Characterizing Regional Tourism in Romania through Web-Scraped Data and Multivariate Statistical Analysis
Articles
Cristina Rodica Boboc
Department of Statistics and Econometrics, Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic Studies, Roma
Ana Maria Babaligea
Department of Statistics and Econometrics, Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic Studies, Romania
Simona Ioana Ghita
Department of Statistics and Econometrics, Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic Studies, Roman
Claudiu Nicolae Ghinea
: Doctoral School of Business Administration I, The Bucharest University of Economic Studies, Romania
Cristian Constantin Francu
Doctoral School of Business Administration I, The Bucharest University of Economic Studies, Romania
Published 2026-03-25
https://doi.org/10.15388/Tibe.2026.25.1.27
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Keywords

web-scraping
regional tourism
multivariate analysis
cluster analysis
principal component analysis

How to Cite

Boboc, C. R., Babaligea, A. M., Ghita, S. I., Ghinea, C. N., & Francu, C. C. (2026). Characterizing Regional Tourism in Romania through Web-Scraped Data and Multivariate Statistical Analysis. Transformations In Business & Economics, 25(1 (67), 556-574. https://doi.org/10.15388/Tibe.2026.25.1.27

Abstract

The study investigates the tourism profile of Romania’s counties by using automatically collected data from a major online travel platform. The analysis integrates variables related to the number of accommodation facilities, average prices, overall and category-specific ratings, number of reviews, and available amenities. To identify regional typologies and the determinant factors of tourism quality and development, cluster analysis and Principal Component Analysis (PCA) were applied. The results revealed four distinct clusters corresponding to different levels of development and attractiveness, as well as two principal components: a Tourism Offer Quality Component, reflecting visitors’ satisfaction and perceptions of services, and a Tourism Development Component, associated with the scale and intensity of tourism activity. The study provides an integrated view of regional disparities, highlighting mature tourism destinations, counties with growth potential, and emerging areas, and offers recommendations for differentiated regional development and tourism promotion policies. The innovative contribution of this research lies in the use of alternative, web-scraped data that complement and enrich official statistics and data, offering timely, detailed insights, oriented towards the actual experience of tourists. Based on the findings, the study proposes recommendations for decision-makers, aiming to stimulate growth in emerging regions, improve service quality, and support balanced regional tourism development across Romania. By integrating digital data and multivariate methods, the research makes an original contribution to understanding the competitiveness and performance of regional tourism in Romania.

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