Volume 1 - Issue 2, May - June 2026

Mountain tourism represents a rapidly growing sector of the global hospitality industry, yet hillside hotels frequently struggle with volatile demand, extreme seasonality, and fragmented management practices. This paper introduces a comprehensive framework designed to optimize revenue generation for hillside hotels through cooperative tourism development and advanced predictive analytics. By shifting away from siloed operations toward a collaborative model, regional hospitality providers can share vital data, pool resources, and develop unified pricing strategies that benefit the entire destination. Central to this framework is the integration of cutting-edge artificial intelligence for tourism demand forecasting, which enables stakeholders to accurately predict both short-term fluctuations and long-term dependencies. Through a proposed methodology that combines stakeholder data integration, AI-driven forecasting, and dynamic cooperative pricing, this study provides a strategic blueprint for mountain destinations. Ultimately, the framework aims to stabilize income streams, enhance the resilience of hillside accommodations, and promote sustainable economic growth in geographically challenging tourism regions.

Dr.Muhammed Anas .B, Dr.Sajimon PP, Dr.N.Subbu Krishna Sastry, Dr. V Basil Hans, Dr.Sini.V, "A Collaborative Structure for Advancing Mountain Tourism: Enhancing Revenue Generation in Hillside Hotels and Resorts" International Journal of Humanities and Social Sciences Research Studies, V1(2): Page(01-08) May-June 2026. ISSN: 3139-0854. www.ijarsmet.com. Published by Scientific and Academic Research Publishing.