IDEAS home Printed from https://ideas.repec.org/a/prg/jnlcbr/v2019y2019i4id222p1-25.html
   My bibliography  Save this article

Bipartite Competency Schemas on Polish Labor Market

Author

Listed:
  • Paweł Lula
  • Anna Kovaleva
  • Renata Oczkowska
  • Małgorzata Tyrańska
  • Sylwia Wiśniewska

Abstract

The complexity and variability of the contemporary labour markets creates the need for continuous improvement of methods used for their description, analysis and forecasting. Looking for a tool that allows for the simultaneous analysis of various aspects of contemporary labour markets, the authors focused their attention on k-partite graph models (with particular emphasis on bipartite graphs). The assessment of the usefulness of models based on bipartite graphs for analysis of regularities occurring on the Polish labour market is the main aim of the paper. The authors studied the regional distribution of the demand for employee competencies and evaluated the specificity of localities and competencies. The concept of bipartite competency schemas is also introduced in the paper. These schemas can be used as models representing strongly related competencies and localities. The usefulness of bipartite competency schemas was confirmed by empirical research presented in the paper. The content of job offers published online formed the main source of data examined. All analyses were performed with the use of the R programming language.

Suggested Citation

  • Paweł Lula & Anna Kovaleva & Renata Oczkowska & Małgorzata Tyrańska & Sylwia Wiśniewska, 2019. "Bipartite Competency Schemas on Polish Labor Market," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 1-25.
    • Handle: RePEc:prg:jnlcbr:v:2019:y:2019:i:4:id:222:p:1-25
    DOI: 10.18267/j.cebr.222
    as

    Download full text from publisher

    File URL: http://cebr.vse.cz/doi/10.18267/j.cebr.222.html
    Download Restriction: free of charge
    File URL: http://cebr.vse.cz/doi/10.18267/j.cebr.222.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.cebr.222?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Laszlo Gadar & Janos Abonyi, 2018. "Graph configuration model based evaluation of the education-occupation match," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-19, March.
    2. Dario Antonelli & Giulia Bruno & Teresa Taurino & Agostino Villa, 2015. "Graph-based models to classify effective collaboration in SME networks," International Journal of Production Research, Taylor & Francis Journals, vol. 53(20), pages 6198-6209, October.
    3. Guerrero, Omar A. & López, Eduardo, 2015. "Firm-to-firm labor flows and the aggregate matching function: A network-based test using employer–employee matched records," Economics Letters, Elsevier, vol. 136(C), pages 9-12.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cindy-Pamela Lopez & Jose Aguilar & Marco Santorum, 2023. "Autonomous VOs management based on industry 4.0: a systematic literature review," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1275-1291, March.
    2. Axtell, Robert L. & Guerrero, Omar A. & López, Eduardo, 2016. "The Network Composition of Aggregate Unemployment," MPRA Paper 68962, University Library of Munich, Germany.
    3. Axtell, Robert L. & Guerrero, Omar A. & López, Eduardo, 2019. "Frictional unemployment on labor flow networks," Journal of Economic Behavior & Organization, Elsevier, vol. 160(C), pages 184-201.
    4. Kathyrn R. Fair & Omar A. Guerrero, 2023. "Endogenous Labour Flow Networks," Papers 2301.07979, arXiv.org, revised Mar 2023.

    More about this item

    Keywords

    bipartite; competency schema; labour market;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General
    • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:prg:jnlcbr:v:2019:y:2019:i:4:id:222:p:1-25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.