Title: The impact mechanism of scenario-driven and AI-enabled approaches on the competency of cross-border air logistics talent

Authors: Yongchuang Zhang; Gai Hang

Addresses: Guilin University of Aerospace Technology, Guilin 541004, China ' Guilin University of Aerospace Technology, Guilin 541004, China

Abstract: China-ASEAN economic cooperation and AI advancement are reshaping cross-border air logistics, driving demand for interdisciplinary talent. This study examines how 'scenario-driven' and 'AI-enabled' approaches enhance talent competency. Based on situated learning and technology enablement theories, a dual-path mediation model was tested using mixed methods: grounded theory analysis identified key scenarios and AI technologies, followed by a survey of 268 students analysed via structural equation modelling. Results show that both approaches directly improve competency and indirectly enhance it through practical ability and innovative thinking, with AI-Enabled approaches having a stronger total effect. The study supports a progressive, integrated teaching model and offers theoretical and practical insights for constructing a deeply integrated 'scenario-AI-capability' talent cultivation model in digital-era logistics education.

Keywords: scenario-driven; AI-enabled; talent competency; cross-border air logistics; structural equation modelling; SEM.

DOI: 10.1504/IJADS.2026.156118

International Journal of Applied Decision Sciences, 2026 Vol.19 No.5, pp.562 - 588

Received: 06 Jan 2026
Accepted: 11 Feb 2026
Published online: 04 Sep 2026 *

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