The Impact of AI-Driven Personalization on Consumer Purchase Intentions: A Survey of the Leisure Industry

Abstrak

This study analyzes AI personalization's effects on consumer’s purchase intention in the leisure industry. We collected data from 298 respondents through online survey following a quantitative research design on respondents who had previous experience with AI driven platforms in leisure type contexts. AI personalization has different forms including personalized recommendations, dynamic content, personalized communication, behavioral tracking and algorithm transparency. The collected data were processed using IBM SPSS 27th version, which included a descriptive analysis, tested classical assumptions, and conducted regression analyses to test our research hypotheses on each of the different forms of AI personalization. The findings indicated that AI personalization can have a significantly positive influence on consumer purchase intention, but its explanatory power remains limited, and its effectiveness depends on the integration of other critical factors, particularly trust and user experience. Within the different forms of personalization, we found behavioral tracking and algorithm transparency to be the greatest influencers of trust and perceived value and willingness to buy outcomes. Furthermore, we found trust and transparency to be significant mediating variables in the relationship between AI driven systems and consumer purchase decisions. These findings will be useful and timely to marketers and developers that plan to develop their digital engagement and conversion strategies, and for the future research is encouraged to further explore the interplay between AI, consumer trust, and purchasing behavior to support the development of more effective and sustainable digital marketing strategies.

Identifier

• DOI: https://doi.org/10.5281/zenodo.19840778
• OpenAlex: https://openalex.org/W7157001582