• Journal of Digital Convergence
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• v.19 no.3
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• pp.55-64
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• 2021

Public libraries are a space where residents learn a wide range of knowledge and ideologies, and as they are directly connected to life, various related studies have been conducted. In most previous studies, variables such as population, traffic accessibility, and environment were found to be highly relevant to library use. In this study, it can be said that the difference from previous studies is that the book borrow demand and relevance were analyzed by reflecting the variables of cultural characteristics based on the book borrow history (1,820,407 cases) and member information (297,222 persons). As a result of the analysis, it was analyzed that as the increase in borrows for social science and literature books compared to technical science books, the demand for book borrows increased. In addition, various descriptive statistical analyzes were used to analyze the characteristics of library book borrow demand, and policy implications and limitations of the study were also presented based on the analysis results. and considering that cultural characteristics change depending on the location and time of day, it is believed that related research should be continued in the future.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.201-221
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• 2015

The purpose of this study is to suggest the usability of collection evaluation methods for collection development policy in public libraries. To achieve this purpose, this study applied Bonn's Use Factor, Turnover Rate of Collection, and Trueswell's 80/20 Rule to actual circulation data of the Gwangjin District Public Library in Seoul during last ten years. This study added practical meanings and values in collection evaluation through the analysis of total holdings and subject classes. Main items of analysis are the rate of use to total holdings and to holdings in specific subject classes by year, and the rate of core collection circulation by year. The results show relations between the rate of use and library's performance through the analysis of the rate of use both total holdings and subject classes. The results also figure out user's patterns and library appraisal of community users through the analysis of circulation data. In addition, the analysis of core collection gives a good basis for an effective collection development policy.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.31-50
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• 2017

This study was to suggest the problems and the improvement plan of Digital Library System (DLS) which has solved the library management and has supported the data building for resource sharing in school libraries since 2001. The 9 DLS committees were interviewed about the current situation of DLS use and the problems of DLS system in the 6 areas of acquisition, cataloging, circulation and discharge, inventory, library statistics, and searching interface as the research methods. Based on the interviews, the improvement plans were suggested as followed. In acquisition, it was to need the acquisition system development and online purchase for users. In cataloging, the improvement of data quality management, and indexes and vocabularies control for upgrade of searching function were needed. The advanced circulation speed in circulation, the restoration of discarded data in inventory and the exact statistic data in library statistics were need to improve the DLS. This study would contribute to the betterment of DLS and increase the use of DLS.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.265-272
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• 2019

In this study, we conducted a prediction study to qualitatively identify the continuous growth rate that causes problems every year for deposit bank mortgage loans, identify the characteristic factors that could once again stabilize, and come up with measures for future quantitative analysis of mortgage loans and growth trends. Based on data analysis using the R program, which is widely used for big data analysis, the parameters of ARIMA model (0.1,1)(0.1,1)[12] were found to be most suitable. In these indicators, estimates over the next five years (60 months) increased 4.5% on average. However, this has limitations that do not reflect socio-environmental factors, which require further study of these limitations.

• Journal of Information Management
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• v.39 no.1
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• pp.109-129
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• 2008

This study was prepared for the purpose of suggesting the reasonable method of library management by reflecting it to the library acquisition and collection development through the user survey and analysis of an academic library. The 97,164 circulation records of C-academic library which were occurred between March 2006 and February 2007 were used, and sixteen subjects by five user groups ((1)undergraduate, (2)graduate students, (3)faculties(professors), (4)staffs, and (5)the other users) were surveyed for the study. The subject and the number of publication lapse year were categorized in this study. The non-parametric method and correlation coefficient were used for the analysis of subject part after the use factor and the number of publication lapse year were crossed by their status. Also, the same methods by use factor were used for the analysis of the number of year part.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.15-26
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• 2007

In this study, a SOHO (Small Office Home Office) bankruptcy prediction model is proposed using Modified Bagging Predictors which is modification of traditional Bagging Predictors. There have been several studies on bankruptcy prediction for large and middle size companies. However, little studies have been done for SOHOs. In commercial banks, loan approval processes for SOHOs are usually less structured than those for large and middle size companies, and largely depend on partial information such as credit scores. In this study, we use a real SOHO loan approval data set of a Korean bank. First, decision tree induction techniques and artificial neural networks are applied to the data set, and the results are not satisfactory. Bagging Predictors which has been not previously applied for bankruptcy prediction and Modified Bagging Predictors which is proposed in this paper are applied to the data set. The experimental results show that Modified Bagging Predictors provides better performance than decision tree inductions techniques, artificial neural networks, and Bagging Predictors.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.43-62
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• 2015

This study was implemented to suggest various indicators of collection evaluation for collection development policy in public libraries. For the sake of the exploratory research, this study tried to show the usability of indicators of collection evaluation through actual data of a case study. Also to analyze indicators of collection evaluation, this study used the ten years circulation records of the Gwangjin District Public Library in Seoul. Majors indicators of collection evaluation were the rate of use and use factor of purchasing books by annual, the rate of use and use factor of librarian's recommended books by annual, the rate of non circulating books by annual, and the rate of use by residence annually.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• The Journal of Bigdata
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• v.1 no.1
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• pp.77-84
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• 2016

We investigate the types and characteristics of Fintech has become a major issue. Through this, we believe that the essence of Fintech are platform business and market occupancy. To success Fintech business, the price of Fintech services needs to be lower than that of traditional financial services. The solution is to take advantage of big data and big data analysis. Finally, we think only a win-win cooperation with Fintech startups and financial companies in the direction we need to go.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.272-277
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• 2010

In respect complication of group, rate of arrearage in domestic bank is composed of various factors. This paper studies focus on estimating the determinants of the rate of arrearage in domestic bank using panel data model. The volume of analysis consist of 3 groups(loaned patterns of enterprise, housekeeping, credit card). Analyzing period be formed over a 54 point(2005. 1~ 2009. 06). In this paper dependent variable setting up rate of arrearage in domestic bank, explanatory(independent) variables composed of the consumer price index, composite stock price index, rate of exchange, the coincident composite index, national housing bonds and employment rate. The result of estimating the rate of arrearage in domestic bank provides empirical evidences of significance positive relationships between the consumer price index However this study provides empirical evidences of significance negative relationships between the coincident composite index and the composite stock price index. The explanatory variables, that is, rate of exchange, national housing bonds and the employment rate are non-significance variables of negative factor. Implication of these findings are discussed for content research and practices.