Have a personal or library account? Click to login
An Analysis of Tourist Attractiveness of Poviats of the Lesser Poland Voivodeship Cover

An Analysis of Tourist Attractiveness of Poviats of the Lesser Poland Voivodeship

By:
Open Access
|Aug 2020

Abstract

Research background: Lesser Poland is one of the most visited regions in Poland. Among the reasons why it is so, there are a variety of attractions located in this voivodeship and also the activities taken by local government, for which the development of the tourism industry is one of the key goals.

Purpose: Building a ranking of poviats of Lesser Poland in terms of tourist attractiveness.

Research methodology: Selected multivariate analysis tools, i.e. three methods of linear ordering and cluster analysis.

Results: Using the Ward algorithm, poviats are grouped into four clusters of areas with similar characteristics due to tourist values. In addition, using three linear ordering techniques, poviats of the Lesser Poland voivodeship are ordered according to tourist attractiveness. The results of ordering are rather consistent and indicate that the most attractive poviats are: nowotarski, oświęcimski, tatrzański and the city of Kraków. Interestingly, these areas belong to three different groups obtained as part of a cluster analysis. This means that Lesser Poland is a diversified region in terms of the attractions that draw tourists’ to the area.

Novelty: The study of tourist attractiveness using linear ordering techniques is not an original topic. The thesis is of cognitive value and fills a gap in the literature, in which there are no studies based on data from Lesser Poland.

DOI: https://doi.org/10.2478/foli-2020-0029 | Journal eISSN: 1898-0198 | Journal ISSN: 1730-4237
Language: English
Page range: 506 - 518
Submitted on: Oct 15, 2019
Accepted on: Mar 30, 2020
Published on: Aug 20, 2020
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year

© 2020 Jacek Wolak, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.