Autori: Saltelli, Andrea, Lachi, Alessio, Llach, Josep, Perramon, Jordi, Baccini, Michela
Titolo: Robustification of structural equation modelling via global sensitivity analysis
Periodico: Statistical methods & applications : Journal of the Italian Statistical Society
Anno: 2025 - Volume: 34 - Fascicolo: 2 - Pagina iniziale: 211 - Pagina finale: 236

We propose a method for enhancing the robustness of Structural Equation Modelling (SEM), a multivariate statistical analysis technique employed for analyzing causal relationships among different aspects of given phenomena. This enhancement is achieved through the integration of Global Sensitivity Analysis, which assesses how uncertainties in model output can be attributed to various sources of input uncertainty. The robustification process involves several key steps, including bootstrapping evidence, error propagation, and uncertainty quantification. This method extends the approach named in the literature "modeling of the modelling process". To illustrate this approach, we apply it to two previously published test cases where SEM is used. The first one is related to the impact of artificial intelligence adoption on employee engagement and the second one investigates the effects of service quality and environmental practices on the competitiveness and financial performance of hotels. By quantifying the uncertainty inherent in the inference of our test cases, this procedure increases the robustness of the results derived from the test cases, thus generating a more defensible inference.




SICI: 1618-2510(2025)34:2<211:ROSEMV>2.0.ZU;2-G

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