An Investigation of Factors that Influence Passengers' Intentions to Use Biometric Technologies at Airports
This research investigated the factors that influence passengers’ intentions to choose the use of biometrics over other methods of identification. The current study utilized a quantitative research method via an online survey of 689 persons from Amazon ® Mechanical Turk ® (MTurk) and employed structural equation modeling (SEM) techniques for data analysis. The study utilized the theory of planned behavior (TPB) as the grounded theory, while perceived usefulness and perceived ease of use were included as additional factors that could influence individuals’ intentions to use new technology.
The study further assessed the impact of passengers’ privacy concerns on the intentions to use biometrics and investigated how the privacy concerns moderate the influencing factors of passengers’ behavioral intentions. Because of the coronavirus (COVID-19) pandemic that became prevalent at the time of the study, a COVID-19 variable was introduced as a control variable to examine if there were any effects of COVID-19 on passengers' behavioral intentions while controlling for the other variables.
Results showed that for the TPB factors, attitudes and subjective norms significantly influenced passengers’ behavioral intentions to use biometrics, while the effect of perceived behavioral control (PBC) on passengers’ intentions was not significant. The additional factors of perceived usefulness and perceived ease of use did not significantly influence passengers’ intentions. In addition, the hypothesized relationships between privacy concerns and four factors, behavioral intentions, attitudes, PBC, and perceived ease of use were supported, while the relationships between privacy concerns and perceived usefulness and between privacy concerns and subjective norms were not supported.
The examination of the moderating effects found that privacy concerns moderated the relationships between passengers’ intentions and three factors: attitudes, subjective norms, and perceived usefulness. However, because the interaction plots showed that the moderating effects were weak, the effects were not considered to be of much value and were therefore not added to the final model. Results also showed that the control variable (COVID-19) did not significantly influence passengers’ behavioral intentions and passengers’ privacy concerns while controlling for the other variables.
Practically, the study contributed a research model and specified factors that were postulated to influence passengers’ behavioral intentions to use biometrics at airports. Further research would be required to determine additional factors that influence behavioral intentions. Finally, although the moderating effects were not used in the final model, the findings suggest that stakeholders can customize biometric systems and solutions appropriately to cater to passengers’ concerns.
Ph.D. In Aviation Program, Dissertation, Biometrics, MTurk, SEM, Structural Equation Modeling