Designing a Performance Management Model Based on Think Tank Network Participation

Document Type : Original Article (Qualitative)

Authors

1 Department of Public Administration, Ki.C, Islamic Azad University, Kish, Iran.

2 Department of Public Administration, CT.C., Islamic Azad University, Tehran, Iran

3 Department of Business Management, ShQ.C., Islamic Azad University, Shahr-e Qods, Iran.

10.22034/jnamm.2026.538532.1107
Abstract
The aim of this study is to design a performance management model based on the participation of think tank networks. The research method was qualitative. The statistical population consisted of 19 university professors, public management executives, and experts, who were selected through purposive sampling. The data collection tool in the qualitative phase was semi-structured interviews. In the qualitative section, the data were analyzed using grounded theory.

In the qualitative phase, 543 initial codes were extracted through grounded theory and classified into 122 indicators, 32 components, and ultimately 13 dimensions. The qualitative analysis led to the formation of a model of “government performance management based on think tank network participation,” which includes five key dimensions: first, identifying and formulating the organization’s problem system; second, designing and validating organizational performance indicators; third, monitoring and measuring organizational performance; fourth, analyzing performance and providing feedback to the organization; and fifth, improving organizational performance and organizational learning.



In general, government performance management based on think tank network participation provides a systematic response to the inefficiencies of traditional and linear approaches to public performance evaluation. From problem identification to organizational learning, this model outlines a “participatory-feedback” cycle in which think tanks and elite networks are no longer merely external observers or critics, but strategic partners of government in the path toward transparency, intelligent monitoring, and continuous improvement. This approach, while compensating for structural weaknesses in the existing evaluation system, creates a foundation for learning-oriented, accountable, and problem-centered governance.

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Articles in Press, Accepted Manuscript
Available Online from 21 December 2026

  • Receive Date 18 May 2025
  • Revise Date 13 June 2026
  • Accept Date 01 August 2026