• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.291-299
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• 2021

In 2019, SUV sales surpassed sedans in the domestic sales market with phenomenal domestic sales. The strength of SUVs around the world is expected to continue in the future. South Korea's K-company aggressively launched small SUVs in the SUV market. Its simple lineup is recognized as a brand image, not as a SUV. It is time to evaluate this. Therefore, it influences the purchasing decisions of potential customers and buyers of small SUVs through the evaluation of design images of small SUVs in Korea. Rather than the functional properties of the SUV model, it is purchased by emotional characteristics, brand symbolism, and image. Subconsciousness of the purchasing psychology of the end consumer was used by metaphor extraction techniques. Customers wanted to study the evaluation of small SUV design images that fit their needs. We wanted to see if consumers who intend to purchase or purchase small SUVs in Korea had a connection with the image of design of small SUVs in Korea. The conclusion of the study was extracted through ZMET, a metaphor extraction technique, with the latent consciousness of the primary ambiguous message from the consumer's feeling and representation of the image. Therefore, based on the results of this study, we hope that the images presented in SUVs in the future will be used as a design guide in the development of small SUVs to influence customer thinking and behavior.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.152-166
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• 2022

This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.