1,720,994 research outputs found
Different ranking methods: potentialities and pitfalls for the case of European opinion poll
No full textPrioritization and ranking of objects are primary needs in various substantive fields. It might be said that ranking and comparison are the first step in every risk assessment procedure, whatever the ‘risk’ is intended as: social, environmental, political or economic. Often objects to be ranked are valued by a multi-dimensional attribute which is usually transformed into a composite numerical score. In spite of conventional solutions, the author agrees with recent recommendations of performing multiple ranking, keeping indicators separated. Different innovative methods are analyzed and compared: Hasse diagrams method, POSAC and Nonlinear PCA. The first one stems directly from partial order theory, the second one may be seen as an approximation of Hasse representation in a two dimensional space, whilst the third one belongs to the wide set of non-linear multivariate techniques and it is particularly suitable in handling data of categorical type. Among them, the first two methods compare objects on the basis only on order property of data, whilst the last one simultaneously performs an optimal scale of qualitative attributes and a ranking of objects. The case study is based on the Eurobarometer survey carried out in 2002, at the request of the European Commission, which collects Europeans opinion about various political and social issues. The analysis is focused on users’ level of satisfaction about access easiness, cost, quality, information received and contracts of various services of general interest, such as telephone services, power (gas and electricity) providers, water and postal utilities, urban and rail transports. Separate indicators are set up for each facet of each service within different European regions. Eventually, the ranking of European regions is performed on the basis of the overall performance of services of general interest, as perceived by users. Selected methods lead to almost alike results, still with some differentiations due to different approaches used. As it frequently occurs, each method has its own advantages and pitfalls which are here explored and compared
Europeans and services of general interest: where is the best quality perceived?
No full textThis paper aims to classify eighteen European regions on the basis of various criteria which reflect the overall performance of services of general interest, as perceived by consumers. The analysis is based on the Eurobarometer survey carried out in 2002, at the request of the European Commission, which collects citizens
opinion about various political and social issues. The focus of the analysis is on public level of satisfaction about
access easiness, cost, quality, information received and contracts of different services, such as telephone services, power (gas and electricity) providers, water and postal utilities, urban and rail transports. The final goal is the comparison of the overall perceived performance of public utility service providers among countries. The paper agrees with recent recommendations of performing multiple ranking, keeping indicators separated, in spite of conventional solutions based on composite indicators.
To obtain a country ranking on services, satisfaction indicators are set up for each country and different innovative data-analysis methods are applied: a partial order methodology, based on Hasse diagrams and two dimensionality reduction techniques, POSAC method and Nonlinear PCA, particularly suitable to handle data of categorical type. As it frequently occurs, each method has its own advantages which are here explored and compared.
Such evaluation has the aim of detecting prospective weak points within European areas. Results could be jointly used, mutatis
mutandis, with typical Eurobarometer reports carried out regularly at request of the European Commission - Directorate of General
Health and Consumer Protection, such as those specifically focused on services of general interest
The dualistic approach of FCA : a further insight into Ontario Lake sediments
No full textThe investigation of object-by-attribute matrices is very common in statistics and data analysis with the aim of uncovering every possible relationships among objects and/or attributes. Formal Concept Analysis (FCA) is a method, which stems directly from partial order and lattice theory, that allows to symmetrically uncover linkages among objects and attributes whenever a relation stands among the two sets. It provides efficacious graphical representation and computes association rules between attributes, thus helping in the detection of possible synergism or antagonism of attributes. In the paper, FCA potentialities are discussed and described by means of a case study already investigated by other partial order techniques: the case of Lake Ontario sediment samples. Data derive from a 'test battery' for a simultaneous analysis of
degradation of Lake Ontario samples, which are basically of two typologies: hygienic and toxicity tests. A multi-valued approach is adopted to cope with the ordinal feature of data. Results highlight interesting interaction among hygienic compounds and a synergism between the two toxicity tests
Exploring partial order of European countries.
No full textPartial Order Theory has been recently more and more employed in applied science to overcome the intrinsic disadvantage hidden in
linear ranking, if a multiple indicator system is available. Despite its numerous positive features, there are many practical cases where the interpretation of the partial order can be rather troublesome.
In these cases the analysis of underlying dimensions could be useful to uncover particular data structures. The paper shows a way of addressing the problem with the help of an actual case study, which
deals with European opinions on services of general interest. In particular, an overall ranking of countries is firstly provided and
then a method to detect dimensions is discussed and applied. The analysis stems directly from the Partially Order Set (poset) and Lattice theory with particular references to dimension theory and
Formal Concept Analysis. The study is eventually able to pinpoint role and relevance of both different services and different criteria in defining the partial order
From multiple choice questionnaires to synthetic indicators : jointly use of Rasch analysis and NonLinear PCA
No full textCalibration of multiple-choice questionnaires to assess quantitative indicators
No full textThe joint use of two latent factor methods is proposed to assess a measurement instrument for an underlying phenomenon. For this purpose, Rasch analysis is initially used to properly calibrate questionnaires, to discard non informative variables and redundant categories. As a second step, an optimal scaling technique, Nonlinear PCA, is applied to quantify variable categories and to compute a continuous indicator. Specifically, the paper deals with the state of decay of Italian buildings of great architectural and historical interest, which function as a case study . The decay level of the buildings is quantified on the basis of a broad set of observed ordinal variables and the final indicator may be independently used for buildings of future inventory. Overall, similarity and diverse potentiality of the techniques are analyzed and discussed with the purpose of exploring the synergic effect of their combined use
Setting-up of indicators to measure and to compare users’ dissatisfaction : the case of public services in Europe
No full textWe propose the setting-up of indicators for classifying European countries with relation to consumers' dissatisfaction for services of general interest (SGI). The reference data set is the 2002 Standard Eurobarometer database (EB58) and it refers to EU members before 2004 enlargement. Proposed indicators are based on nonlinear principal component analysis. Their robustness is verified by a Monte Carlo approach. The level of dissatisfaction is used for country comparison and for detecting possible hotspots
Exploring partial order of European countries
No full textPartial Order Theory has been recently more and more employed in applied science to overcome the intrinsic disadvantage hidden in aggregation, if a multiple attribute
system is available. Despite its numerous positive features, there are many practical cases where the interpretation of the partial order can be rather troublesome. In these cases the analysis of underlying dimensions could be useful to uncover particular data structures. The paper shows a way of addressing the problem with the help of an actual case study, which deals with European opinions on services of general interest. In particular, a partial
order of countries is firstly provided and then a method to detect dimensions is discussed and applied. The analysis stems directly from the Partially Order Set (poset) and Lattice theory with particular references to dimension theory and Formal Concept Analysis. The study is eventually able to pinpoint role and relevance of different attributes characterizing
EU countries which are used to define the partial orde
Evaluation and comparison of European countries : public opinion on services
No full textWe propose the setting-up of an indicator for classifying European countries with relation to consumers' satisfaction for services of general interest. Services considered are fixed telephone service, electricity supply, railways and postal service. The reference data set is the 2002 Standard Eurobarometer database (EB58) and it refers to EU members before 2004 enlargement. The proposed indicator is based on nonlinear principal component analysis and supplies a measure for the citizen's satisfaction. Its robustness is verified by a Monte Carlo approach. The level of satisfaction is eventually
used for country comparison and for detecting possible hotspots, in
order to support decision making policies
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