Understanding Driver Acceptance of Ergonomics and Fatigue Warning Applications Among Low and High Physical Discomfort Groups
Source abstract
Abstract
Road accidents related to long-distance driving remain a major safety concern, primarily driven by fatigue and musculoskeletal discomfort. This study investigates the acceptance of driver assistance technologies, specifically seat adjustment and fatigue warning applications using the Technology Acceptance Model (TAM). Data were collected from 1600 drivers in Thailand. Participants were categorized into low-discomfort (n = 785) and high-discomfort (n = 815) groups based on the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ). Multi-group Structural Equation Modeling (SEM) demonstrated that the TAM framework adequately explains technology acceptance in both groups. However, significant differences in the underlying mechanisms were observed. For drivers with lower discomfort levels, attitude toward technology played a more prominent role in shaping usage intention. In contrast, perceived usefulness emerged as the dominant factor for drivers experiencing higher musculoskeletal discomfort. These findings indicate that physical discomfort functions as a critical moderator in technology acceptance. Practically, the results highlight the need for driver assistance systems that prioritize ergonomic effectiveness to enhance adoption among physically strained users.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ergonomics and Musculoskeletal Disorders · Human-Automation Interaction and Safety · Musculoskeletal pain and rehabilitation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Industrial Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand
School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand
Institute of Research and Development, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
Program of Systems Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand
School of Electronics Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand
Funding
This study received financial support from Suranaree University of Technology (SUT), Thailand Science Research and Innovation (TSRI), and the National Science, Research and Innovation Fund
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