The growing integration of Artificial Intelligence (AI) in tourism is widely reflected in academic research; however, this literature reveals significant methodological and theoretical limitations. Most studies remain descriptive, relying on low-rigour designs and producing fragmented, repetitive, and weakly generalizable findings. The field is also theoretically underdeveloped, lacking robust social science and tourism-specific frameworks. To address these gaps, this paper proposes an actionable framework structured around three pillars: methodological advancement, ethical foresight, and theoretical enrichment. By aligning rigorous methods with theory and ethical considerations, researchers can generate more explanatory, impactful scholarship and support a meaningful paradigm shift in AI tourism research.
Tourism transformation in agricultural heritage sites is vital for linking rural revitalisation with conservation. Based on resource orchestration theory and mixed methods evidence from 18 Chinese agricultural heritage sites, this study examines how resources, service innovation, and management strategies shape tourism outcomes. It identifies three high-performance paths: Resource - Creative, Resource - Infrastructure, and Infrastructure - Creative, while showing that weak creative conversion and insufficient infrastructure constrain low performance. The findings reveal tourism transformation as spatial reorganisation shaped by creative place-making, infrastructure support, and institutional coordination. The study advances debates on multifunctional agriculture and spatial production, informing upgrades to agricultural heritage destinations.
This study explores how climate change attributes in tourist destinations influence the emotional and behavioral responses of travelers. It identifies key climate-related factors and tests their effects through a structural model using qualitative and quantitative approaches. An invariance test examined the differences based on the emotional attachment and regulation of travelers, whereas an fsQCA analysis identified causal combinations that affected destination avoidance behavior. Six hypotheses were supported, and no significant group differences were found. The findings provide theoretical and practical implications in order to understand the responses of travelers in regard to climate change within tourism contexts.
Authentic emotion recognition is vital for future tourism marketing, yet single-modality approaches overlook the disparity between performed narratives and visual reality. This study introduced a within-subject, cross-context multimodal AI framework grounded in Plutchik's emotion theory and Goffman's self-presentation lens to quantify emotional differences in paired tourist selfies and captions. Analyzing user-generated content, the results showed a consistent amplification of joy in captions (front-stage). In contrast, selfies revealed complex back-stage emotions, such as trust, surprise, fear, disgust, and anger. These robust disparities challenge text-only sentiment analysis and underscore the need for integrated visual - textual emotional intelligence to better capture authentic tourist experiences.
This study investigates how negative environmental imagery shapes tourists' responses to subsequent green initiative messages within a stage-based emotional processing framework. Study 1 uses electroencephalography to show that exposure to environmental degradation imagery heightens early-stage affective arousal and attentional engagement during subsequent message processing. Study 2 demonstrates that negative-to-positive message sequencing induces contrast-based shifts in emotional valence, enhancing pro-environmental behavioral intention. The findings indicate that sustainability communication functions as a sequential emotional process, in which early neural arousal facilitates message processing, while valence-based evaluative contrast governs intention formation, offering a refined account of green persuasion.
This study aims to identify the travel experiences that postmodern tourists pursue in religious tourism and classify the market segments of non-religious postmodern tourists . It contains three studies: Content analysis from social media data (Study 1) and semi-structured interviews (Study 2) were used to identify four dimensions of travel experiences. The cluster analysis of a questionnaire survey (Study 3) classified three non-religious postmodern tourist market segments: relaxed, utilitarian, and deeply experienced. The similarities and differences of travel characteristics among groups were explored. This study contributes to tourism marketing research by distinguishing an emerging tourist market and its segments.
This study investigates how brand sustainable management practices (BSMPs) influence customer perceptions of interactional justice in the U.S. specialty coffee context, guided by the value-attitude-behavior framework. Results show that BSMPs significantly enhance perceptions of interactional justice, both directly and indirectly via perceived social value (SPV) and perceived altruistic value (APV). Interactional justice strongly predicts brand advocacy. While product knowledge did not moderate the SPV - justice link, it amplified the positive effect of APV on justice perceptions. These findings underscore the dual pathway through which BSMPs foster fairness perceptions and highlight the boundary condition of product knowledge in interpreting altruistic brand value.
Non-fungible tokens (NFTs) represent an emerging innovation in tourism, enabling destinations to create digital assets embedded within socio-technical ecosystems. Drawing on assemblage theory and qualitative data from netnography and semi-structured interviews, this study explores how motivations and constraints of tourism NFT consumption emerge through consumer interactions. Findings identify self-extension motivations including memorization, symbolic meanings, and socialization, and self-expansion motivations including ownership, economic and transferability benefits, hedonism, and learning. Additionally self-restriction and self-reduction constraints are identified. These findings advance understanding of tourism NFTs from an interaction-centric perspective and provide practical strategies for destinations marketing using blockchain technologies.
This research employs a mixed-methods design to examine how travelers respond to online reviews of pet-friendly hotels. Study 1 analyzes 13,604 TripAdvisor reviews from 2020 to 2024 using machine learning to identify decision rules, showing that cleanliness outweighs value for money and functions as a threshold requirement. Study 2 finds that cleanliness-focused reviews reduce perceived health-safety concerns and improve hotel attitude. Study 3 demonstrates that under a cleanliness - value trade-off, cleanliness becomes more influential in pet-friendly hotel choice only when health-safety concerns are heightened. The findings highlight how and why cleanliness shapes pet-friendly hotel choice and when it does not.
This research explores how perceived power influences tourists' photo editing behavior. Through four experiments, we demonstrate that tourists feeling more powerful are less likely to edit travel photos. Drawing on self-authenticity theory, we propose that this effect is driven by tourists' pursuit of self-authenticity: the goal of aligning actions with their true selves. The effectiveness of power in discouraging photo editing varies with destination characteristics. The effect is more pronounced in hedonic destinations and low-reputation destinations than in utilitarian destinations and high-reputation destinations. The findings offer practical insights into fostering authentic destination word-of-mouth by incorporating empowerment into social media campaigns.
Despite hotels increasingly embracing green practices, many initiatives remain symbolic and fragmented. Responsible brand leadership (RBL) enables hotels to guide stakeholder relationships and assume moral responsibility. Using a mixed-methods approach (Study 1: interviews with 27 hoteliers; Study 2: surveys of 271 consumers), we investigate the role of perceived brand authenticity and brand trust as mediators under conditions of uncertainty and green skepticism. RBL positively affects perceived brand authenticity and brand trust, alongside booking intentions through the independent mediating effects of these two variables. We establish RBL as a robust leadership mechanism for driving consumer responses in green hospitality contexts.
