• Title/Summary/Keyword: filing system

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A Comparative Study of the Security Prevention Strategies on Arson: Focused on the Behavioral Characteristics between Serial Arsonists and Simple Arsonists (방화범죄의 경비예방 전략에 관한 비교연구 - 연쇄방화범과 단순방화범의 행위적 특성을 중심으로 -)

  • You, Wan-Seok;Hwang, Sung-Hyun
    • Korean Security Journal
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    • no.29
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    • pp.139-162
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    • 2011
  • The purpose of this study is to compare with the general and behavioral characteristics between simple and serial arsonists using the data derived from Scientific Crime Analysis System, Criminal Filing Search System, and Crime Information Management System. The analysis and findings reported here are derived from data extracted from 160 arsonists arrested by police officer. The independent variables included such socio-economic characteristic as arsonists' gender, age, occupation, education level, and previous criminal records of arsonists, and finally the general characteristics of the scene of fire settings. The dependent variable is whether or not serial fire setter. To achieve the purpose, the analysis of frequencies and cross-tab were conducted. According to frequence and cross-tab analysis, there are great differences of the general and behavior characteristics between two groups. In the comparison of simple and serial arsonists, serial arsonists are more likely to have previous criminal records, low socio-economic status, unmarried and no cohabitants than simple arsonists. furthermore, serial arsonists are more likely to use garbage papers for fire setting in the scene of the crime, to have mental or psychological problems, and to get involved in fire setting for the psychological pleasure than simple arsonists do. The present research has some obvious limitations. First, the analysis is based only on arsonists arrested by police officers. These may be considerable differences in arsonists arrested by police officers and fire setters not arrested by them. Additional research is needed to assess the extent to which these findings would apply to fire setters not arrested by police officer in Korea. Secondly, the data in this study are cross-sectional and simple cross-tab analysis are used. Potential limitation of cross-sectional data concerns the inability to specify the changes in measures as arsonists behavioral characteristics. Therefore, further studies need to use longitudinal data and more complicate statistical techniques such as correlation analysis, multiple regression analysis, or LISREL models to specify the casual relationships between dependent and independent variables for fire settings. Even if this study has some limitations, it is meaningful in which it first investigated the comparison of simple and serial arsonists focusing on the general and behavioral characteristics between two groups in Korea.

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Measuring the Public Service Quality Using Process Mining: Focusing on N City's Building Licensing Complaint Service (프로세스 마이닝을 이용한 공공서비스의 품질 측정: N시의 건축 인허가 민원 서비스를 중심으로)

  • Lee, Jung Seung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.35-52
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    • 2019
  • As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

A Study on the Characteristics of Enterprise R&D Capabilities Using Data Mining (데이터마이닝을 활용한 기업 R&D역량 특성에 관한 탐색 연구)

  • Kim, Sang-Gook;Lim, Jung-Sun;Park, Wan
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.1-21
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    • 2021
  • As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.