AI-BASED RECOMMENDATION SYSTEMS IN TOURISM MARKETING AND THEIR IMPACT ON TRAVEL DECISIONS

Abstract

By enabling businesses to evaluate tourist data and provide tailored recommendations, artificial intelligence (AI) has revolutionized tourism marketing. AI-based recommendation systems make recommendations for locations, lodging, attractions, transit, dining, and activities based on search history, booking trends, destination preferences, reviews, demographics, social media interactions, and real-time behavior. By enhancing information search, personalization, and customer experience, these solutions assist passengers at every stage of the decision-making process. With a focus on machine learning, predictive analytics, natural language processing, recommender algorithms, customer segmentation, and intelligent travel aides, this paper investigates the function of AI-based recommendation systems in tourist marketing and their impact on travel decisions. Destination awareness, visit intention, booking decisions, and customer loyalty can all be influenced by elements including suggestion relevancy, perceived usefulness, trust, convenience, information quality, and personalization