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

Aug 5, 2026

Upload by Aurelia

The onset of the COVID-19 pandemic profoundly affected the global economy, with tourism among the hardest-hit sectors. This study uses machine learning-driven web scraping and data analysis to examine job advertisements in Greece, with the goal of quantifying changes in tourism-related employment demand. Results indicate a 7.5% rise in part-time roles with short-term contracts and growth in blue-collar high-skilled positions requiring tertiary education. The online job skill profile shifts toward healthcare, information management, and food service administration, informing post-pandemic policy priorities.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages30

Reading Time1 h 16 min

AccessFree to download

Abstract

Introduction

COVID-19 disruption to tourism and employment demand

Research gap on job-demand effects

Methods and data (web scraping and machine learning)

Findings

Contract type and job-role shifts

Blue-collar high-skill and education targeting

Evolving online skill profiles

Implications for policy and post-pandemic adaptation

Current Issues in Tourism ISSN: 1368-3500 (Print) 1747-7603 (Online) Journal [homepage: ](homepage: www.tandfonline.com/journals/rcit20)[www.tandfonline.com/journals/rcit20](homepage: www.tandfonline.com/journals/rcit20) Unpacking the impact of COVID-19 on tourism job demand: a machine learning-driven web scraping analysis in Greece Evangelos Mourelatos , Panagiotis Zervas , Nikos Zotos , Konstantinos C. Giotopoulos & Giannis Tzimas To cite this article: Evangelos Mourelatos , Panagiotis Zervas , Nikos Zotos , Konstantinos C. Giotopoulos & Giannis Tzimas (25 Sep 2025): Unpacking the impact of COVID-19 on tourism job demand: a machine learning-driven web scraping analysis in Greece, Current Issues in Tourism, DOI: 10. 1080/13683500 .2025.2563790 To link to this article: [https://doi.org/10.1080/13683500.2025.2563790](https://doi.org/10.1080/13683500.2025.2563790) © 2025 The Author(s) . Published by Informa UK Limited, trading as Taylor & Francis Group | Published online: 25 Sep 2025. | | | --- | --- | | | Submit your article to this journal | | | Article views: 88 | | | View related articles | | View Crossmark data | | Full Terms & Conditions of access and use can be found at [https://www.tandfonline.com/action/journalInformation?journalCode=rcit20](https://www.tandfonline.com/action/journalInformation?journalCode=rcit20) CURRENT ISSUES IN TOURISM [https://doi.org/10.1080/13683500.2025.2563790](https://doi.org/10.1080/13683500.2025.2563790) RESEARCH ARTICLE Unpacking the impact of COVID-19 on tourism job demand: a machine learning-driven web scraping analysis in Greece Evangelos Mourelatosa, Panagiotis Zervasb, Nikos Zotosc, Konstantinos C. Giotopouloscand Giannis Tzimasb aDepartment of Economics, Accounting and Finance, Oulu Business School, University of Oulu, Oulu, Finland; bData and Media Laboratory, Department of Electrical and Computer Engineering, University of Peloponnese, Tripoli, Greece; cDepartment of Management Science and Technology, University of Patras, Patras, 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 parttime 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. ARTICLE HISTORY Received 8 January 2024 Accepted 15 September 2025 KEYWORDS COVID-19; tourism employment; machine learning; job portals; job skills; scraping analysis 1. Introduction The global COVID-19 pandemic initiated an unprecedented crisis in the tourism industry, triggering severe economic repercussions worldwide. Tourism, an industry deeply dependent on mobility and social interaction, suffered extensive disruptions as nations imposed restrictions to contain the virus (Plzáková & Smeral, 2022) . Critical subsectors within tourism, such as hospitality, entertainment, and cruise lines, were significantly impacted, leading to a dramatic decline in both international and domestic travel (Sigala, 2020) . Consequently, the demand for tourism-related jobs dropped sharply, affecting economies heavily reliant on this sector. The pandemic prompted governments across Europe to enforce strict lockdowns and curtail nonessential activities, impacting tourism more severely than other sectors (Lenzen et

FAQs

What data and approach does the study use to assess tourism job demand?

The study applies machine learning-driven web scraping and data analysis to examine job advertisements in Greece.

What changes in tourism employment demand were observed during the pandemic?

Findings show a 7.5% surge in part-time positions with short-term contracts and an increase in blue-collar high-skilled occupations.

Which skills became more prominent for online tourism jobs?

The skill profile emphasizes competencies in healthcare, information management, and food service administration.

Aug 5, 2026

Upload by Aurelia