The study proposes to analyze the complex role of the soft skills in the recruitment process. Competences are playing a key role in improving the competitiveness of businesses and employees, reshaping compensation structures. In an innovation-driven environment, soft skills emerge as a response to the challenge of change, essential for mitigating the risk of skill obsolescence. This study uses a dataset of over one and a half million job placements across the main macro-sectors in Italy (2016-2024), with statistical units relating to candidates and the soft skills necessary for selection. The analysis focuses on professional profiles within the tourism sector, reclassified according to the European Skills, Competences, Qualifications and Occupations (ESCO) classification. From a methodological point of view, since the structure of the datasets contemplates three dimensions as job positions, soft skills and time, the proposed approach provides a reduction on two dimensions stacking the three-way matrix. A further reduction of the data dimensionality has been obtained through a Weighted Factor Analysis in order to achieve a time trajectory given by the points projected on the first two components. Furthermore, socio-demographic information of the employees as age, education level and gender are introduced in the model as supplementary variables in order to detect potential contact points between them and the requested soft skills.
Mariani, P., Marletta, A., Pirotta, D. (2025). Labour Market Dynamics in the Tourism Sector: Professional Trends and Emerging Skill Requirements. Intervento presentato a: ASA 2025. Data, Statistics and AI for the Well-Being of People and Organizations, San Marino, San Marino.
Labour Market Dynamics in the Tourism Sector: Professional Trends and Emerging Skill Requirements
Mariani, P;Marletta, A
;Pirotta, D
2025
Abstract
The study proposes to analyze the complex role of the soft skills in the recruitment process. Competences are playing a key role in improving the competitiveness of businesses and employees, reshaping compensation structures. In an innovation-driven environment, soft skills emerge as a response to the challenge of change, essential for mitigating the risk of skill obsolescence. This study uses a dataset of over one and a half million job placements across the main macro-sectors in Italy (2016-2024), with statistical units relating to candidates and the soft skills necessary for selection. The analysis focuses on professional profiles within the tourism sector, reclassified according to the European Skills, Competences, Qualifications and Occupations (ESCO) classification. From a methodological point of view, since the structure of the datasets contemplates three dimensions as job positions, soft skills and time, the proposed approach provides a reduction on two dimensions stacking the three-way matrix. A further reduction of the data dimensionality has been obtained through a Weighted Factor Analysis in order to achieve a time trajectory given by the points projected on the first two components. Furthermore, socio-demographic information of the employees as age, education level and gender are introduced in the model as supplementary variables in order to detect potential contact points between them and the requested soft skills.| File | Dimensione | Formato | |
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