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A Study on Setting Expected Targets for Satisfaction with the Frequency of Use of Construction Technology Information

건설기술정보의 활용 빈도 만족도에 대한 기대 목표치 설정에 관한 연구

  • Received : 2024.04.22
  • Accepted : 2024.05.12
  • Published : 2024.05.31

Abstract

Recently, with the implementation of the "e-Government Performance Management Guidelines," there is a growing demand for setting performance indicators for information systems. For systems that provide information services to the public, such as CODIL, it is not easy to set performance indicators. This study presented a research model that applies Monte Carlo simulation to set expected performance targets that can be achieved through CODIL based on objective evidence. Among the survey contents conducted from 2015 to 2023, the statistical characteristics of user satisfaction regarding the frequency of use of construction technology information provided by CODIL were designated as input variables. Future expected targets and confidence intervals from 2024 to 2026 were designated as outcome variables. The expected target value was measured by generating 5 simulation alternatives and 1,000 random numbers for each alternative. Next, the measured expected goals were interpreted and compared with the results of time series regression analysis measured in previous studies. Although, as in previous studies, the expected target value could not be predicted based on time series regression analysis that considers the correlation between years. However, compared to previous studies, this study can be considered a more accurate analysis result because it predicted the expected target value based on 5,000 input variables.

최근에 「전자정부 성과관리 지침」이 시행되면서 정보시스템의 성과 지표 설정에 대한 요구가 커지고 있다. CODIL과 같이 대국민을 대상으로 정보서비스를 하는 시스템은 성과 지표 설정이 쉽지 않다. 본 연구는 객관적인 근거에 준하여 CODIL을 통해 얻을 수 있는 성과의 기대 목표치를 설정하기 위해 몬테카를로 시뮬레이션을 적용하는 연구모형을 제시하였다. 2015년부터 2023년까지 실시한 설문조사 내용 중 CODIL에서 제공하는 건설기술정보의 활용 빈도에 관한 이용자 만족도의 통계적 특성을 입력변수로 지정하였고 2024년부터 2026년까지의 미래의 기대 목표치와 신뢰구간을 결과변수로 지정하였다. 5개의 시뮬레이션 대안과 대안별로 1,000회의 난수를 발생하여 기대 목표치를 측정하였다. 다음으로 측정한 기대 목표치를 해석하였고, 선행연구에서 측정한 시계열 회귀분석 결과와 비교하였다. 비록 선행연구처럼 연차 간에 연관관계를 고려하는 시계열 회귀분석을 기반으로 기대 목표치를 예측하지는 못하였다. 하지만 본 연구는 5,000회의 입력변수를 기초로 하여 기대 목표치를 예측하였기 때문에 선행연구에 비해 좀 더 정확한 분석 결과라고 볼 수 있다.

Keywords

Acknowledgement

논문은 국토교통부의 재원으로 국토교통부 출연사업인 "24 건설기술정보시스템 DB 확충 및 유지보수" 과제의 지원을 받아 수행되었음.

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