The Influence of Machine Learning on Consumer Decision-Making Patterns in Germany: The Mediating Role of AI Recommendation Systems for Achieving Sales and Customer Satisfaction
DOI:
https://doi.org/10.65080/c0nevs55Keywords:
Machine learning, consumer decision-making patterns, AI recommendation systems, customer trust, SEM, AI technologiesAbstract
Introduction: Consumer behaviour in global markets has been affected by the rapid evolution of machine learning (ML) and artificial intelligence (AI). The research aimed to evaluate the impact of ML on consumer decision-making, along with the mediating role of the AI recommendation system, using the case of Germany. Germany was a good case study because of its stringent duty to protect privacy and sizeable tech-savvy consumer base.
Methods: A quantitative, cross-sectional design was used with 385 German consumers surveyed through a structured Likert scale questionnaire. The data was analyzed using the PLS-SEM and SmartPLS.
Results: The findings indicated that ML (B = 0.250, p-value = 0.00) significantly and positively impacts consumer decision making. It also indicated that the AI recommendation system (B = 0.222, p-value = 0.000) partially mediates the relationship between ML and consumer decision making.
Conclusion: This research provides practical guidance for companies, focusing on a transparent, user-centric AI system that empowers rather than controls consumers. In contexts like Germany, success relies on cultural alignment, trust, and user autonomy, not just advanced technology, elaborating the need to tailor AI design and deployment strategies to specific consumer environments.
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