This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline.

Tourism is especially suitable for this exercise because it naturally combines traveler behavior, destination image, hospitality experience, mobility, sustainability, seasonality, local community impacts and digital platforms. It also supports quantitative, qualitative and mixed methods designs, making it ideal for showing how the same tourism issue can be studied through visitor metrics, survey data, reviews, interviews, observational material and integrated designs.

In tourism, research questions and hypotheses often build on frameworks such as destination image theory, tourist motivation models, experience economy, place attachment, service quality and satisfaction models, sustainable tourism frameworks, tourism impacts models, resident attitude theory, consumer behavior in travel and mobility and destination-choice approaches. These frameworks define constructs such as satisfaction, loyalty, destination attractiveness, perceived authenticity, travel intention, place attachment, sustainability orientation, resident support or tourist experience, which are measured through survey scales, booking or visitation data, reviews, observations, interviews, geospatial traces or integrated tourism datasets.

Note: The entries in the Methodology are intentionally general and indicative. They are meant to illustrate plausible methodological directions, not to exhaust the full range of possible methods, model variants or analytic choices available to the researcher. Researchers are not expected to apply all of the methodological tools listed in column Methodology in a single study. The entries are intended to indicate suitable methodological options or families of approaches from which the researcher selects those that best fit the research question, hypothesis, data, and design.