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Developments in Higher-Order PLS-PM for the building of a system of Composite Indicators

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  • Rosanna Cataldo

    (University “Federico II”)

  • Maria Gabriella Grassia

    (University “Federico II”)

  • Natale Carlo Lauro

    (University “Federico II”)

  • Marina Marino

    (University “Federico II”)

Abstract

Many phenomena are complex and therefore difficult to measure and to evaluate. Research, in the last years, has been focusing on the development and use of a system of Composite Indicators in order to obtain a global description of a complex phenomenon and to convey a suitable synthesis of information. The existing literature offers several alternative methods for obtaining a Composite Indicators. The work focuses on building them through to Structural Equation Modeling, specifically with the use of Partial Least Squares-Path Modeling. In recent years many advances have been developed, in the context of these models to solve some problems related to the role that the Composite Indicators play within that system; in particular, the research focuses on a particular aspect linked to the high level of abstraction, when a Composite Indicator is manifold, lacks its own manifest variables and is described by various underlying blocks. In this regard we have proposed two alternative methods for analyzing and studying higher-order construct Composite Indicator, on the calculation of the estimates for the determination of endogenous block, so as to be the best estimated and represented by the blocks below.

Suggested Citation

  • Rosanna Cataldo & Maria Gabriella Grassia & Natale Carlo Lauro & Marina Marino, 2017. "Developments in Higher-Order PLS-PM for the building of a system of Composite Indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 657-674, March.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:2:d:10.1007_s11135-016-0431-1
    DOI: 10.1007/s11135-016-0431-1
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    References listed on IDEAS

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    2. Pasquale De Muro & Matteo Mazziotta & Adriano Pareto, 2011. "Composite Indices of Development and Poverty: An Application to MDGs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(1), pages 1-18, October.
    3. Ernest Reig-Martínez, 2013. "Social and Economic Wellbeing in Europe and the Mediterranean Basin: Building an Enlarged Human Development Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 111(2), pages 527-547, April.
    4. Jörg Henseler & Marko Sarstedt, 2013. "Goodness-of-fit indices for partial least squares path modeling," Computational Statistics, Springer, vol. 28(2), pages 565-580, April.
    5. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
    6. Kettaneh, Nouna & Berglund, Anders & Wold, Svante, 2005. "PCA and PLS with very large data sets," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 69-85, January.
    7. Laurens Cherchye & Wim Moesen & Tom Van Puyenbroeck, 2004. "Legitimately Diverse, yet Comparable: On Synthesizing Social Inclusion Performance in the EU," Journal of Common Market Studies, Wiley Blackwell, vol. 42(5), pages 919-955, December.
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    Cited by:

    1. Manuel Ángel Fernández-Gámez & A. Manuel Gutiérrez-Ruiz & Rafael Becerra-Vicario & Daniel Ruiz-Palomo, 2019. "The Effects of Creating Shared Value on the Hotel Performance," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    2. Matheus Pereira Libório & Oseias da Silva Martinuci & Sandro Laudares & Renata de Mello Lyrio & Alexei Manso Correa Machado & Patrícia Bernardes & Petr Ekel, 2020. "Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    3. Gisela Casado Salguero & Manuel Ángel Fernández Gámez & Ignacio Aldeanueva Fernández & Daniel Ruíz Palomo, 2019. "Competitive Intelligence and Sustainable Competitive Advantage in the Hotel Industry," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
    4. Venera Tomaselli & Mario Fordellone & Maurizio Vichi, 2021. "Building Well-Being Composite Indicator for Micro-Territorial Areas Through PLS-SEM and K-Means Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 407-429, January.
    5. Roberto Fasanelli & Ida Galli & Maria Gabriella Grassia & Marina Marino & Rosanna Cataldo & Carlo Natale Lauro & Chiara Castiello & Filomena Grassia & Caterina Arcidiacono & Fortuna Procentese, 2020. "The Use of Partial Least Squares–Path Modelling to Understand the Impact of Ambivalent Sexism on Violence-Justification among Adolescents," IJERPH, MDPI, vol. 17(14), pages 1-22, July.
    6. Rosanna Cataldo & Corrado Crocetta & Maria Gabriella Grassia & Natale Carlo Lauro & Marina Marino & Viktoriya Voytsekhovska, 2021. "Methodological PLS-PM Framework for SDGs System," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 701-723, August.
    7. Corrado Crocetta & Laura Antonucci & Rosanna Cataldo & Roberto Galasso & Maria Gabriella Grassia & Carlo Natale Lauro & Marina Marino, 2021. "Higher-Order PLS-PM Approach for Different Types of Constructs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 725-754, April.

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