AI-Supported Participant Experience Management in Recreational Areas: The Case of Smart Parks

Abstract

The aim of this study is to examine individuals’ reasons for participating in recreational activities within the context of AI-supported recreational area applications and to evaluate their relationship with overall participation levels. Data were collected using only the Recreational Activity Participation Motivation Scale and the responses of 485 participants were analyzed. Significant and positive correlations were found between the subdimensions of the scale -intellectual motivation, social component, competence mastery and avoidance motivation- and the overall level of participation. Correlation, reliability, and factor analyses supported all hypotheses. The study’s unique contribution lies in its focus on how these findings can be applied to the design of AI- supported user experience management systems. Results indicate that integrating user motivations into AI- supported platforms can enable more personalized and interactive recreational experiences. Accordingly, this research aims to contribute to public space planning within the broader context of digital transformation and intelligent systems in recreation management.