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Analysis of students' perceptions of seafaring career in China based on artificial neural network and genetic programming


Fei, J and Lu, J, Analysis of students' perceptions of seafaring career in China based on artificial neural network and genetic programming, Maritime Policy and Management: An International Journal of Shipping and Port Research, 42, (2) pp. 111-126. ISSN 1464-5254 (2015) [Refereed Article]

Copyright Statement

Copyright 2014 Taylor and Francis

DOI: doi:10.1080/03088839.2013.873545


Research indicates that the worldwide shortage of qualified seafarers has been due to the rapidly increasing world merchant fleet on the one hand and the difficulty of attracting and retaining people in the industry on the other. The paper argues that in the context of the Chinese shipping industry, the high "wastage" is one of the major contributors to the shortage. The aims of the research are to examine the motives of students studying nautical courses; identify the key factors affecting nautical students to choose seafaring career, and to predict students’ career choice behavior. The research finds that (a) those who had a clear sense of their future career when enrolled in the nautical studies tend to choose a seafaring career and remain active for a longer period of time; (b) high wage is the most important factor affecting students’ decisions to choose seafaring as a career; (c) prolonged separation from family, job opportunities ashore, and concern about children’s growth and education are among the top three factors for students not to choose a seafaring career or to quit it early; and (d) nautical students’ career choice behaviors can be predicted through the use of artificial neural network (ANN) and genetic programming (GP) with five rules being generated. This novel methodological approach, a combination of ANN and GP, has been proven to be effective in analyzing complex variables and in generating rules.

Item Details

Item Type:Refereed Article
Keywords:Seafaring, seafaring career, maritime education, seafarer shortage, human resource management, skill shortage, artificial neural network, genetic programming,
Research Division:Commerce, Management, Tourism and Services
Research Group:Human resources and industrial relations
Research Field:Human resources management
Objective Division:Economic Framework
Objective Group:Management and productivity
Objective Field:Management
UTAS Author:Fei, J (Associate Professor Jiangang Fei)
ID Code:90041
Year Published:2015 (online first 2014)
Web of Science® Times Cited:12
Deposited By:Maritime and Logistics Management
Deposited On:2014-03-25
Last Modified:2018-03-15

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