Financial Performance-Based Clustering of Spa Enterprises in Slovakia

This paper presents a cluster analysis of 20 spa enterprises operating in Slovakia, based on key financial indicators for the years 2018 and 2023. A comparative time-based approach was adopted to capture changes in financial performance over time. The primary objective is to group the spas into homogeneous clusters to better understand their financial performance and strategic positioning. Ten financial indicators were selected across five dimensions: profitability (return on assets, return on sales), efficiency (assets turnover), cost efficiency (personnel cost ratio, cost-to-sales ratio, return on costs), liquidity (net working capital, current ratio), and indebtedness (equity to total liabilities ratio, debt ratio). Hierarchical cluster analysis—a widely used statistical method in unsupervised machine learning and a foundational technique in artificial intelligence—was employed, serving as a robust tool for data-driven decision making. The analysis identified distinct clusters of spas with similar financial characteristics. The results reveal meaningful segmentation that can inform resource allocation, performance benchmarking, and strategic planning. The findings provide spa managers, investors, and policy makers with a clearer understanding of financial patterns in the Slovak spa sector and offer practical implications for enhancing competitiveness and operational effectiveness.

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Publication Details

Journal
Journal of risk and financial management
Published
2025-08-28
DOI
https://doi.org/10.3390/jrfm18090482
Citations
1
Primary Topic
Global Healthcare and Medical Tourism
Type
article
Field-Weighted Citation Impact
2.82

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Financial Performance-Based Clustering of Spa Enterprises in Slovakia

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Journal of risk and financial management
Global Healthcare and Medical Tourism
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article

Financial Performance-Based Clustering of Spa Enterprises in Slovakia

Marta Miškufová, Sylvia Jenčová, Petra Vašaničová, Jaroslav Korečko, Martina Košíková
article en
1 citations

Abstract

This paper presents a cluster analysis of 20 spa enterprises operating in Slovakia, based on key financial indicators for the years 2018 and 2023. A comparative time-based approach was adopted to capture changes in financial performance over time. The primary objective is to group the spas into homogeneous clusters to better understand their financial performance and strategic positioning. Ten financial indicators were selected across five dimensions: profitability (return on assets, return on sales), efficiency (assets turnover), cost efficiency (personnel cost ratio, cost-to-sales ratio, return on costs), liquidity (net working capital, current ratio), and indebtedness (equity to total liabilities ratio, debt ratio). Hierarchical cluster analysis—a widely used statistical method in unsupervised machine learning and a foundational technique in artificial intelligence—was employed, serving as a robust tool for data-driven decision making. The analysis identified distinct clusters of spas with similar financial characteristics. The results reveal meaningful segmentation that can inform resource allocation, performance benchmarking, and strategic planning. The findings provide spa managers, investors, and policy makers with a clearer understanding of financial patterns in the Slovak spa sector and offer practical implications for enhancing competitiveness and operational effectiveness.

Journal of risk and financial managementVol. 18(9)
University of Prešov (SK)
Slovenská Akadémia Vied, Kultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR, Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
Openalex Percentile: Top 9%
Global Healthcare and Medical Tourism
2.82
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