Identifying and Stratifying Factors Influencing Digital Leadership in Higher Education Systems Using Interpretive Structural Modeling (ISM)
Subject Areas : Human resource management
Mohammad Naghi Imani
1
,
Elham Ghobadi
2
,
friba hanifi
3
1 - Associate Professor, Department of Educational Management, Faculty of Educational Sciences and Counseling, Islamic Azad University, Roudehen Branch, Iran. (Corresponding Author)
2 - PhD Student, Department of Educational Management, Islamic Azad University, Damavand Branch, Iran
3 - Associate Professor, Department of Educational Management, Faculty of Educational Sciences and Management, Roudehen Azad University, Tehran, Iran.
Keywords: Digital Leadership, Higher Education, Interpretive Structural Modeling (ISM), Digital Transformation ,
Abstract :
This study aims to identify and stratify the factors influencing digital leadership in higher education systems. The research adopts a mixed-methods approach, consisting of qualitative and quantitative phases. In the qualitative phase, content analysis of semi-structured interviews with 15 academic experts was conducted to extract the key components of digital leadership. In the quantitative phase, interpretive structural modeling (ISM) and MICMAC analysis were employed to stratify the identified factors and determine their interrelationships. The results revealed that the factors influencing digital leadership can be categorized into 10 main components: vision and strategy, digital culture, digital security, digital communication, digital structure, digital economy, digital intelligence, digital literacy, digital leadership competencies, and stakeholder engagement. These factors were classified into four levels: independent variables (vision and strategy), linkage variables (digital culture and stakeholder engagement), dependent variables (digital economy, digital intelligence, digital literacy, and competencies), and foundational variables (digital security and communication). The MICMAC analysis further confirmed the mutual influence of these factors. This study demonstrates that the success of digital leadership in higher education requires simultaneous attention to various factors at different levels. The findings can assist policymakers and educational administrators in designing localized models for digital leadership.
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