Model-based post hoc segmentation (with REBUS-PLS) for capturing heterogeneous consumer behaviour

Abstract

There is in the marketing literature a consensus that consumer behaviour varies across segments. Capturing this heterogeneity poses a considerable challenge for marketing scientists. Several researchers have consequently formulated a priori and post hoc techniques for detecting consumer heterogeneity. One such recent post hoc technique is model-based segmentation enabled by REBUS-PLS (response-based procedure for detecting unit segments in partial least squares), which has been developed within the framework of partial least squares approach to structural equation modelling. This article argues that model-based segmentation, as opposed to the alternative techniques, is a more objective and reliable approach for capturing heterogeneity in consumer behaviour. Moreover, this article illustrates how a model-based segmentation can be performed using REBUS-PLS through a set of consumer data, and explains conceptually the advantages of this statistical procedure. From a practical point of view, the article also proposes that model-based segmentation with REBUS-PLS or similar statistical procedures can contribute to the appeal of segmentation studies in the eyes of marketing managers.

Is psychosis a syndemic manifestation of historical and contemporary adversity? Findings from UK Biobank

“…[48][49][50][51][52] Support from available guidelines enabled a threshold to be set for interpreting relative GOF values equal to or higher than 0.900 as arguing in favour of the model. 51,[53][54][55][56] In addition, we conducted subgroup analyses by: gender (dichotomised by UKBB, with male as the reference) based on National Health Service records and self-report; and ethnicity (ethnic minorities aggregated; then Black, South Asian, White other, Other, and White British.…”