2002
DOI: 10.1007/bf03396655
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Capturing Customer Heterogeneity using a Finite Mixture PLS Approach

Abstract: An approach for capturing unobserved customer heterogeneity in structural equation modeling is proposed based on partial least squares. The method uses a modified finite-mixture distribution approach. An empirical analysis using quality, customer satisfaction and loyalty data for convenience stores illustrates the advantages of the new method vis-à-vis a traditional market segmentation scheme based on well known grouping variables. The results confirm the assumption of heterogeneity in the individuals' percept… Show more

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Cited by 225 publications
(139 citation statements)
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“…In our exploratory study context of examining the drivers and outcomes of wine consumption based on a cross-generation sample, PLS path modelling was considered as the appropriate method for the empirical tests of our hypotheses. PLS integrates principal components analysis with multiple regression (Hahn et al, 2002) based on least squares estimation with the primary objective to maximize the explanation of variance (or, equivalently, the minimization of error) in the dependent constructs of a structural equation model (Henseler et al, 2009). PLS path modelling is considered more as an exploratory approach than as a confirmatory one.…”
Section: Methodsmentioning
confidence: 99%
“…In our exploratory study context of examining the drivers and outcomes of wine consumption based on a cross-generation sample, PLS path modelling was considered as the appropriate method for the empirical tests of our hypotheses. PLS integrates principal components analysis with multiple regression (Hahn et al, 2002) based on least squares estimation with the primary objective to maximize the explanation of variance (or, equivalently, the minimization of error) in the dependent constructs of a structural equation model (Henseler et al, 2009). PLS path modelling is considered more as an exploratory approach than as a confirmatory one.…”
Section: Methodsmentioning
confidence: 99%
“…Consequently, one cannot rule out that countries exhibiting fairly different levels of Regulatory, Business and Resources emerge in the same response-based group. The FIMIX-PLS procedure (Hahn et al, 2002;Ringle et al, 2008) is employed to account for the discrete heterogeneity residing in the data set of the destination competitiveness of 129 countries. Recent comparison studies of heterogeneity-capturing PLS methods by Esposito Vinzi et al (2007) and Sarstedt (2008) demonstrate that the FIMIX-PLS routine as implemented in SmartPLS excels five rivalling approaches.…”
Section: Considering Unobserved Heterogeneity Among the Destination Cmentioning
confidence: 99%
“…Since the ECSI model was not analysed yet regarding the existence of mutual exclusive homogenous subgroups in terms of its relations, there is not previous information about possible sources of heterogeneity (observed heterogeneity), i.e., about the variables that could be beyond the different segments. Therefore, in order to identify the graduates' segments, the FInite MIXture Partial Least Squares (FIMIX-PLS) method will be applied (Hahn et al, 2002). This method is particularly adequate for the analysis of unobserved heterogeneity in PLS-PM (Rigdon et al, 2010;Ringle et al, 2010;Sarstedt, 2008), i.e., to identify segments when there is no prior information about the relevant segmentation variables.…”
Section: Introductionmentioning
confidence: 99%