Modeling the Probability of Consumer Boycott Participation Among Europeans Using Artificial Intelligence

Abstract

Consumer boycotts are vital tools for shaping corporate and socio-political landscapes. Despite extensive research, the influence of individual and sociocultural factors on boycott participation across diverse European nations remains unclear. This study addresses this gap by applying machine learning techniques, such as decision trees and gradient boosting, to data from 24 countries in the European Social Survey. The analysis identifies civic activities, including petition signing and volunteering, as key drivers of consumer boycott participation, alongside political interest, environmental concern, and Internet usage. It also reveals complex interactions with age, religiosity, and national context. By integrating AI into consumer activism research, the study enhances predictive accuracy and deepens the theoretical understanding of political and civic behavior dynamics. Understanding the predictors of consumer boycotts can help policymakers and organizations design more effective strategies for addressing civic demands, potentially influencing market responses to consumer activism.