By Topic

Performance Evaluation of the Judicial System in Taiwan Using Data Envelopment Analysis and Decision Trees

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chih-Fong Tsai ; Dept. of Inf. Manage., Nat. Central Univ., Jhongli, Taiwan ; Jung-Hsiang Tsai

A time-honored maxim says that the judicial system is the last line of defending justice. Its performance has a great impact on how the citizen trust or distrust their state apparatus in a democracy. Technically speaking, the judicial process and its procedures are very complicated and the purpose of the whole system is to go through the law and due process to protect civil liberties and rights and to defend the public good of the nation. Therefore, it is worthwhile to assess the performance of judicial institutions in order to advance the efficiency and quality of judicial verdict. This paper combines data envelopment analysis (DEA) and decision trees to achieve this objective. In particular, DEA is first of all used to evaluate the relative efficiency of 18 district courts in Taiwan. Then, the efficiency scores and the overall efficiency of each decision making units are then used to train a decision tree model. Specifically, C5.0, CART, and CHAID decision trees are constructed for comparisons. The decision rules in the best decision tree model can be used to distinguish between efficient units and inefficient units and allow us to understand important factors affecting the efficiency of judicial institutions. The experimental result shows that C5.0 performs the best for predicting (in) efficient judicial institutions, which provides 80.37% average accuracy.

Published in:

Computer Engineering and Applications (ICCEA), 2010 Second International Conference on  (Volume:2 )

Date of Conference:

19-21 March 2010