Date of Award

Summer 2022

Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation

Department

College of Aviation

Committee Chair

Dothang Truong, Ph.D.

First Committee Member

Jing Yu Pan, Ph.D.

Second Committee Member

David Cross, Ph.D

Third Committee Member

Joshua Sperling, Ph.D.

College Dean

Alan J. Stolzer, Ph.D

Abstract

Commercial short-haul flights (SF) are vital to airports and airlines because they account for one-third of hub traffic and have higher profit margins than the long-haul market. While U.S. commercial air passenger travel has increased steadily over the past decades, SF has been declining and was doing so before the unprecedented decrease in air travel caused by restrictions related to the COVID-19 global pandemic. Once autonomous mobility-on-demand (aMoD) is more viable than the human-driven car, demand for SF could be negatively impacted. Although there is published research on SF and aMoD, studies on factors influencing the choice between SF and aMoD are missing. Based on goal framing theory (GFT) variables, contextual trip attributes, COVID-19 items, and demographics, this study used a quantitative survey design to answer two research questions. The first question sought to identify factors that most influence U.S. air travelers’ modal choice for inter-regional travel. The second question aimed to identify distinct passenger clusters for SF and aMoD and evaluate the similarities and differences within these passenger segments. An online questionnaire of 69 items was developed based on extant literature and the theoretical foundation of the GFT. The survey was administered online with an air passenger sample in October 2021 via Amazon’s MTurk Results from 1,388 air passenger respondents qualified for data analyses, including exploratory factor analysis (EFA), multinomial logistic regression (MNL), two-step cluster analysis (CA), and multivariate analysis of variance (MANOVA).

The findings support the GFT as a theoretical framework for modeling future mode choice and SF and aMoD clusters. The current primary transport mode was the most critical predictor for future mode choice. Self-efficacy, value of time, trust, and habit are new variables added to the GFT framework. The first two were useful in predicting future mode choice; trust and habit were not. Two-thirds (66%) of the current SF passengers intend to shift to other transport modes once aMoD is available; 31% of the current SF market share could be lost to aMoD and 20% to conventional driving. More than half of the current most-traveled air passengers intend to use aMoD as their main transport choice. The potential significant shifts in the ground- and air-mode shares revealed in this study may have crucial impacts on airlines, airports, infrastructure, future air/land-use planning, and the travel and hospitality industries.

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