• Human Ecology Research
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• v.55 no.5
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• pp.555-566
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• 2017

This study analyzes the practical tasks and required competency for technical designers to provide basic data on the training of domestic technical designers. The survey was applied to 21 technical designers of big vendors as well as investigated tasks, task flow, important tasks, time-consuming tasks, and required competencies. The results of the study are as follows. First, the technical designers were in charge of several brands of buyers and distributors of fashion companies, or several lines of the same brand. The main production items were cut and sewn knits. Second, the flow of task and tasks were in the order of buyer comments analysis, sloper decision to matching style, sewing specification, productive sewing method research, size specification suggestion, pattern correction comments, construction decision to matching style & fabric, sample evaluations, fit approval, business e-mail writing, specification & grading confirmation, and communication with buyer. Third, five tasks (analysis of buyer comments analysis, communication with buyer, pattern correction comments, productive sewing methods research, sample evaluation) were important and time-consuming tasks. Fourth, reeducation was required in order of sewing, pattern, English, fabric, and fitting. Fifth, competencies to be a technical designers were fitting, pattern correction, size specification & grading, construction & sewing specification, sewing terms & techniques, and communication skills. In conclusion, technical designer training should focus on technology-based instruction, such as sample evaluation, fitting, pattern correction, and productive sewing methods research of cut and sewn knits.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.97-121
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• 2019

In this paper, factors affecting intra-organizational diffusion of Big Data systems from the perspective of the Big Data system vendors have been analyzed. In particular, the theory of resistance against innovation that exists in some form before the adoption or rejection of innovation has been focused on. In order to do that, the resistance has been divided into three categories : postponement, rejection and opposition. The variables affecting each type are also divided into four independent variables : perceived risk, innovation characteristics, user attributes, and organizational attributes. As a result of the survey, it was confirmed that the influences of each variable are different according to the type of resistance. As the strength of the resistance was increased, the influence of the trialability was increased as well. As the strength of the resistance was decreased, the satisfaction with the existing system became more influential on the resistance. The time risk and the satisfaction with the existing system were found to affect all types of resistance. From the vendor's point of view, strategic implications are presented in terms of marketing or system development for diffusion, depending on the degree of resistance of the adopter.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.93-99
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• 1998

There is only authentication of end-to-end in electronic commerce technique. But in a distributed system, an authentication that is ensured users and computers has a big threats which an identify of those is unbelievable because it can be occurred an fabrication or a false personation. Authentication for other elements included customers and vendors is required in the case that there is many a broker connecting customers with vendors as well. In authentication like above, many elements playing different role participated, were performed by the known techniques, processing was more complicated. In this paper, the Mutual Indirect Authentication technique is used to solve and avoid that condition and the generalized electronic commerce using a mobile agent is accomplished with this technique.

• Journal of Distribution Science
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• v.12 no.2
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• pp.17-25
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• 2014

Purpose - This study used empirical methods to investigate the consciousness structure of vendors in the S marketing area, which is a commercial revitalization district in the country, and examined its effect on their business activities. Based on the results derived through the performance of an actual proof analysis, this study aims to facilitate the promotion of changes in the consciousness structures of traditional market vendors, with a view to allowing them to adapt to the current economic realities in the country. Further, this study aims to provide suggestions that would improve the efficiency of the commercial revitalization program of the government. Research design, data, and methodology - This study examined all the stores in the S marketing area using a questionnaire survey conducted over three weeks beginning on July 4, 2012, and involved the performance of a data analysis on 1,859 samples. The questionnaire consisted of two parts. The first part addressed the market revitalization and the second part addressed the store management strategies. Questionnaire responses were calibrated based on a Likert scale. Statistical analysis was conducted using PASW version 18.0. Results - The results of the analysis of the consciousness structure of merchants in the S marketing area have led to the discovery that they have a medium level of satisfaction with market revitalization. There was a difference in the perceptions of the concept of store management between merchants and customers. Merchants have poor strategies for store management, which do not go much beyond an imitation of the practices of large domestic discount stores. Conclusions - The appearance of big discount stores and the accompanying changes in people's consumption patterns have led to a decline in local market areas. The government has sought new ways to secure autogenic power for local markets. To create regional economies, the government enacted a revised "Law for creating traditional markets and shopping streets" in 2010 and introduced a commercial district revitalization program. This program, which originally supported only the S marketing area, has subsequently expanded into neighboring shopping districts so that the whole of the regional market can be revitalized. However, since the revitalization of the traditional market and the government support required for it were mostly limited to facilities, the result has not proved to be effective. Although there are several reasons why the government investment was characterized by poor efficiency, traditional market vendors' consciousness structure, which did not adapt well to the vagaries of time and its consequent changes, was a major cause. Only when vendors have a true merchant spirit can they have a real service focus that will enable them to clearly understand the distribution organization. This will have the effect of bring about complete customer satisfaction and will ensure the survival and development of traditional markets.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.211-219
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• 2013

The analysis method using Big Data has evolved based on the Big data Management Technology. There are quite a few researching institutions anticipating new era in data analysis using Big Data and IT vendors has been sided with them launching standardized technologies for Big Data management technologies. Big Data is also affected by improvements of IT gadgets IT environment. Foreran by social media, analyzing method of unstructured data is being developed focusing on diversity of analyzing method, anticipation and optimization. In the past, data analyzing methods were confined to the optimization of structured data through data mining, OLAP, statics analysis. This data analysis was solely used for decision making for Chief Officers. In the new era of data analysis, however, are evolutions in various aspects of technologies; the diversity in analyzing method using new paradigm and the new data analysis experts and so forth. In addition, new patterns of data analysis will be found with the development of high performance computing environment and Big Data management techniques. Accordingly, this paper is dedicated to define the possible analyzing method of social media using Big Data. this paper is proposed practical use analysis for social media analysis through data mining analysis methodology.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.

• Electronics and Telecommunications Trends
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• v.32 no.5
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• pp.107-116
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• 2017

Artificial intelligence has recently been regarded as a key engine of future industry, and cloud computing and big data technologies have begun to receive significant attention. Major global vendors such as IBM, Microsoft, Google, and Amazon have been launching cloud-computing services for artificial intelligence. On the other hand, the situation domestically is now at an early stage. This report describes the industry trends both domestically and internationally regarding cloud computing for artificial intelligence. We also describe to significance of cloud computing ecosystem and data competitiveness for artificial intelligence.

• The Journal of Information Systems
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• v.16 no.4
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• pp.33-49
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• 2007

The purpose of this study is to identify the interorganizational factors that influence both the supplier-buyer's EDI utilization and the business performance in domestic retail industry. In terms of successful supply chain implementation and operation, we deduced the structural factors in the context of the interorganizational characteristics between mass merchandisers and vendors. This study therefore focused on suggesting the ways of managing the partnership in supply chain and conceptualizing the big picture of EDI development model in the scope of a retailer's IT strategy. This paper implicates that it is important to leverage the level of organizational capabilities for the success of supply chain adoption and operation. In the stream of SCM initiatives from the manufacturing industry, retailers should concentrate on improving the interorganizational environment and implementing the effective information technology for supporting business strategy.

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

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.605-612
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• 2011

As the power grids are integrated into one big umbrella called a "smart grid," communication protocol plays a key role in successful operations. The successful deployment of smart grid interoperability is a major hurdle that must be overcome. The micro grid, a small power system that distributes energy resource, is operated in diverse regions. Different vendors use different communication protocols in the operation of the micro grid. Recently, the IEC 61850 has been legislated to solve the interoperability problems in power utility automation. The present paper presents a micro grid system based on the IEC 61850 protocol. It consists of a micro grid monitoring system, a protocol converter that transforms serial data to IEC 61850 data, and distributed energy resource controllers for diverse DER nodes. A developed communication gateway can be deployed for DER controllers with serial links to exchange data with IEC 61850-based devices. The gateway can be extended to IEC 61850-based distribution automation systems, substation automation systems, or SCADA.