Asset Details
Do you wish to reserve the book?
Using the Fuzzy Method and Multi-Criteria Decision Making to Analyze the Impact of Digital Economy on Urban Tourism
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Using the Fuzzy Method and Multi-Criteria Decision Making to Analyze the Impact of Digital Economy on Urban Tourism
Do you wish to request the book?
Using the Fuzzy Method and Multi-Criteria Decision Making to Analyze the Impact of Digital Economy on Urban Tourism
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Using the Fuzzy Method and Multi-Criteria Decision Making to Analyze the Impact of Digital Economy on Urban Tourism
2024
Overview
Urban tourism promotes the economic growth of a nation around the year through direct and indirect incomes. In recent years, the digital economy has impacted the growth of urban tourism through hassle-free money transactions and expenditures. This article, therefore, introduces a Multi-Criteria Fuzzy-based Decision-Making Method (MCFDMM) for validating the impact of the digital economy impact over tourism. The study introduces a new framework, DLFDSS-RRM, that uses deep learning and fuzzy decision support systems for residence right management, enhancing resource allocation, security, and resident satisfaction in urban residential communities. The criteria such as expenses, positive response, and repeated payments are validated by the tourists across their travel plan. These conditions satisfying the tourist’s expectations are estimated based on their reviews of economic conditions are validated. The validation is performed against the growth of the country from urban tourism. The fuzzy process validates the growth of the country between two successive financial quarters based on the above conditions. In the condition analysis, the fuzzy process identifies the least derivatives contributing to minimal economic growth. This is reversed using the hiking condition that occurs in any quarter and hinders economic growth. Therefore, the process is validated using the metrics growth rate, condition satisfaction, analysis rate, analysis time, and unrelated assessment. The comparative analysis across various models reveals growth rates ranging from 0.263 to 0.4055, condition satisfaction percentages from 53.747 to 74.351, and analysis rates from 0.275 to 0.4662.
Publisher
Springer Netherlands,Springer
