Human Error in Commercial Fishing Vessel Accidents: An Investigation Using the Human Factors Analysis and Classification System

<p>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.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Engineering Management & Systems Engineering

Year dc:date.available

2020

Author dc:creator

• Zohorsky, Peter J.

Contributors dc:contributor

• Holly Handley
• Cesar Pinto
• Charles Daniels
• George Yacus

• Commercial fishing safety
• Human error
• Human factors
• Human Factors Analysis and Classification System
• Human Factors Psychology
• Operational Research
• Systems Engineering

Identifier

9798678109811

OAI identifier oai:identifier

oai:digitalcommons.odu.edu:emse_etds-1178