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Strategic Foresight Scenarios for Tourism Development in Uzbekistan
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General Background: Tourism is increasingly recognized as a strategic sector within Uzbekistan’s national economy, demonstrating robust growth and rising contributions to GDP in recent years. Specific Background: Despite impressive gains, the sector remains vulnerable to global disruptions, such as pandemics, highlighting the need for adaptive and forward-looking strategies. Knowledge Gap: While foresight technologies are gaining traction globally in tourism planning, their application in Uzbekistan remains underexplored and institutionally undeveloped. Aims: This study investigates the role of foresight methodologies—scenario analysis, horizon scanning, and long-term forecasting—in shaping strategic tourism development in Uzbekistan and proposes a structured framework for their implementation. Results: Empirical analysis revealed a strong correlation (r ≈ 0.99) between tourist inflows and export revenues, and scenario modeling projected 2030 arrivals ranging from 10 to 14 million tourists depending on external and policy factors. Novelty: The study presents the first integrated application of foresight tools in Uzbekistan’s tourism context, including custom growth scenarios and institutional foresight recommendations. Implications: Embedding foresight into national tourism planning will enhance Uzbekistan’s resilience to global shocks, align sectoral strategies with market trends, and strengthen its position as a leading destination in Central Asia.Highlight :
Foresight tools such as scenario planning and forecasting are crucial for anticipating and shaping the future of Uzbekistan's tourism sector.
Tourism recovery post-COVID has shown strong momentum, with projections aiming at 10–14 million tourists by 2030.
Strategic integration of foresight into policy can enhance resilience, competitiveness, and sustainability in national tourism development.
Keywords : Foresight, Strategic Planning, Tourism Development, Uzbekistan, Scenario Analysis
Title: Strategic Foresight Scenarios for Tourism Development in Uzbekistan
Description:
General Background: Tourism is increasingly recognized as a strategic sector within Uzbekistan’s national economy, demonstrating robust growth and rising contributions to GDP in recent years.
Specific Background: Despite impressive gains, the sector remains vulnerable to global disruptions, such as pandemics, highlighting the need for adaptive and forward-looking strategies.
Knowledge Gap: While foresight technologies are gaining traction globally in tourism planning, their application in Uzbekistan remains underexplored and institutionally undeveloped.
Aims: This study investigates the role of foresight methodologies—scenario analysis, horizon scanning, and long-term forecasting—in shaping strategic tourism development in Uzbekistan and proposes a structured framework for their implementation.
Results: Empirical analysis revealed a strong correlation (r ≈ 0.
99) between tourist inflows and export revenues, and scenario modeling projected 2030 arrivals ranging from 10 to 14 million tourists depending on external and policy factors.
Novelty: The study presents the first integrated application of foresight tools in Uzbekistan’s tourism context, including custom growth scenarios and institutional foresight recommendations.
Implications: Embedding foresight into national tourism planning will enhance Uzbekistan’s resilience to global shocks, align sectoral strategies with market trends, and strengthen its position as a leading destination in Central Asia.
Highlight :
Foresight tools such as scenario planning and forecasting are crucial for anticipating and shaping the future of Uzbekistan's tourism sector.
Tourism recovery post-COVID has shown strong momentum, with projections aiming at 10–14 million tourists by 2030.
Strategic integration of foresight into policy can enhance resilience, competitiveness, and sustainability in national tourism development.
Keywords : Foresight, Strategic Planning, Tourism Development, Uzbekistan, Scenario Analysis.
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