Determinants of consumers’ continuance intention to use dynamic ride-sharing services

Chen-ming

2022

Front. Psychol.

BackgroundThe primary objective of this study is to ascertain whether the Expectation Confirmation Model can be expanded by external variables including computer anxiety, social interaction, and self-efficacy to better understand the intention to continue using online learning systems in the post-pandemic era among vocational college students. Moreover, this research argues that the intention to continue using online learning systems among students may be gender-sensitive.MethodsThe researchers surveyed 482 students from eight vocational colleges in Jiangxi Province using a structured questionnaire. Partial Least Squares Structural equation modeling is used to verify the research model.ResultsThe outcomes demonstrate that the proposed model adequately explains the continuous use intention for online learning systems at a 76.6% confidence level. All of the newly introduced variables in the ECM are shown to be significant and relevant to explicate continuous use intention. Our survey results show that gender differences in intention to continue using online learning systems exist objectively, but this difference is not a natural difference.ConclusionThis research fills a void in the current literature on online learning and probes into how learning may be made more long-lasting in intricate environments.

Section: Discussioncontrasting

confidence: 83%

Section: Expectation Confirmation Modelmentioning

confidence: 97%

Antecedents of continuance intention in online learning systems among vocational college students: The moderating effect of gender

Chen-ming

2022

Front. Psychol.

“…Demographic factors affect continuance intention and behavior [ 53 ]. For example, among drivers who have different jobs, the continuous use of dynamic transport-sharing services is considered a pro-environmental and pro-social behavior [ 54 ]. Williams-Nwagwu et al [ 55 ] found that the user’s age differentiates satisfaction with media technology.…”

Section: Methodsmentioning

confidence: 99%

Motivations Influencing Alipay Users to Participate in the Ant Forest Campaign: An Empirical Study

Habes

2022

IJERPH

As one of the largest payment platforms in China, Alipay, launched a green behavior project called Ant Forest. The purpose of taking this initiative by Alipay is to make the world greener. This mobile application has motivated many users to plant millions of trees. However, minimal studies have been conducted to empirically disclose the factors that motivate Alipay users to participate in Ant Forest. A mixed-method approach is used to examine the factors influencing Alipay users to participate in Ant Forest and the level of satisfaction they got from it. The qualitative method was carried out through a structured questionnaire from 400 Alipay users and qualitative data from 20 users who have applied to Ant Forest and successfully planted trees. Additionally, alongside the mixed method employed to rationalize the relationship highlighted, a multiple regression model was employed to predict the value of a dependent variable (level of satisfaction) based on the value of several independent variables (namely, number of years engaged with Ant Forest activities, age, gender, profession, and education). The empirical results show that intrinsic motivations (enjoyment, social interaction, fulfilment, altruism) and extrinsic motivations (external rewards, competition) influence Alipay users to participate in the Ant Forest project. Further insights are presented in the concluding section for all stakeholders for environmental sustainability among the users of Alipay.

“…Previous studies examined various factors that influence shared mobility use, divided into external and internal types. External factors are exogenous to shared mobility ridership, such as socio-demographics (e.g., gender, age, income, education, and car ownership) [ 12 ], attitudes [ 14 ], and weather [ 15 ]. Internal factors include trip-related variables (e.g., trip purpose, trip distance, and time of day) [ 7 ] and mode-specific attributes (e.g., travel time, time spent searching for parking, and waiting time) [ 16 ].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China

Zhang

Shao

et al. 2022

IJERPH

Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bike sharing. Then, latent class analysis is used to divide the population in terms of their attitudes toward shared mobility. Nested logit models are applied to compare travel mode choice behavior during the two periods. The results suggest that shared mobility has the potential to avoid the high transmission risk of public transport and alleviate the intensity of private car use in the COVID-19 context, but this is limited by anxiety about shared spaces. As the perceived severity of the pandemic increases, preference for ride hailing and ride sharing decreases, and a price discount for ride hailing is more effective than that for ride sharing at maintaining the ridership despite the impact of COVID-19. These findings contribute to understanding the change in travel demand and developing appropriate strategies for shared mobility services to adapt to the pandemic.