Search Conferences

Type in any word, words or author name. This searchs through the abstract title, keywords and abstract text and authors. You may search all conferences or just select one conference.


 All Conferences
 EMAC 2019 Annual Conference
 EMAC 2020 Annual Conference
 EMAC 2020 Regional Conference
 EMAC 2021 Annual Conference

EMAC 2020 Regional Conference


A Latent Allocation Model for Mindset Variables
(R2020-83486)

Published: September 16, 2020

AUTHORS

pablo marshall, puc

KEYWORDS

LDA; Mindset; Modelling

ABSTRACT

Mindset metrics, the measure of consumer’s perceptions, attitudes, and intentions, have a long tradition in marketing. Two important mindset metrics are brand awareness and attribute importance. This paper aims to use an extension/modification of the Latent Dirichlet Allocation (LDA) model used for text analytics that incorporates Bernoulli observations instead of the multinomial specification in the LDA model. Dichotomous variables are usual in mindset metrics, and for these variables, the model extension proposed in this study is more appropriate than the usual LDA model. Two applications, the first in brand awareness and the second in attribute importance, illustrate the model.