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Research Article

A market driven identification of current and emerging skills requiring an MBA degree: a topic modelling approach

ORCID Icon, ORCID Icon & ORCID Icon
Received 06 Feb 2024, Accepted 22 Apr 2024, Published online: 03 May 2024

Figures & data

Figure 1. Text processing pipeline.

Figure 1. Text processing pipeline.

Figure 2. Procedure for determining coarser skills. (a) relation among skills from narrower to broader. (b) the red node is the selected skill from the set of keywords. (c) sub-graph of related skills to a top skill marked with green. (d) yellow nodes are coarser skills that are three edges from the top skill.

Figure 2. Procedure for determining coarser skills. (a) relation among skills from narrower to broader. (b) the red node is the selected skill from the set of keywords. (c) sub-graph of related skills to a top skill marked with green. (d) yellow nodes are coarser skills that are three edges from the top skill.

Figure 3. Coherence measures changes based on the number of topics and the number of hidden layers of the encoder/decoder. The spread is calculated based on the variation of the learning rate parameter.

Figure 3. Coherence measures changes based on the number of topics and the number of hidden layers of the encoder/decoder. The spread is calculated based on the variation of the learning rate parameter.

Figure 4. Selected topics and keywords.

Figure 4. Selected topics and keywords.

Figure 5. Topic (job function, and/or industry sector) clusters and number of openings.

Figure 5. Topic (job function, and/or industry sector) clusters and number of openings.

Figure 6. From full-text search results to granular and subsequent broader skill sets.

Figure 6. From full-text search results to granular and subsequent broader skill sets.

Figure 7. Relative significance of extracted skills.

Figure 7. Relative significance of extracted skills.

Figure 8. Topic coherence in the SBERT text processing pipeline.

Figure 8. Topic coherence in the SBERT text processing pipeline.