Sabah Leads The Way In Wellness Tourism And Cross Border Collaborations: Key Takeaways From SWWICE Initiative – Travel And Tour World

AI News Q&A (Free Content)

Q1: What are the key findings of the study on multistakeholder fairness in tourism management?

A1: The study emphasizes that tourism management employs qualitative, inclusive, and participatory methods to address fairness from a holistic perspective. It highlights the need for interdisciplinary collaboration, as computer science often lacks sufficient understanding of stakeholder needs and primarily focuses on measurable discrimination, missing the multidimensional nature of fairness in tourism.

Q2: How does sustainable tourism impact South Asian countries, and what challenges does it face?

A2: Sustainable tourism significantly contributes to foreign exchange profits and job creation in South Asia. However, challenges include inadequate infrastructure, insufficient recreation facilities, security issues, lack of proper planning and marketing, and political instability. The study recommends government policies involving public and private investment for long-term growth.

Q3: What role do algorithmic decision-support systems play in tourism, according to recent research?

A3: Algorithmic decision-support systems, such as recommender systems, are widely used to guide tourists in choosing destinations. However, they can inadvertently negatively impact environments and communities due to limited understanding of stakeholder relationships. The research suggests that improved interdisciplinary collaboration could enhance these systems for better multistakeholder fairness.

Q4: In what ways does tourism influence land prices in Japan, based on recent studies?

A4: Recent studies show that tourism can lead to significant increases in land prices, particularly in 'superstar' cities with high tourist arrivals. However, most municipalities experience little to no effect. This highlights the uneven impact of tourism on land prices across different regions.

Q5: What factors influence disaster preparedness among tourist village managers in Indonesia?

A5: The study identifies belief, knowledge, risk perception, and experience as key predisposing factors. Enabling factors include infrastructure and training availability, while reinforcing factors involve support from various stakeholders. This comprehensive understanding aims to foster effective disaster preparedness behavior.

Q6: What are the implications of the study on tourism and land prices for policy makers?

A6: The findings suggest that policy makers should focus on managing the effects of tourism in 'superstar' cities to prevent excessive land price increases, while supporting other regions to benefit from tourism. This could involve targeted infrastructure development and marketing to distribute tourism benefits more evenly.

Q7: What are the potential benefits of interdisciplinary collaboration in enhancing tourism management systems?

A7: Interdisciplinary collaboration between tourism management and computer science can lead to the development of more equitable and inclusive decision-support systems. By integrating qualitative insights from tourism management with quantitative frameworks from computer science, these systems can better address the complex needs of various stakeholders.

References:

• Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?
• Prospects and Challenges for Sustainable Tourism: Evidence from South Asian Countries
• When Does Tourism Raise Land Prices? Threshold Effects, Superstar Cities, and Policy Lessons from Japan
• Disaster preparedness behaviour of tourist village managers in Mount Merapi, Indonesia