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Quantile composite-based path modeling

Author

Listed:
  • Cristina Davino

    (University of Macerata)

  • Vincenzo Esposito Vinzi

    (ESSEC Business School)

Abstract

The paper aims at introducing a quantile approach in the Partial Least Squares path modeling framework. This is a well known composite-based method for the analysis of complex phenomena measurable through a network of relationships among observed and unobserved variables. The proposal intends to enhance potentialities of the Partial Least Squares path models overcoming the classical exploration of average effects. The introduction of Quantile Regression and Correlation in the estimation phases of the model allows highlighting how and if the relationships among observed and unobserved variables change according to the explored quantile of interest. The proposed method is applied to two real datasets in the customer satisfaction measurement and in the sensory analysis framework but it proves to be useful also in other applicative contexts.

Suggested Citation

  • Cristina Davino & Vincenzo Esposito Vinzi, 2016. "Quantile composite-based path modeling," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 491-520, December.
    • Handle: RePEc:spr:advdac:v:10:y:2016:i:4:d:10.1007_s11634-015-0231-9
    DOI: 10.1007/s11634-015-0231-9
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    References listed on IDEAS

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    Cited by:

    1. Pasquale Dolce & Cristina Davino & Domenico Vistocco, 2022. "Quantile composite-based path modeling: algorithms, properties and applications," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 909-949, December.
    2. Cristina Davino & Vincenzo Esposito Vinzi & Estefania Santacreu-Vasut & Radu Vranceanu, 2019. "An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(2), pages 811-838, June.
    3. Cristina Davino & Pasquale Dolce & Stefania Taralli & Vincenzo Esposito Vinzi, 2018. "A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 999-1029, April.
    4. Cristina Davino & Pasquale Dolce & Stefania Taralli & Domenico Vistocco, 2022. "Composite-Based Path Modeling for Conditional Quantiles Prediction. An Application to Assess Health Differences at Local Level in a Well-Being Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 907-936, June.
    5. Hao Cheng, 2023. "Composite quantile estimation in PLS-SEM for environment sustainable development evaluation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6249-6268, July.
    6. Hao Cheng, 2023. "Environmental Effect Evaluation: A Quantile-Type Path-Modeling Approach," Sustainability, MDPI, vol. 15(5), pages 1-21, March.

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