Artificial intelligence in aviation and airports

: understanding the determinants of adoption and intention to recommend the technology

Abstract

The aviation, an industry usually at the forefront of technological innovation, welcomed Artificial Intelligence (AI) in the last years as a catalyst for transformative change, with several benefits in many domains. Aviation and airports are two sectors of upmost importance in global economy, technology adoption studies in this area involving AI are still scarce and, in some cases, present disperse results, therefore requiring further investigation. In this study we used a mix method approach, combining an initial qualitative analysis with a quantitative analysis with structured equation modelling (SEM). We advance the body of knowledge by designing and using an innovative theoretical research model that combines the strengths of three well-established theories: Artificial Intelligent Device Use Acceptance (AIDUA), the Technology Acceptance Model (TAM), and the Innovation Resistance Theory (IRT), with an Intention to Recommend construct. The research model was empirically tested using one hundred and ninety-six (196) responses mainly collected in a European country. Hedonic motivation, social influence, performance expectancy, value barrier, and behavioural intention were found to influence the adoption of AI. The likelihood of a customer recommending the technology was also confirmed. For researchers, this study may serve as an initial basis for further acceptance models9 refinement. For practitioners, understanding the factors that influence AI adoption is crucial to implement and to refine devices, applications, and services in the aviation industry, with increasing the levels of acceptance and recommendation.

Date of Award	28 Oct 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Gonçalo da Costa Aleixo Monteiro Melhorado Baptista (Supervisor)