Norms are a theoretical construct that has been widely used in sociology and the social sciences more broadly. Norm theory and related empirical methods have been applied in a range of park, recreation, and tourism contexts. This chapter reviews and illustrates the resulting body of scientific and professional literature. In particular, this body of work has measured the personal and social norms of recreation visitors and other stakeholders through survey research, and illustrates the ways in which resulting data can help inform 1) standards of quality for the ecological and experiential conditions of park, recreation, and tourism areas, and 2) the associated carrying capacity of such areas. A variety of research issues are addressed, including question and response formats, norm prevalence, norm salience, evaluative dimensions of norms, crystallization of norms, norm congruence, statistical measures of norms, stability of norms, effect of existing conditions on norms, and the validity of norms.
Benchmarking oneself against the best-in-class offers valuable information. This chapter presents theoretical insights in the benchmarking process as well as guidelines on how to apply it in practice.
True experimentation, where an independent variable is altered to determine the effects on the dependent variable(s), is not a common research method for tourism research. While not applicable to most situations, it can be a valuable technique to better understand relationships and assign causation. Many key considerations can guide the successful use of experiments in tourism. Experimentation requires control and manipulated subjects, randomly assigned to the different conditions, to determine the impacts of the manipulation. To better assess the changes, only one factor should be altered at a time, and statistical tests that do not selectively leave out certain data should be employed. Ten possible errors can impact on the results of the experiment, so these need to be minimized through the experimental design chosen. Experiments can be more involved than other methods of tourism research, but when used in the right situations, they can be powerful tools in the researcher’s toolbox.
Analysis of hypothesis and other forms of relationship testing are often performed using secondary (or desk) data sets which are nowadays widely available. These data sets are fed into specifications or models derived from sound theoretical underpinnings, and these are then subjected to regression analysis. This chapter aims at introducing a simple model specification and regression analysis using a tourism data set. The chapter dwells deeper into time series, cross-section and panel data analysis.