Passengers' self-protective intentions while using ride-hailing services during the COVID-19 pandemic

Career resilience of the tourism and hospitality workforce in the COVID-19: The protection motivation theory perspective

“…The PMT is widely applied in the domain of health behavior and has a strong ability to predict individuals' intentions towards protective behavior ( DeFranco & Morosan, 2017 ). In particular, PMT has been applied to explore a variety of health-related behaviors, such as cancer-preventive behaviors ( Zare Sakhvidi et al, 2015 ), sun-protection behaviors ( Lowe et al, 2000 ), SARS preventive behaviors ( Jiang et al, 2009 ), or even preventive behaviors during the Covid-19 crisis ( Nguyen-Phuoc, Su, Dinh, Newton, & Oviedo-Trespalacios, 2022 ; Rad et al, 2021 ). Floyd, Prentice-Dunn, and Rogers (2000) argued that PMT could be applied to evaluate any kind of threat for which an individual can take adequate preventive measures.…”

Investigating changes in travel behavior over time in response to the COVID-19 pandemic

“…Lyu (2021 ) found females generally are more likely to feel unsafe in ride-hailing environments, which could lead to a gender gap in using these services. Nguyen-Phuoc, Su, Dinh, Newton, and Oviedo-Trespalacios (2023 ) showed that passengers’ perceived risk of COVID-19 substantially influenced their self-protective behavior toward ride-hailing services. Females usually perceive higher risk than other genders in using shared mobility; hence, they are more likely to avoid shared mobilities at the time of a virus outbreak ( Chauhan et al, 2021 , Hotle et al, 2020 ).…”

Understanding the motivational mechanisms behind the usage frequency of ride-hailing during COVID-19 pandemic

“…A study conducted in Chicago revealed a substantial decline in the number of ride-hailing trips when compared to those using private cars during the COVID-19 pandemic ( 36 ). Nguyen-Phuoc et al ( 38 ) concluded that self-efficacy has the most significant influence on self-protective behaviors among ride-hailing passengers during the COVID-19 pandemic. According to the regression results of this study, it can be concluded that the travelers' usage frequency of ride-hailing services is highly correlated with the following seven factors: ATT, SOC, TRU, AGE, INC, PRIVATE, and LOC.…”