The Accuracy of Tourism Forecasting and Data Characteristics: A Meta-Analytical Approach

Abstract

Sound policies and efficient managerial decisions in a wide range of touristic endeavors rely on accurate forecasts, but despite decades of extensive research and hundreds of published studies on the topic, neither a single model nor a category of forecasting models have proven to be superior. This meta-analysis of nearly 2,000 published tourism forecasts provides strong evidence that data characteristics are associated with forecast accuracy, and that this relationship varies across different categories of forecasting methods. The findings indicate that data characteristics might provide reliable indications as to which models are likely to be more accurate for certain tourism forecasting tasks, resulting in a more efficient and less costly process for identifying the best tourism forecasting model for the task.