 Design of “Fly-Cruise” products with advanced algorithm: A case study of cruise tours in ChinaWei-You Guo, Feng Lian, Huanxiu Guo and Zhong-Zhen Yang Transport Policy, 2022, vol. 121, issue C, 35-45 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. Keywords: Inbound tourism; Hybrid solution algorithm; Fly-cruise; Itinerary planning; Dynamic pricing (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:trapol:v:121:y:2022:i:c:p:35-45 Ordering information: This journal article can be ordered from DOI: 10.1016/j.tranpol.2022.03.012 Access Statistics for this article Transport Policy is currently edited by Y. Hayashi More articles in Transport Policy from Elsevier |
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