AI-powered travel recommendations and decision-making: The role of spatio-temporal efficiency, destination type, and travel party composition

Sunyoung Hlee (), Zhijun Yan () and Ping Li ()
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Sunyoung Hlee: Beijing Institute of Technology
Zhijun Yan: Beijing Institute of Technology
Ping Li: Beijing Institute of Technology

Electronic Markets, 2025, vol. 35, issue 1, No 75, 18 pages

Abstract: Abstract This study examined the influence of AI-driven recommendation systems on perceived helpfulness in travel decision-making, emphasizing spatio-temporal efficiency, destination type, and travel party composition. Although AI-driven travel recommendations are becoming more common, current research has mainly concentrated on text-based suggestions, neglecting the advantages of real-time, location-aware AI recommendations. Our study posited that integrating spatio-temporal efficiency into AI suggestions enhance travel itineraries and diminish cognitive burden, thus facilitating improved user decision-making. The study employed a scenario-based experimental approach to gather data from 320 South Korean passengers assessing AI recommendations for trip. The results indicate that spatio-temporal AI recommendations are regarded as more beneficial than non-spatio-temporal alternatives. Furthermore, individuals seeking tourist attractions find spatio-temporal recommendations considerably more advantageous, but those searching for restaurants do not observe a substantial distinction between the two recommendation modes. Moreover, the travel party composition affects perceived helpfulness, as companion travelers recognize greater advantages from spatio-temporal AI recommendations, whereas sole travelers demonstrate no distinct preference. These findings facilitate both theoretical progress and practical implementations in AI-driven tourism.

Keywords: AI-powered travel recommendations; Spatio-temporal efficiency; Perceived helpfulness; Destination type; Travel party composition (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12525-025-00825-4

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