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

• The Korean Journal of Blood Transfusion
• /
• v.23 no.2
• /
• pp.107-114
• /
• 2012

Background: Leukocyte reduction filters are widely used to prevent transfusion reactions caused by leukocytes in blood components. Commercial filters are not sufficient for removal of leukocytes for prevention of transfusion associated graft-versus-host disease; therefore, irradiation of blood components was performed using expensive equipment. Techniques using an aptamer substituted for antibody have been developed and are available in clinical areas. The purpose of this study is to develop the aptamer filter system and to evaluate its efficiency and the possibility of its clinical application. Methods: Aptamers targeted to CD45 were selected by the Postech Aptamer Initiative. The aptamer filter in which aptamers attached to beads were bound to leukocytes and removed by magnetic field was developed. Filtration of 14 units of leukoreduction-red blood provided by Korean Red Cross Blood Services was performed using aptamer filters. Leukocyte removal rate and red cell recovery rate were evaluated and bacterial culture was performed. Results: After filtration using the aptamer filters, 45.6% of leukocytes were additionally removed and the red cell recovery rate was 92.8%. No growth in the bacterial culture was observed. Conclusion: In order to apply the cell depletion technique utilizing an aptamer to blood filter system, we developed and evaluated the aptamer filter system. Through improvement of the binding efficiency of the aptamer and the filtering process, and application of the various aptamers for other different cells, we suggest that this technique can be applied in the clinical area, such as a substitution for the irradiation process for TAGVHD prevention.

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.191-208
• /
• 2018

This paper focuses on the integration aspect of operators to determine an improvement strategy for the operating system to enhance competitiveness of Busan Port. This Study proposes the following alternatives: valuation standards for the integration of operators, the road map for the integration period, the scope and role setting of integrated operators' participation of Busan Port Authority(BPA), and the separation and linkage North Port and the New Port operators. First, the valuation standards for operator integration should be based on international standards. Additionally quantitative factors such as financial situation, business performance and participating companies' profitability, and the qualitative factors such as management ability, technology, and labor relations should be considered. Second, the timing of North Port's operator integration should be prioritized in the short term in conjunction with the commencement of its phase 2-4, 2-5, and 2-6. The integration of New Port operators should provide a road map for a relatively long-term perspective. Third, the participation of BPA' integrated operators should be considered in terms of publicity as a policy coordinator between terminals and by pursuing the profitability of entering into overseas business by fostering Korean global terminal operators. The scope and role of participation ensures that the experience and technology of the terminal operation business is maximized. Fourth, because physically intergrating the North Port' operator into a single corporate form is difficult, initially establishing a special purpose company to maximize the effect of the integrated operation is necessary. Then, the operators decided to convert to a holding company given the termination of the lease term contract with the State or BPA, and ultimately proposed a merger into a single corporation.

• Journal of Food Hygiene and Safety
• /
• v.36 no.5
• /
• pp.400-406
• /
• 2021

The purpose of this study was to evaluate the microbial contamination level of Korean traditional rice cakes (Garaetteok, Injeolmi, Gyeongdan), as well as manufacturing environment of small-sized businesses in Korea. The contamination levels of total aerobic bacteria, coliforms, and Bacillus cereus in raw materials were 3.76-4.48, 2.21-4.14, and 1.02-1.15 log CFU/g respectively. On the other hand, Escherichia coli was not found. It has been found that the contamination level of total aerobic bacteria, coliforms, and B. cereus in the raw material decreased after the washing process, but it increased again during the soaking and grinding process. However, after the steaming stage, the contamination level increased again during the molding and cooling process, suggesting the need to take cautions in managing cooling water and molded rice cakes in the process. These results suggest that the safe management of cooling water and taking cautions in the drying process after steaming of rice cakes are necessary for controlling cross-contamination. No E. coli was detected during the manufacturing process involving all tested rice cakes. The microbial contamination level of manufacturing environment such as rice grinder and rice cake forming machine was high. Therefore, in terms of food safety strategy, it is necessary to consider introducing systematic cleansing and disinfection procedure to processing equipment and environment for the sake of reducing microbiological risks.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.99-122
• /
• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.13 no.6
• /
• pp.1-14
• /
• 2018

As interest and consumption of luxury goods have become more popular, luxury goods market is growing rapidly. Consumers can acquire psychological satisfaction with material abundance by purchasing and using luxury goods. Also, from the view of corporations, luxury goods have price inelastic characteristics, so they can enjoy price premium and it is good to produce good performance. That is the reason why they should pay much attention to securing luxuriousness. This study examined the establishment of brands luxuriousness in Korean SMEs. First, it examined the world market of luxury goods industry and the present condition of Korean market. Then it identified the constituents of luxuriousness by examining the prior studies and related literatures, and designed a research model based on the theoretical grounds to suggest the methods of brand luxuriousness building of Korean SMEs. Luxuriousness can be defined as the attribute of product that distinguishes luxury goods from other products by consumers' perceptions, and the factor that provides situational benefits that motivate consumers' purchasing behavior. In this study, I identified the sub-dimensions of luxuriousness according to whether there are product related attributes and consumers' benefit in consideration of the problems of existing studies. Product related luxuriousness are classified into superiority(functional benefit) and scarcity(experiential benefit), while non-product related luxuriousness are classified into differentiation(symbolic benefit) and traditionality(exclusive benefit). The following are the ways to build brand luxuriousness. First, company can use product factors. High quality, excellent design, high recognized brand with strong, favorable and unique images can enhance the luxuriousness of brand. Second, company can use price factors. Consumers tend to perceive luxury goods as high-priced items, so lowering the price of product can undermine the luxuriousness of product. Third, company can use distribution factors. It is effective for making consumers to perceive the differentiation and scarcity of luxuriousness through limited distribution channel. In addition, store atmosphere suitable for luxury brands should be created. Fourth, company can use promotion factors. The more consumers are exposed to advertisements, the more positive attitudes toward luxury brands are made, and consumers recognize luxuriousness higher. Price promotion negatively affects consumers' perception of luxuriousness. Fifth, company can use corporate factors. Consumer evaluations of products are influenced not only by the product attributes but also by the corporate association and corporate image surrounding the product. Considering the existing researches, it is possible to enhance the brand luxuriousness through high corporate competence and good corporate reputation. In order to increase the competence of the enterprise, it is useful to approach multidimensionally in relation with the knowledge creation capability. In corporate reputation, the external stakeholders' reputation is important, but the internal members' reputation is also important. Korean SMEs will be able to build brand luxuriousness by establishing marketing strategies as above and/or mix(integrate) them according to the situation.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.239-251
• /
• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.3
• /
• pp.175-186
• /
• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.1
• /
• pp.55-69
• /
• 2021

For the national economic development, the participation of women in the social and economic activities is crucial. The popularization of start-ups, digital transformation, and WEconomy trends have lowered the barriers to opportunities for women to start a business and provide an environment in which women can grow faster. This paper examines the significance and process of success of women entrepreneurs and the characteristics of innovation strategies and achievements by linking the recently changing business environment of a company, factors influencing the success of women entrepreneurship, and innovation activities. To this end, four companies' cases were analyzed in the fields of distribution/service and consumer products/services, which are areas of large investment among female startups. The result shows that women entrepreneurs recognize the meaning of success as creating and continuing to create a 'corporate value through establishing a trust relationship with customers' within the 'balance between personal life and work.' In terms of the business ecosystem, women entrepreneurs strive for 'business activities based on the win-win growth of consumers, producers and sellers' for success, and rather 'focus on the process with a problem-solving approach' rather than achieving performance-oriented goals. Also through excellent power of observation, flexibility, and execution power, women entrepreneurs conduct business by adapting to changing trends. In terms of innovation activities, the innovation strategy of women-led companies puts priority on 'creating the value customers want' and focuses on innovation in the 'customer-centric business model' rather than technological innovation. As such, women-led companies show several differentiated characteristics, which enable them to create corporate value and achieve sustainable growth. The barriers to challenges and opportunities for women to start a business have been lowered, and an ecosystem has been created for female startups to grow. But why are there still so few women entrepreneurs, and the answer to where we need to close these gaps is ultimately a close analysis and investigation of the field. We must present milestones for growth steps through the accumulation of case studies of women startups that have exited. In addition, women can stand as economic agents only when the policy targets are subdivided and specific approaches to child-rearing and childcare for women entrepreneurs must be taken. This paper expects to serve as basic data for follow-up studies and become the basis of research for women entrepreneurs to grow as economic agents.

• The Journal of the Korea Contents Association
• /
• v.22 no.10
• /
• pp.599-614
• /
• 2022

The purpose of this study was to investigate the effect of organizational culture (group culture, development culture, rational culture, hierarchical culture) on job satisfaction based on the mediating effect of organizational trust on workers corporations. In particular, in the relationship between organizational culture and job satisfaction, the mediating effect of organizational trust was demonstrated, which varies by communication control variables. The results of the study of 8,615 workers in the manufacturing, financial, and non-financial industries in HCCP(Human Capital Corporate Panel) are as follows. First of all, the result of research showed that rational culture, group culture, development culture among organizational culture had a positive effect on job satisfaction. But, the hierarchical culture had a negative influence on job satisfaction. Second, rational culture, group culture, development culture among organization culture had a positive effect on organizational trust. But, hierarchical culture had a negative influence on organizational trust. Third, in the relationship between organizational culture and job satisfaction, the partial mediating effect of organizational trust was verified. In other words, although organizational culture directly affects job satisfaction, it indirectly affects job satisfaction through organizational trust. Fourth, it showed a significant moderating effect of communication between organization trust and job satisfaction. In other words, it was found that the group with high organizational trust in the relationship between organizational trust and job satisfaction had higher job satisfaction than the group without it. Finally, in the relationship between organizational culture and job satisfaction, the mediating effect of organizational trust was demonstrated, which varies by communication control variables. In other words, the indirect effect of organizational culture on job satisfaction through organizational trust is higher in the group with high communication capabilities. Through discussion and conclusion, the academic and practical implications, limitations, and research directions of this study were presented.