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A study on the Effect of Quality Characteristics of M2M Big Data providing real-time Information on User Satisfaction

실시간 정보를 제공하는 M2M 빅데이터 품질특성이 사용자 만족에 미치는 영향에 대한 연구 - 버스기사의 교통정보 시스템 중심으로 -

  • 양동식 (공주대학교 산업시스템공학과) ;
  • 박동진 (공주대학교 산업시스템공학과) ;
  • 이윤재 (공주대학교 산업시스템공학과)
  • Received : 2022.10.17
  • Accepted : 2022.11.29
  • Published : 2022.12.30

Abstract

This study is about how the quality of M2M big data that provides real-time information affects users. Recently, there are many difficulties in acquiring and managing data because data types such as variety, data volume, and data velocity are changing rapidly and diversified. This not only leads to a decrease in data quality but also it can give a negative impact when making decisions using data. Generally, the quality of data is defined as 'suitability for use', which means that data quality must meet the expectations of user needs. Therefore, data providers need activities to improve data quality for this purpose, and the key is to identify data quality dimensions in each field where data is used and provide data suitable for the level of user needs. In this study, the relationship between the quality area of real-time M2M data used in the traffic information system and user satisfaction was analyzed. Research models and hypotheses were established to analyze the effects between variables related to M2M big data. In order to test the hypothesis, a causal relationship between the major factors was identified by conducting a survey and analyzing the data users.

본 논문은 실시간 정보를 제공하는 M2M 빅데이터의 품질이 사용자에게 어떤 영향을 미치는지에 관한 것이다. 최근 들어 데이터의 종류(Variety), 양(Volume), 속도(Velocity) 등이 급변함에 따라 데이터의 획득 및 관리에 많은 어려움이 있다. 이러한 문제는 데이터의 품질 저하로 이어질 뿐만 아니라 데이터를 활용하여 의사결정을 내릴 때 부정적인 영향을 줄 수 있다. 일반적으로 데이터의 품질을 '사용 적합성'으로 정의하는 데 이는 데이터 품질이 사용자 요구의 기대치를 충족해야 함을 의미한다. 이것은 데이터의 품질이 빅데이터의 활용에 중요한 요소임으로 데이터의 획득과정에서부터 데이터 품질 영역(Data Quality Dimensions)에 대한 관리가 필요하다. 본 연구에서는 교통정보 시스템에 사용되는 실시간 M2M 데이터의 품질 영역과 사용자 만족도의 관계를 분석하였다. M2M 빅데이터 관련 변수 간의 영향을 분석하기 위해 연구 모델과 가설을 설정하였다. 가설을 검증하기 위해 데이터 이용자를 대상으로 설문조사 실시하고 분석을 하여 주요 요인들 간의 인과관계를 파악했다.

Keywords

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