This study examines the psychological and technological barriers that prevent aging travelers from adoptinggenerative artificial intelligence (GAI)-enabled apps at tourism destinations. It addresses the growing needto bridge digital divides among aging travelers in GAI-enabled service contexts. Data were collected from492 travelers aged 60 and older who used GAI-enabled travel apps during trips in Egypt. Digital self-efficacywas adversely affected by privacy anxiety, cognitive load, and limited trust. These barriers were significantlyindirectly associated with self-reported app use through digital self-efficacy. The findings provide practicalinsights for tourism policymakers on promoting GAI inclusion for aging travelers through self-efficacybuildingcontent.
This research examines the adoption of AI-powered chatbots in the hospitality industry by extending theconventional Technology Acceptance Model (TAM) to include perceived competence and perceived understandability.Using data from 266 hotel guests, the study applies Partial Least Squares Structural EquationModeling (PLS-SEM) to test the hypothesized relationships. The results indicate that perceived competenceand perceived understandability significantly shape customers’ perceptions of ease of use and usefulness.Among these, perceived ease of use emerged as the dominant factor influencing customers’ attitudes towardhotel chatbots, which in turn strongly affected their behavioral intentions. In contrast, perceived usefulnessshowed no meaningful association with attitude development in this context. The study contributes to thehospitality chatbot literature by extending TAM in the hotel context by including perceived understandabilityand perceived competence, and it offers practical guidance for improving chatbot adoption in hotel settings.
Thalassotherapy, a health practice dating back to ancient times in coastal areas, is closely linked to the originsof tourism in several regions. This study aims to identify the impacts of thalassotherapy practices on touristdestinations. A systematic review was conducted from the perspectives of tourism and health. A total of 61documents were selected from the Scopus, Web of Science, and PubMed databases. The PRISMA (PreferredReporting Items for Systematic Reviews and Meta-Analyses) method and the VOSviewer software were used forword analysis. The primary findings indicate that thalassotherapy activities in tourist destinations do notgenerate negative environmental impacts and contribute positively to the socioeconomic conditions of theregion. Health-related benefits include improved patient outcomes, enhanced quality of life, and increasedwork capacity. The study highlighted case studies from Greece, Spain, Croatia, and Japan. The co-occurrenceanalysis underscored the relationship between thalassotherapy and tourism development. This researchcontributesto tourism management by emphasising the inclusion of health benefits in assessing tourismdestinations, alongside environmental and socioeconomic impacts. A health-sector method was adaptedto improve systematic reviews in tourism, adding specific items. No economic evaluations were found inthalassotherapy projects despite evidence from case studies.
The influence of dynamic factors on the management of congestion in tourist infrastructure is widely studied in academic literature. The tourism sector is one of the most important economic engines in many countries, contributing to job creation, income generation, and cultural exchange. However, managing the load on tourist infrastructure is complex and requires accounting for dynamic factors such as seasonal fluctuations, changes in event intensity, and unexpected environmental or economic disruptions. This article analyzes how seasonality and events affect the load on tourist infrastructure and offers recommendations for managing these dynamic factors effectively. Traditional deterministic models often cannot accurately predict these situations because of high uncertainty and limited information. This study proposes a structured fuzzy decision-making model that allows for flexible assessment of both quantitative and qualitative indicators characterizing the load on tourism infrastructure. Fuzzy logic enables work with uncertain data, and the concept of organizational reflex allows quick adaptation to changing conditions through optimized management decisions. Theoretical modeling techniques revealed connections, and computer simulation examined these connections under different conditions using Spyder (a Python environment based on NumPy, etc.), which provides the necessary functions to perform calculations and visualize results.
Each local community has distinct traditions and customs that define its cultural heritage and make it recognizable. This paper examines how cultural heritage can strengthen and develop rural tourism. To do so, a model was developed to assess the extent to which cultural heritage is integrated into tourism activities in rural areas. The model includes seven rural households in Bosnia and Herzegovina (BiH) engaged in rural tourism, along with ten criteria for evaluating them. Using multi-criteria decision-making (MCDM), the importance of the criteria and the selected rural households were first assessed through expert evaluation. The results of fuzzy LMAW (Logarithmic Methodology of Additive Weights) indicate that attractiveness (C9) and economic potential (C7) are the most important criteria for evaluating rural households. Ranking the rural households using the fuzzy RAWEC (Ranking of Alternatives with Weights of Criterion) method shows that the Ibrišimović household is the most successful example of integrating cultural heritage into rural tourism offerings. This research offers a new approach to valuing cultural heritage in tourism and aims to support the continued development of rural tourism in BiH through sustainable practices.
