Interpretive structural modelling of leadership development strategies in order to establish and develop digital universities

Objective: The digital university is an institution that, by leveraging modern technologies, not only provides specialized services to its stakeholders but also expands its scope of activities and impact relative to classic universities. For this reason, the development of university leadership for managers capable of effectively achieving the distinguished characteristics and specific goals of these universities is of great importance. Accordingly, the purpose of this study was to model the structural-interpretive strategies for developing leadership to create and expand digital universities. This research is applied in terms of its goal and is considered mixed-methods research in terms of its methodology.
Method: The identification of leadership development strategies was conducted through semi-structured interviews based on theoretical saturation with the participation of 15 faculty members at Shahid Beheshti University, serving as the research field. The validity and reliability of the interviews were confirmed using relative content validity and Cohen's kappa index, respectively. In the quantitative part of the modeling process, the opinions of 63 faculty members with management experience were utilized through convenience non-probability sampling. The validity and reliability of the questionnaire were confirmed using content validity and a test-retest method, respectively. Coding the interviews using MAXQDA software led to the identification of strategies for developing university leadership.
Conclusion: The modeling of identified indicators was performed using structural-interpretive methods and MIC-MAC analysis. Thirteen identified strategies, as outcomes of coding, include: forming think tanks; structural empowerment; self-development processes; talent management; opportunity selection; succession planning; feedback mandate; program integration; systematic/regulated training; knowledge sharing; enhancing resilience levels; systemic thinking; and process reconstruction. The use of structural-interpretive methods and MIC-MAC analysis helped to position the thirteen identified leadership development strategies into six levels for establishing a conceptual relationship among them. These levels are opportunity selection, succession planning, enhancing resilience levels and process reconstruction, talent management, and program integration. Each category contains one or more strategies. Under each strategy, components are placed that are related to expanding the concept of strategy in the development of leadership for digital universities.

Objective: The digital university is an institution that, by leveraging modern technologies, not only provides specialized services to its stakeholders but also expands its scope of activities and impact relative to classic universities. For this reason, the development of university leadership for managers capable of effectively achieving the distinguished characteristics and specific goals of these universities is of great importance. Accordingly, the purpose of this study was to model the structural-interpretive strategies for developing leadership to create and expand digital universities. This research is applied in terms of its goal and is considered mixed-methods research in terms of its methodology.
Method: The identification of leadership development strategies was conducted through semi-structured interviews based on theoretical saturation with the participation of 15 faculty members at Shahid Beheshti University, serving as the research field. The validity and reliability of the interviews were confirmed using relative content validity and Cohen's kappa index, respectively. In the quantitative part of the modeling process, the opinions of 63 faculty members with management experience were utilized through convenience non-probability sampling. The validity and reliability of the questionnaire were confirmed using content validity and a test-retest method, respectively. Coding the interviews using MAXQDA software led to the identification of strategies for developing university leadership.
Conclusion: The modeling of identified indicators was performed using structural-interpretive methods and MIC-MAC analysis. Thirteen identified strategies, as outcomes of coding, include: forming think tanks; structural empowerment; self-development processes; talent management; opportunity selection; succession planning; feedback mandate; program integration; systematic/regulated training; knowledge sharing; enhancing resilience levels; systemic thinking; and process reconstruction. The use of structural-interpretive methods and MIC-MAC analysis helped to position the thirteen identified leadership development strategies into six levels for establishing a conceptual relationship among them. These levels are opportunity selection, succession planning, enhancing resilience levels and process reconstruction, talent management, and program integration. Each category contains one or more strategies. Under each strategy, components are placed that are related to expanding the concept of strategy in the development of leadership for digital universities.