Measuring hospitality efficiency in Europe: a dea benchmarking approach
Purpose – This paper re-examines the relative efficiency of the European hospitality industry by
applying DEA to 35 countries and identifies benchmarking insights into performance differences.
Methodology/Design/Approach – Three DEA models (CCR, slack-based, and super-efficiency) are
applied to publicly available Eurostat data on labour and bed capacity (inputs) and tourist arrivals
and nights spent (outputs), with an additional VRS (BCC) specification used as a robustness check.
The super-efficiency model allows a full ranking of countries beyond the efficiency frontier.
Findings – Only two countries (Iceland and Malta) lie on the efficiency frontier, with Iceland
ranked highest under the super-efficiency model. Most countries exhibit decreasing returns to scale
and substantial labour inefficiencies, suggesting significant room for improvement. Benchmarks
are provided to help lagging countries identify relative performance gaps.
Originality of the research – This study extends DEA-based benchmarking to the national level for
the European hospitality sector, combining multiple DEA models with slack-based diagnostics and
scale-efficiency analysis. By identifying frontier performers and benchmarking gaps, it contributes
to the understanding of cross-country differences in hospitality efficiency and supports evidence-
based analysis of tourism performance.
applying DEA to 35 countries and identifies benchmarking insights into performance differences.
Methodology/Design/Approach – Three DEA models (CCR, slack-based, and super-efficiency) are
applied to publicly available Eurostat data on labour and bed capacity (inputs) and tourist arrivals
and nights spent (outputs), with an additional VRS (BCC) specification used as a robustness check.
The super-efficiency model allows a full ranking of countries beyond the efficiency frontier.
Findings – Only two countries (Iceland and Malta) lie on the efficiency frontier, with Iceland
ranked highest under the super-efficiency model. Most countries exhibit decreasing returns to scale
and substantial labour inefficiencies, suggesting significant room for improvement. Benchmarks
are provided to help lagging countries identify relative performance gaps.
Originality of the research – This study extends DEA-based benchmarking to the national level for
the European hospitality sector, combining multiple DEA models with slack-based diagnostics and
scale-efficiency analysis. By identifying frontier performers and benchmarking gaps, it contributes
to the understanding of cross-country differences in hospitality efficiency and supports evidence-
based analysis of tourism performance.
Publisert i Tourism and Hospitality Management, 2026
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