Predicting Job Skills in Demand: A Big Data Approach

Authors

  • Md Rakibul Hoque Associate Professor, Department of Management Information Systems, University of Dhaka, Dhaka
  • Md Ariful Islam Assistant Professor, Department of Management Information Systems, University of Dhaka, Dhaka

DOI:

https://doi.org/10.3329/dujbst.v42i2.59723

Keywords:

Big Data, Skill Gap, Data Mining

Abstract

The number of unemployed graduates is increasing due to a mismatch in the job skills and skill shortage. The mismatch in job skills has increased further due to technological changes like digital transformation. In Bangladesh, many companies hire skilled people from abroad because of the lack of training among graduates. Therefore, the study aims to apply big data analysis to find and predict job skills in demand. The data was mainly collected from the largest job-posting website (i.e., bdjobs.com) in Bangladesh. Natural Language Processing (NLP) was used for linguistic analysis components (for pre-processing) and tagging named identity. The finding shows business development skills, data visualization, oral communication, Microsoft Excel and working under pressure have the most demand in the categories of business knowledge skills, analytical problem skills, interpersonal communication skills, computer literacy skills, and organizational skills respectively. The study shows that big data analysis and the use of the Auto Regressive Integrated Moving Average (ARIMA) model can predict job skills in demand, which can help reduce the mismatch and gaps in job skills in demand. Overall, this study will contribute to reducing the number of unemployed graduates in Bangladesh.

Journal of Business Studies, Vol. XLII, No. 2, August 2021 Page 221-239

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Published

2023-05-08

How to Cite

Hoque, M. R. ., & Islam, M. A. . (2023). Predicting Job Skills in Demand: A Big Data Approach. Dhaka University Journal of Business Studies, 42(2), 221–239. https://doi.org/10.3329/dujbst.v42i2.59723

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Articles