Analysis of Logistics Curriculum and Recruitment Requirements Based on Text Mining: A Case Study of China

Ziyao Li and Xiaobo Jia

SAGE Open, 2024, vol. 14, issue 2, 21582440241239839

Abstract: This study aims to explore the logistics curriculum and the recruitment requirements and to compare the relationship between the two systems. Text mining is applied to collect data from an online recruitment website, extract latent topics, and dynamically visualize the extracted latent topics. The online and on-site survey is conducted to collect logistics curriculum syllabi from 29 selected universities in China. This study demonstrates that (1) The logistics curriculum direction in China mostly meets the employment demands; (2) The curriculum distribution does not fully match the employment demands. That is, knowledge areas of general management and logistics IT are over-supplied, whereas knowledge areas of transportation and distribution are under-supplied. It is suggested that to balance the actual talent demands, Chinese higher education should increase the courses concerning transportation and distribution and appropriately reduce the courses related to logistics IT, and universities need to apply course modules into the logistics curriculum revision to meet the changes in the demand of the employment market.

Keywords: logistics curriculum; recruitment requirements; text mining; curriculum direction; curriculum distribution (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:2:p:21582440241239839

DOI: 10.1177/21582440241239839

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