DYNAMIC PRICING AND ARTIFICIAL INTELLIGENCE IN TOURISM MARKETS: A THEORETICAL FRAMEWORK FOR UZBEKISTAN'S HOSPITALITY SECTOR

Description

The aim of the study is to consider the potential of introducing Artificial Intelligence (AI) and dynamic pricing into the hotel industry in Uzbekistan and present a methodological approach to assessing the contribution of these innovations to the revenue and satisfaction of guests. The Study design involves testing a quantitative model where AI capabilities, dynamic pricing success, and customer perceptions are tested using simulated survey data from hotel managers and tourists. The simulated results show that although AI-based pricing could help to boost revenue and bookings, it relies on customers’ feeling that prices are fair. Applications and limitations: The obvious limitation is that of using simulated data; field experiments are the next step required. This framework allows regional hoteliers to become aware of the risks and needs that come with algorithmic pricing. Practical implications: Uzbekistan hotels need to get clean operational data and have clear pricing policies before giving up on the established seasonal rates for the AI systems. Social implications: Limited hotel inventory can be used to its fullest potential during the peak tourist season by employing better pricing strategies which can help increase economic growth in the area. Originality: Transition economies are excluded from most revenue management research. This study explores the interaction between algorithmic pricing and the unique cultural and market contexts in Central Asia.

Authors

DOI: 10.5281/zenodo.20781271

Publication Date: 2026-06-21

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