• Journal of Korea Technology Innovation Society
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• v.14 no.2
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• pp.373-404
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• 2011

The purpose of research is to reveal the effect of innovation to enterprises' economic performance. The kind of this study has begun since 1960s and lively progressed then. The fmal theoretical result of the effect of innovation to the performance came positive in compare to the mixed results came out in empirical analysis. There are several reason why empirical results are different to the theoretical results. However the major factor is that of using imperfect statistics and inappropriateness of analysis method. This study used a population (1990~2008) provided from Korean Intellectual Property Office, KIPO for patent and also used a population (1990~2008) provided from Korea Investors Service, KIS for research and development. The contribution of this study is enormous statistical analysis. This study used principal component analysis made innovativeness index for appropriate index sampling, and made effort to minimize the error by using appropriate quantile regression for both to panel analysis and rapidly developed company analysis. Dividing the final results into two parts, the growth and the profit, the effect of technological innovation to the firm's growth is not significant to the panel analysis but heavily significant to the upper 10% of high growth firm. By classifying large company and small and medium enterprise, it is significant to upper 10% of high growth firm for large company and generally significant to small and medium enterprise. But for both lower 10% of low growth firms and 25% of low ranking firms are negatively effected, and for high growth firms larger than the medians are positively effected. Especially for upper 10% of high growth firms are mostly effected. It is more effective to the profitability than the growth. The effect to the profit for every enterprises are not significant, but effected significant to the larger enterprises than 25% of low ranking enterprises especially most effective to the upper 10% of high-profit enterprises. The analysis for the large company, it was significant and positively effected to the upper 10% of high profit enterprises and 25% of low ranking enterprises, but the negatively effected for the low-profit enterprises. For the small and medium enterprises, it is negatively effected for both 10% of low ranking enterprises and 25% of low ranking enterprises. However it is positively effective and significant for the high ranking enterprises than median, especially for those high growth firms. It is meaningful to recognize significancy by quantile, but more implicative result is to finding more effectiveness to the small and medium enterprises than to the large company.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.33-43
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• 2007

Because usually signal controllers on the crosswalks of mid-block provide pedestrian signals every cycle based on the fixed signal plan, pedestrian signals are provided even when there is no pedestrian demand. Consequently, signal is operated inefficiently and this may cause drivels to experience useless delay or violate the signal. Even though recently pushbuttons have been installed to improve the efficiency of pedestrian signal control in the crosswalks of mid-block and the pedestrian safety. they are not spread out national-wide in Korea because of the cost of the pushbutton equipments and the lack of an acknowledgement of the efficiency of the pushbutton. In this study, the effectiveness of the pushbutton on saving the vehicle delay was verified through before and after study in 4 study sites using a traffic micro-simulation model, VISSIM. To evaluate the viability of the pushbutton, a benefit/cost analysis was also performed for 4 study sites. It was found that B/C ratio of all of 4 study sites was greater than 1. The sensitivity analysis for the traffic volume and pedestrian volume were performed to identify the impact of the both volume on the operation of pushbutton. And, a benefit/cost analysis was performed for all scenarios. It was found that when the pedestrian volume is greater than 90ped/h, the pedestrian signal was operated same as the fixed signal plan. That is, there is no benefit of pushbutton at all once the pedestrian volume is greater than 90ped/h. When the pedestrian volume is equal to or less than 90ped/h and the traffic volume is greater than 2,500veh/h, B/C ratio is greater than 1. Also it was found that as traffic volume increases and pedestrian volume decreases, the benefit increases. In this study, the criteria for installation of pushbutton on the crosswalks of mid-block are developed through the sensitivity analysis and benefit/cost analysis. The results of this study may be used as a criteria for expansion of pushbutton system.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.55-80
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• 2009

Technology innovation activity plays a pivotal role in constructing the entrance barrier for other firms and making process improvement and new product. and these activities give a profit increase and growth to firms. Thus, technology innovation activity can reduce the default risk of firms. However, technology innovation activity can also increase the firm's default risk because technology innovation activity requires too much investment of the firm's resources and has the uncertainty on success. The purpose of this study is to examine the effect of technology innovation activity on the default risk of firms. This study's sample consists of manufacturing firms listed on the Korea Securities Market and The Kosdaq Market from January 1,2000 to December 31, 2008. This study makes use of R&D intensity as an proxy variable of technology innovation activity. The default probability which proxies the default risk of firms is measured by the Merton's(l974) debt pricing model. The main empirical results are as follows. First, from the empirical results, it is found that technology innovation activity has a negative and significant effect on the default risk of firms independent of the Korea Securities Market and Kosdaq Market. In other words, technology innovation activity reduces the default risk of firms. Second, technology innovation activity reduces the default risk of firms independent of firm size, firm age, and credit score. Third, the results of robust analysis also show that technology innovation activity is the important factor which decreases the default risk of firms. These results imply that a manager must show continuous interest and investment in technology innovation activity of one's firm. And a policymaker also need design an economic policy to promote the technology innovation activity of firms.

• Journal of Distribution Science
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• v.7 no.4
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• pp.47-56
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• 2009

The purpose of this study is to present an alternative improving the efficient and reasonable of the physical distribution system management is influenced by many factors. Therefore, the study depends on the documentary method and survey method to achieve the purpose of this study. The major components of a physical distribution system are refers to as elements, include warehouse·storage system, transportation system, inventory system, physical distribution information system. The factors used in this study are ① factor of product(quality·A/S·added value of product·adaption of product·technical competitive power to other enterprises), ② factor of market(market channel·kinds of customer·physical distribution share), ③ factor of warehouse·storage(warehouse design·size·direction·storage ability·warehouse quality), ④ factor of transportation(promptness·reliability·responsibility·kinds of transportation·cooperation united transportation system·national transportation network), ⑤ factor of packaging (packaging design·material·educating program·pollution degree measure program), ⑥ factor of inventory(ordinary inventory criterion·consistence for inventories record), ⑦ factor of unloaded(unloaded machine·having machine ratio), ⑧ factor of information system (physical distribution quantity analysis·usable computer part), ⑨ factor of physical distribution cost(sales ratio to product) ⑩ factor of physical distribution system(physical distribution center etc). The implication of this study can be summarized as follows: ① In firms that have not adopted a systems integrative approach, physical distribution is a fragmented and often uncoordinated set of activities spread throughout various functions with function having its own set of priorities and measurements. ② The physical distribution is recognized as more an important strategic factor than a simple cost reduction factor, ③ It can be used a strategic competition tool to enterprise.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.517-534
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• 2021

Hydrogen fuel is emerging as an new energy source to replace fossil fuels in that it can solve environmental pollution problems and reduce energy imbalance and cost. Since hydrogen is eco-friendly but highly explosive, there is a high concern about fire and explosion accidents of hydrogen fueled vehicles. In particular, in semi-enclosed spaces such as tunnels, the risk is predicted to increase. Therefore, this study was conducted on the applicability of the equivalent TNT model and the numerical analysis method to evaluate the hydrogen explosion pressure in the tunnel. In comparison and review of the explosion pressure of 6 equivalent TNT models and Weyandt's experimental results, the Henrych equation was found to be the closest with a deviation of 13.6%. As a result of examining the effect of hydrogen tank capacity (52, 72, 156 L) and tunnel cross-section (40.5, 54, 72, 95 m²) on the explosion pressure using numerical analysis, the explosion pressure wave in the tunnel initially it propagates in a hemispherical shape as in open space. Furthermore, when it passes the certain distance it is transformed a plane wave and propagates at a very gradual decay rate. The Henrych equation agrees well with the numerical analysis results in the section where the explosion pressure is rapidly decreasing, but it is significantly underestimated after the explosion pressure wave is transformed into a plane wave. In case of same hydrogen tank capacity, an explosion pressure decreases as the tunnel cross-sectional area increases, and in case of the same cross-sectional area, the explosion pressure increases by about 2.5 times if the hydrogen tank capacity increases from 52 L to 156 L. As a result of the evaluation of the limiting distance affecting the human body, when a 52 L hydrogen tank explodes, the limiting distance to death was estimated to be about 3 m, and the limiting distance to serious injury was estimated to be 28.5~35.8 m.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.