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

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  • Schivinski, Bruno

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.

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  • Schivinski, Bruno, 2021. "Eliciting brand-related social media engagement: A conditional inference tree framework," Journal of Business Research, Elsevier, vol. 130(C), pages 594-602.
    • Handle: RePEc:eee:jbrese:v:130:y:2021:i:c:p:594-602
    DOI: 10.1016/j.jbusres.2019.08.045
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