This Special Issue has drawn inspiration from the Conference “Innovation & Society 2017—Statistical Methods for Evaluation and Quality” (IES2017), held at the University of Naples “Federico II” (Italy) September 6–7, 2017. The IES2017 Conference was the 8th Scientific Meeting of the “Statistics for the Evaluation and Quality of Services Group of the Italian Statistical Society—(SVQS)”. It has been organized to offer an overview of statistical approaches and methodologies on evaluation of services and to contribute to the discussion on services’ innovation evaluation, focusing on various of economic and social policies actors. To make it as useful and constructive as possible, the Conference IES2017 was open to the participation of scholars from several disciplines, experts, development policies managers dealing with the relationships among evaluation, innovation and society. The 23 articles of this Special Issue, selected after double-blind peer reviews, concern studies with applications in different fields and with many different statistical approaches sharing the common aim stated by the Conference IES2017. From the empirical point of view, the articles can be classified in three macro-fields: Education (Centoni et al., De Iaco et al., Di Palma and Gallo, Tan et al., Mariani et al., Masserini et al., Maturo et al., Sarra et al., Vanacore and Pellegrino.); Economics (Antolini and Simonetti, Arbolino et al., Cerqueti et al., Ciavolino et al., Crisci et al., Petrella et al., Simonacci and Gallo) and Services (D’Ambra et al., De Simone et al., Di Palma and Gallo, Lombardo et al., Montanari and Doretti, Nissi et al., Oliveri et al.). On the other hand, considering the statistical methods used by the authors, three methodological approaches can be identified: Latent Variable Models (Centone et al., Tan et al., Maturo et al., Masserini et al., Palma et al., Ciavolino et al., Montanari and Doretti); Regression Models (Arbolino et al., Crisci et al., De Iaco et al., De Simone et al., Nissi et al., Petrella et al., Sarra et al.) and Data Analysis Models (Antolini and Simonetti, Cerqueti et al., D’Ambra et al., Di Palma and Gallo, Lombardo et al., Mariani et al., Oliveri et al., Simonacci and Gallo, Vanacore and Pellegrino). The heterogeneity of application and statistical approaches highlights the broad spectrum of data analyses and the richness of the methodologies.

Socio-Economic Indicators for Performance Evaluation and Quality Assessment: Statistical Methods and Applications

Donato Posa;
2019

Abstract

This Special Issue has drawn inspiration from the Conference “Innovation & Society 2017—Statistical Methods for Evaluation and Quality” (IES2017), held at the University of Naples “Federico II” (Italy) September 6–7, 2017. The IES2017 Conference was the 8th Scientific Meeting of the “Statistics for the Evaluation and Quality of Services Group of the Italian Statistical Society—(SVQS)”. It has been organized to offer an overview of statistical approaches and methodologies on evaluation of services and to contribute to the discussion on services’ innovation evaluation, focusing on various of economic and social policies actors. To make it as useful and constructive as possible, the Conference IES2017 was open to the participation of scholars from several disciplines, experts, development policies managers dealing with the relationships among evaluation, innovation and society. The 23 articles of this Special Issue, selected after double-blind peer reviews, concern studies with applications in different fields and with many different statistical approaches sharing the common aim stated by the Conference IES2017. From the empirical point of view, the articles can be classified in three macro-fields: Education (Centoni et al., De Iaco et al., Di Palma and Gallo, Tan et al., Mariani et al., Masserini et al., Maturo et al., Sarra et al., Vanacore and Pellegrino.); Economics (Antolini and Simonetti, Arbolino et al., Cerqueti et al., Ciavolino et al., Crisci et al., Petrella et al., Simonacci and Gallo) and Services (D’Ambra et al., De Simone et al., Di Palma and Gallo, Lombardo et al., Montanari and Doretti, Nissi et al., Oliveri et al.). On the other hand, considering the statistical methods used by the authors, three methodological approaches can be identified: Latent Variable Models (Centone et al., Tan et al., Maturo et al., Masserini et al., Palma et al., Ciavolino et al., Montanari and Doretti); Regression Models (Arbolino et al., Crisci et al., De Iaco et al., De Simone et al., Nissi et al., Petrella et al., Sarra et al.) and Data Analysis Models (Antolini and Simonetti, Cerqueti et al., D’Ambra et al., Di Palma and Gallo, Lombardo et al., Mariani et al., Oliveri et al., Simonacci and Gallo, Vanacore and Pellegrino). The heterogeneity of application and statistical approaches highlights the broad spectrum of data analyses and the richness of the methodologies.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11587/433854
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