• Journal of Korean Public Health Nursing
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• v.7 no.2
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• pp.53-66
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• 1993

By this time, a few of previous studies of factors related to separation from their jobs and job satisfaction only have dealt with the separation rate. the cause of separation and related factors that induce job satisfaction and incentive factors, the actualities of morale some suggestions for reduction of the separation rate. This study is attempted to determine factors that have effect on job satisfaction of national hospital nurses. and to proide information and materials for the development of the administration of nursing through the appreciation of factors influencing on job satisfaction between isolated ward nurses and general ward nurses working at national hospitals. 185 nurses of national hospitals responsed th this study, and were divided into two groups. Group 1: 57 nurses working at isolated wards for tuberculosis patients and Group 2 : 128 nurses at general wards. Relevant data were collected from August, 5, 1992 through August 20, 1992. The questionnaire consisted of 8 genalized items and 4 items concerning job satisfaction. The collected data were processed with SPSS, and the relationship among vaviables was analyzed by means of $X^2-test$, Pearson Correlation, Multiple Regression. The results of this study are as follows: 1. There is no significant difference between two groups in terms of generalized items. Age distributions show $44.3\%$ under the category of less than 34. and $55.7\%$ under the category more than 35, $19.3%$ was single and $74.6\%$ was married respectively. 2. $79.4\%$ of the nurses have the desire to have in-service education under the satisfactory physical environments such as welfare system, accommodating structures and facilities, instruments or management systems of the hospital, but under the category of unsatisfactory circumstances, $60.3\%$ have the intention of having in- service education. The concern in terms of in-service education shows statistically significant difference between two groups $(X^2=8.85,\;p<0. 05)$. This result accepts the hypothesis that good physical environments could intensify interests in service education. 3. The extent of satisfaction related to psychological environments is heightend according to good physical environments. In result, the hypothesis that the extent of satisfaction in terms of physical environments could raise satisfaction about psychological environment is accepted. 4. In the light of the extent of satisfaction about physical environments, $33.3\%$ of isolated ward nurses are satisfied with physical environments, but only $11.7\%$ of general ward nurses are satisfied. $(X^2=10.88,\; p<0.01)$. This result shows that the satisfaction degree about phusicalenvironments of isolated war nurses was higher than that of general ward nurses in spite of high physical and psychological risks due to exposure to infection. Consequently. the hypothesis was rejected that the satisfaction degree about physical environments would be lower in isolated ward nurses than in general ward nurses. 5. The fact that $87.7%$ of isolated ward nurses took interest in service education and $53.19\%$ of general ward nurses took interest in service education demonstrats that isolated ward nurse have more interest in service education than gerneral ward nurses. The result shows that the hypothesis is accepted that isolated ward nurses would have mor interests in service education than general ward nurses. 6. In the extent of satisfaction about physical environments such as morale human relationship promotion, there is no significant difference between two groups in terms of statistics. The hypothesis is rejected that satisfaction about psychologic environments would be high in isolated ward nurses than in general ward nurses. In conclusion. factors influencing on job satisfaction are considered to have effect on. another, and also interdisciplinary amelioration of factors accompanied with systematic inter cooperative investigation is necessary.

• Korean Business Review
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• v.17 no.2
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• pp.63-87
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• 2004

To create and maintain comparative supremacy as a strategic tool of business, many organizations have introduced informational technology and system. By using this system, Some companies got a beneficial value for achieving organizational goals but others could not obtain their effectiveness and efficiency. In particular, a lot of organizations that tried to make strategic supremacy with e-commercial trade are under hard condition because of poor profit. It implies that it is essential to identify and analyse the consumer who uses e-commercial trade. This paper, therefore, focusing on internet shopping malls between business and consumer as one of areas of e-commercial trades, shows the difference between consumer expectation and performance. The results of this study are as follows: First, as for the significant difference of influencing factors to consumer satisfactions according to the types of internet shopping malls, there is a meaningful difference in consumer anxiety and internet usefulness, but not in consumer service. Prior to verify the differences in detail on consumer's anxiety and internet usefulness, we examined that there is any difference between expectation and performance. T-test was used for the variants of consumer anxiety and internet usefulness, and its meaningful probability was 0.000, which means that both showed statistically significant difference. Based on the results, we also found that regardless of the types of internet shopping malls, consumer expectation was greater than performance. although the difference between expectation and performance was not equal according to the internet shopping malls. Second, a regression analysis was performed to understand the relation between consumer service, internet usefulness, consumer anxiety, and consumer satisfaction, it was found that consumer service, internet usefulness, consumer anxiety had significantly effected on consumer satisfaction. Third, To verify the relation between consumer satisfaction and repurchase-intentions, intentions to spread out, Pearson correlation analysis was used. it was found that consumer satisfaction had positive effect on both intentions. This study has some limitations because of the shorts of money and time. since the sample of this study was consumers who have ever bought one or more products via internet shopping mall, this sample was appropriate. but the major parts of sample were college students, and the sample size was so small. therefore this results should carefully be generalized. For further study, it is required to select more precise samples and to include more variables.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.