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Explore for a day? Generating personalized itineraries that fit spatial heterogeneity of tourist attractions

Ji, H.; Zheng, W.; Zhuang, X.; Lin, Z.

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Authors

H. Ji

W. Zheng

X. Zhuang



Abstract

Recommender systems are widely adopted by firms as an innovative personalization tool across various industries. Most of the existing tour recommender systems treat the spatial structure of tourist attractions as a single type, which neglects the spatial heterogeneity among these attractions. This study attempts to address this problem by modeling the spatial heterogeneity in the design of personalized trips. We propose a two-phase heuristic approach, which involves an improved artificial bee colony algorithm and a differential evolution algorithm. The results of a field experiment confirm that our new model outperforms the benchmark models in maximizing customer utilities.

Citation

Ji, H., Zheng, W., Zhuang, X., & Lin, Z. (2021). Explore for a day? Generating personalized itineraries that fit spatial heterogeneity of tourist attractions. Information and Management, 58(8), Article 103557. https://doi.org/10.1016/j.im.2021.103557

Journal Article Type Article
Acceptance Date Nov 2, 2021
Online Publication Date Nov 4, 2021
Publication Date 2021-12
Deposit Date Nov 8, 2021
Publicly Available Date Nov 5, 2023
Journal Information & Management
Print ISSN 0378-7206
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 58
Issue 8
Article Number 103557
DOI https://doi.org/10.1016/j.im.2021.103557
Public URL https://durham-repository.worktribe.com/output/1222815

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