Research on Tourism Destination Marketing Strategy Optimization based on Big Data

Ce Zheng () and Mingdi Gao
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Ce Zheng: Qinghai University, College of Finance and Economics
Mingdi Gao: Qinghai University, College of Finance and Economics

A chapter in Proceedings of the 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024), 2024, pp 307-313 from Springer

Abstract: Abstract The advent of big data technology has introduced a duality of opportunities and challenges to the marketing of tourist destinations. The utilisation of big data enables tourist destinations to differentiate themselves from their competitors and rapidly attain a prominent position in the market, thereby conferring substantial economic and social advantages. This paper mainly uses big data technology to optimize the marketing strategy of tourist destinations. First, data mining technology is used to extract key information such as tourist behavior and preferences from multi-source data such as social media and travel platforms. Secondly, combined with the forecasting model, the dynamic changes of tourism demand are analyzed, the potential tourist groups are accurately predicted, and the factors affecting the attractiveness of the destination are identified. This study also applied machine learning algorithms to optimize precision marketing strategies to improve tourist engagement and promote the promotion effect of tourist destinations. In the experimental analysis part, the effectiveness of the optimization strategy is verified by comparing the actual cases and performance indicators.

Keywords: Personalized tutoring system; Neural network; Optimization method; Learning path (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-638-3_31

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DOI: 10.2991/978-94-6463-638-3_31

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