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Exploring into contributing factors to young seafarer turnover: empirical evidence from China

Published online by Cambridge University Press:  23 March 2021

Junzhong Bao
Affiliation:
Marine College, Dalian Maritime University, No.1 Linghai Road, Dalian, Liaoning 116026, China
Yan Li
Affiliation:
Foreign Language College, Dalian Maritime University, No.1 Linghai Road, Dalian, Liaoning 116026, China
Guoping Zheng
Affiliation:
Marine College, Dalian Maritime University, No.1 Linghai Road, Dalian, Liaoning 116026, China
Pengfei Zhang*
Affiliation:
Navigation College, Jimei University, No.1 Jiageng Road, Jimei District, Xiamen, Fujian 361021, China
*
*Corresponding author. E-mail: shippinglaw@163.com
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Abstract

Various studies suggest that the maritime industry will continue to face the challenge of seafarer shortages. Young seafarer turnover has become a serious issue that cannot be underestimated. This paper aims to identify the root causes of young seafarer attrition in China and explore relevant solutions. It collects information via semi-structured interviews and questionnaires. Independent sample t-test, one-way ANOVA and least-significant difference are utilised for the variance analysis. The findings of the study show that occupational recognition and family responsibility are the two major factors contributing to young seafarers’ outflow. Chinese seafarers’ health status is another important factor that has received little attention. In addition, young seafarers of 31–35 years old have the most possibility of turnover, due to a number of reasons discussed in this paper. Age 40 or thereabouts is viewed as the watershed moment in a seafarer's career, so efforts should be made to help young seafarers pass through the hard period in their early thirties. This paper suggests that a clear career plan could be a potential solution to retain this backbone group as prospective senior officers.

Information

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2021
Figure 0

Figure 1. The process of study

Figure 1

Table 1. Profile of respondents

Figure 2

Table 2. Factor analysis of measurement items (17)

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Table 3. Indexes of model fitting

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Table 4. Variance by marital status

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Table 5. Family origins

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Table 6. Variance by age group

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Table 7. Variance by capacity onboard

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Table 8. Variance by ship types

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Figure 2. The result of CFA as a hierarchical structure