A Bayesian multidimensional IRT approach for the analysis of residents’ perceptions toward tourism

In this study, a Bayesian multidimensonal item response theory (IRT) model assuming the presence of correlated general and specific latent traits is proposed for the investigation of residents' perceptions toward the tourism industry. Data collected in 2012 in the Italian Romagna area were used to study the perceived benefits and costs related to tourism. By using posterior predictive model checks and Bayesian deviance, the additive IRT model was found to fit the data well. More importantly, the results could be interpreted meaningfully, showing the most and least important perceived advantages and disadvantages of tourism for the local community. Finally, thanks to the compensatory structure of the model, the different influence of the overall attitude and the specific perceptions of the respondents could be investigated for each aspect included in the questionnaire.