Pro-environmental behaviour of the residents in sensitive tourism destinations

Li, Jiaqi; Lee, Timothy Jeonglyeol; Chen, Nan; Park, Keun-Soo

doi:10.1177/13567667221101406

Cited by 10 publications

(7 citation statements)

References 99 publications

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“…Many innovative and radical technologies are emerging frequently [45,46] while the existing technologies are evolving at a fast pace, and these advancements and dynamics are making unforeseeable impacts on societies and hence on tourism, its nature, and requirements [30,31,47]. It is important for all stakeholders, such as governments, businesses, and local communities, to work together to develop sustainable and responsible tourism practices, a concept being pursued internationally under the sustainable tourism umbrella [5][6][7][8][9][10].…”

Section: The Need For Smart Responsible and Sustainable Tourismmentioning

confidence: 99%

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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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Section: The Need For Smart Responsible and Sustainable Tourismmentioning

confidence: 99%

“…However, the exploitative practices of capitalist approaches have had a detrimental effect on social, environmental, and economic sustainability. In response, sustainable tourism has emerged as an alternative approach that seeks to enhance both the tourism experience and promote longer-term sustainability [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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

2023

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“…Many innovative and radical technologies are emerging frequently while the existing technologies are evolving at a high pace and these advancements and dynamics are making unforeseeable impacts on societies and hence on tourism, its nature, and requirements. It is important for all stakeholders, such as governments, businesses, and local communities, to work together to develop sustainable and responsible tourism practices, a concept being pursued internationally under the sustainable tourism umbrella [30][31][32][33][34][35].…”

Section: The Need For Smart Responsible and Sustainable Tourismmentioning

confidence: 99%

“…This parameter captures various dimensions of Sustainable Tourism including Environment, Sustainability, Ecotourism, Communities, Destinations, Visitors, Residents, Homes, Impacts, Management, People's Behaviors, Norms, and Attitudes. The research activities in this parameter include, among others, managing ecotourism by protecting natural resources and environments, preserving traditional cultures of the host communities, and enhancing the environmental protection awareness of the local population [30,31], tourists' attitudes toward sustainable consumption and purchasing habits concerning eco-friendly products [33], managing overtourism and their impacts on residents [34], and citizens' participation in environmentally sustainable actions [35]. For example, Schubert et al [34] asserted that over-tourism brings negative impacts on the cultures of the residents and consumption such as booked-out restaurants, crowded hiking trails.…”

Section: Sustainable Tourismmentioning

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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“…Fortunately, academics have expressed interest in the novel concept of community citizenship behavior (CCB) lately [5,6]. This concept aligns with the evolving research trend where scholars are shifting focus from supporting destination residents to investigating a broader spectrum of resident behaviors [7,8]. Additionally, the altruistic extra-role characteristic of CCB can significantly enhance destination development efficiency and Behav.…”

Section: Introductionmentioning

confidence: 99%

Can Positive Social Contact Encourage Residents’ Community Citizenship Behavior? The Role of Personal Benefit, Sympathetic Understanding, and Place Identity

Wang,

Wu,

et al. 2024

Behavioral Sciences

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Identified as an increasingly pivotal aspect, the benevolent extra-role characteristic of community citizenship behavior contributes to destination development efficiency and social cohesion. Based on the egoistic–altruistic motivation framework, this study investigated three motivations that propel residents to exercise community citizenship behaviors in a positive social contact context, namely self-focused, other-focused, and place-focused motivation. A conceptual model combined with positive contact, personal benefit, sympathetic understanding, place identity, and community citizenship behavior was developed and tested using partial least squares structural equation modeling (PLS-SEM) through data from 366 residents in Kaifeng, China. The findings showed that of the three motivations for community citizenship behaviors, place identity contributed the most, and personal benefits failed to predict community citizenship behaviors. Furthermore, sympathetic understanding with tourists was most fostered by residents from the perception of positive contact with tourists. These findings offer a novel theoretical framework for scholarly investigation and provide practical insights for tourism managers regarding strategies to influence residents’ community citizenship behavior.

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Pro-environmental behaviour of the residents in sensitive tourism destinations

Cited by 10 publications

References 99 publications

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

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

Can Positive Social Contact Encourage Residents’ Community Citizenship Behavior? The Role of Personal Benefit, Sympathetic Understanding, and Place Identity

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