04325nam 22005655 450 991025269790332120200707031335.03-319-60595-X10.1007/978-3-319-60595-1(CKB)4340000000061947(MiAaPQ)EBC4930066(DE-He213)978-3-319-60595-1(EXLCZ)99434000000006194720170728d2017 u| 0engurcnu||||||||rdacontentrdamediardacarrierComplexity in Society: From Indicators Construction to their Synthesis /edited by Filomena Maggino1st ed. 2017.Cham :Springer International Publishing :Imprint: Springer,2017.1 online resource (332 pages) illustrations, tablesSocial Indicators Research Series,1387-6570 ;703-319-60593-3 Includes bibliographical references at the end of each chapters.Part I. Conceptual issues -- Chapter 1. Epistemology of Complexity (Alberto Peruzzi) -- Chapter 2. Building Knowledge. Between Measure and Meaning: A Phenomenological Approach (Rocco Sacconaghi) -- Part 2. Methodological Issues -- Chapter 3. Socio-Economic Statistics for A Complex World: Perspectives and Challenges in the Big Data Era (Marco Fattore) -- Chapter 4. Developing Indicators and Managing the Complexity (Filomena Maggino) -- Chapter 5 -- Dealing with Syntheses in a System of Indicators (Filomena Maggino) -- Chapter 6. Scalability of Composite Indices: Complexity Complications (Kenneth C. Land, Vicki L. Lamb, Xiaolu Zang) -- Part 3. Technical Issues -- Chapter 7. Synthesis of Indicators: The Composite Indicators Approach (Matteo Mazziotta & Adriano Pareto) -- Chapter 8. Synthesis of Indicators: The Non-Aggregative Approach (Marco Fattore) -- Chapter 9. The Role of Extended IRT Models for Composite Indicators Construction (Michela Gnaldi, Simone Del Sarto & Filomena Maggino) -- Part 4. Particular Experiences -- Chapter 10. Synthesis of Indicators Through Weighting: The Experiences of Quality of Life Measures (Chang-Ming Hsieh) -- Chapter 11. The Role of Normalization in Building Composite Cndicators. Rationale and Consequences of Different Strategies (Ludovico Carrino) -- Chapter 12. Steps Towards a Synthetic Measure Derived from a Partially Ordered Set (Giovanna Boccuzzo & Giulio Caperna) -- Chapter 13. Joint analysis of Structural Models and Performance: Merging Clustering and Composite Indicators in the Analysis of Europe 2020 strategy (Tommaso Rondinella & Elena Grimaccia).This volume discusses the many recent significant developments, and identifies important problems, in the field of social indicators. In the last ten years the methodology of multivariate analysis and synthetic indicators construction significantly developed. In particular, starting from the classical theory of composite indicators many interesting approaches have been developed to overcome the weaknesses of composites. This volume focuses on these recent developments in synthesizing indicators, and more generally, in quantifying complex phenomena.Social Indicators Research Series,1387-6570 ;70Social sciencesStatistics Quality of lifeMethodology of the Social Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/X17000Statistics for Social Sciences, Humanities, Lawhttps://scigraph.springernature.com/ontologies/product-market-codes/S17040Quality of Life Researchhttps://scigraph.springernature.com/ontologies/product-market-codes/X23000Social sciences.Statistics .Quality of life.Methodology of the Social Sciences.Statistics for Social Sciences, Humanities, Law.Quality of Life Research.301.0723Maggino Filomenaedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910252697903321Complexity in Society: From Indicators Construction to their Synthesis2531091UNINA