Tourists' Attitudes toward Artificial Intelligence Powered Recommendation Systems in Tourism Planning Dataset

The data were collected through an online survey of 367 respondents, aiming to explore tourists' attitudes toward AI-powered recommendation systems in tourism planning. This study examines various constructs from the extended Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), including Perceived Usefulness (PU), Behavioral Intention to Use AI (BIUA), Social Influence (SI), Trust in AI (TA), Tourist Awareness & Attitude (TAA), Privacy Concern (PC), Perceived Value (PV), and Tourist & Contextual Factors (TCF). The respondents were selected using purposive sampling , representing a mix of demographic information such as gender, age, education level, residence area, tourism travel frequency (per year), technology access, and prior use of AI travel tools. This dataset contains the respondents’ original responses, containing demographic details and ratings on constructs on a Likert scale ranging from 1 to 5.