Article: Enhancing tourism routes optimisation accuracy as well as dynamic adjustments using data analytics approach Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.51 pp.17 - 35 Abstract: Tourism route planning has traditionally emphasised shortest-path optimisation, often over-looking the importance of enhancing tourists' overall experiences. Many travellers rely on user-generated content to guide their journeys, yet manually searching and adjusting routes in real-time can be inefficient and inaccurate. This study focuses on building a high-quality database to support model training for tourism route optimisation and dynamic adjustments. By leveraging graph theory and the Floyd-Warshall algorithm, the proposed approach integrates various tourism-related data factors to enhance route planning accuracy based on personalised preferences. The high-quality dataset, sourced from travel agencies and user-generated data, ensures the algorithm's adaptability in real-world scenarios. The model is tested on an online tourism platform, with its effectiveness evaluated through a framework grounded in tourism theories and user behaviour research. The results demonstrate significant improvements in both route planning accuracy and the efficiency of real-time adjustments when travellers modify their plans mid-journey. Inderscience Publishers - linking academia, business and industry through research

Title: Enhancing tourism routes optimisation accuracy as well as dynamic adjustments using data analytics approach

Authors: Qinyun Liu; Zhicheng Hao

Addresses: Tourism College, Beijing Union University, Beijing, 100101, China ' Tourism College, Beijing Union University, Beijing, 100101, China

Abstract: Tourism route planning has traditionally emphasised shortest-path optimisation, often over-looking the importance of enhancing tourists' overall experiences. Many travellers rely on user-generated content to guide their journeys, yet manually searching and adjusting routes in real-time can be inefficient and inaccurate. This study focuses on building a high-quality database to support model training for tourism route optimisation and dynamic adjustments. By leveraging graph theory and the Floyd-Warshall algorithm, the proposed approach integrates various tourism-related data factors to enhance route planning accuracy based on personalised preferences. The high-quality dataset, sourced from travel agencies and user-generated data, ensures the algorithm's adaptability in real-world scenarios. The model is tested on an online tourism platform, with its effectiveness evaluated through a framework grounded in tourism theories and user behaviour research. The results demonstrate significant improvements in both route planning accuracy and the efficiency of real-time adjustments when travellers modify their plans mid-journey.

Keywords: database establishment; machine learning; tourism route planning adjustment.

DOI: 10.1504/IJICT.2026.153704

International Journal of Information and Communication Technology, 2026 Vol.27 No.51, pp.17 - 35

Received: 30 Sep 2025
Accepted: 31 Dec 2025
Published online: 21 May 2026 *

Title: Enhancing tourism routes optimisation accuracy as well as dynamic adjustments using data analytics approach

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