Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/113858 
Year of Publication: 
2013
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 16 [Publisher:] Universidad Pablo de Olavide [Place:] Sevilla [Year:] 2013 [Pages:] 143-164
Publisher: 
Universidad Pablo de Olavide, Sevilla
Abstract (Translated): 
Access to information on competencies demanded by companies may be performed by a prospective study of job offers posted by employers. But, these include a large amount of quantitative and qualitative but mainly textual data, so an appropriate approach should be chosen in order to obtain a detailed knowledge of competencies in certain areas and professional profiles. The aim of this paper is to provide empirical evidence of the competencies required to HR professionals both generally and in terms of different job profiles in this area. The identification of competencies is accomplished by the application of statistical methods to automatically processed texts, which dispenses with previous categorization of competences in order to preserve the texts in their native format. The research is based on a textual corpus on "Soft Competencies", which has been built from hundreds of job offers for HR professionals, posted by either recruitment consultants or direct employers within the labor Spanish market. After a process of standardization and lemmatization of the textual corpus, the key terms on HR soft competencies has been drawn and thus the overall most requested competencies. Likewise, combining the textual information about competencies with qualitative data concerning job profiles, modal texts may be determined and different competency profiles can be outlined. Finally, the visualization of the associations between soft competencies and HR job profiles has been carried out by means of a Correspondence Analysis of an aggregated lexical table.
Subjects: 
competencies
human resources
textual statistics
labor market
JEL: 
J24
C38
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

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