PU and PEU is a strong predictor of BI,
this paper attempts to explore students’ behavior regarding the use of ride-sharing services by extending the “Technology Acceptance Model.”
the study focuses on determining the moderating role of perceived risk between the proposed relationships.
findings of this research are useful for ride-sharing service providers and policymakers who can pro- mote the services among students by reducing the perceived risks and promoting the environmental benefits of ride-sharing.
he first recommendation is to target the students of other cities as well.
future researchers can conduct the same research by adopting a mixed-method approach, i.e., quantitative and qualitative.
it is recommended to study the same research model in two different countries and conduct a comparative analy- sis.
Fourth, other mediating and moderating factors can also be added to extend the model further and identify predictors of ride-sharing behavior.
Such as govern- ment support, inflation, green values, and price value can be incorporated as moderators, and consumers’ attitudes can be used as a mediator.
uture researchers can increase independent variables. For instance, the research framework can add constructs of the “Unified theory of acceptance and use of technology” (performance expectancy, hedonic moti- vation, social influence, facilitating conditions, and effort expectancy).
So, when students observe that ride-sharing services are easy to use, accessible, reliable, and convenient for daily use, they will prefer ride-sharing services instead of local transportation.
This means that students’ concern for the environment is not a strong predictor of their BI to use ride-sharing services.
It means that knowledge and awareness about the environment strongly impact students’ BI to use ride-sharing services.
When students have enough knowledge about the environment and are aware of the deteriorating facts, they will ultimately participate in eco-friendly activities that might reduce pollution.
As ride- sharing services help reduce travel expenses, pollution, and traffic (Wang et al., 2019; Wang et al., 2020). So, students will depict a positive BI towards a sustainable transporta- tion system.
It means that when students are highly concerned about the risks of ride- sharing services so, despite environmental knowledge, they will depict negative behavioral intention because of the risk
PR can affect stu- dents’ BI.
the benefits and its convenient process influence
a students’ BI regarding ride-sharing services.
application of ride-sharing services should be user-friendly.
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