In the digital era, social media plays a crucial role in shaping tourist preferences and behaviours, particularly in pilgrimage tourism. Social media platforms shape destination selections and enrich the overall travel experience through user-generated content. This paper explores a shifting demand characteristic in pilgrimage tourism due to the rise of the experience economy and widespread social media use. It also examines the managerial implications and strategic use of social media marketing in promoting religious sites. A quantitative research design was employed, using numerical data to draw conclusions. Primary data was collected through a standardised questionnaire completed by 450 respondents, supplemented by interviews. Data was analysed using IBM SPSS Version 29, applying descriptive, bivariate, and multivariate methods. The findings were anticipated to highlight social media's significant impact on pilgrimage tourism, particularly in influencing destination image and motivating travel behaviour. The study adds to existing literature by focusing on sub-Saharan pilgrimage destinations, a region often underrepresented in tourism studies. It recommends leveraging social media tools as effective strategies for promoting pilgrimage destinations and engaging potential visitors.

商業地の都市の多様性は様々な空間によって形成されている。本研究は、吉祥寺エリアにおけるSNS利用と来街行動における目的地選択の関係性を明らかにした。InstagramやTikTok上の「デジタル的目的地」と「アナログ的目的地」の比較により、両者には正の相関があり、SNS投稿が都市イメージの形成に寄与していることが明らかになった。これにより、SNSが来街者の都市の捉え方や潜在的な場所の認識に大きな影響を与えていることが示唆された。戦略的なデジタル活用は、都市の多様性を維持し、持続可能な都市の魅力を高めるために極めて重要である。

ABSTRACT University-level geography education benefits from direct, field-based learning beyond traditional lectures. For nearly three decades, the elective university course Field Course Abroad (FCA) has offered students intensive multi-day excursions to foreign regions. This paper presents the long-term concept, organizational framework, and didactic value of FCA, alongside feedback from 31 participants across fourteen iterations. Most respondents were students or graduates of teacher education programs. Qualitative analysis using MaxQDA revealed three core clusters. The organizational – social cluster highlights the preparatory phase, destination selection, and the role of teamwork and group dynamics. The didactic cluster emphasizes place-based and peer learning, enhancing geographical knowledge and understanding of spatial relationships. The critical cluster reflects individual concerns, such as accommodation, food, and program intensity. Students rated the course highly, valuing both its academic relevance and socio-emotional benefits, including informal learning, interpersonal interactions, and supportive teachers. The FCA’s long-term success demonstrates that this model of preparation and implementation provides an effective framework for higher education institutions aiming to integrate international field-based learning into their curricula.

The intracerebral hemorrhage (ICH) score is widely used to predict mortality in ICH, but its ability to predict functional outcomes, length of stay (LOS), and discharge placement remains unclear. This study evaluates its predictive performance across these clinical outcomes. This retrospective, single-center study included 273 patients admitted with ICH between 2018 and 2023. Logistic regression models assessed the ICH score's predictive performance for in-hospital mortality, modified Rankin Scale (mRS) at discharge, intensive care unit and hospital LOS, and discharge placement. Performance metrics, including accuracy, sensitivity, and specificity, were assessed using leave-one-out cross-validation. Stepwise selection was used to identify the predictive value for the individual ICH score components. The ICH score accurately predicted in-hospital mortality (accuracy: 0.89, sensitivity: 0.80, specificity: 0.91). It showed moderate performance for mRS at discharge (accuracy: 0.67, Kappa: 0.49), particularly for mortality (mRS 6, sensitivity: 0.84, specificity: 0.91), but was less reliable for predicting functional independence (mRS 0-3, sensitivity: 0.59, specificity: 0.85) and severe disability (mRS 4-5, sensitivity: 0.66, specificity: 0.70). The score poorly predicted intensive care unit LOS (accuracy: 0.70, Kappa: 0.39) and hospital LOS (accuracy: 0.53, Kappa: 0.04). While it identified favorable (home/acute rehab) and poor (hospice/death) discharge outcomes, it failed to predict intermediate placement (subacute rehab/long-term care). Stepwise selection consistently excluded infratentorial location, suggesting limited predictive value. The ICH score reliably predicts in-hospital mortality but has limited accuracy for functional outcomes, LOS, and discharge placement. While useful for risk stratification, its role in individualized prognostication is limited. Future studies incorporating additional clinical and socioeconomic factors may improve predictive accuracy.

People who travel in today's world face mental exhaustion because they need to stay connected to digital devices and social media and they have to maintain their online activities. The rise of Digital Detox Tourism as a holiday trend shows that travelers choose to break their connection with smartphones and internet access and digital platforms to experience nature and their personal self and genuine life moments. This paper investigates digital detox tourism as a travel behavior phenomenon that exists in contemporary travel patterns. The research examines how digital detox programs affect tourist well-being and satisfaction and emotional recovery and destination selection and return visit probabilities. The study analyzes secondary research which includes academic publications and tourism studies and wellness research and industry publications. The research demonstrates that digital detox tourism has evolved into a growing niche which functions as an effective movement that supports environmentally responsible travel through mindful travel practices. The study demonstrates that tourism destinations and providers can create substantial value by developing detox-oriented travel packages which deliver experiences of genuine peace and authentic presence and mental peace. The study demonstrates that tourism destinations and providers can create substantial value by developing detox-oriented travel packages which deliver experiences of genuine peace and authentic presence and mental peace. The study demonstrates that tourism destinations and providers can create substantial value by developing detox-oriented travel packages which deliver experiences of genuine peace and authentic presence and mental peace.

The rapid growth of social media has significantly transformed the way travelers discover destinations and plan their trips. Among various platforms, Instagram has emerged as a powerful tool influencing tourism marketing through visual storytelling, influencer content, and user-generated experiences. This study examines the impact of Instagram marketing factors on destination selection and the promotion of tourism services among travelers in the Delhi NCR region. A quantitative research design was adopted, and data were collected from 250 Instagram users through a structured questionnaire using a five-point Likert scale. The study analyzed key variables including visual appeal, user-generated content, influencer engagement, brand endorsements, trust in influencers, and trust in travel companies. The results of multiple regression analysis indicate that visual appeal, user-generated content, and influencer engagement significantly influence destination selection, with influencer engagement emerging as the strongest predictor. However, brand endorsements were not found to have a significant impact on destination choice. Furthermore, trust in Instagram influencers and trust in travel companies were found to significantly influence the promotion of tourism services, with influencer trust showing a stronger effect. The findings highlight that authenticity, engaging content, and credibility play a crucial role in shaping travelers’ perceptions and decisions. The study contributes to the growing literature on social media marketing in tourism and provides practical insights for tourism businesses in Delhi NCR to design more effective Instagram marketing strategies.

Purpose This paper presents an analysis of tourists’ motivations, their cognitive image and the satisfaction they take away as a result of a trip to the city of Naples (Italy), as well as the possibilities of revisiting the destination and recommending it. Design/methodology/approach To achieve this research objective, a comparative analysis was carried out between Italian tourists and tourists from other countries. Findings The results highlight the presence of different types of motivations for tourists’ destination selection, as well as a positive relationship between these motivations and the tourist’s image of the city after visiting with the satisfaction of the trip. Originality/value There also appears to be a direct relationship between trip satisfaction and the possibility of a future return to the city, as well as recommending the destination. Finally, the results highlight the differences between domestic and foreign tourists.

Purpose The study aims to develop and validate the Ethically Minded Tourist Behavior (EMTB) scale to assess tourists’ ethical considerations in destination selection. Based on the Stimulus-Organism-Response (S-O-R) theory, it tests a nomological framework where electronic word-of-mouth (eWOM) and perceived destination social responsibility (DSR) drive EMTB, with regional background (Asia vs. Europe) acting as a moderator. Design/methodology/approach This study uses a two-stage mix-method approach consisting of Stage 1 - identification of EMTB dimensions and generation of measurement items and Stage 2 - nomological network analysis of EMTB. Findings This study developed and validated the EMTB scale in the destination context, comprising four dimensions (i.e., Eco-Buy, Eco-Boycott, DSR-Boycott, Pay-More). Moreover, empirical findings revealed that eWOM and perceived DSR significantly influence EMTB, with perceived DSR acting as a mediator. Notably, regional background moderates the relationships between eWOM, perceived DSR and EMTB. Research limitations/implications Generalization of the findings must be taken with caution across the sample and regions. Nevertheless, the study suggests future research directions to guide EMTB research. Originality/value This study pioneers the validation of the EMTB scale to measure pre-trip ethically minded tourist behavior. It also confirms the nomological framework where eWOM and perceived DSR—representing online media influence and sustainability awareness, respectively—drive EMTB. Theoretically, this research advances both ethical tourist behavior and sustainable tourism studies. Practically, it provides tourists with self-reflective guidelines for making ethically minded destination choices. For sustainable tourism bodies, the study offers a practical framework to foster cross-sector collaboration in promoting EMTB among tourists.

The m-polar fuzzy (mF) PROMETHEE methodology provides a robust framework for solving multi-criteria group decision-making (MCGDM) problems by combining the flexibility of fuzzy sets with the outranking strength of PROMETHEE. Despite its growing applications, in the literature, no attention has been given to the effect of data normalization on m-polar fuzzy PROMETHEE method performance. This study systematically examines five normalization techniques—linear sum, linear max, max–min, vector, and logarithmic—using both single-valued and fuzzy inputs. Two case studies, electric vehicle (EV) selection and tourist destination selection, are employed to evaluate the sensitivity of rankings to normalization. The novelty of this work is in the use of m-polar fuzzy PROMETHEE method to MCDM and MCGDM problems. EV selection problem provides the single value input for the m-polar fuzzy PROMETHEE approach while the tourist destination provides the fuzzy input for the algorithm. Results show that the choice of normalization significantly influences the final rank order, with linear sum normalization yielding the most stable rankings for EV selection, while nonlinear methods introduce rank reversals in both domains. Comparative analysis using Spearman’s rank correlation validates these findings. The research highlights the importance of carefully selecting normalization methods to ensure reliable decision outcomes and extends the applicability of the mF PROMETHEE framework to industrial and service sectors, including transportation, tourism, and beyond.

ABSTRACT The present study aims to shed light on the impact of the presence of refugees on tourist preferences, examining its implications for destination selection and image. In this regard, a qualitative research method was employed, and the vignette technique, based on short stories, was utilised within the framework of a case study design. The findings demonstrate that the presence of refugees has a discernible impact on perceptions of cultural change, influencing various elements that affect the destination's attractiveness, including appeal, accessibility, safety, quality of life, promotion, and general atmosphere. This perception has the potential to negatively impact the destination image and lead to significant changes in tourists’ travel preferences. The results provide significant insights for the development of destination management and tourism policies, emphasising the necessity to consider the presence of refugees when shaping the destination image and tourists’ decision-making processes.

Tourism journeys always begin with a planning stage, involving the selection of destinations to visit and the accommodation to be used throughout the trip. The Orienteering Problem with Hotel Selection (OPHS) serves as a model for recommending multi-day travel itineraries that are both efficient and profitable, as it aims to maximize total reward (or profit) while keeping the total travel distance within reasonable limits. This research extends the conventional OPHS by incorporating the time-dependent satisfaction of destinations, resulting in a model referred to as the Orienteering Problem with Hotel Selection and Time-Dependent Satisfaction (OPHS-TDS). The motivation for this development arises from the observation that the quality of tourist experience at certain destinations varies depending on the time of arrival. This phenomenon is particularly evident in nature-based attractions, where visiting during specific period can significantly affect both the visitor’s experience and the perceived benefit gained from the trip. The study presents a mathematical formulation of the OPHS-TDS and proposes a solution approach based on the Skewed Variable Neighborhood Search (SVNS) algorithm by allowing exploration of wide range neighborhood of solutions to search for near optimum solution. Computational experiments on benchmark datasets demonstrate that SVNS is efficiently solve OPHS-TDS with only 3.17% average differential with ILP, and further experiments using real-world data from the Province of Bali confirm the model’s applicability and potential in practical multi-day tourism planning scenarios.

Sports and recreational activities, together with tourist animation programs, have become increasingly relevant factors in contemporary destination choice, yet their role is still insufficiently explored from a behavioral and social perspective. This study investigates how tourists’ everyday engagement in sports and recreational activities translates into participation during vacations and how these activities influence destination selection. Using a quantitative research design, data were collected through an online survey of 217 respondents and analyzed using non-parametric and parametric statistical methods. The results reveal significant differences between tourists’ sports-recreational behaviors at home and during travel, particularly with respect to physical health, emotional well-being, spatial attachment, and environmental support factors. The findings further indicate that supportive environmental factors such as the attractiveness of the natural environment and climatic suitability play a particularly relevant role in destination choice compared to the mere availability of sports facilities. In contrast, interest in animation programs appears more moderate, suggesting differentiated tourist preferences. By distinguishing between opportunities for sports-recreational activities and supporting environmental factors, this study contributes to a more nuanced understanding of tourist behavior and destination attractiveness. The results offer practical implications for destination managers and policymakers aiming to develop socially and environmentally sustainable tourism products.

The current research utilizes a data-driven approach to segment Expedia users based on their behavior, using a dataset of user records to delineate traveler segments and their behaviors. The current study employed a dataset of 2,000 real Expedia users, and the collected variables included search behavior, booking actions, travel distances, travel party attribut es, and device usage. Using K-means clustering and subsequent statistical analysis, four segments were identified: the LastMinute Mobile Bookers, the Advanced Planning Researchers, the Package-Seeking Families, and the Business Travelers. Tests of cluster validity confirmed the statistical fit using the four-segment structure. Each segment exhibited unique patterns across lead time to book, device preference, conversion rates, and destination selections. Logistic regression analysis found that package searches and mobile device usage were significant predictors of booking conversion, with differences across segments. The results reinforce the idea that tourism marketing cannot use an umbrella approach and provide empirical evidence for a segment-based approach. This research contributes to tourism marketing theory by demonstrating that an integrated behavioral approach to segmentation is useful for scholars and offers practical applications for personalized marketing, better use of mobile, and improved conversion rates in online travel retailing. Furthermore, the results underscore the significance of identifying journey-specific differences between travelers as well as the importance adopting tailored interventions for information needs and decision speed of each segment. The findings support the idea that understanding different behavioral patterns will help improve customer experience and optimize human and financial marketing resources in an increasingly competitive, digital travel marketplace. Overall, the study offers effective guidance on how to allocate resources for digital marketing, which would ultimately enhance performance outcomes across customer segments.

This research investigates the evolving dynamics of global tourist preferences and consumer behavior in the postpandemic era, with a particular focus on identifying the key factors influencing destination choices. The study compares tourist preferences across three popular destinations – Spain, Italy, and Thailand – by analyzing statistical data and reviews from tourists in these countries. The findings highlight significant variations in the ways that economic, cultural, and safety concerns shape travel decisions. Economic factors such as income levels, travel costs, and service availability are shown to play a crucial role in destination selection, with tourists increasingly becoming sensitive to price fluctuations. The study also emphasizes the growing importance of safety, especially in light of the COVID-19 pandemic, with many tourists prioritizing destinations that offer clear health protocols and measures to ensure their well-being. Furthermore, the research reveals a rising demand for environmentally conscious travel, with a focus on destinations that promote sustainability and eco-friendly practices. Social media also emerges as a pivotal tool influencing trip planning, with a notable 72% of tourists indicating its impact on their destination choices. The research suggests that tourism businesses must adapt to these shifting consumer demands by enhancing safety measures, adopting digital technologies, and emphasizing sustainability in their offerings. The results provide valuable insights for tourism experts seeking to navigate the post-pandemic landscape and enhance the competitiveness of their destinations on the global market.

Indonesia has a rapidly growing tourism industry, supported by numerous destinations with extraordinary natural beauty. According to the Travel Tourism Development Index (TTDI) 2024, Indonesia ranks 22nd globally and second in ASEAN. One of its prominent provinces is the Special Region of Yogyakarta, which recorded 3.2 million tourists in May 2024. The tourism industry contributed 4.1% to Indonesia’s Gross Domestic Product (GDP) in 2023, with the government targeting an increase to 4.6% by 2025. Despite its economic value, tourism accounts for 8% of global carbon emissions, with 49% originating from its transportation. The government is committed to reducing carbon emissions by 50% by 2030 and achieving net-zero emissions between 2045–2060. Many tourists rely on travel agencies to purchase tour packages. These packages are designed by travel agencies by considering routes, costs, time, and tourist satisfaction. The selection of destinations aligns with the Orienteering Problem (OP), which aims to maximize scores within time constraint, along with carbon emissions generated and trip days. This study applies a green team orienteering model to 65 destinations in Yogyakarta to maximize tourist satisfaction while minimizing costs and carbon emissions over a 3-day tour (8 hours per day). The model is solved using AMPL software and Gurobi. The optimal route includes 5 destinations on the first day, 4 destinations on the second day, and 5 destinations on the third day, achieving a total score of 3,521. Sensitivity analysis shows that increasing tour hours and the number of days leads to higher total scores. Weighting significantly influences each objective function, potentially resulting in trade-offs among objectives or dominance over others.

The French Language Acculturation Programme in Nigerian Colleges of Education is designed to equip future French teachers with the linguistic proficiency, cultural competence, and socio-communicative skills necessary for effective engagement in Francophone environments. Despite its importance, students have increasingly faced barriers that hinder their full participation, including financial limitations, visa and travel difficulties, low initial language proficiency, cultural adjustment challenges, security concerns, and limited access to healthcare. Insights from structured interviews with staff at the Nigerian French Language Village (NFLV), Badagry, and the Pan-African University Institute (PAUI), Porto-Novo revealed that, while institutional practical and logistical challenges such as delayed visa processing, high programme costs, and inadequate pre-departure preparation continue to restrict student engagement. The main aim of this paper isto identify, analyse, and explain these barriers, drawing on student questionnaires, participation records, and staff interviews to capture both the prevalence and intensity of the challenges. Furthermore, it explores innovative interventions to strengthen the acculturation programme, including expanded TETFund scholarships, institutional agreements to facilitate visa and travel processes, systematic exposure to French media and language labs, comprehensive pre-departure cultural orientation, selection of secure Francophone destinations, and guidance on accessing healthcare abroad. The findings are expected to provide valuable insights for policymakers, educational administrators, and teacher trainers, ultimately contributing to the development of a more effective, accessible, and sustainable French Language Acculturation Programme in Nigerian Colleges of Education.

Choosing the right location is crucial for the success of a business. Selecting an inappropriate site for accommodation investments can adversely impact the business and potentially lead to failure. Therefore, it is essential to determine the most suitable location through an objective and systematic approach. This research proposes a methodology that combines entropy-based weighting and TOPSIS multi-criteria decision-making (MCDM) methods to support the tourism destination selection process in investment decisions. The study analyzed 19 tourism destinations in Turkey that hosted 100,000 or more foreign tourists, according to the Ministry of Culture and Tourism's 2024 Border Statistics Annual Bulletin. The evaluation criteria included distance to the nearest airport (in kilometers), population, Herfindahl Index Contribution Level, hotel occupancy rate, number of tourists (demand), and seasonality. Criterion weights were calculated using the entropy method, and destination rankings were established using the TOPSIS method. The reliability of the findings was validated through Spearman's Rank Correlation analysis. Additionally, the robustness of the results was confirmed via Monte Carlo sensitivity analysis. The analysis revealed that Istanbul and Antalya are the most attractive destinations for accommodation investments. Conversely, cities with smaller populations and limited tourism activities, such as Ardahan, Iğdır, and Hakkari, ranked lower. The methodology employed in this study is expected to aid investors and policymakers in evaluating tourism destinations effectively.

The swift expansion of social media platforms has profoundly altered travel behaviour among Indian consumers. This exploratory study investigates the impact of social media on travel decision-making, destination selection, and comprehensive travel planning within the Indian context. As more people use the internet and smartphones, sites like Instagram, YouTube, and travel blogs have become important places to get ideas and information about travel. The study utilises secondary data obtained from published research articles, industry reports, and online sources to analyse emerging trends in social media-influenced travel behaviour. The results show that social media content, like reviews from users, travel influencers, and visual storytelling, has a big impact on how tourists think and what they like. Things like how real reviews are, recommendations from friends, advertising campaigns, and real-time updates have a big impact on travel choices. Social media also encourages people to plan trips on the spur of the moment, promotes less well-known places to visit, and makes people more aware of travel deals and experiences. But there are also worries about too much information, false information, and expectations that were too high. The study finds that social media has become a strong tool for marketing and communication that affects how people travel in India. It emphasises the necessity for tourism marketers to implement effective digital strategies and for travellers to assess online information critically. The study sheds light on changing travel trends and opens the door for more empirical research.

Social networks have profoundly influenced human thinking and behaviour patterns and have effectively promoted the development and evolution of the urban tourism economy. However, the front-end impact of social network information differences on travel intention and the back-end effect of travel intention on actual behaviour have not been considered from the perspective of behavioural psychology. Based on the three-stage division of SOR theory, namely, “Stimulus‒Organism‒Response”, this study takes the tourist destination image, personal characteristics and information quality of key opinion leaders (KOLs) as external stimulus variables, combines basic theories such as the theory of planned behaviour and the technology acceptance model, and builds a theoretical framework to analyse the impact of social network information on travel intention. It also incorporates variables such as individual socioeconomic attributes and tourism attributes and establishes a tourist destination selection behaviour model (ICLV) that considers latent psychology variables, analysing the mechanism whereby multiple factors influence travel behaviour intention and behaviour in social network interaction scenarios. Specifically, we analysed 522 valid questionnaires from two internet celebrity cities (ICCs), Chongqing and Chengdu. The results show that the personal characteristics and information quality of KOLs can effectively stimulate tourist travel intention by influencing travel motivation, travel attitude and perceived value but have no significant effect on tourist destination decisions. Furthermore, tourist destination decision-making behaviour is affected mainly by factors such as the travel attitude, destination image, individual attributes of tourists and travel attributes. This study enriches the research and empirical investigation of tourist travel behaviour in the digital environment and provides a reference for the creation of ICCs and the marketing of tourist destinations.

Purpose The current study probes the impact of digital itinerary through Artificial Intelligence (AI)-driven Smart Tourism System (STS) on travel experiences by adopting a mixture of qualitative and quantitative approaches. It discovers the elements influencing the acceptance and satisfaction, emphasizing on timeliness, price, destination selection, safety and hedonic values. The study attempts to offer actionable insights for the tourism industry to maximally provide digital travel solutions for better user experiences. Design/methodology/approach The study used a mixed-methods approach. Qualitative interviews were carried out with 16 participants and unraveled numerous perspectives and unique decision-making discourses pertaining to digital travel technologies. Later, a quantitative survey was administered with 1,129 respondents via online to investigate the factors influencing the adoption of STS. Partial Least Squares Structural Equation Modeling was used to measure the mediating and moderating effects. Findings The findings of the study indicate that tourists who adopt technology-driven itineraries are influenced by timeliness, price, safety, destination selection and hedonic values. On one hand, destination brand equity dimensions mediated these effects and on the other hand, demographic features moderated user experience preferences. This study stresses the factors influencing the adoption of STS-based digital itineraries. Research limitations/implications The study relies on self-reported data derived from a digital community, which restricts the generalizability. Future studies can discover cross-cultural contexts and aim for longitudinal designs, pertaining to STS-based digital itineraries. Practical implications The study highlights a better user experience by focusing on timeliness, safety and destination through STS itinerary features. Customizing services considering on demographic choices can further enhance the adoption of STS. Social implications STS-driven digital itineraries can enhance the user experiences by limiting the level of insecurity and uncertainty and creating a sense of informed decision-making, resulting in improved travel experiences. Originality/value The study combines a qualitative and quantitative approach to probe the factors for the adoption of STS, which enhances user experience satisfaction by highlighting unique practical insights for creating smart tourism.