This study examines how Hofstede’s cultural dimensions explain cooperatives’ tendency to embrace innovative sustainable social economy projects. The study employs a quantitative cross-sectional design using a standardized survey of 499 Spanish cooperatives with no record of implementing such projects. The results suggest that collectivism, long-term orientation, and high power distance strongly predict cooperatives’ willingness to adopt innovative sustainable social economy projects. Cluster analysis reveals two cultural profiles of cooperatives. Cooperatives in the cluster defined by collectivism, long-term vision, and low uncertainty avoidance appear to have the highest adoption propensity. This finding demonstrates that Hofstede’s cultural dimensions theory offers a powerful framework to explain cooperatives’ adoption of innovation- and sustainability-oriented social economy projects, even though the effects of masculinity and indulgence appear to be weak or nonsignificant. A major implication of this research is therefore that cultural dimensions should be considered in policy design and cooperative support programs. This research extends the scope of application of Hofstede’s cultural dimensions theory to the social economy, specifically innovation in cooperatives. It also demonstrates that culturally relevant interventions boost the effectiveness of sustainability-oriented programs. Future research should study longitudinal data sets and qualitative data to develop a more comprehensive understanding of the phenomena discussed in this paper.

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.

Despite the potential of AI to revolutionize product creation and service delivery, a lack of consumer trust could significantly, hinder its adoption and utility. This research explores how transparency, simplicity, familiarity, and authenticity collectively impact consumer trust in AI-created products, which includes both goods and services. AI-created products refer to those in which artificial intelligence systems play a critical role in design, manufacturing, or decision-making processes. This study collected, data from 504 respondents which were then analysed through partial least square – structural equational modelling, (PLS-SEM). The results indicate that higher levels of transparency about AI involvement directly correlate with increased consumer trust. Conversely, increased product complexity is found to negatively affect trust. While greater consumer familiarity with AI positively, impacts trust levels. Furthermore, the perceived authenticity, of AI-generated content significantly enhances consumer trust. Each of these findings contribute to a greater understanding of the variables influencing consumer, trust in AI-created goods. For policymakers, the importance of establishing clear guidelines on AI transparency, and authenticity is underscored, potentially through the introduction of, standardized labelling for AI-created products. For practitioners, the results highlight the need for simplifying AI technologies and enhancing consumer familiarity through education and engagement strategies. The theoretical contribution of the study lies in its holistic examination of factors, influencing consumer trust in AI-created goods, filling a significant gap in existing literature. By integrating, multiple variables into a single conceptual framework, this research provides, valuable insights into the dynamics of consumer trust in context of AI integration.