Developing a Smart and Sustainable Tourism Resource Management Model for Enhancing Regional Service Sector Resilience: Evidence From Uzbekistan
Year: 2026
Type: article
Abstract: The rapid expansion of tourism in Uzbekistan creates significant opportunities for regional service-sector development while simultaneously increasing the need for efficient, sustainable and data-driven management of tourism resources. This study develops a Smart and Sustainable Tourism Resource Management Model designed to strengthen the resilience of regional service sectors in Uzbekistan. The research combines secondary statistical analysis, literature synthesis, trend analysis and conceptual modelling. Official data of the National Statistics Committee of the Republic of Uzbekistan for 2021–2025 are used as the primary empirical source. The number of foreign tourist trips increased from 1.881 million in 2021 to 11.680 million in 2025, demonstrating substantial post-pandemic recovery and growing pressure on destination infrastructure, service capacity and tourism resources. A linear baseline forecasting model is applied to estimate foreign tourist flows for 2026–2030. The results indicate that, if the observed long-term trend continues, international tourist trips may reach approximately 22.3 million by 2030. Based on the empirical and theoretical findings, the paper proposes an integrated management model connecting smart infrastructure, data-driven governance, resource efficiency, service innovation and regional resilience. The study argues that the sustainable growth of tourism in Uzbekistan should no longer be evaluated solely through tourist numbers; digital capacity, environmental efficiency, local economic benefits, service quality and destination resilience should be incorporated into regional tourism policy. The proposed model provides a practical framework for regional authorities, tourism organizations and service enterprises seeking to transform tourism-resource growth into sustainable regional development.
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7208736376
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