An App for Promoting Health and Local Tourism

Chao, Chien Lei; Lin, Ker Cheng; Tseng, Chien-Ming; Erdene, T; Chen, Yung Fu

doi:10.1109/is3c.2014.305

Cited by 5 publications

(7 citation statements)

References 20 publications

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“…The previous literature revealed that there has been little research attention devoted to the study of ecotourism emphasizing young people although the topic is significant in terms of the impact on future ecotourism (Chao et al, 2014;Halvatzaras & Kabassi, 2016;Meiliana et al, 2017;Nitti et al, 2017;Reisinger & Mavondo, 2002;Ruíz et al, 2017;World Tourism Organization, 2010). Nevertheless, the studies by Cini et al (2015), Kasim and Wickens (2018), as well as the study of Sangpikul and Batra (2007) relating to ecotourism and young Thais suggest that ecotourism is a new and important trend in tourism.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, tourism services can use smart technology to offer their services and gain information through user feedback to ensure service sustainability. Finally, Destination marketing organizations, which are responsible for providing information to potential visitors can use smart technologies to encourage visitors to purchase destination-related products (Chao et al, 2014;Halvatzaras & Kabassi, 2016;Meiliana et al, 2017;Nitti et al, 2017;Ruíz et al, 2017).…”

Section: Role Of Smart Ecotourism-related Applicationmentioning

confidence: 99%

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Smart application of learning ecotourism for young eco-tourists

Chai-Arayalert

2020

Cogent Social Sciences

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Ecotourism is supposed to make efficient, responsible and sustainable use of tourism resources at the destination. The aims of ecotourism can be accomplished by encouraging the appropriate activities, enhancing eco-tourist experiences, and managing tourism resources in a sustainable manner. Smart ecotourism application refers to the innovative tools and approaches to improve the ecotourism practices and experiences. The smart application focusing ecotourism aspect has emerged as a result of the rise of Information and Communication Technologies (ICTs) and the need for sustainability. This study emphasis on young people who are likely to be first-time eco-tourists or to have little experience of ecotourism. However, young people are a great capacity to spread ecotourism awareness both in the present and the future. This study was designed and developed a smart application which aimed to allow young people to learn about ecotourism. This research was conducted using a qualitative approach, utilizing a case study in Klong Noi Community in Surat Thani Thailand. The results of this study will contribute to the current ecotourism literature and broaden understanding of the ICTs-based ecotourism, particularly on the Thailand context. Moreover, they will provide suggestions for ecotourism business in Thailand to develop the smart application attractive to the targets of young people.

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Section: Discussionmentioning

confidence: 99%

Section: Role Of Smart Ecotourism-related Applicationmentioning

confidence: 99%

Smart application of learning ecotourism for young eco-tourists

Chai-Arayalert

2020

Cogent Social Sciences

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“…Blockchain has the potential to revolutionize the way the industry operates by enabling secure, transparent, and decentralized transactions [22]. These technologies are coming together to provide innovative capabilities and services including forecasting tourism demand [23], mining tourist locations, pathways, and travel itineraries [24], the visualization of tourist mobility activity patterns, identifying tourist congestion zones and tourist routes in specific areas [25], measuring tourist satisfaction [26], support for decision-making [27], identifying factors related to tourist satisfaction [28], integration of the Android platform and GPS services for guiding tourists to their preferred sites [29], augmented reality for historical tourism using mobile and smart devices [30,31], and more.…”

Section: Technologies and Their Impact On Tourismmentioning

confidence: 99%

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

2023

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Global natural and manmade events are exposing the fragility of the tourism industry and its impact on the global economy. Prior to the COVID-19 pandemic, tourism contributed 10.3% to the global GDP and employed 333 million people but saw a significant decline due to the pandemic. Sustainable and smart tourism requires collaboration from all stakeholders and a comprehensive understanding of global and local issues to drive responsible and innovative growth in the sector. This paper presents an approach for leveraging big data and deep learning to discover holistic, multi-perspective (e.g., local, cultural, national, and international), and objective information on a subject. Specifically, we develop a machine learning pipeline to extract parameters from the academic literature and public opinions on Twitter, providing a unique and comprehensive view of the industry from both academic and public perspectives. The academic-view dataset was created from the Scopus database and contains 156,759 research articles from 2000 to 2022, which were modelled to identify 33 distinct parameters in 4 categories: Tourism Types, Planning, Challenges, and Media and Technologies. A Twitter dataset of 485,813 tweets was collected over 18 months from March 2021 to August 2022 to showcase the public perception of tourism in Saudi Arabia, which was modelled to reveal 13 parameters categorized into two broader sets: Tourist Attractions and Tourism Services. The paper also presents a comprehensive knowledge structure and literature review of the tourism sector based on over 250 research articles. Discovering system parameters are required to embed autonomous capabilities in systems and for decision-making and problem-solving during system design and operations. The work presented in this paper has significant theoretical and practical implications in that it improves AI-based information discovery by extending the use of scientific literature, Twitter, and other sources for autonomous, holistic, dynamic optimizations of systems, promoting novel research in the tourism sector and contributing to the development of smart and sustainable societies.

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“…Blockchain has the potential to revolutionize the way the industry operates by enabling secure, transparent, and decentralized transactions [11]. These technologies are coming together to provide innovative capabilities and services including forecasting tourism demand [12], mining tourist locations, pathways, and travel itineraries [13], visualization of tourist mobility activity patterns, identifying tourist congestion zones and tourist routes in specific areas [14], measuring tourist satisfaction [15], support for decision-making [16], identifying factors related to tourist satisfaction [17], integration of the Android platform and GPS services for guiding tourists to their preferred sites [18], augmented reality for historical tourism using mobile and smart devices [19], [20], and more.…”

Section: Technologies and Their Impact On Tourismmentioning

confidence: 99%

“…Looking at the scientific papers that belong to this parameter we were able to find several topics that capture various mobile application services. These services include integration of the Android platform and GPS services in guiding tourists to their preferred sites [18], augmented reality for historical tourism using mobile and smart devices [19], [20], the use of Mobile Applications for tracking tourist travel experiences [241], determining different types of tourists mobility and providing location-based services [9], [242], and implementing QR systems for shopping centers [243].…”

Section: Mobile Applicationsmentioning

confidence: 99%

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Alsahafi¹,

Alzahrani²,

Mehmood³

2023

Preprint

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The Global natural and manmade events are exposing the fragility of the tourism industry and its impact on the global economy. Prior to the COVID-19 pandemic, tourism contributed 10.3% to the global GDP and employed 333 million people but saw a significant decline due to the pandemic. Sustainable and smart tourism requires collaboration from all stakeholders and a comprehensive understanding of global and local issues to drive responsible and innovative growth in the sector. This paper presents an approach for leveraging big data and deep learning to dis-cover holistic, multi-perspective (e.g., local, cultural, national, and international) and objective information on a subject. Specifically, we develop a machine learning pipeline to extract parameters from academic literature and public opinions on Twitter, providing a unique and comprehensive view of the industry from both academic and public perspectives. The academic-view dataset was created from the Scopus database and contains 156,759 research articles from 2000 to 2022, which were modelled to identify 33 distinct parameters in 4 categories: Tourism Types, Planning, Challenges, and Media &amp; Technologies. A Twitter dataset of 485,813 tweets was collected over 18 months starting March 2021 to August 2022 to showcase public perception of tourism in Saudi Arabia, which was modelled to reveal 13 parameters categorized into two broader sets: Tourist Attractions and Tourism Services. Discovering system parameters are re-quired to embed autonomous capabilities in systems and for decision-making and problem-solving during system design and operations. The proposed approach improves AI-based information discovery by extending the use of scientific literature, Twitter, and other sources for autonomous, dynamic optimizations of systems, promoting novel research in the tourism sector and contributing to the development of smart and sustainable societies. The paper also presents a comprehensive knowledge structure and literature review of the tourism sector based on over 250 research articles.

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An App for Promoting Health and Local Tourism

Cited by 5 publications

References 20 publications

Smart application of learning ecotourism for young eco-tourists

Smart application of learning ecotourism for young eco-tourists

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

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