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Evaluation of Ecotourism Opportunities for Sustainable Development: A Comprehensive Approach and Ecotourism Opportunity Index for Alula, Saudi Arabia

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posted on 2024-05-13, 06:10 authored by Riyan Sahahiri
Ecotourism opportunity evaluation is essential for sustainable tourism management. However, the inherent complexity of the tourism system presents considerable challenges. This complexity arises from ecotourism opportunities' continuous adaptation, diversification, and interconnectedness. Furthermore, the system's cascading adaptive behaviour makes it difficult to accurately predict future outcomes, adding another challenge for planners seeking to evaluate these opportunities. The current approaches to evaluating ecotourism opportunities depend primarily on qualitative measures and fail to sufficiently capture the system's dynamics. Furthermore, these methods lack a comprehensive understanding of the relationships between local communities, tourists, and the natural environment. This limits the evaluation of ecotourism opportunities as a sustainable development strategy. A more systematic and comprehensive approach is needed to address this complexity. Considering the development of ecotourism opportunities in a Complex Adaptive System (CAS), this study proposes a systematic method for measuring the extent of ecotourism opportunities and developing an Ecotourism Opportunity Index (EOI). Alula, Saudi Arabia, was selected as a case study due to its rapidly expanding ecotourism opportunities, providing an efficient environment to comprehend the system’s complexity. To develop this method, three research questions were set for this study: 1. What types of ecotourism opportunities coexist in Alula? 2. Will these opportunities contribute to sustainable tourism? 3. How can ecotourism opportunities be evaluated to develop an index for assessing potential destinations? The study's threefold methodology begins by identifying ecotourism opportunities using the SWOT-Ecotourism Opportunity Spectrum (ECOS) framework. In the second stage, Sustainable Ecotourism Opportunities Indicators (SEOIs) are compiled and validated in their relation to the identified ecotourism opportunities using the Delphi method. In the third stage, Confirmatory Factor Analysis (CFA) is applied to test the validity and reliability of the hypothetical relationships developed by the Delphi method. Data is collected and analyzed using several quantitative methods, including the Weight Scoring Method (WSM), Entropy Weight Method (EWM), Delphi method, and Ecotourism Opportunities Gap Analysis (EOGA), resulting in the measurement of the EOI. The findings of the first research question show that the development of ecotourism opportunities as a CAS is shaped by external (opportunities) and internal factors (strengths). The SWOT-ECOS analysis demonstrated that the destination possessed several variables (95 strengths, 15 weaknesses, 25 opportunities and 10 threats) under five ecotourism opportunity dimensions (nature, environmental education/protection, sustainability, socio-cultural benefits, and tourists' satisfaction) and thirteen criteria. More opportunities have led to more strengths across all dimensions, showing that external factors (opportunities) influence internal (strengths) factors. In addition to this interconnection and adaptive behaviour, the destination’s current ecotourism potential also determines its level of adaptation to internal or external influences. In the second research question, by applying the Delphi method, the study used expert consensus to identify 25 interconnected SEOIs and their corresponding 120 sustainable ecotourism opportunities (strengths and opportunities). It also developed a systems diagram to describe how external or internal factors activate adaptations among dimensions, indicators, and variables (ecotourism opportunities), finally influencing the sustainability of Alula's entire ecotourism opportunities system. The findings demonstrate that no single indicator of sustainability works in isolation because impacts in one part of the system can change another. For instance, Saudi Vision 2030 (an external factor) influenced the sustainable indicator “long-term economic growth” strongly by stimulating long-term planning and infrastructure. However, in an indirect link, Saudi Vision 2030 also affected some other variables. Although protecting threatened species and promoting natural heritage are not a part of Saudi Vision 2030, the long-term planning it provoked with the establishment of the Royal Commission for Alula led to actions to produce these outcomes. This underscores the importance of a comprehensive approach to understanding the sustainability of ecotourism, which is needed because a decision to improve one indicator, such as biodiversity conservation, must consider its effects on others, such as local community engagement or tourist satisfaction. In the third research question, the relationships between the dimensions, criteria and variables are explored quantitatively using confirmatory factor analysis (CFA). The CFA results validated the hypothetical construct that explains relationships between indicators and variables that was developed in the second research question. From this construct, the EOI was developed. The EOI findings demonstrate that Alula and its districts offer promising ecotourism opportunities, and the correlation between dimensions, indicators, and variables in the ecotourism opportunities system is complex and fluctuates based on internal and external factors. The RCU and other government agencies can monitor the sustainability of each of Alula’s ecotourism districts using the index and the ecotourism indicators, such as the indicator “employment opportunities (N21)”, which can bring economic sustainability to local residents. This indicator can allow the local stakeholders to monitor the percentage of local employment that can enhance economic empowerment in the community. RCU has initiated employment-generating programs such as the Alula Oasis. The RCU’s ambitious aim to create the world’s largest living agricultural museum will necessitate a huge workforce, creating employment opportunities for the local residents. By using an employment opportunities indicator to track how many local people are hired for this project, professionals can see how it helps the local economy. Moreover, measuring these sustainable ecotourism opportunities can optimise resource allocation, help monitor sustainability growth, support risk management, encourage stakeholder engagement, and serve as an effective promotional and marketing tool. The development of the EOI represents an innovative method for evaluating ecotourism opportunities. It introduces a new degree of rigour to ecotourism evaluations, allowing for more accurate comparisons and benchmarking among ecotourism destinations and activities. The application of CAS theory to the interpretation of the results provides a more comprehensive comprehension of the dynamics that shape ecotourism opportunities. It broadens the theoretical landscape of the field and may serve as a crucial step for future research employing this theoretical lens. Given the complexity of ecotourism opportunities, this study contributes by developing comprehensive evaluation approaches, such as the SWOT-ECOS analysis and ECOS-Delphi, that assess ecotourism opportunities qualitatively and quantitatively. These approaches are valuable for ecotourism practitioners, policymakers, and researchers as they provide comprehensive evaluations covering all interconnected ecotourism opportunity dimensions, laying a solid foundation for future sustainable ecotourism initiatives, informed decision-making, practical strategies, and policies. The Ecotourism Opportunity Index (EOI) can be used to identify potential ecotourism destinations and inform sustainable tourism plans. EOI can empower local businesses and community leaders to make informed decisions, fostering cultural collaboration and sustainable practices that benefit local economies while preserving environmental and cultural integrity.

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Degree Type

Doctorate by Research

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© Riyan Sahahiri 2024

School name

Science