ing in-depth interviews (N = 15) and surveys (total N = 800), we demonstrate a consistently strong association between dispositional awe and pro-environmental behavior intention. Two survey-based studies incorporating both self-reported pro-environmental behavior intention and peer-reported pro-environmental behavior reveal that this relationship is partially mediated by connectedness to nature and place identity. By shifting attention from tourists’ momentary awe experiences to residents’ enduring dispositional awe, this research advances tourism scholarship on emotion and sustainability and offers novel insights for Broaden-and-Build theory.

2e:T4c0,

Digital transformation has reconfigured the competitive landscape of tourism, expanded opportunities, and intensified exposure to digitally mediated harms. Online platforms have become crucial arenas in which reputation, legitimacy, and visibility are produced, circulated, and contested. Drawing on Bourdieu’s theory of symbolic power, this research conceptualizes digital bullying as a set of targeted, repeated, or coordinated practices intended to intimidate, delegitimize, or damage tourism actors. We examine organized reputational attacks, influencer-led mobilizations, and algorithmically amplified review manipulation as forms of cyber-symbolic aggression that erode symbolic capital, weaken credibility, and destabilize competitive position. However, we do not equate these practices with conventional technical cyber incidents; rather, we argue that they are cybersecurity-relevant because they exploit digital infrastructures and platformized visibility regimes to amplify vulnerability and reduce organizational control. A key practical implication is that tourism and hospitality organizations should integrate reputational threat monitoring into their cybersecurity and governance strategies.

2f:T446,

Artificial Intelligence (AI) technologies have become increasingly integrated into travel experiences. Understanding how and why travelers adopt these technologies and whether they will continue to use them is essential. This study adopts a qualitative approach to examine how travelers interact with AI during their journeys. Data were collected through semi-structured interviews with 50 Omani travelers who had used AI tools while traveling and analyzed using thematic analysis guided by abductive reasoning. The findings reveal a range of motivations for adoption, including functional, social, and emotional drivers, as well as key challenges such as impersonal recommendations, technical limitations, and privacy concerns that influence satisfaction and future use. Theoretically, the study develops the MAO (Motivation–Adoption–Outcome) model, which extends existing technology adoption theories. The study offers practical implications for developers and tourism providers aiming to design AI tools that are more human-centered, culturally relevant, and emotionally engaging.

30:T4b3,

The impacts of urban tourism on local communities have drawn increasing attention, yet quantitative studies to evaluate these effects remain limited. This study addresses this gap by developing and validating the Perceived Tourism Urban Segregation (PTUS) scale, a multidimensional instrument capturing residents’ perception of tourism-related segregation. Following Churchill’s scale development method and drawing on 36 stakeholder and resident interviews, this scale extends beyond conventional housing and interaction segregation to introduce two novel dimensions: facility segregation and consumption segregation. These dimensions reveal how tourism reshapes access to public amenities and consumption spaces, influencing residential satisfaction. Challenging the assumption that segregation is inherently negative, the findings reveal both positive and negative impacts, highlighting tourism’s complex social implications. By embedding PTUS in a residential satisfaction model, the study offers a theoretical and practical framework for identifyi