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Title Circular Economy Model for Elderly Tourism Operation Based on Multi-source Heterogeneous Data Integration
ID_Doc 28616
Authors Zhang, YS
Title Circular Economy Model for Elderly Tourism Operation Based on Multi-source Heterogeneous Data Integration
Year 2023
Published Applied Artificial Intelligence, 37.0, 1
DOI 10.1080/08839514.2023.2205228
Abstract The emerging senior tourism industry has attracted increasing attention in China due to the continuous development of social, economic and technological factors. However, the senior tourism market in China still faces significant shortages, and further market development is needed. To address this issue, a senior tourism business model based on the circular economy, artificial intelligence (AI) technology and multi-source heterogeneous data integration has been proposed in this study. The model uses AI technology to integrate and analyze multi-source heterogeneous data, providing insights into the senior tourism market and facilitating precise marketing. Additionally, the model combines senior tourism products with sustainable development by adopting a circular economy model, achieving both economic and environmental benefits. The application of this model is expected to enhance the competitiveness and sustainable development of the Chinese senior tourism market, providing new ideas and references for the development of the industry. The integration of multi-source heterogeneous data is a significant feature of this model, which facilitates a more in-depth understanding of the senior tourism market. By analyzing various data sources, such as social media, search engines, and online reviews, the model can better identify senior tourists' preferences and behaviors, thereby improving the precision of marketing strategies. Furthermore, by integrating environmental data, such as carbon footprint and energy consumption, the model can assess the sustainability of senior tourism products, contributing to the development of eco-friendly senior tourism.
Author Keywords
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000975991000001
WoS Category Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic
Research Area Computer Science; Engineering
PDF https://www.tandfonline.com/doi/pdf/10.1080/08839514.2023.2205228?needAccess=true&role=button
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