A study on the quality of information in potential incident report

Tatsuya Shimada, Yusaku Okada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In corporate safety activities, it is necessary to pay attention not only to the number of incident reports, but also to the quality of information of incident report. In this research, based on the experiment, we have created the evaluation axis of the information quality in the incident report. The evaluation axis is the measurement axis relating to the information amount and the measurement axis relating to the breadth of the information viewpoint. When applied to incident report collected by enterprise, relevance was observed between application result and safety activity or safety activity consciousness survey result and validity of evaluation axis was shown.

Original languageEnglish
Title of host publicationAdvances in Safety Management and Human Factors - Proceedings of the AHFE 2018 International Conference on Safety Management and Human Factors, 2018
PublisherSpringer Verlag
Pages229-239
Number of pages11
ISBN (Print)9783319945880
DOIs
Publication statusPublished - 2019 Jan 1
EventAHFE International Conference on Safety Management and Human Factors, 2018 - [state] FL, United States
Duration: 2018 Jul 212018 Jul 25

Publication series

NameAdvances in Intelligent Systems and Computing
Volume791
ISSN (Print)2194-5357

Other

OtherAHFE International Conference on Safety Management and Human Factors, 2018
CountryUnited States
City[state] FL
Period18/7/2118/7/25

    Fingerprint

Keywords

  • Potential incident report
  • PSF
  • Safety management

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Shimada, T., & Okada, Y. (2019). A study on the quality of information in potential incident report. In Advances in Safety Management and Human Factors - Proceedings of the AHFE 2018 International Conference on Safety Management and Human Factors, 2018 (pp. 229-239). (Advances in Intelligent Systems and Computing; Vol. 791). Springer Verlag. https://doi.org/10.1007/978-3-319-94589-7_23