Abstract To assist cruise companies in designing the technic-economic specifications of “fly-cruise” products and attracting international tourists, this paper proposes a model of itinerary planning and dynamic pricing with advanced algorithm. We integrate the Reinforcement Learning (RL) and Genetic Algorithm (GA) to develop a hybrid algorithm to obtain the optimal solution of the model. Taking Malaysian consumers travelling to China for cruise tours as a case study, we empirically test the model with real market data and use it to analyze the impact of innovating “fly-cruise” products on the deficit of China's inbound and outbound tourists. The results show that the innovating “fly-cruise” products will attract 20.52 million Southeast Asian tourists to China annually and generate a profit of US$ 3.56 billion for cruise companies. It highlights that the advanced algorithm based “fly-cruise” products can help China to effectively reduce the deficit of inbound and outbound tourists and improve the international balance of service trade.


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    Title :

    Design of “Fly-Cruise” products with advanced algorithm: A case study of cruise tours in China


    Contributors:
    Guo, Wei-You (author) / Lian, Feng (author) / Guo, Huanxiu (author) / Yang, Zhong-Zhen (author)

    Published in:

    Transport Policy ; 121 ; 35-45


    Publication date :

    2022-03-18


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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