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Topics 19/11/2025

Greater transparency in Europe’s complex location structure with the GARBE LOFIN Score

The LOFIN Score: An analytical tool for evaluating logistics locations

With the LOFIN Score (Logistics Affinity Score), GARBE Research has developed a data-driven analytical model that assesses the attractiveness of municipalities at the Local Administrative Unit (LAU) level for logistics uses. In a market where the demands on logistics networks continue to grow and investment decisions rely ever more on robust data, the LOFIN Score provides a structured and objective basis for strategic location decisions.

A key feature of the model is its cross-country applicability: thanks to carefully selected and comparable evaluation factors, the LOFIN Score can be used consistently across all countries in which GARBE Industrial operates – and can easily be extended to additional European markets.

Key Findings

  • The LOFIN score evaluates the logistical attractiveness of municipalities across Europe based on quantitative indicators.
  • Thanks to standardized calculations, the model can be used to compare different countries and can be flexibly applied to other markets.
  • The score serves as a macro filter tool that creates transparency and supports data-driven investment decisions.

Strategic investment focus: From Core to Core+

The LOFIN Score particularly supports investment-driven location decisions. As part of the analysis, locations are classified according to their logistical suitability on a scale ranging from Core locations (LOFIN value 7) to Core+ opportunities (LOFIN values 5–6). Core locations are characterised by a high level of existing suitability and well-established structures, while Core+ regions represent emerging, dynamic markets with strong growth and value-creation potential. This classification enhances transparency and enables investment strategies to be targeted towards either stable core markets or high-growth future regions.

Data basis and indicators

The LOFIN Score is based on a carefully selected set of quantitative location indicators that combine economic performance, infrastructural connectivity and demographic dynamics. The following variables are specifically included in the calculation:

  • Household disposable income
  • Growth in disposable income
  • Number of highway junctions per LAU
  • Gross domestic product per capita (GDP/capita)
  • Gross value added at production prices (GVA)
  • Population density
  • Population growth (five-year average)
  • Business density
  • Employment density

These indicators capture the key dimensions of logistics location quality, providing a comprehensive picture of overall attractiveness that goes beyond isolated metrics.

Statistical processing: transformation and standardization

To ensure comparability between municipalities and avoid distortions due to different scales, data is processed in several stages:

  1. Box-Cox transformation of indicators:
    This statistical method reduces skewness in the distribution of variables, bringing them closer to a normal distribution. It mitigates the influence of extreme outliers and enhances interpretability.
  2. Min–max standardisation per municipality:
    Following the transformation, the values of individual indicators are rescaled to a uniform range. This ensures that indicators with large numerical spans do not dominate the overall result.
  3. Aggregation and second Box-Cox transformation:
    The standardised indicators are aggregated into a composite value for each municipality. To correct for remaining distributional distortions, a second Box-Cox transformation is applied.
  4. Final min–max scaling:
    Finally, the aggregated values are normalised to a scale from 1 to 7. This scale is intuitively interpretable: 1 represents low and 7 very high logistics location affinity.

Result: A uniform location assessment

The result is a uniform LOFIN Score for each municipality, ranging from 1 to 7. Municipalities with a score of 7 are particularly well suited for logistics uses – for example, due to above-average transport connectivity, strong economic dynamism and a robust business environment.

Areas with lower scores are typically located in structurally weaker regions or have less developed infrastructure, but may still offer attractive development potential, particularly in emerging markets.

 

Logistics Attractiveness in Europe with a Focus on the Netherlands–Germany Corridor based on GARBE LOFIN-Score

Figure: Logistics Attractiveness in Europe
with a Focus on the Netherlands–Germany Corridor based on GARBE LOFIN-Score

Macroeconomic perspective instead of object view

It is important to note that the LOFIN Score provides a macro-level assessment of location potential rather than a property-specific analysis of individual plots or assets.

It serves as a filtering and pre-selection tool to identify regions with a high logistics affinity. Based on this, more detailed analyses can then be conducted at the micro-location or property level – for example, regarding land availability, planning regulations or specific project requirements.

Conclusion: A data-driven compass for logistics real estate strategy

The LOFIN Score is a powerful tool for identifying, evaluating and prioritising locations for logistics uses. By combining economic, infrastructural and demographic indicators within a consistent model, it brings greater transparency to Europe’s complex logistics landscape. This provides investors and developers with a clear compass for shaping their strategies based on reliable data – whether to consolidate existing portfolios in core markets or to identify dynamic future regions with Core+ potential.

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iStock: Dark Earth Map With Glowing Details Of The City And Human Population Density Areas Like Europe 3D Illustration. kasezo

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