The present study aims to cluster the world's main tourist destinations according to the growth of the economic performance of the tourist activity and of the tourist and economic development experienced during the last decade. With this objective, we combine the information from a set of...

This study examines the importance of online reviews for price determination in the hotel industry in the pre-pandemic period. The research is conducted for Croatian small open economy with a developed tourism sector. The paper fills the gap in existing literature by using multivariate principal...

COVID-19 has destroyed the tourism market, and it was essential to analyze the impact of the pandemics to reconstruct the tourism sector. In this work, we analyze the tourism demand in Italy using Social Big Data. In particular, we investigate the search behavior related to relevant tourism...

Tourism satisfaction is one of the most important components in the analysis of tourism behavior as, it not only affects the choice of tourism destination and the consumption of products, but also affects tourist's future decision to return to the same destination. The main objective of this...

Yachting tourism is an emerging industry in coastal regions, particularly in the Mediterranean countries. The rising success of yachting tourism induces a significant boom in its relevant business segments. As a type of leisure tourism, yachting tourism plays a big role in an experience economy,...

In this paper, I have investigated the out of sample forecast performance for a case study on the determination of the nominal exchange rate for USD vis-à-vis IN¬R under VEC, VAR (in first difference) and Bayesian VAR specification with the help of set of economic theories. The forecast...

This paper expands the existing informational and analytical opportunities of application of the results of business tendency surveys which solve the problem of the loss of valuable statistical information in its traditional aggregation into simple and composite indicators. Based on methods of...

Sign restrictions on impulse response functions are used in the literature to identify structural vector autoregressions and structural factor models. I extend the rank condition used for exclusion restrictions and provide a necessary and sufficient conditions for point identification for sign...

Asset returns exhibit grouped heterogeneity, and a “one-size-fits-all” model has been elusive empirically. This paper proposes a Bayesian Clustering Model (BCM) combining Bayesian factor selection and panel tree for asset clustering. The Bayesian model marginal likelihood guides the tree...

Nowadays, anomaly detection in data is an important field of research. A couple of methods have already been developed for this purpose, among which clustering-based anomaly detection remains an important one. Most methods using clustering approaches consider either numeric or categorical...