Limitations of Two-Dimensional Indicators and unconstrained radial DEA models in Evaluating Judicial Efficiency: Insights from Poland's Appellate Court System

Motivation: Two-dimensional efficiency indicators provide only a narrow perspective on a system’s functional efficiency, a limitation that is addressed by multidimensional methods such as the widely used Data Envelopment Analysis. However, the uncritical application of this class of methods—which appears to be a common practice in judicial efficiency research—can result in misleading conclusions regarding efficiencies of Decision-Making Units (DMUs). Aim: The aim of this study is to evaluate the technical efficiency of Poland's appellate court system in the first two decades of the 21st century (years 2002-2021) using a constrained version of Data Envelopment Analysis (DEA) applied to time-series data. Unlike two-dimensional judicial performance indicators, such an approach facilitates a comprehensive assessment of the aggregated efficiency of the legal, administrative, procedural, organizational, and economic macro-frameworks—consistently implemented across all appellate courts—which collectively shape the system’s performance during each year under review. Results: The outcomes of this research show the fundamental shortcomings of classical applications of DEA, raising valid concerns about the reliability and interpretability of the outcomes derived from this approach. To mitigate these challenges, it presents a novel procedure specifically aimed at addressing these limitations in evaluating judicial efficiency, which is next successfully implemented.

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Publication Details

Journal
Ekonomia i Prawo
Published
2025-12-30
DOI
https://doi.org/10.12775/eip.2025.20
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

Limitations of Two-Dimensional Indicators and unconstrained radial DEA models in Evaluating Judicial Efficiency: Insights from Poland's Appellate Court System

Waldemar Florczak
Ekonomia i Prawo
Efficiency Analysis Using DEA
article

Limitations of Two-Dimensional Indicators and unconstrained radial DEA models in Evaluating Judicial Efficiency: Insights from Poland's Appellate Court System

Waldemar Florczak
article en

Abstract

Motivation: Two-dimensional efficiency indicators provide only a narrow perspective on a system’s functional efficiency, a limitation that is addressed by multidimensional methods such as the widely used Data Envelopment Analysis. However, the uncritical application of this class of methods—which appears to be a common practice in judicial efficiency research—can result in misleading conclusions regarding efficiencies of Decision-Making Units (DMUs). Aim: The aim of this study is to evaluate the technical efficiency of Poland's appellate court system in the first two decades of the 21st century (years 2002-2021) using a constrained version of Data Envelopment Analysis (DEA) applied to time-series data. Unlike two-dimensional judicial performance indicators, such an approach facilitates a comprehensive assessment of the aggregated efficiency of the legal, administrative, procedural, organizational, and economic macro-frameworks—consistently implemented across all appellate courts—which collectively shape the system’s performance during each year under review. Results: The outcomes of this research show the fundamental shortcomings of classical applications of DEA, raising valid concerns about the reliability and interpretability of the outcomes derived from this approach. To mitigate these challenges, it presents a novel procedure specifically aimed at addressing these limitations in evaluating judicial efficiency, which is next successfully implemented.

Ekonomia i PrawoVol. 24(4)
Jagiellonian University (PL)
Peace, Justice and strong institutions
Openalex Percentile: Top 26%
Efficiency Analysis Using DEA
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Limitations of Two-Dimensional Indicators and unconstrained radial DEA models in Evaluating Judicial Efficiency: Insights from Poland's Appellate Court System — Waldemar Florczak · Ekonomia i Prawo (2025) | TGRS Research Map | TGRS