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A deflated indicators approach for estimating second-order reflective models through PLS-PM: an empirical illustration

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  • M. Nitti
  • E. Ciavolino

Abstract

The paper provides a procedure aimed at obtaining more interpretable second-order models estimated with the partial least squares-path modeling. Advantages in interpretation stem from the separation of the two sources of influence on the data. As a matter of fact, in hierarchical models effects on manifest variables (MVs) are assigned to both first-order (specific) factors and second-order (general) factors. In order to separate these overlapping contributions, MVs are deflated from the effect of the specific latent variables (LVs) and used as indicators of the second-order LV. A case study is presented in order to illustrate the application of the proposed method.

Suggested Citation

  • M. Nitti & E. Ciavolino, 2014. "A deflated indicators approach for estimating second-order reflective models through PLS-PM: an empirical illustration," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(10), pages 2222-2239, October.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:10:p:2222-2239
    DOI: 10.1080/02664763.2014.909786
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    Cited by:

    1. Paola Pasca & Evelyn Simone & Enrico Ciavolino & Alessia Rochira & Terri Mannarini, 2023. "A higher-order model of community resilience potential: development and assessment through confirmatory composite analysis based on partial least squares," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1033-1054, April.
    2. Enrico Ciavolino & Sergio Salvatore & Piergiorgio Mossi & Gloria Lagetto, 2019. "High-order PLS path model for multi-group analysis: the prosumership service quality model," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2371-2384, September.
    3. Antonello D’Ambra & Pietro Amenta & Antonio Lucadamo, 2019. "Analyzing Customer Requirements to Select a Suitable Service Configuration Both for Users and for Company Provider," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 383-394, November.
    4. Jun-Hwa Cheah & Hiram Ting & T. Ramayah & Mumtaz Ali Memon & Tat-Huei Cham & Enrico Ciavolino, 2019. "A comparison of five reflective–formative estimation approaches: reconsideration and recommendations for tourism research," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1421-1458, May.
    5. Sharon Tan & Evan Lau & Hiram Ting & Jun-Hwa Cheah & Biagio Simonetti & Tan Hiok Lip, 2019. "How Do Students Evaluate Instructors’ Performance? Implication of Teaching Abilities, Physical Attractiveness and Psychological Factors," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 61-76, November.
    6. Maurizio Carpita & Enrico Ciavolino & Mariangela Nitti, 2019. "The MIMIC–CUB Model for the Prediction of the Economic Public Opinions in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 287-305, November.
    7. Majid Ghasemy & Hazri Jamil & James E. Gaskin, 2021. "Have your cake and eat it too: PLSe2 = ML + PLS," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 497-541, April.
    8. Enrico Ciavolino & Gloria Lagetto & Andrea Montinari & Amjad D. Al-Nasser & Amer I. Al-Omari & Matteo J. Zaterini & Sergio Salvatore, 2020. "Customer satisfaction and service domains: a further development of PROSERV," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1429-1444, December.
    9. Maurizio Carpita & Paola Pasca & Serena Arima & Enrico Ciavolino, 2023. "Clustering of variables methods and measurement models for soccer players’ performances," Annals of Operations Research, Springer, vol. 325(1), pages 37-56, June.

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