This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo…
This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months.
A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression.
Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results.
Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad.
The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.
Financial analysis at international level has to overcome a lot of obstacles that increase the uncertainty which the financial analyst is used to handling. It is commonly…
Financial analysis at international level has to overcome a lot of obstacles that increase the uncertainty which the financial analyst is used to handling. It is commonly argued by accounting regulators, academics, and so on, that different accounting standards are one of these handicaps. For this reason European listed companies will be required in year 2005 to elaborate consolidated financial statements according to International Accounting Standards. Will it be a solution for the handicaps that face financial analysts? The objective of this study is to see how accounting diversity can be resolved and what are the conclusions of financial analysts in capital markets. The prior hypotheses will be: first, that accounting diversity is not what introduces the most important uncertainty in the international financial analysis, and second, that accounting diversity is avoided instead of being corrected. It is evidenced that the most important factors of diversity are strategies of the company and that analysts try to reduce the impact of accounting diversity, for example, using less biased ratios such as Enterprise Value/EBITDA.