Applying Large Language Models to investigate how people with disabilities interact at airports

Steven Tanner McCullough, Ariana Grant, Evan Mistur and June Young Park

Journal of Air Transport Management, 2026, vol. 130, issue C

Abstract: Rapid transition in social and environmental conditions consistently demand changes in how airport facilities are operated and managed, creating an ongoing stream of new and unique barriers to accessibility. In this paper, a novel framework in conjunction with Large Language Model (LLM) and accessibility design standards is used to discover the perceived accessibility of people with disability (PWD) in airports, mined from location-based social media reviews. The analysis uncovered key insights into how different airports perform in terms of accessibility among 64 hub airports in the United States. While some airports excel in most areas that are legislated by the Americans with Disabilities Act (ADA), others face challenges in providing consistent and inclusive experiences. Primarily, the initial arrival experiences at airports are seen as the most significant factor influencing PWD overall perceptions of accessibility throughout the entire airport, highlighting the importance of consistent and effective first contact in shaping the journey of PWD.

Keywords: Disability; Perceived accessibility; Airport; Social media; Large Language Model (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:130:y:2026:i:c:s0969699725001437

DOI: 10.1016/j.jairtraman.2025.102880

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