Design aesthetics play a crucial role in product design. Stakeholders expect to develop highly valuable premium products by improving the design aesthetics of products. Nevertheless, the question of how to evaluate the value of design aesthetics has not been fully addressed. In this study, the effects of design aesthetics on the evaluation of the value of a product were investigated through a strictly controlled experiment in which the neural responses of the participants were measured. Forty participants completed the design aesthetics experiment in a laboratory setting. Images of products were divided into two categories: those representing high– and low–design-aesthetic stimuli. Both types of images were labeled with the same price. Overall, the images representing high design aesthetics elicited smaller N100 and lower P200 amplitudes than did the images representing low design aesthetics. This finding indicates that low design aesthetics attracted more attention than high design aesthetics did and that high design aesthetics triggered positive emotions. Low–design-aesthetic products elicited a larger N400 amplitude. This finding reveals the inconsistency between labeled and expected prices. The present study indicates that the N400 component can be used as an indicator for measuring the perceived value of a product in a future product design study. Our study provides event-related potential indicators that can be easily applied in decision making for measuring the perceived value of a product’s design.

Mobile devices are becoming an indispensable part of the daily lives and learning habits of older adults with the easy access of the Internet. It enhances the connection between old users and online education, which supplies an approach to cultivate them with innovative concepts and entrepreneurship of education. However, the complicated navigation of information systems (IS) confuses older adults, and gets them disoriented in searches of information, in addition, to influencing online activities for older adults. This study aims to investigate what kind of navigation of IS is suitable for older adults. A 2 × 2 (2 factors, 2 levels) mixed experimental design was employed. The two factors were, respectively, cognitive load (CL) and navigation structure (NS). A sample of 40 older participants (mean age = 64.37, SD = 4.03) performed online learning tasks in terms of innovative concept using linear hierarchical or mixed NSs under different time pressures. The results showed that linear hierarchical navigation is more appropriate for the elderly when learning and generating innovative concepts on smartphones, as the interaction between CL and NS exists. Overall, the findings combined suggest that the linear hierarchical NS, compared to mixed hierarchical navigation, obtained better usability in terms of task efficiency, CL, and subjective ratings. The findings can provide theoretical support for designers to design and develop mobile websites for older adults.

The emotional experience of the driver is influenced by the design of the in-vehicle interaction interface. User experience journey maps are commonly used by designers to reveal interface design pain points and refine user needs, and further studies are required to effectively characterize and quantify user emotional needs. This study provides a method for accurately presenting a driver’s emotional experience through a human–machine interface using Kansei engineering and user experience journey. Firstly, the semantic difference approach was used to match the relationship between user behavioral touchpoints and Kansei imagery words of the interface. And then the emotional quantification curve was built to generate an average value for Kansei imagery word evaluation. Finally, design pain points were identified and iterative design was carried out. A validation study was implemented to ensure the method’s validity. The study demonstrated that a quantitative map of user emotional experience could efficiently quantify and depict the findings of emotional quantification. This method enables designers to accurately recognize user needs while also facilitating product iterations.

Bamboo oriented strand boards (BOSB) are very suitable for application in construction structures because of their excellent mechanical properties. This research investigated the shear performance of bamboo I-beams composed of BOSB to verify the structural performance of I-beams. Short beam shear tests and uniform vertical load capacity tests were performed to investigate the effects of various factors on the properties of bamboo I-beams. The results showed that shear bearing capacity and uniform vertical load capacity of bamboo I-beams exceeded the requirements for performance-rated I-Joists in APA PRI-400-2021. The shear bearing capacity, stiffness, and failure types of bamboo I-beams were determined by the web materials, flange–web joint type, and beam depth. Increasing the bamboo I-beam depth without changing the flange dimensions had no significant effect on the shear bearing capacity and stiffness of bamboo I-beams. The shear bearing capacity and stiffness of wooden orientated strand board webbed I-beams were almost half of those of bamboo I-beams with the same depth. The shear bearing capacities of specimens calculated based on the shear bearing capacity calculation formula of I-beams recommended in the Canadian standard were reasonably close to the experimental results. The uniform vertical load capacity of bamboo I-beams gradually decreased as the depth of the bamboo I-beam increased from 300 mm to 500 mm.

BACKGROUND: Larger dual screens have been widely used during office work and their biomechanical exposure should be explored. OBJECTIVE: To investigate the biomechanical effect of two dual screen layouts on neck-shoulder muscle activity and the variability of head-neck posture in computer users. METHODS: A preliminary study of the user-preferred dual screen angles was carried out in V-shaped and L-shaped layouts. Twenty healthy participants aged 19 to 26 years were recruited and assigned to perform reading, typing, and searching tasks for 30 minutes in both workstation layouts. Electromyography was measured at bilateral cervical erector spinae (CES), sternocleidomastoid (SCM), and upper trapezius (UT). The head-neck lateral bending, rotation, and flexion angles were recorded. The visual analog scale (VAS) was used to evaluate visual strain. RESULTS: The muscle activity at the left UT and right CES sites when using the V-shaped layout was significantly higher than the L-shaped. There were significant differences in head-neck rotation and flexion angles between the two layouts in reading and typing tasks. In the searching task, there was no significant difference in the head-neck rotation and flexion angles between the two layouts. The visual strain score was significantly higher in the V-shaped layout. CONCLUSION: The CES and UT muscles displayed higher levels of activation while using the V-shaped layout in comparison to the L-shaped layout. The head-neck rotation and flexion angles differed due to varied types of work when using V-shaped and L-shaped layouts.

Augmented Reality Head-Up Displays (AR HUDs) have been shown to enhance drivers’ performance and road safety. However, with the growing attention to trust in automated driving systems, excessive reliance on automation may lead to complacency and dependency. This study therefore aimed to examine how drivers with different levels of experience depend on AR warning messages under varying environmental conditions (daytime vs. nighttime urban driving) and to propose strategies for optimizing AR warning interaction design. A before-and-after comparative experimental design was employed. Participants completed driving tasks involving a typical urban hazard—pedestrians suddenly running into the road—under two conditions: (1) without AR warning messages and (2) with an induced random AR warning failure in an AR message environment. The perceived time-to-pedestrian values were analyzed to quantify driving dependence. Participants were divided into experienced and novice driver groups, and the effects of driving experience and lighting condition were examined. Objectively, both experienced and novice drivers’ dependence on AR warning messages was primarily influenced by the driving environment. Under high-load conditions such as nighttime driving, both groups maintained higher attention and exhibited minimal dependence on AR warnings. Under lower-load daytime conditions, dependence varied by driving experience: experienced drivers remained self-reliant due to ingrained driving habits and situational awareness, while novice drivers displayed increased relaxation and dependence on AR cues. Subjectively, drivers’ perceived dependence and anticipation of AR warnings correlated more strongly with the perceived intrusiveness of the AR system than with its effectiveness. These findings suggest that dependence on AR HUD warning messages is a complex interaction between environmental load, user experience, and perceived system intrusiveness. To mitigate automation complacency, future AR HUD design should tailor warning strategies according to user experience levels and driving context. The study provides practical insights for optimizing AR interaction design and highlights directions for future research to address additional urban driving risks.