our approach on various datasets, attribution methods, and models, emphasizing the importance of faithfulness in generating plausible and reliable explanations while also illustrating the distinct behaviour of different feature attribution methods

A confusion matrix for evaluating feature attribution methods

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The increasing use of deep learning models in critical areas of computer vision and the consequent need for insights into model behaviour have led to the development of numerous feature attribution methods. However, these attributions must be both meaningful and plausible to end-users, which is not always the case. Recent research has emphasized the importance of faithfulness in attributions, as plausibility without faithfulness can result in misleading explanations and incorrect decisions. In this work., we propose a novel approach to evaluate the faithfulness of feature attribution methods by constructing an ‘Attribution Confusion Matrix’, which allows us to leverage a wide range of existing metrics from the traditional confusion matrix. This approach effectively introduces multiple evaluation measures for faithfulness in feature attribution methods in a unified and consistent framework. We demonstrate the effectiveness of our approach on various datasets, attribution methods, and models, emphasizing the importance of faithfulness in generating plausible and reliable explanations while also illustrating the distinct behaviour of different feature attribution methods.This work is conducted within the NL4XAI project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 860621. This work is also supported by the Spanish Ministry of Science, Innovation and Universities (grants PID2021-123152OB-C21, TED2021-130295B-C33 and RED2022-134315-T) and the Galician Ministry of Culture, Education, Professional Training and University (grants ED431G2019/04 and ED431C2022/19). These grants were co-funded by the European Regional Development Fund (ERDF/FEDER program). This work is also supported by the European Union-Horizon 2020 Program under the scheme “INFRAIA-01-2018-2019 - Integrating Activities for Advanced Communities”, Grant Agreement n.871042, “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics” (http://www.sobigdata.eu) and by the Departament de Recerca i Universitats of the Generalitat de Catalunya under the Industrial Doctorate Grant DI 2018-100.Peer ReviewedPostprint (author's final draft

A Variance-Based Consensus Degree in Group Decision Making Problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

Empowerment Evaluation in Spain: The Critical Friend Role in Working with Rural Communities

Rural communities in Cuenca (Spain) are characterized by a great social dislocation, mostly due to the low population density in these areas. In this way, the existence of groups of citizens able to be active agents of their development process is a critical aspect for any community-based development process in this Spanish region. The Institute of Community Development of Cuenca (IDC) has been working with this type of groups for the last 30 years focusing on the organizational empowerment of the rural communities. Main tools in this process have been the empowerment evaluation approach and the critical friend role when helping the groups to achieve their objectives and reinforcing them. This chapter analyses the empowerment process and how the critical friend role is nourished by the facilitator figure

Nutritional status and clinical outcome of children on continuous renal replacement therapy: a prospective observational study

BACKGROUND: No studies on continuous renal replacement therapy (CRRT) have analyzed nutritional status in children. The objective of this study was to assess the association between mortality and nutritional status of children receiving CRRT. METHODS: Prospective observational study to analyze the nutritional status of children receiving CRRT and its association with mortality. The variables recorded were age, weight, sex, diagnosis, albumin, creatinine, urea, uric acid, severity of illness scores, CRRT-related complications, duration of admission to the pediatric intensive care unit, and mortality. RESULTS: The sample comprised 174 critically ill children on CRRT. The median weight of the patients was 10 kg, 35% were under percentile (P) 3, and 56% had a weight/P50 ratio of less than 0.85. Only two patients were above P95. The mean age for patients under P3 was significantly lower than that of the other patients (p = 0.03). The incidence of weight under P3 was greater in younger children (p = 0.007) and in cardiac patients and in those who had previous chronic renal insufficiency (p = 0.047). The mortality analysis did not include patients with pre-existing renal disease. Mortality was 38.9%. Mortality for patients with weight < P3 was greater than that of children with weight > P3 (51% vs 33%; p = 0.037). In the univariate and multivariate logistic regression analyses, the only factor associated with mortality was protein-energy wasting (malnutrition) (OR, 2.11; 95% CI, 1.067-4.173; p = 0.032). CONCLUSIONS: The frequency of protein-energy wasting in children who require CRRT is high, and the frequency of obesity is low. Protein-energy wasting is more frequent in children with previous end-stage renal disease and heart disease. Underweight children present a higher mortality rate than patients with normal body weight

A variance-based consensus degree in group decision making problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

An Analysis on Consensus Measures in Group Decision Making

In Group Decision Making (GDM) problems before to obtain a solution a high level of consensus among experts is required. Consensus measures are usually built using similarity functions measuring how close experts’ opinions or preferences are. Similarity functions are defined based on the use of a metric describing the distance between experts’ opinions or preferences. Different distance functions have been proposed to implement consensus measures. This paper analyzes the effect of the application of different aggregation operators combined with the use of different distance functions for measuring consensus in GDM problems. It is concluded that the application of different aggregation operators together with different distance functions has a significant effect on the speed of achieving consensus. These results are analysed and used to derive decision support rules, based on a convergent criterion, that can be used to control the convergence speed of the consensus process using the compared distance functions

A Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Making

Research conducted in collaboration between DMU and University of Granada (Spain). DIGITS, Department of Informatics, Faculty of Technology, De Montfort University, Leicester LE1 9BH, UK; Department of Quantitative Methods in Economic and Business, University of Granada, 18071 Granada, Spain; Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain; Department of Computer Science and A.I., University of Granada, 18071 Granada, SpainNOTICE: this is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences. http://dx.doi.org/10.1016/j.ins.2012.09.014An essential aim in group decision making (GDM) problems is to achieve a high level of consensus among experts. Consensus is defined as general or widespread agreement, and it is usually modelled mathematically via a similarity function measuring how close experts’ opinions or preferences are. Similarity functions are defined based on the use of a metric describing the distance between experts’ opinions or preferences. In the literature, different metrics or distance functions have been proposed to implement in consensus models, but no study has been carried out to analyse the influence the use of different distance functions can have in the GDM process. This paper presents a comparative study of the effect of the application of some different distance functions for measuring consensus in GDM. By using the nonparametric Wilcoxon matched-pairs signed-ranks test, it is concluded that different distance functions can produce significantly different results. Moreover, it is also shown that their application also has a significant effect on the speed of achieving consensus. Finally, these results are analysed and used to derive decision support rules, based on a convergent criterion, that can be used to control the convergence speed of the consensus process using the compared distance functions.The authors would like to acknowledge FEDER financial support from the Project FUZZYLING-II Project TIN2010-17876; the financial support from the Andalusian Excellence Projects TIC-05299 and TIC-05991, and also from the research Project MTM2009-08886. Prof. Francisco Chiclana would like to acknowledge the financial support from the University of Granada 2012 GENIL Strengthening through Short-Visits research program (Ref. GENIL-SSV)