The identification of human errors leading to accidents for improving aviation safety


Ting and Dai (2011) conducted a research to determine if Human Factors Analysis Classification System (HFACS) framework originally developed for US military aviation is also applicable to analyse accident data from the R.O.C Air Force. This article provides a meta-analysis of the original findings.

The HFACS framework consists of four main general headings and each main heading is further broken down to sub-categories as depicted in table 1. The HFACS framework follows the top to bottom hierarchy i.e. accident causation is traced from the organisational level down to operator. Total mishaps of 1,831 were recorded out of a sample of 545 accident reports.

Table 1: HFACS framework
Main category Sub-category Human factors mishaps occurrences
Organisational Influences Resource management, Organisational climate, Organisational processes 272 (14.9%)
Unsafe supervision Inadequate supervision,
Planned inappropriate operations,
Failure to correct problem,
Supervisory violation
237 (12.9%)
Precondition for unsafe acts Environmental factors, Condition of operator, Personal factors 570 (31.1%)
Unsafe acts of operators Errors, Violations 752 (41.1%)

Reported accidents at sub-category level were then statistically tested for association with categories at the organizationally higher levels. A test for association between dependent and independent variables was conducted using Pearson’s chi-square test.

Results reliability

The reliability of the results of this research also depends on the thoroughness of accidents investigation and the completeness of the sampled reports. Secondly, due to the fact that there exists many-to-one mapping of errors and unsafe acts (Reason, 1990) in Human Factors, mapping is then open to subjectivity. This is evident when assigning dependent variables to independent variables.


Research approach

The study is a descriptive research to determine if the HFACS framework originally developed for United States military aviation by Wiegmann and Shappell in 2003 is also applicable for the analysis of accidents data from R.O.C Air Force.


A sample data used for the study originates from the 545 accidents reports. The accidents occurred between 1978 and 2008 in R.O.C Air Force. The majority of the sample is from class-3 accidents accounting for 240 accidents.  The second largest accidents are class-1 by 219 accidents and followed by class-2 accounting for 78 accidents.


Ting and Dai (2011) used an already existing system to analyse human factors in R.O.C Air Force. The system is called Human Factors Analysis and Classification System (HFACS). The system was established by Wiegmann and Shappell in 2003 which is based on Reason’s model published in 1990.

The four main categories of HFACS in this article are treated as independent variables. Dependent variables are of nominal value and can only take one of two possibilities, existence or non-existence of the activity. All sub-category members of HFACS are dependent variables.

The four Independent variables are:

Organizational influences
Dependent variables

  1. Inadequate supervision
  2. Planned inappropriate operations
  3. Failed to correct problem
  4. Supervisory violations

Unsafe supervision
Dependent variables

  1. Environmental factors
  2. Condition of operator
  3. Personal factors

Preconditions for unsafe acts
Dependent variables

  1. Violations
  2. Errors

Unsafe acts of operators
Dependent variables

  1. None assigned

Data analysis

The original authors of the article performed chi-square statistical analysis to test the association between variables. The Guttmann and Krustall analysis was also performed in order to calculate proportional reduction in error. The interpretation of the chi-square analysis is also included.

1. TING Li-Yuan A & DAI Dzwo-Min B (2011). The identification of human errors leading to accidents for improving aviation safety. International IEEE Conference on Intelligent Transportation System, 2011, pages 38 - 43.
2. REASON J (1990). Human error. Cambridge University, New York.

Authors / Editors


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