| Autor: |
Mirjam Bächli, Hélène Benghalem, Doriana Tinello, Damaris Aschwanden, Sascha Zuber, Matthias Kliegel, Michele Pellizzari, Rafael Lalive |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Swiss Journal of Economics and Statistics, Vol 160, Iss 1, Pp 1-17 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2235-6282 |
| DOI: |
10.1186/s41937-024-00125-2 |
| Popis: |
Abstract Information friction makes it difficult for job seekers to find new employment opportunities. We propose a method for providing individual-specific occupation recommendations by ranking occupations based on their proximity to the worker’s profile. We identify a set of twelve skills, abilities and work styles that capture the worker-oriented requirements of all occupations and discuss how to measure these items using online questions and tasks. We use the Euclidean distance between the measured items pertaining to a worker and the requirements of an occupation to measure the proximity between job seekers and occupations. We show that the proximity between job seekers’ profiles and their preunemployment occupation predicts their intention to change occupations, thus suggesting that our method captures a meaningful conceptualization of mismatch. We also show that our method generates recommendations that differ from the previous occupations of mismatched job seekers, thereby potentially expanding their search scope. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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