Design of "Fly-Cruise" products with advanced algorithm: A case study of cruise tours in China. (June 2022)

• Record Type: Journal Article
• Authors: Guo, Wei-You; Lian, Feng; Guo, Huanxiu; Yang, Zhong-Zhen
• Is Part Of: Transport policy. Volume 121(2022)
• Page Start: 35
• Page End: 45
• Publication Date: 2022-06
• Subjects: Inbound tourism -- Hybrid solution algorithm -- Fly-cruise -- Itinerary planning -- Dynamic pricing; Transportation and state -- Periodicals; Transportation -- Rates -- Periodicals; 388
• DOI: 10.1016/j.tranpol.2022.03.012
• Languages: English
• ISSNs: 0967-070X

Abstract

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.