arbiter
JournalsAccount

Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning

Dušan Mladenović et al.

Journal of Consumer Behaviour2026https://doi.org/10.1002/cb.70126article
AJG 2ABDC A
Weight
0.37

Abstract

This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision‐making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus–organism–response framework and domain literature, data were gathered through semi‐structured interviews (UK) and scenario‐based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision‐making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision‐making literature.

1 citation

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1002/cb.70126

Or copy a formatted citation

@article{dušan2026,
  title        = {{Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning}},
  author       = {Dušan Mladenović et al.},
  journal      = {Journal of Consumer Behaviour},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/cb.70126},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.