Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients

نویسندگان

چکیده

Partial least squares structural equations modeling (PLS-SEM) uses sampling bootstrapping to calculate the significance of model parameter estimates (e.g., path coefficients and outer loadings). However, when data are time series, as in marketing mix modeling, shows inconsistencies that arise because series has an autocorrelation structure contains seasonal events, such Christmas or Black Friday, especially multichannel retailing, making analysis PLS-SEM unreliable. The alternative proposed this research maximum entropy (meboot), a technique specifically designed for which maintains preserves occurrence over events changes occurred original bootstrapped series. results showed meboot had superior performance than terms coherence quality analysis.

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ژورنال

عنوان ژورنال: Mathematics

سال: 2021

ISSN: ['2227-7390']

DOI: https://doi.org/10.3390/math9151832