Text analysis of job offers for mismatch of educational characteristics to labour market demands

被引:0
作者
Beręsewicz M. [1 ,4 ]
Cherniaiev H. [2 ]
Mantaj A. [2 ]
Pater R. [2 ,3 ]
机构
[1] Department of Statistics, Poznań, University of Economics and Business, Poznań
[2] Department of Economics and Finance, University of Information Technology and Management in Rzeszów, Rzeszów
[3] Educational Research Institute, Warsaw
[4] Statistical Office in Poznań, Poznań
关键词
Job offer; Mismatch; Online data; Qualification; Skill; Text mining;
D O I
10.1007/s11135-023-01707-7
中图分类号
学科分类号
摘要
Nowadays, the traditional ways of job seeking have become less popular than digital methods. Recruitment websites are more attractive to job seekers since they provide easy, convenient access to a greater number of job vacancies. The biggest disadvantage, however, is that job vacancies published online are often unstructured and confusing. Studies related to online job vacancies are usually restricted to a short duration and a small number of recruitment websites. Such studies frequently use proxies for skills and occupations, or aggregate them into wider groups. The aim of our research is to provide full educational characteristics of job vacancies in Poland and calculate a complete list of educational mismatches. We introduce an approach that includes stages of source selection; data collection; and extraction of occupations, qualifications, and skills. We describe difficulties with data scraping and ways to overcome them. Thanks to our large dataset, we are able to determine and describe the labour demand. We also show the results of a survey that estimates educational traits of the labour supply. To measure mismatch between education and labour supply and demand, we use structural compliance indices. The paper also offers a case study for chosen occupational groups. Our findings reveal the greatest mismatch is in education and job-related skills, with the least mismatch occurring between geographic regions. © The Author(s) 2023.
引用
收藏
页码:1799 / 1825
页数:26
相关论文
共 35 条
  • [1] Acemoglu D., Autor D., Hazell J., Restrepo P., AI and jobs: Evidence from online vacancies, National Bureau of Economic Research Working Paper No, (2020)
  • [2] Askitas N., Zimmermann K., The internet as a data source for advancement in social sciences, Int. J. Manpower, (2015)
  • [3] Barnichon R., Building a composite help-wanted index, Econom. Lett, (2010)
  • [4] Beresewicz M., Pater R., Inferring job vacancies from online job advertisements, Publ, (2020)
  • [5] Blair P.Q., Deming D.J., Structural increases in demand for skill after the great recession, AEA Papers Proc, 110, pp. 362-365, (2020)
  • [6] Cedefop: Mapping the landscape of online job vacancies, Background Country Report.
  • [7] Cedefop: The online job vacancy market in the EU. Driving forces and emerging trends, Cedefop Research Paper, (2019)
  • [8] Online job vacancies and skills analysis: A Cedefop pan-European approach, Cedefop Research Paper, (2019)
  • [9] Choi H., Varian H., Predicting the present with Google trends, Econom. Rec, (2012)
  • [10] Clark P.J., An extension of the coefficient of divergence for use with multiple characters, Copeia, (1952)