<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Under the background of the Internet, the effective use of new media means can improve the marketing level of rural tourism and adapt to the development needs of the new era. The construction of a new media marketing platform for rural tourism uses Hadoop, an extensive data framework system, to analyze the tourism preferences of various consumers. Based on the constructed platform, a rural tourism consumer portrait model is designed using the fuzzy-C mean clustering algorithm and the personalized recommendation algorithm considering the time effect to realize the precise marketing of rural tourism consumers. In the analysis of consumer precision marketing, consumers can be subdivided into three categories of growing, high-value and general consumers through clustering, and the marketing success rate of the recommendation algorithm in this paper reaches 0.765. The regression analysis further understands that the quality of the products and services of the rural tourism website (0.586) is the factor that has the most significant influence on the satisfaction of the consumers, followed by brand awareness (0.556), and that the different new rural tourism media marketing strategies have the most significant influence on the satisfaction of consumers. Consumer satisfaction is affected by media marketing strategies in other ways. Based on the study’s results, this paper proposes relevant optimization of new media marketing strategies for rural tourism to promote sustainable development.</p>
</abstract>

Under the background of the Internet, the effective use of new media means can improve the marketing level of rural tourism and adapt to the development needs of the new era. The construction of a new media marketing platform for rural tourism uses Hadoop, an extensive data framework system, to analyze the tourism preferences of various consumers. Based on the constructed platform, a rural tourism consumer portrait model is designed using the fuzzy-C mean clustering algorithm and the personalized recommendation algorithm considering the time effect to realize the precise marketing of rural tourism consumers. In the analysis of consumer precision marketing, consumers can be subdivided into three categories of growing, high-value and general consumers through clustering, and the marketing success rate of the recommendation algorithm in this paper reaches 0.765. The regression analysis further understands that the quality of the products and services of the rural tourism website (0.586) is the factor that has the most significant influence on the satisfaction of the consumers, followed by brand awareness (0.556), and that the different new rural tourism media marketing strategies have the most significant influence on the satisfaction of consumers. Consumer satisfaction is affected by media marketing strategies in other ways. Based on the study’s results, this paper proposes relevant optimization of new media marketing strategies for rural tourism to promote sustainable development.

Research on optimization strategy of new media marketing of rural tourism under the background of “Internet+”

Applied Mathematics and Nonlinear Sciences

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

Under the background of the Internet, the effective use of new media means can improve the marketing level of rural tourism and adapt to the development needs...

Research on optimization strategy of new media marketing of rural tourism under the background of “Internet+”

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 15 abr 2024

Aceptado: 20 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1036

Palabras clave
Rural tourism, New media marketing platform, Fuzzy-C mean, Personalized recommendation, Consumer portrait

© 2024 Xi Ai, published by Sciendo

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

Research on optimization strategy of new media marketing of rural tourism under the background of “Internet+”

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 15 abr 2024

Aceptado: 20 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1036

Palabras claveRural tourism, New media marketing platform, Fuzzy-C mean, Personalized recommendation, Consumer portrait

© 2024 Xi Ai, published by Sciendo

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

Palabras clave
Rural tourism, New media marketing platform, Fuzzy-C mean, Personalized recommendation, Consumer portrait