Performance Evaluation Method of Public Administration Department Based on Improved DEA Algorithm.

Area of Science:

• Public Administration
• Operations Research
• Performance Management

Background:

• Traditional performance evaluation methods for public administration departments often face quality challenges.
• The Data Envelopment Analysis (DEA) model is crucial for assessing efficiency and effectiveness in public services.
• Public service satisfaction is a key indicator for evaluating administrative performance.

Purpose of the Study:

• To propose an improved DEA algorithm for enhancing the performance evaluation of public administration departments.
• To address the quality issues in current performance evaluation systems.
• To provide a foundation for long-term development and performance improvement in public administration.

Main Methods:

• Utilizing an improved Data Envelopment Analysis (DEA) algorithm as the core methodology.
• Employing public service satisfaction as a primary parameter within the DEA model.
• Conducting empirical research on eight social security departments to test the DEA model's effectiveness.

Main Results:

• Five out of eight social security departments were found to be DEA effective (Departments 2, 3, 4, 5, and 6).
• Three departments were identified as non-DEA effective (Departments 1, 7, and 8).
• Public satisfaction and total service cost were confirmed to significantly influence performance quality.

Conclusions:

• The improved DEA algorithm offers a robust method for evaluating public administration performance.
• Optimizing public services and enhancing service satisfaction are critical for improving evaluation quality.
• Balancing various influencing factors, including public satisfaction and service costs, is essential for maximizing performance evaluation quality.