Unpacking the impact of COVID-19 on tourism job demand: a machine learning-driven web scraping analysis in Greece

Abstract

The onset of the COVID-19 pandemic profoundly impacted the global economy, particularly the tourism sector. This study employs machine learning-driven web scraping and data analysis to examine job advertisements in Greece, aiming to quantify the pandemic's effects on tourism employment. Empirical findings reveal a 7.5% surge in part-time positions with short-term contracts and an increase in blue-collar high-skilled occupations, targeting individuals with tertiary-level education. The skill profile for online tourism jobs has transformed, emphasising competencies in healthcare, information management, and food service administration. These insights can inform policy decisions to revitalise the tourism sector and help it adapt in the post-pandemic period. The study sheds light on the changing employment landscape, highlighting the demand for specific skills in the evolving tourism industry.

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