2016
DOI: 10.1002/asmb.2168
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The Pathmox approach for PLS path modeling segmentation

Abstract: Modeling has very often failed to live up to expectations, mostly because of the difficulty of comprehending relationships within phenomena and expressing them in mathematical models. Reality is frequently too complex to be reflected in a single model. This is often the case of marketing research, where variables relating to socioeconomics, psychographics or consumption constitute potential sources of heterogeneity. In such cases, the assumption of "one model fits all" is unrealistic and may lead to inaccurate… Show more

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Cited by 28 publications
(27 citation statements)
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References 27 publications
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“…To test the invariance of the measurement model across different sub PLS-PM models we follow the same approach of model comparison, first stated by (Chow, 1960;Lebart, et al, 1979;Lamberti, et al, 2016). We propose to perform a comparison of models test applied to the outer model.…”
Section: Invariance Testmentioning
confidence: 99%
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“…To test the invariance of the measurement model across different sub PLS-PM models we follow the same approach of model comparison, first stated by (Chow, 1960;Lebart, et al, 1979;Lamberti, et al, 2016). We propose to perform a comparison of models test applied to the outer model.…”
Section: Invariance Testmentioning
confidence: 99%
“…Here we just present the model, the main results of sub-models obtained by integrating the heterogeneity in the study and the outcome of the invariance test. The details and the results of this application are fully discussed in (Lamberti et al, 2016).…”
Section: Applicationmentioning
confidence: 99%
See 1 more Smart Citation
“…The Pathmox algorithm detects significant partitions in the presence of heterogeneity. However, it does not provide any information about the endogenous equations and the path coefficients that cause differences between 2 subgroups.…”
Section: Introductionmentioning
confidence: 99%
“…This model, developed by Wold (1982) [32] and extended more than ten years ago [33], consists of estimating the parameters of the model by a succession of simple and multiple regressions based on the relationships between the latent variables ("internal" or structural model) and the manifest variables ("external" or measurement model). It is recommended to [34]:…”
Section: Sample Selectionmentioning
confidence: 99%