Developing Parameters of Forecasting Models in the Field of Distribution Science to Forecast Vietnamese Seafarer Resources

DANG,, D. , NGUYEN,, T. , & NGUYEN,, N. (2021). Developing Parameters of Forecasting Models in the Field of Distribution Science to Forecast Vietnamese Seafarer Resources. The Journal of Distribution Science, 19(8), 47-56, https://doi.org/https://doi.org/10.15722/jds.19.8.202108.47

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Abstract

Purpose: Maritime sector is fundamental to international trade; there is no doubt that seafarers have played an essential role in maritime shipping and distribution science industry. Thus, this study uses Grey models to predict the number of seafarers in Vietnam expecting to provide a range of future seafarers. Research design, data and methodology: Statistics data are adopted for numbers of seafarers by Vietnam Maritime Administration categorizing into three types: Officers at Management level, Officers at Operational level and Navigation - Engine officer cadet. Results: The results have showed that a lack of qualified seafarers in the distribution industry, which has become a global issue and Vietnam is facing challenges of providing enough supply of seafarers in the next few years. Since there has been a concern of the unbalance between demand and supply of seafarers, researches in maritime sector needs a high accuracy in forecasting the number of available qualified seafarers in Vietnam. Conclusion: This method can be applied to predict numbers of other human resources in transportation, distribution and/or logistics industries when the information is poor and insufficient. The next few years are predicted to witness a downtrend in sailors - oilers which leads to the fact that the total number of available seafarers is decreased.

keywords: Distribution, Grey models, seafarers, logistics, prediction, accuracy

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Article Contents

Vol.19 No.8

Developing Parameters of Forecasting Models in the Field of Distribution Science to Forecast Vietnamese Seafarer Resources

Abstract

Reference

The Journal of Distribution Science