Chinese Ride-Hailing Drivers' Adoption Intention of New Risk Visualization System: A Questionnaire Analysis Based on the Improved UTAUT2 Model Southeast University

Format:

Book

Conference/Event

Author/Creator:

Zhang, Jiayan, author.

Contributor:

Li, Linheng

Pan, Yan

Qu, Xu

Ran, Bin

Conference Name:

2024 International Conference on Smart Transportation Interdisciplinary Studies (2024-12-13 : Nanjing, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

Advanced Driver Assistance Systems (ADAS) have achieved significant progress worldwide, with the primary goals of enhancing driving safety, improving operational efficiency, and supporting vehicle automation. These systems are increasingly dependent on intelligent connected technologies, which enhance drivers' awareness and capacity to recognize and respond to potential road hazards in real-time. Within ADAS, risk visualization systems have become especially crucial, as they provide immediate alerts, thereby promoting safer driving behavior and enabling drivers to make more informed decisions on the road. This study expands upon existing frameworks by investigating the adoption of advanced risk visualization systems among Chinese ride-hailing drivers through an improved Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The improved model introduces two novel constructs: Technology Trust and Perceived Risk, addressing critical gaps in understanding safety-critical technology adoption. Using a structured questionnaire, data were collected from 774 Chinese ride-hailing drivers, focusing on elements such as performance expectancy, ease of use, available support, pricing value, trust in technology, and perceived risk. Additionally, the study assesses how factors like age, gender, years of driving experience, and familiarity with technology may moderate these adoption intentions. The results reveal that facilitating conditions and price value have a strong positive effect on adoption intentions, while perceived risk discourages adoption. While demographic factors such as age, gender, and driving experience exert less influence, they remain statistically significant. Based on these findings, this study proposes practical strategies to enhance adoption, including improving technical support, offering targeted training, implementing appealing pricing strategies, and strengthening risk management. These strategies aim to mitigate barriers to adoption and foster trust, promoting broader adoption of risk visualization systems to advance safety and efficiency in the ride-hailing industry

Notes:

Vendor supplied data

Publisher Number:

2025-01-7122

Access Restriction:

Restricted for use by site license