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Smart tourism products and services design based on user experience under the background of big data

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Abstract

The rapid advancements in big data techniques and artificial intelligence (AI) have led to a radical transformation of the tourism industry, resulting in the development of smart tourism services and products. Big data and AI algorithms allow smart tourist services and products that prioritize the customers’ experience. Big data and AI-enabled smart tourism aim to improve consumer satisfaction and offer personalized recommendations. These products and services need to be customized to the evolving needs of the tourists by providing exceptional experiences. This study proposes a Decision Tree algorithm for smart tourist products and services based on user experience and big data techniques. Big data analysis of client satisfaction in smart tourism has led to the development of smart tourism products. In this study, the system components and a design strategy prioritize the users’ needs and preferences to generate personalized experiences. Smart tourism services need demand and experience analysis. Smart tourist facilities and big data analysis emphasize the clients’ satisfaction. This research examines a smart tourist product service system's logic, data, and visuals. The product services in smart tourism and essential tourist product’s service features and subsystems are used to compare tourist initiatives. Customized food, attractions, and lodgings are some of the byproducts of smart tourism product designs. In the proposed study, the real-time decision trees are used to recommend trips based on location, budget, interests, previous remarks, and context. The study suggests timely and relevant information and recommendations depending on the user's location, preferences, and external elements like weather and neighboring events by assuring an uninterrupted experience. Moreover, user input improves the communication based on decision trees to enhance ideas, knowledge, and big data analysis. The decision Tree algorithm improves the experience of users in a smart tourism ecosystem. Tourists enjoy using ideas, quick decision-making tools, and user-driven improvement of tourist experiences by enhancing the quality of products and suggestions.

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Funding

This study was funded by the National Social Science Foundation of China in 2021(Grant No. 21BMZ073): Research on the Coupling Mechanism between the Culture Revitalization of Traditional Village and the High-Quality Development of Rural Tourism in Yunnan, Guizhou and Guangxi.

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Authors and Affiliations

  1. School of Business, Guilin Tourism University, Guilin, 541006, Guangxi, China

    Huimin Hu

  2. School of Tourism Management, Guilin Tourism University, Guilin, 541006, Guangxi, China

    Chunhong Li

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  1. Huimin Hu
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  2. Chunhong Li
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Correspondence to Chunhong Li.

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Hu, H., Li, C. Smart tourism products and services design based on user experience under the background of big data. Soft Comput 27, 12711–12724 (2023). https://doi.org/10.1007/s00500-023-08851-0

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