Post-modern Religiosity and Consumer Ethics: A Research by K-Means Based Consumer Segmentation and Random Forest Assisted Classification
DOI:
https://doi.org/10.63556/tisej.2025.1532Keywords:
Postmodern Religiosity, Consumer Ethics, Ethical Consumption, Machine Learning, Consumer SegmentationAbstract
This study examines the relationship between postmodern religiosity and consumer ethics using machine learning techniques, particularly K-Means clustering and Random Forest classification. Participants were categorized into three groups based on their religiosity levels: religious, undecided, and distant from religious beliefs. The findings reveal that higher religious belief, in the postmodern sense, correlates with stronger ethical consumption behaviors. The religious group exhibited both cognitive and behavioral ethical consumption, while the undecided group demonstrated cognitive ethical attitudes without translating them into actions. The secular group, however, showed individualistic and utilitarian consumption patterns, lacking a clear ethical consumption tendency. The Random Forest model, which achieved 92% accuracy, was employed to predict ethical consumption patterns, with key variables identified through SHAP analysis. This study highlights how postmodern religiosity influences consumer ethics, offering valuable insights for marketers aiming to target ethical consumers.
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