• Journal of Information Technology Services
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• v.11 no.2
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• pp.49-68
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• 2012

The purpose of this study is to analyse the country image, the pre-assessment, and the usage intention about overseas internet shopping mall service in china and how these factors are related to one another according to internet shopping mall using experience. And this study divided the country image for internet shopping mall service into two components : general country attribute and general service product attribute. In this study it is found that the country image of international internet shopping service is directly related to the pre-assessment, and the pre-assessment is related to usage intention especially in case that chinese consumer has a lot of internet shopping mall using experience. In the other case, the general country attributes affect the general service product attributes but the general service product attributes don't have any relationship with the pre-assessment. For a successful international internet shopping mall service business in China, marketer should recognize that it is important to formulate the policy extending the internet shopping mall experience as well as using the country image.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.8
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• pp.1396-1405
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• 1997

This study investigated country-of-origin effects by comparatively analyzing consumer attitude toward country-of-origin of imported apparel according to apparel product attributes. Fishbein attitude model was used. The effects of consumer characteristics such as attitude of consumers toward general imported apparel and demorgraphic variables on consumer attitude toward country-of-origin were also identified. Italy, U.S.A, Japan, Hong Kong, Korea were used as country of origin. Data were obtained from male and female subjects(total 570) aged mostly 20's. Statistical analysis showed: 1) Apparel product attributes were classified into 3 factors, expressive, instrumental and brand, which are the order of importance for purchasing. 2) Consumer indicated more favorable attitude toward 'made in 'Italy' nd made in 'Korea' in each attribute factor. 'Made in Korea' roducts were evaluated highest in expressive attribute factor but less favored than 'made in Italy' n brand attribute factor. 'Made in U.S.A and made in Japan' were evaluated favorable in instrumental factor, whereas 'made in Hong Kong' had the least favorable attitude in every attribute factor. 3) The uniqueness and good quality of imported apparel appeared to be the most strong variable in predicting consumer attitude toward each country-of-origin. 4) The attitude toward country of origin was different according to sex and age.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.29-40
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• 2024

Recently, the technology of autonomous driving, one of the core of the fourth industrial revolution, is developing, but sensor-based autonomous driving is showing limitations, such as accidents in unexpected situations, To compensate for this, HD-map is being used as a core infrastructure for autonomous driving, and interest in the public and private sectors is increasing, and various studies and technology developments are being conducted to secure the latest and accuracy of HD-map. Currently, NGII will be newly built in urban areas and major roads across the country, including the metropolitan area, where self-driving cars are expected to run, and is working to minimize data error rates through quality verification. Therefore, this study analyzes the spatial relationship of reference objects in the attribute structuring process for rapid and accurate renewal and production of HD-map under construction by NGII, By applying the attribute input automation methodology of the reference object in which spatial relations are established using the library of open source-based PyQGIS, target sites were selected for each road type, such as high-speed national highways, general national highways, and C-ITS demonstration sections. Using the attribute automation tool developed in this study, it took about 2 to 5 minutes for each target location to automatically input the attributes of the spatial relationship reference object, As a result of automation of attribute input for reference objects, attribute input accuracy of 86.4% for high-speed national highways, 79.7% for general national highways, 82.4% for C-ITS, and 82.8% on average were secured.