EAI Endorsed Transactions on Tourism, Technology and Intelligence

Understanding Visitor Perceptions and Attitudes Towards UNESCO WHS Designation: A Case Study of Hoi An City

2024-05-14T02:07:12+00:00

UNESCO is dedicated to identifying, protecting, and preserving global heritage. The designation of a site as a World Heritage Site, recognized as a prestigious brand, significantly enhances its appeal, drawing an increasing number of visitors to these locations. The study sought to determine visitors' perceptions and attitudes of World Heritage emblem, in sync with UNESCO's overall objectives. Concentrating on Hoi An, Vietnam, as a case study, unstructured interviews were conducted with over 30 travelers. The interview sampling was non-probability, using the snowball sampling method to examine awareness amongst visitors’ awareness of the Hoi An WHS emblem and designation, with the goal of providing essential insights for both locals and tourists to help preserve the genuine spirit endorsed by UNESCO regulations. The findings revealed that visitors' impressions were more aligned with the World Heritage Site (WHS) designation than with the emblem itself. Only a small percentage of visitors were aware of Hoi An’s WHS status before their visit and were able to recognize the logo and its association with UNESCO. The concept of a World Heritage site evoked numerous positive product attributes, such as "night, street, friendly people," and some negative associations, such as "river, garbage. crowded". This research idea offers valuable insights for professionals and policymakers in their future applications.

The night economy: a novel approach to illuminating city tourism in Vietnam

2024-05-15T02:33:16+00:00

Danang, a famous coastal city in Vietnam, is considered a global, attractive destination and a relatively safe place, with an annually increasing number of tourists. However, there has been a lack of leisure activities at night for visitors, which limits the city from exploiting its full potential to the degree it could. Policymakers have launched the 3-stages of Night-time economy (3-s NTE) development in 2021-2025 to stimulate tourism in Da Nang in the post pandemic period. Research introduced numerous features to assure the Danang 3-s NTE's smooth functioning from policymakers’ perspectives and to understand citizens' viewpoints on how it affects their daily lives. This study applied an inductive qualitative research method through interviews, sentiment analysis, and text data analysis to understand policymakers’ and citizens' positive and negative viewpoints to provide feedback on ensuring the NTE’s smooth operation. Twelve experts and twelve citizens were invited to the discussion and answered several questions related to Night-time economy elements oriented by city leaders. The data gathered were examined and deeply analyzed to explore interviewees’ reactions to the Night-time economy operation. In a post-pandemic world, issues related to fragility, sensitivity, and responsibility are interesting to Danang policymakers and citizens. The study outcomes explore the Da Nang government and citizens in relation to "landscapes" and "security," followed by the themes "development capability", "efficiency", "infrastructure" and "attractiveness". The results will contribute to managerial and practical implications for city leaders in considering how effective the Night-time economy is during the first phase of the operation process.

Machine Learning Applications in Smart Tourism: Overview, Research Challenges, and the Road Ahead

2024-06-14T10:47:59+00:00

Tourism plays a vital role in stimulating economic growth, creating employment opportunities and facilitating cultural exchange and mutual understanding between people of different backgrounds. However, as an industry facing increasing competition on a global scale, tourism needs to embrace technologies to adapt quickly to changes. The emergence of smart tourism offers a route to achieve a competitive edge. To this end, machine learning techniques are used to analyze the abundant data available, forecast trends and and provide best solutions. This paper provides an overview, challenges and future directions of research on machine learning techniques applied in smart tourism.

Impact of 6G Space-Air-Ground Integrated Networks on Hard-to-Reach Areas: Tourism, Agriculture, Education, and Indigenous Communities

2024-08-01T03:33:38+00:00

Due to low population density, difficult terrain, and insufficient infrastructure, the deployment of wireless communication in hard-to-reach areas has long been a challenge in the perspective of leadership corporations, companies, and governments despite the high demand from many local communities. The birth of space-air-ground integrated networks (SAGINs) which are designed to provide ubiquitous, seamless, and high-throughput connectivity is a promising solution to these challenges. In this paper, we investigate the unique difficulties faced by rural and remote areas without wireless communication in the information era. To address these problems, a general architecture of SAGINs is described with the aim to apply in these regions, following the unprecedented benefits in four key sectors including tourism, agriculture, education, and indigenous communities. Although SAGINs have been proposed recently, they are still in their fancy with a focus on the application in remote areas. Therefore, important open research topics are crucial to be investigated at the beginning of the design process to ensure that their full potential is leveraged to enhance the well-being of local populations and create sustainable development.

The Role of Machine Learning in Smart Education: Taxonomy, Challenges, and Use Cases

2024-08-04T19:15:34+00:00

Education is a powerful domain of any country where the changes happened in this domain will reflect all other domains as well. The technical advancement should start with education domain or else there is no strength to that particular advancement. After COVID-19 cause severe upheaval to almost all the industries. In education, the adaptation were significantly impact the development of smart education. Even the developing countries were in the position to adapt the technological advancement through this pandemic. Machine learning plays pivotal role in the technological improvement. The intrusion of smart education fosters an abundance of electronic data and solutions. Machine learning techniques are used to implement models to analyse these larger datasets. In recent years, there have been plenty of studies which address the changes in education and model solutions using various machine learning techniques, such as Supervised, Unsupervised, Semi-supervised, Deep learning and Reinforcement learning techniques. This paper provides an overview, challenges and future directions of research on machine learning techniques applied in education with different levels.