Eliciting brand-related social media engagement: A conditional inference tree framework

Bruno Schivinski

Journal of Business Research, 2021, vol. 130, issue C, 594-602

Abstract: This study presents a machine learning approach using conditional inference tree (Ctree) to determine cognitive patterns that elicit consumer engagement into social media. Using the Ctree algorithm, a predictive model was computed using self-reported data on consumers' perceptions of brand equity and engagement into brand-related social media behavior from a sample of 1356 individuals. The predictive modeling analysis revealed 5 different cognitive patterns (rules) that stimulate brand-related social media behavior. Each rule comprises behavioral engagement discriminating low, medium, and high levels of consumption, contribution, and creation of brand-related social media content. Furthermore, based on the different patterns, the analysis portrait a typology of 5 subtypes of consumers according to their behavior, which by complementing the predictive analysis information may be used to stimulate different levels of consumption, contribution, and creation of brand-related social media content.

Keywords: CBBE; COBRAs; Social media; Machine learning; Typology; Consumer brand engagement (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:130:y:2021:i:c:p:594-602

DOI: 10.1016/j.jbusres.2019.08.045

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