PREFERENCES OF DIGITAL NOMADS: ANALYZING POPULAR DESTINATIONS AND DECISION-MAKING FACTORS THROUGH INTERACTIVE DATA VISUALIZATIONS USING PUBLIC ACCESS DATABASES

Abstract

Digital nomadism is a rapidly spreading form of location-independent work that is fundamentally transforming the global labour market, economy, and tourism. The aim of this study is to quantitatively explore and model the destination preferences of digital nomads and to present an innovative, interactive data visualization framework. Our research analyses the structural changes of the period 2021-2024 following the logic of the PEST model (Political, Economical, Social, Technological). The study is based on a longitudinal database collected by a proprietary Python-based web scraping method from the nomads.com platform, which was analyzed using Spearman's rank correlation and multiple linear regression (OLS). The methodological innovation of the research is an interactive visualization dashboard based on the PEST framework, created with Tableau software, which enables the real-time exploration of complex decision factors and their trade-offs. Our results indicate significant restructuring of preferences. In the post-pandemic period, the social dimension, especially the quality of community life and safety, has become the most decisive attraction. The correlation coefficient between the Community factor and popularity increased from 0.58 to 0.65, and its explanatory power in our regression models nearly doubled relative to 2021. In parallel, technological infrastructure (internet speed) and healthcare have become critical, significant factors, indicating the professionalization of lifestyle. The relative importance of the cost factor has decreased. Geographically, Bangkok (Thailand) leads the global ranking, and Europe (Spain, Portugal) is making significant progress with the introduction of digital nomad visas. The higher coefficient of determination (R² = 0.455) for the 2024 decision models indicates that nomadic choices are becoming more rational and can be better described by objective indicators. Our study demonstrates how the integrated application of modern data science and infocommunication tools can support conscious decision-making for both digital nomads and host tourism destinations in this dynamically changing market environment.