“Smart Tourism Symposium 2025: Intersection of Technology and Applications” (20 May) is open for registration

“Experience-based Competitiveness Analysis: An AI Approach” Presented by Prof. Gang LI from Deakin University, Australia

Abstract: Tourism is a key economic driver, and destination competitiveness is critical for sustaining tourism growth. Traditional resource-based competitiveness models often struggle to capture the evolving dynamics of the tourism market. This presentation introduces an AI-driven, experience-based approach to evaluating and enhancing destination competitiveness. Leveraging big data, it develops a sentiment-based analytical framework using touchpoint theory and aspect-based sentiment analysis to assess tourist satisfaction with key experiences. Furthermore, a prescriptive AI model integrating causal counterfactual reasoning and clustering is introduced to formulate targeted competitiveness improvement strategies. By uncovering competitive advantages and enabling minimal-change strategy optimization, this approach provides data-driven, actionable insights for destinations. This research underscores the power of AI and big data in transforming destination competitiveness assessment and strategic planning, offering a novel, experience-centric perspective for sustainable tourism development.

“Impacts of Facial Recognition Payment on Tourists’ Pro-environmental Behaviors” Presented by Prof. Liang WANG from Zhejiang University, China

Abstract: Although facial recognition payment has rapidly spread in the tourism and hospitality domains, its influence on tourists’ behaviors remains limited. This study employs self-awareness theory to explore how facial recognition payment influences tourists’ pro-environmental behaviors via the mediator of self-enhancement, with self-esteem and the presence of companions serving as moderators. Evidence from six experiments demonstrates that facial recognition scenarios can promote pro-environmental behaviors among tourists by enhancing self-enhancement. Furthermore, the study reveals that self-esteem and companion presence moderate the relationship between facial recognition payment and pro-environmental behaviors. By introducing facial recognition payment as an environmental cue within the tourism and hospitality context, this research enriches the literature on technology adoption and offers valuable insights for marketing strategies used by tourism and hotel practitioners.

“Tourists’ Privacy Concerns and Managements in Smart Tourism” Presented by Prof. Ye WANG from the University of Macau, Macao, China

Abstract: In designing privacy-respecting smart tourism systems, understanding tourists’ attitudes and concerns about data privacy is critical—yet nuanced across different stages of their journeys. Through a systematic review of existing research, combined with surveys of 308 tourists and 15 in-depth interviews, the research team uncovered key insights into tourists’ perceptions of privacy at various stages of smart tourism. While most tourists demonstrate awareness of how their data is collected and used, their levels of concern fluctuate significantly based on contextual factors such as trip purpose, technology adoption, and perceived trade-offs. Furthermore, the study observed that travelers’ current strategies for managing privacy risks remain fragmented and often ineffective.

The analysis highlights how distinct phases of travel—from planning to post-trip interactions—introduce unique privacy challenges shaped by shifting user priorities and system dependencies. Practical opportunities for designers, policymakers, and service providers are discussed to better align privacy protections with tourists’ evolving needs, emphasizing human-centered approaches that balance innovation with ethical data practices.

This work underscores the importance of contextual privacy frameworks in smart tourism ecosystems.

Panel Discussion Moderated by Prof. Rob LAW, APAEM Deputy Director

Panelists: Prof. Quan VU from Deakin University, Australia; Prof. Chitlada PINTHONG from Burapha University, Thailand; Dr. Arinya PONGWAT from Chiang Mai University, Thailand; Dr. Chris ZHANG from Deakin University, Australia