<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>With the rapid development of Internet communication technology, the tourism industry will certainly transform and upgrade to the direction of wisdom, and the organization and dissemination of tourist destination information will become a breakthrough in tourism development. This paper firstly constructs a tourism management system (DMS) in line with the idea of smart tourism development by constructing a process line from market opportunity analysis, interest motivation analysis, strategic planning stage, strategy implementation stage and evaluation improvement stage, respectively. Secondly, the evaluation model of tourism destination development based on logistic regression is systematically constructed, and the parameter estimation method is used to estimate the value for 8 influencing factors that affect the development of tourism destinations. The results show that through the empirical analysis of the Guizhou smart tourism destination management system, it is found that the AUC value shows an increasing trend, and the 5km grid has the smallest AUC value. When the grid continues to increase, the AUC value shows a decreasing trend, slowly decreasing from 0.836 (20km) to 0.844 (25km). It shows that the intelligent tourism destination management system constructed in this paper is reasonable and lays the theoretical foundation for realizing regional barrier-free tourism and achieving the development goal of integrated symbiosis.</p>
</abstract>

With the rapid development of Internet communication technology, the tourism industry will certainly transform and upgrade to the direction of wisdom, and the organization and dissemination of tourist destination information will become a breakthrough in tourism development. This paper firstly constructs a tourism management system (DMS) in line with the idea of smart tourism development by constructing a process line from market opportunity analysis, interest motivation analysis, strategic planning stage, strategy implementation stage and evaluation improvement stage, respectively. Secondly, the evaluation model of tourism destination development based on logistic regression is systematically constructed, and the parameter estimation method is used to estimate the value for 8 influencing factors that affect the development of tourism destinations. The results show that through the empirical analysis of the Guizhou smart tourism destination management system, it is found that the AUC value shows an increasing trend, and the 5km grid has the smallest AUC value. When the grid continues to increase, the AUC value shows a decreasing trend, slowly decreasing from 0.836 (20km) to 0.844 (25km). It shows that the intelligent tourism destination management system constructed in this paper is reasonable and lays the theoretical foundation for realizing regional barrier-free tourism and achieving the development goal of integrated symbiosis.

Optimization of smart tourism destination management based on linear regression model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the rapid development of Internet communication technology, the tourism industry will certainly transform and upgrade to the direction of wisdom, and the...

Optimization of smart tourism destination management based on linear regression model

Publié en ligne: 27 sept. 2023

Pages: -

Reçu: 21 oct. 2022

Accepté: 07 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00390

Mots clés
Smart tourism, Tourism management system, DMS, logistic regression, Parameter estimation.

© 2023 Yue Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Optimization of smart tourism destination management based on linear regression model

Publié en ligne: 27 sept. 2023

Pages: -

Reçu: 21 oct. 2022

Accepté: 07 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00390

Mots clésSmart tourism, Tourism management system, DMS, logistic regression, Parameter estimation.

© 2023 Yue Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Smart tourism, Tourism management system, DMS, logistic regression, Parameter estimation.