Predicting and Analyzing User Engagement and Economic Impacts of Mobile Interactive Navigation in Smart Tourism Environments

Abstract

The advancement of smart tourism has shifted mobile navigation systems from route guidance tools toward experience-oriented enablers. However, conventional static navigation systems, constrained by limited interaction modes and weak contextual adaptability, fail to support immersive engagement or effectively stimulate tourism consumption. This study examines how mobile interactive navigation enhances user engagement in smart tourism scenarios and quantifies its economic impacts through an integrated “technological innovation–engagement measurement– economic impact” framework. A unified design paradigm integrating context awareness, multimodal interaction, and intelligent tour guidance is proposed. Based on this paradigm, a mobile navigation system incorporating multi-source fused positioning, lightweight dynamic AR rendering, adaptive path planning, and multi-channel interaction is developed, enabling high-precision localization and immersive experiences in complex scenic environments. A three-dimensional user engagement measurement framework covering behavioral, emotional, and cognitive dimensions is constructed, together with a time-series Transformer-based prediction model to capture dynamic engagement trends and inflection points. Furthermore, a structural equation model (SEM) combined with a multi-agent simulation system is employed to analyze the driving mechanisms through which engagement influences tourism consumption and regional economic spillover effects. These results confirm the effectiveness of mobile interactive navigation in enhancing user engagement and scenic-area economic performance.