Technology anxiety and social influence towards intention to use of ride-hailing service in Indonesia

Inan, Dedi Iskandar; Hidayanto, Achmad Nizar; Juita, Ratna; Andiyani, Kemala; Hariyana, Nabilla; Tiffany, Priscilla; Pertiwi, Teresa Prima Tangis; Kurnia, Sherah

doi:10.1016/j.cstp.2022.05.017

Cited by 11 publications

(9 citation statements)

References 39 publications

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“…Second, as predicted, our study supported the positive association of identification with intention to use ride-hailing (H2), which is consistent with previous findings in the literature (Inan et al ., 2022; Liu et al ., 2022; Miocevic et al ., 2022; Prentice et al ., 2019). Third, emotional support significantly and positively influenced the customers' intention to use ride-hailing services (H3).…”

Section: Discussionsupporting

confidence: 92%

“…Miocevic et al (2022) found that social identification influences the adoption of food in a group. Inan et al (2022) and Liu et al (2022) revealed that identification influences the intention to use ridehailing services. As the people in a social network tend to self-identify ways that are The influence of social drivers consistent with the beliefs and actions of others around them, it stands to reason that if a large percentage of its user in social network communities feel comfortable using ride-hailing services, others would likely do the same.…”

Section: Theoretical Background Proposed Research Model and Hypothese...mentioning

confidence: 99%

“…Internalization refers to embracing the induced conduct consistent with the value system (O' Reilly and Chatman, 1986). The information received from others, if found useful is internalized, which further is reflected in an individual's behavior (Inan et al, 2022). Individual behavior driven by internalization encourages the individual to adhere to the expectations of others, resulting in intention to use (Jung et al, 2022;Pham et al, 2021).…”

Section: Theoretical Background Proposed Research Model and Hypothese...mentioning

confidence: 99%

“…more appealing to consumers (Li et al ., 2023; Mosseri, 2022). Mobile applications, booking convenience, payment transparency and promotional incentives make the ride-hailing model successful (Inan et al ., 2022). Apart from abovementioned factors, ride-hailing companies integrate information technology with data to provide excellent customer service (Aw et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

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The influence of social drivers on using ride-hailing services

Rana

Singh

Parayitam

et al. 2023

MIP

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PurposeThe pandemic has severely affected sharing economy businesses specially ride-hailing services due to high levels of human-touch points. This research investigates the impact of COVID-19 infodemic, identification, and emotional support on intention to use ride-hailing. The authors further examine the moderating effects of internalization, compliance, social currency and informational support in the proposed conceptual model.Design/methodology/approachThe data were collected from 412 respondents from Delhi in India, and hypothesized relationships were tested using hierarchical regression.FindingsThe results indicate that COVID-19 infodemic has a negative association with intention to use ride-hailing. Identification and emotional support show a positive association with intention to use ride-hailing. The results also support internalization and compliance as moderators between infodemic, identification and intention to use ride-hailing. Further, social currency and information support moderate the relationship between emotional support and intention to use.Originality/valueThis is the first research, which adds to the expanding literature on ride-hailing, especially during the post-pandemic period of “new normal”.

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Section: Discussionsupporting

confidence: 92%

Section: Theoretical Background Proposed Research Model and Hypothese...mentioning

confidence: 99%

Section: Theoretical Background Proposed Research Model and Hypothese...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The influence of social drivers on using ride-hailing services

Rana

Singh

Parayitam

et al. 2023

MIP

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“…Similar to the peer influence in the context of social environment influence obtained by others, external influence in a similar vein, is defined as influence acquired by individuals for their intention to adopt a new technology because of other factors such as social, culture, economics, politics (Chang et al, 2014;Inan et al, 2022). In this context, economic influence is perhaps the most determinant factor that affects the adoption intention.…”

Section: Relationship Between External Influence and Adoption Intentionmentioning

confidence: 99%

How personal, technical, social environments affecting generation Z to utilise video-based sharing platform in learning process during crisis?

Inan¹,

Hidayanto

Juita³

et al. 2023

RPTEL

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In a crisis such as COVID-19 that struck the world in 2019, social and community activities are restricted, including in-person classes. On the one hand, these restrictions are aimed as a precautionary measure against the virus spread; on the other hand, this could lead to a lost generation without an educational process. Notwithstanding this, online learning through a video-sharing platform is envisaged as the best way to keep learning in this particular situation. However, students have their learning style preferences. While a video-based sharing platform is seen as the most representative way of facilitating self-directed learning, understanding the motivations driving the adoption is crucial. This paper investigates technical, social, and personal environments that motivate generation Z to utilise this tool for self-directed learning, employing Social Cognitive Theory (SCT) as the theoretical lens. A total of 251 survey responses from this cohort were collected and analysed with a structural equation modelling approach. The findings reveal that perceived usefulness and content quality, peer influence, and self-efficacy and outcome from three perspectives, respectively, determine the adoption intention substantially by 67.1%. These findings provide several important implications for video-sharing platform acceptance in terms of both research and practice. Limitations and future research directions are also discussed.

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