A Process Mining Framework for University of Tehran Using a Meta-Ethnography Approach

Document Type : Research Paper

Authors

1 Associate Professor, Leadership and Human Capital Department, Public Management and Organizational Sciences Faculty, Collage of Management, University of Tehran,Tehran, Iran

2 PhD Candidate, University of Tehran Aras international campus, Tehran, Iran

3 Associate Professor, Faculty of Management and Accounting, Farabi Campus, University of, Tehran, Qom, Iran

Abstract
Objective: Digital transformation in higher education necessitates empirical evidence for managerial decision-making. This study designed and validated a comprehensive Process Mining (PM) framework for the University of Tehran to bridge the gap between technical analytics and institutional governance.
Methodology: A multi-method approach was employed, including a systematic review, meta-ethnography of eight reference models (e.g., CRISP-PM, L* Lifecycle), and a qualitative case study. A synthesized 6-phase conceptual model was refined into a 10-phase operational framework through semi-structured interviews with 18 academic experts.
Findings: Effective PM implementation requires alignment across technical, managerial, and learning layers. The framework was applied to the "PhD Proposal Approval" process using the Heuristic Miner algorithm. Analysis revealed a 325-day average cycle time caused by structural bottlenecks and manual plagiarism checks. Monte Carlo simulations demonstrated that process optimization and parallelization could yield a 43% efficiency gain, reducing the duration to under 200 days.
Conclusion: The proposed 10-phase framework elevates PM from a diagnostic tool to a robust governance protocol. Institutionalizing this model via real-time monitoring dashboards facilitates data-driven governance and enhances the student academic experience at the University of Tehran.

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Articles in Press, Accepted Manuscript
Available Online from 05 September 2026

  • Receive Date 26 November 2025
  • Revise Date 31 August 2026
  • Accept Date 01 September 2026