Date of Award
Summer 8-2020
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Engineering Management & Systems Engineering
Program/Concentration
Engineering Management and Systems Engineering
Committee Director
Holly Handley
Committee Member
Cesar Pinto
Committee Member
Charles Daniels
Committee Member
George Yacus
Abstract
The commercial fishing industry is frequently described as one of the most hazardous occupations in the United States. The objective, to maximize the catch, is routinely challenged by a variety of elements due to the environment, the vessel, the crew, and several external considerations and how they interact with each other. The analysis of fishing vessel accidents can be complicated due to the diverse nature of the industry, including the species caught, the type and size of boat that is employed, how far travelled from their homeport, and the adequacy of the support organizations ensuring safe and uninterrupted operations. This study will develop and evaluate a version of Wiegmann and Shappell’s (2003) Human Factors Analysis and Classification System (HFACS), specifically for commercial fishing industry vessels (HFACS-FV), using ten years of data documenting the causes of fatal accidents in the commercial fishing industry. For this study, the accident investigation information will be converted into the HFACS-FV format by independent raters and measured for inter-rater reliability. The results will be analyzed for the frequency of the causal factors identified by the raters, and causal factors will also be evaluated for their relationship with vessel demographic information. Based on the results, the conclusion of the study will determine the efficacy of the HFACS-FV model.
DOI
10.25777/sb7t-mr44
ISBN
9798678109811
Recommended Citation
Zohorsky, Peter J..
"Human Error in Commercial Fishing Vessel Accidents: An Investigation Using the Human Factors Analysis and Classification System"
(2020). Doctor of Philosophy (PhD), Dissertation, Engineering Management & Systems Engineering, Old Dominion University, DOI: 10.25777/sb7t-mr44
https://digitalcommons.odu.edu/emse_etds/178
ORCID
0000-0003-4933-0601
Included in
Human Factors Psychology Commons, Operational Research Commons, Systems Engineering Commons