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Analyzing the Research Grant Process in Iran’s National Elites Foundation: An Approach Based on Process Mining and Machine Learning

Publish Year: 1402
Type: Journal paper
Language: English
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Document National Code:

JR_JIJMS-16-2_007

Index date: 12 March 2023

Analyzing the Research Grant Process in Iran’s National Elites Foundation: An Approach Based on Process Mining and Machine Learning abstract

Analyzing the event logs extracted from the process-aware information systems provide critical insights into improving the organizational processes. This case study reports the essential findings and lessons from a process mining project run in analyzing the postdoctoral research grant process in Iran’s National Elites Foundation (INEF). Different deductions are reached by exploring the process participants’ activities in the INEF web portal, including (1) the organizational inefficiencies exposed through the process mining techniques, where the most time-consuming activities are detected and suggested to the domain experts, and (2) the decision tree technique applied in determining how the successful applicants are scored. The extracted rules indicate an 18% application admission with a final score of more than 403. This article contributes to interpreting the behavioral patterns in INEF and determining who among the applicants has a higher chance of receiving the grant, supporting the policymakers and managers to assign rational budgeting and adopt appropriate human resource strategies.

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Analyzing the Research Grant Process in Iran’s National Elites Foundation: An Approach Based on Process Mining and Machine Learning authors

منصوره یاری ایلی

Department of Computer Engineering, Faculty of Technology and Engineering, University of Qom, Iran

جلال رضایی نور

Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Iran

امیر جلالی بیدگلی

Department of Computer Engineering, Faculty of Technology and Engineering, University of Qom, Iran

شهریار بیژنی

Department of Mathematics and Computer Science, Shahed University, Iran

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