• Journal of Distribution Research
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• v.17 no.5
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• pp.129-146
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• 2012

Recently, Korea became the 7th country in the world which has got into the 20-50 clubs that means the population is 50 million and per capital income is $20,000. From the view point of the retail industry, it suggests that Korea should have its own self-sufficient market by itself. With abundant labor and increased disposable income, it made the consumer's needs change. Responding to the change, retail and F&B oriented retail malls are now starting to add culture, art and entertainment facilities in the configurations. Such complexity and variety of the shopping malls became trendy and many shopping complexes are scheduled to open in the near future across the country. Due to above reasons, it became the common trend to develop shopping complex all over the cities now. However, the history of the shopping mall in Korea is much shorter than developed countries such as America and Japan. Thereby, a lot of problems, trial and error have occurred in the process of developing and operating them. If development of shopping complex failed, it would return lots of damages to the stakeholder. Therefore, the corporations should develop the mall properly and government might support positively. In this study, we would like to propose on how all the mall should be developed and well managed and what are the ways for the vitalizing factors of the shopping complex after benchmarking other shopping mall cases. Through the case study, we realized that the most crucial factors for vitalizing shopping complex were interior design, merchandising and how well they operate the mall. In case of the failed shopping mall, developers sell each store to individual proprietors and never take care of them after they get the profit, which make it hard to have integrated marketing strategies. That causes the overall slump of the mall. Corporations developing the mall should operate it as well, so that it could be possible to make the mall consistently well managed and promoted. There is a certificate for the shopping mall expert in The States and Japan. However, we do not have this kind of certificate. In fact, if we judge the capability of a person who is involved in the shopping mall industry, we usually measure how many years they stick to the same industries and that is not equally the same as their competence. Therefore it is necessary to organize "Shopping Mall Associate" and introduce shopping mall license for the mall expert. Due to retail trends, we can easily see a lot of shopping facilities all over the cities but not every mall is able to be successful. We think it's essential that the government should certify the malls which are qualified for the design, merchandising and proficiency of the operation. For the qualified mall, the government could confer a benefit on the company such as reducing corporation taxes. In multi-complex shopping mall it is possible to make convenient for customers. However, if a mall failed to succeed, it would be disaster. To build a shopping complex, developers should invest huge money even take out loan so that many people would be connected to the project, which may affect their whole financial conditions. In addition, only qualified corporation should develop and operate shopping complex and the government must support and aid the developers in order to make a better shopping environment in which customers might be happy during their shopping experience.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.67-80
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• 2022

This study was conducted to derive policy measures such as fostering and supporting by examining the actual conditions of domestic startups. The subject of this study was the start-ups located in Seongnam-si, where Pangyo Techno Valley, which is the highest-level innovation cluster in Korea and is evaluated as a start-up mecca. Startups were defined as startups under 7 years old based on new technologies such as IT, BT, and CT, and the subjects of the study were selected. This can be seen as a step forward from previous research in that it embodies the concept of a startup that was previously abstract in a quantitatively measurable way. As a result of the analysis, about 94% of startups are distributed in the so-called "Death Valley" growth stage, and startups above scale-up, which means full-scale growth beyond BEP, account for about 6%. appeared to be occupied. He cited the problem of start-up funds as the biggest difficulty in the early stages of startups, and cited the loan evaluation method that prioritizes sales or collateral in raising funds as the biggest problem. In addition, start-ups rated the access to private investment capital such as VC, AC, and angel investors at a low level compared to policy funds, which are public funds. Most startups showed a lot of interest in overseas expansion, and they chose matching overseas investors such as overseas VCs as the biggest support for overseas expansion. The overall competitiveness in the overseas market was 49.6 points, which is less than 50 points out of 100, indicating that the overall competitiveness was somewhat inferior. It was analyzed that public support and investment in overseas sales channels (sales channels, distribution networks, etc.) should be prioritized along with enhancement of technological competitiveness in order for domestic startups to increase their competitiveness in overseas markets as well as in the domestic market.