Journal of Intelligence and Information Systems (지능정보연구)

Korea Intelligent Information System Society (한국지능정보시스템학회)
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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

  • Received : 2019.11.13
  • Accepted : 2019.12.23
  • Published : 2019.12.31
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Abstract

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.

전자정부를 포함한 다양한 형태의 공공서비스가 제공됨에 따라 공공서비스 품질에 대한 국민의 요구 수준이 점점 높아지고 있다. 공공서비스의 품질을 높이기 위해서 공공서비스 품질에 대한 상시적 측정과 개선이 필요함에도 불구하고 전통적인 설문조사는 비용과 시간이 많이 소요되어 한계가 있다. 따라서 공공서비스에서 발생하는 데이터를 기반으로 원하는 시점에 언제라도 공공서비스의 품질을 빠르고 정확하게 측정할 수 있는 분석적 기법이 필요하다. 본 연구에서 공공서비스의 품질을 데이터 기반으로 분석하기 위해 N시의 건축 인허가 민원 서비스를 대상으로 프로세스 마이닝 기법을 이용하여 분석하였다. N시의 건축 인허가 민원 서비스는 분석에 필요한 데이터를 확보할 수 있고 공공서비스 품질관리를 통해 타 기관으로 확산 가능할 것으로 판단되었기 때문이다. 본 연구는 2014년 1월부터 2년 동안 N시에서 발생한 총 3678건의 건축 인허가 민원 서비스에 대해 프로세스 마이닝을 실시하여 프로세스 맵을 그리고 빈도가 높은 부서와 평균작업시간이 긴 부서를 파악하였다. 분석 결과에 따르면 특정 시점에 한 부서별로 업무가 몰리거나 상대적으로 업무가 적은 경우가 발생하였다. 또한 민원의 부하가 늘 경우 민원완료까지 걸리는 시간이 늘어날 것이라는 합리적인 의심을 하였으나 분석 결과 상관관계는 크게 없었다. 분석 결과에 따르면 민원완료까지 걸리는 시간은 당일처리에서 1년 146일까지 매우 다양하게 분포하였다. '하수처리과,' '수도과,' '도시디자인과,' '녹색성장과'의 상위 4개 부서의 누적빈도가 전체의 50%를 넘고 상위 9개 부서의 누적빈도가 70%를 넘어서는 등 빈도가 높은 부서는 한정적이며 부서 간 부하의 불균형이 심했다. 대부분의 민원 서비스는 서로 다른 다양한 패턴의 프로세스를 갖고 있었다. 본 연구의 결과를 활용하면 특정 시점에 민원의 부하가 큰 부서를 찾아내 부서 간 인력 배치를 탄력적으로 운영할 수 있을 것이다. 또한 민원 특성별 협의에 참여하는 부서의 패턴을 분석한 결과, 협의 부서 요청 시 자동화 혹은 추천에 활용할 수 있는 가능성이 보인다. 본 연구는 민원 서비스에 대한 프로세스 마이닝 분석을 통해 향후 공공서비스 품질 개선방향을 제시하는데 활용될 것으로 기대한다.

Keywords

References

  1. Bellazzi, R., et al, "Temporal data mining for the quality assessment of hemodialysis services," Artificial intelligence in medicine, Vol.34, No.1(2005), 25-39. https://doi.org/10.1016/j.artmed.2004.07.010
  2. Chang, Y.-K., "A Study of e-Service Quality and User Satisfaction in Public Libraries," Journal of the Korean Society for Library and Information Science, Vol.41, No.4(2007), 315-329. https://doi.org/10.4275/KSLIS.2007.41.4.315
  3. Cheng, B.-W., C.-L. Chang, and I-S. Liu, "Enhancing care services quality of nursing homes using data mining," Total Quality Management & Business Excellence, Vol.16, No.5(2005), 575-596. https://doi.org/10.1080/14783360500077476
  4. Choi, S. H., K. H. Han, and G. H. Lim, "Analysis of a Repair Processes Using a Process Mining Tool," The Journal of the Korea Contents Association, Vol.13, No.4(2013), 399-406. https://doi.org/10.5392/JKCA.2013.13.04.399
  5. Ha, S. H., and S. C. Park, "Service quality improvement through business process management based on data mining," ACM SIGKDD Explorations Newsletter, Vol.8, No.1(2006), 49-56. https://doi.org/10.1145/1147234.1147242
  6. Han, J. H., and P. S. Kim, "The effect on service quality, customer satisfaction and customer loyalty by job satisfaction: Based on Dae-gu city's local public enterprises," Korean Academic Association of Business Administration, Vol.25, No.5(2012), 2317-2340.
  7. J. D. Power and Associates, "Poor Social Media Practices can Negatively Impact a Businesses' Bottom Line and Brand Image," Press Releases, 2013, Available at http://www.jdpower.com/press-releases/2013-social-media-benchmark-study
  8. Kang, Y.-S., et al., "Exploring Process Innovation Knowledge Discovery and Diagnostics based on Process Mining: Electronic Approval Process," The Journal of Business and Economics, Vol28, No.1(2012), 55-75.
  9. Kawamura, T., T. Kimura, and S. Tsumoto, "Data Mining-Based Service Quality Estimation in Hospital Information System," 2014 IEEE International Conference on Data Mining Workshop, (2014) 289-295.
  10. Khan, K. M., ed., Managing Web Service Quality: Measuring Outcomes and Effectiveness: Measuring Outcomes and Effectiveness, IGI Global, 2008.
  11. Kim, S., "A study on customer satisfaction framework for public library services," Journal of Korean Library and Information Science Society, Vol.37, No.3(2006): 193-208.
  12. Kim, Y. H., "An analysis of the relationship among the internal service quality, internal customer satisfaction and the level of customer satisfaction with the administrative service in local government," Journal of The Korean Association for Local Government Studies, Vol.8, No.2(2004), 300-327.
  13. Kim, Y.-H., "A study on the service quality and customer loyalty in regional cultural festival," Journal of the Korean Data and Information Science Society, Vol.21, No.3(2010), 437-446.
  14. KMAC, KSQI(Korea Service Quality Index), 2004, Available at http://www.kmac.co.kr/certify/cert_sys02_2.asp
  15. Korean Standards Association, Public KS-SQI(Korean Standard-Service Quality Index), 2006, Available at https://www.ksa.or.kr/ks-sqi/3383/subview.do.
  16. Lee, C. and Y. Yi, "Development and Application of the Public-service Customer Satisfaction Index (PCSI) Model," Journal of Korean Marketing Association, Vol.27, December (2012), 69-99.
  17. Lee, H.-S., "The IPA on the SERVQUAL of the Museum as a Cultural Tourist Product: The Case of the National Museum Visitors," Korea Journal of Tourism and Hospitality Research, Vol.22, No.1(2008), 55-66.
  18. Lee, J.-P. and S. Lee, "A Study on the Quality Evaluation of Public Services in Local Government - Focusing on Civil Affairs Public Service in Daegu Metropolitan City," Social Science Research Review, Vol.27, No.2(2011), 187-211.
  19. Lee, J.-P. and S. Lee, "Newly Developed Quality Evaluation Model on Public Service," Korea Public Management Review, Vol.23, No.1 (2009), 1-32.
  20. Lee, K. H., and W. K. Hong, "The measurement and use of customer satisfaction of public administration: Focused on the discontinuous approach of satisfaction," Korean Public Administration Review, Vol.39, No.4(2005), 105-124.
  21. Leggett, K., "Communication Channel Preferences For Customer Service Are Rapidly Changing. Do You Know What Your Customers Need?," Forrester Report, 2013, Available at http://blogs.forrester.com/kate_leggett/13-03-15-communication_channel_preferences_for_customer_service_are_rapidly_changing_do_you_know_what_your_cus
  22. Oh, D.-G., Y.-K. Lim, and J.-S. Yeo, "Gap Analysis of Users Perceptions and Staffs Expectations Regarding the Library Service Qualify, Customer Satisfaction and Loyalty: A Case Study of the National Library of Korea," Journal of the Korean society for library and information science, Vol.40, No.4(2006), 165-181. https://doi.org/10.4275/KSLIS.2006.40.4.165
  23. Parasuraman, A., V. A. Zeithaml, and L. L. Berry, "Servqual: A multiple-item scale for measuring consumer perc," Journal of retailing, Vol.64, No.1(1988) 12.
  24. Rha, J. Y. and S. K. Rhee, "Service quality and customer satisfaction in the public sector: analyzing the causal relationship between process quality, outcome quality, and customer satisfaction," Journal of Service Management Society, Vol.9, No.1(2008), 183-205.
  25. Rha, J. Y., "Analyzing service quality and relationship quality in public services," Journal of Service Management Society, Vol.11, No.3(2010), 267-289.
  26. Rogers, G. and E. Joyner, "Mining your data for health care quality improvement," Technical Report, SAS Institute, Inc., Cary, NC., 2016, 1-7.
  27. Woo, Y. H., and M. Y. Hong, "A Study on the service orientation measurement of civil affair administration on the basis of SERV* OR Scale," Korean Public Administration Review, Vol.39, No.3(2005) 251-274.
  28. Zhan, M., "Exploring the feasibility of applying data mining for library reference service improvement: a case study of Turku Main Library." Technical Report, 2016.