A large-scale decision-making model for the expediency of funding the development of tourism infrastructure in regions
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F23%3A63569098" target="_blank" >RIV/70883521:28120/23:63569098 - isvavai.cz</a>
Výsledek na webu
<a href="https://onlinelibrary.wiley.com/doi/10.1111/exsy.13443" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1111/exsy.13443</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/exsy.13443" target="_blank" >10.1111/exsy.13443</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A large-scale decision-making model for the expediency of funding the development of tourism infrastructure in regions
Popis výsledku v původním jazyce
The main goal of this study was to develop a hybrid decision-making support model regarding the feasibility of financing the development of tourism infrastructure of regions for V4 countries, based on the predicted assessment of the level of tourist movement in relation to the infrastructure and accessibility of the studied regions, expert opinions regarding the level of quality of tourist services and tourism development, as well as opinions of experts regarding the prospects of rapid growth of tourist movement in the region. For the first time, a hybrid fuzzy model for assessing the level of tourism quality in the region was developed, using the opinions of experts regarding the level of quality of tourist services and tourism development. For the first time, a five-layer neuro-fuzzy model was developed to derive a quantitative and linguistic assessment of the level of feasibility of financing the development of tourist infrastructure based on the experience, knowledge, and competences of experts regarding the prospects of rapid growth of tourist movement in the studied region. The research results were tested, and the developed model was verified on real data for 43 regions of the V4 countries.
Název v anglickém jazyce
A large-scale decision-making model for the expediency of funding the development of tourism infrastructure in regions
Popis výsledku anglicky
The main goal of this study was to develop a hybrid decision-making support model regarding the feasibility of financing the development of tourism infrastructure of regions for V4 countries, based on the predicted assessment of the level of tourist movement in relation to the infrastructure and accessibility of the studied regions, expert opinions regarding the level of quality of tourist services and tourism development, as well as opinions of experts regarding the prospects of rapid growth of tourist movement in the region. For the first time, a hybrid fuzzy model for assessing the level of tourism quality in the region was developed, using the opinions of experts regarding the level of quality of tourist services and tourism development. For the first time, a five-layer neuro-fuzzy model was developed to derive a quantitative and linguistic assessment of the level of feasibility of financing the development of tourist infrastructure based on the experience, knowledge, and competences of experts regarding the prospects of rapid growth of tourist movement in the studied region. The research results were tested, and the developed model was verified on real data for 43 regions of the V4 countries.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
50201 - Economic Theory
Návaznosti výsledku
Projekt
—
Návaznosti
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Expert Systems
ISSN
0266-4720
e-ISSN
1468-0394
Svazek periodika
neuveden
Číslo periodika v rámci svazku
neuvedeno
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
16
Strana od-do
—
Kód UT WoS článku
001058431100001
EID výsledku v databázi Scopus
2-s2.0-85169814593