Cultural values and the P-O fit: comparative NLP analysis of German online job advertisements

Marcel Herold and Marc Roedenbeck

Evidence-based HRM, 2024, vol. 13, issue 2, 230-245

Abstract: Purpose - Within the Person-Organization fit framework and Signalling Theory, this study investigates the performance of word dictionaries detecting cultural values in online job advertisements as one form of external communication of an organization. Based upon a merge of the dictionaries, a corporate value analysis of Germany is conducted. Design/methodology/approach - The study builds on a dataset (n > 151 k) of online job advertisements which were scraped from a German job portal. It was pre-processed according to natural language processing standards. For analysing the values of an organization a dictionary based word count was applied. Therefore, the current state-of-the-art dictionaries were tested, and an enhanced dictionary was developed and translated from English to German. Finally, a cluster analysis was conducted. Findings - This study supports the possibility of measuring cultural values in texts where the enhanced dictionary based on Ponitzovskiy shows the best results. It thereby supports the use of the Universal Value Structure model (Schwartz, 1992) as well as the Signalling Theory (Guestet al., 2021), that values spread across 10 core or 4 aggregated dimensions are communicated via online job advertisements. Finally, the study offers a profile of the German corporate culture average as well as 4 cultural clusters and separate organizations, all with different profiles. Originality/value - This study develops an enhanced dictionary based on a large dataset of online job advertisements for analysing the external communication of values or culture of an organization for improving the Person-Organization fit.

Keywords: Job advertisement; Natural language processing; Person-organization fit; Culture (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ebhrmp:ebhrm-05-2023-0120

DOI: 10.1108/EBHRM-05-2023-0120

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