Digital Leadership and System-Level Transformation in Indonesian Higher Education: A Mixed- Methods Study of Institutional Change and Governance

Digital Leadership and System-Level Transformation in Indonesian Higher Education: A Mixed- Methods Study of Institutional Change and Governance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Digital Leadership and System-Level Transformation in Indonesian Higher Education: A Mixed- Methods Study of Institutional Change and Governance Nur Aedi, Bilkis Aulia Luxfiati, Nurrohmatul Amaliyah, Li Bing Wei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9337496/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Purpose. This study aims to examine the role of digital leadership in driving system-level transformation in Indonesian higher education. It seeks to understand how leadership capabilities influence organizational innovation and adaptability, and how these effects contribute to broader transformation through governance quality and institutional readiness. Design/methodology/approach. A national mixed-method approach was employed. Quantitative data were collected from 312 university leaders across Indonesia and analyzed using structural equation modeling (SEM-PLS). This was complemented by qualitative data from case studies and focus group discussions to provide contextual insights and triangulation of findings. Findings The results indicate that digital leadership has a significant positive effect on organizational innovation and institutional adaptability. Furthermore, system-level transformation is indirectly influenced by digital leadership through the mediating roles of governance quality and institutional readiness. The findings highlight that effective digital leadership must be aligned with policy frameworks and supported by institutional capacity to achieve systemic impact. Practical implications. The study provides actionable insights for policymakers and higher education leaders. It suggests the need for strengthening digital leadership competencies, enhancing governance frameworks, and investing in institutional readiness to support coordinated transformation. The findings are particularly relevant for developing countries seeking to improve the global competitiveness of their higher education systems. Originality/value. This study contributes to the literature by integrating digital leadership and system-level transformation within a multi-level framework. It offers empirical evidence from a developing country context using a mixed-method design, addressing a significant gap in existing research that has largely focused on institutional-level analysis in Western settings. Digital leadership higher education system-level transformation governance SEM-PLS Indonesia 1. Introduction The rapid advancement of digital technologies has transformed higher education systems globally, requiring institutions to adapt to new modes of teaching, governance, and competition. In Indonesia, disparities in digital readiness and fragmented governance structures present significant challenges for systemic transformation. While prior research has explored digital transformation at the institutional level, limited studies have examined how digital leadership influences transformation at the system level, particularly in developing countries. This study addresses this gap by investigating the relationship between digital leadership and system-level transformation through a national mixed-method approach (Ahmad & Sulastri 2023). The rapid advancement of digital technologies has fundamentally reshaped the landscape of higher education worldwide, compelling institutions to rethink their pedagogical models, governance structures, and strategic priorities. The proliferation of artificial intelligence, big data analytics, cloud computing, and digital learning platforms has not only transformed how knowledge is produced and disseminated but has also intensified global competition among universities. In this evolving context, higher education systems are no longer insulated national entities; rather, they are embedded within a dynamic and interconnected global ecosystem that demands continuous innovation, agility, and responsiveness. Consequently, the ability of higher education institutions to navigate digital transformation has become a critical determinant of their sustainability and global competitiveness. (Altbach & Salmi 2011) Central to this transformation is the concept of digital leadership, which has emerged as a pivotal factor in enabling organizations to harness the potential of digital technologies effectively. Digital leadership extends beyond the mere adoption of technological tools; it encompasses the strategic vision, cultural orientation, and governance capabilities required to align digital initiatives with institutional goals (Arifin 2022). Leaders in higher education are increasingly expected to act as change agents who can integrate digital innovation into core academic and administrative functions while fostering a culture of adaptability and continuous learning. However, despite the growing recognition of its importance, digital leadership remains an evolving and conceptually fragmented field, with varying definitions and limited empirical validation, particularly in non-Western contexts (Avolio & Kahai 2003). In parallel, the notion of system-level transformation has gained prominence in the discourse on higher education reform. Unlike institutional-level change, which focuses on internal organizational processes, system-level transformation involves coordinated and structural changes across the entire higher education ecosystem, including policy frameworks, governance mechanisms, funding models, and inter-institutional collaboration (Avolio et al. 2014). Such transformation is essential for addressing complex and systemic challenges, such as disparities in access, quality assurance, and digital infrastructure. Importantly, system-level transformation requires alignment between micro-level leadership practices and macro-level policy interventions, highlighting the need for an integrated analytical framework that bridges these dimensions (Azman & Abdullah 2021). 1.1. Background Research Area In the context of Indonesia, the urgency of digital transformation in higher education is particularly pronounced. As one of the largest higher education systems in Southeast Asia, Indonesia faces significant challenges related to uneven institutional capacity, regional disparities, and fragmented governance structures (Bass & Riggio 2006). While the government has introduced various policies aimed at promoting digitalization and innovation, the implementation of these initiatives has been uneven, often hindered by limited leadership capacity, inadequate infrastructure, and lack of coordination among stakeholders. As a result, many institutions struggle to transition from traditional models of operation to more digitally integrated and globally competitive systems. This situation underscores the critical role of digital leadership not only at the institutional level but also as a catalyst for broader system-level transformation (Bolden et al. 2008). Despite the growing body of literature on digital transformation and leadership in higher education, several critical gaps remain. First, existing studies predominantly focus on micro-level analyses, examining the impact of digital leadership on organizational performance, teaching practices, or student outcomes within individual institutions (Brown 2021). While these studies provide valuable insights, they often overlook the broader systemic implications of leadership practices, particularly how they contribute to coordinated transformation across multiple institutions and governance levels. Second, there is a lack of empirical research that integrates quantitative and qualitative approaches to capture the complexity of digital transformation processes. Most studies rely on either survey-based methods or case studies, limiting their ability to provide comprehensive and generalizable findings (Bryman 2007). Third, and perhaps most importantly, there is a notable scarcity of research focusing on developing country contexts, including Indonesia. Much of the existing literature is grounded in Western higher education systems, which differ significantly in terms of resources, governance structures, and socio-economic conditions. As such, the applicability of these findings to contexts like Indonesia remains uncertain (Brynjolfsson & McAfee 2017). This gap is particularly problematic given that developing countries often face unique challenges and opportunities in their digital transformation journeys, necessitating context-specific analyses and policy recommendations (Castells 2010). Furthermore, the relationship between digital leadership and system-level transformation remains underexplored in the literature. While some studies have acknowledged the importance of leadership in driving organizational change, few have examined how leadership practices interact with governance structures, policy frameworks, and institutional readiness to produce system-wide transformation (Chatterjee & Bhattacharjee 2020). This limitation points to the need for a multi-level analytical approach that considers the interplay between individual leadership capabilities, organizational dynamics, and broader systemic factors (Chen & Zhang 2022). Addressing these gaps, this study aims to investigate the role of digital leadership in driving system-level transformation in Indonesian higher education through a national mixed-method approach. By integrating quantitative data from a large-scale survey of university leaders with qualitative insights from case studies and focus group discussions, the study seeks to provide a comprehensive and nuanced understanding of how digital leadership influences transformation processes at multiple levels. Specifically, the study examines the direct effects of digital leadership on organizational outcomes such as innovation and adaptability, as well as the mediating roles of governance quality and institutional readiness in facilitating system-level change (Boer et al. 2007). The contribution of this study is threefold. First, it advances the theoretical understanding of digital leadership by situating it within a multi-level framework that links individual, organizational, and systemic dimensions of transformation (Dwivedi 2021). This approach addresses the fragmentation in existing literature and provides a more holistic perspective on the role of leadership in digital transformation. Second, the study offers robust empirical evidence based on a mixed-method design, enhancing the validity and generalizability of its findings (Fullan & Scott 2009). By combining quantitative and qualitative data, the research captures both the measurable impacts of digital leadership and the contextual factors that shape its effectiveness (Garrison 2017). Third, and most critically, the study provides actionable insights for policymakers and institutional leaders in Indonesia and similar contexts. By identifying key mediating factors such as governance quality and institutional readiness, the research highlights the importance of coordinated policy interventions and capacity-building initiatives in achieving system-level transformation. These findings have significant implications for the design and implementation of digital transformation strategies, particularly in developing countries where resource constraints and structural challenges are prevalent (Goleman 2000). In conclusion, as higher education systems continue to navigate the complexities of digital transformation, the role of leadership becomes increasingly central. Understanding how digital leadership can drive not only organizational change but also system-level transformation is essential for developing effective and sustainable strategies. This study responds to this need by providing a comprehensive analysis of digital leadership in the Indonesian higher education context, offering both theoretical and practical contributions to the field (Greenhalgh 2017). 1.2. Problem Statement The accelerating pace of digital transformation has fundamentally reshaped higher education systems worldwide, compelling institutions to adapt to rapidly evolving technological, economic, and social environments. Universities are increasingly expected to integrate digital technologies into teaching, research, and governance processes to remain competitive in a global knowledge economy (Bond et al., 2018; Selwyn, 2016). However, despite the widespread recognition of digital transformation as a strategic priority, its implementation across higher education systems remains uneven and fragmented, particularly in developing countries. This unevenness raises critical concerns regarding institutional capacity, policy coherence, and the effectiveness of leadership in managing systemic change (Gunawan 2023). Digital leadership has emerged as a central concept in addressing the complexities of transformation in the digital era. It refers to the capacity of leaders to envision, implement, and sustain digital innovation within organizations while aligning technological initiatives with broader strategic goals (Avolio et al., 2000; Kane et al., 2015). In higher education, digital leadership involves not only the adoption of new technologies but also the transformation of organizational culture, governance structures, and decision-making processes (Zhu, 2015). Despite its importance, existing research on digital leadership remains fragmented and predominantly focused on micro-level outcomes, such as teaching effectiveness, technology adoption, and organizational performance (El Sawy et al., 2016). This narrow focus limits the understanding of how leadership contributes to broader system-level transformation (Hair et al. 2022). System-level transformation in higher education refers to coordinated and structural changes across institutions, governance frameworks, and policy environments. It encompasses reforms in funding mechanisms, quality assurance systems, regulatory structures, and inter-institutional collaboration (Marginson, 2016). Such transformation is essential for addressing systemic challenges, including inequalities in access, disparities in institutional capacity, and the need for digital infrastructure development. However, achieving system-level transformation requires alignment between leadership practices at the institutional level and policy interventions at the national level. Without such alignment, transformation efforts often remain fragmented and fail to produce sustainable outcomes (Fullan, 2016). In Indonesia, the challenges associated with digital transformation are particularly complex. As one of the largest higher education systems in Southeast Asia, Indonesia is characterized by significant diversity in institutional capacity, geographical distribution, and governance structures. While some universities have successfully adopted digital technologies and innovative practices, many others continue to face limitations in infrastructure, human resources, and organizational readiness (World Bank, 2020). Furthermore, the governance of higher education in Indonesia involves multiple stakeholders, including government agencies, accreditation bodies, and institutional leaders, which can result in fragmented policy implementation and coordination challenges (Hallinger 2011). These conditions highlight the need for a more integrated approach to understanding how digital leadership can drive system-level transformation (Harvey 2006). Another critical gap in the literature is the lack of empirical research that examines the relationship between digital leadership and system-level transformation in developing country contexts. Most existing studies are based on Western higher education systems, where institutional environments, governance structures, and resource availability differ significantly from those in countries like Indonesia (Altbach & de Wit, 2020). Consequently, the applicability of these findings to developing contexts remains limited (Heifetz 1994). There is a pressing need for context-specific research that takes into account the unique challenges and opportunities faced by higher education systems in developing countries (Hidayat 2022). Moreover, the mechanisms through which digital leadership influences system-level transformation remain underexplored. While leadership is widely recognized as a key driver of organizational change, there is limited understanding of the mediating factors that facilitate or constrain this process (Hitt et al. 2017). Governance quality and institutional readiness are particularly important in this regard. Governance quality refers to the effectiveness of policies, regulatory frameworks, and coordination mechanisms that guide institutional behavior, while institutional readiness encompasses the availability of resources, capabilities, and organizational culture necessary to implement digital initiatives (North, 1990; Weiner, 2009). The interaction between these factors and digital leadership is complex and dynamic, yet it has not been sufficiently examined in existing research (Hood 1991). In addition, methodological limitations in prior studies further constrain the development of comprehensive insights (Kezar 2014). Many studies rely on single-method approaches, either quantitative or qualitative, which limits their ability to capture the multifaceted nature of digital transformation. Quantitative studies often provide generalizable findings but lack contextual depth, while qualitative studies offer rich insights but may not be representative of broader trends. A mixed-method approach, which integrates quantitative and qualitative data, is therefore essential to provide a more holistic understanding of the relationship between digital leadership and system-level transformation (Creswell & Plano Clark, 2018). Given these gaps, there is a clear need for research that integrates digital leadership, governance quality, and institutional readiness within a unified analytical framework to explain system-level transformation in higher education (Kotter 1996). Such research should provide both theoretical and empirical contributions, offering insights that can inform policy and practice (Kurniawan 2021). In particular, understanding how leadership practices can be aligned with governance structures and institutional capacities is critical for achieving sustainable transformation (Lase 2019). Therefore, this study addresses a central problem: the lack of an integrated, evidence-based understanding of how digital leadership drives system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness. By employing a national mixed-method approach, this research seeks to bridge the gap between theory and practice, providing a comprehensive analysis of the factors that enable or constrain digital transformation at multiple levels (Leithwood & Jantzi 2005). The findings are expected to contribute to the development of more effective policies and leadership strategies, ultimately enhancing the global competitiveness and sustainability of higher education systems in Indonesia and similar contexts. 1.3. Research Gap Despite the rapid expansion of research on digital transformation and leadership in higher education, substantial conceptual, empirical, and methodological gaps persist, limiting a comprehensive understanding of how digital leadership contributes to system-level transformation (Mulyadi 2022). While existing studies provide valuable insights into organizational change, much of the literature remains fragmented and confined to specific analytical levels, particularly focusing on individual institutions rather than the broader higher education system (Nasution 2023). A primary gap lies in the level of analysis adopted in prior research. Most studies on digital leadership in higher education emphasize micro-level dynamics, such as leadership influence on teaching effectiveness, technology adoption, and institutional performance (Bond et al., 2018; Zhu, 2015). Although these studies enhance understanding of internal transformation processes, they fail to account for the interconnected and systemic nature of higher education. Institutions operate within complex ecosystems shaped by governance structures, regulatory frameworks, and policy environments. Consequently, there is limited empirical evidence explaining how leadership practices at the institutional level translate into coordinated transformation across the system. This absence of a multi-level analytical perspective restricts the explanatory power of existing models and undermines their relevance for large-scale policy reform (Northouse 2019). A second critical gap concerns the lack of conceptual integration between digital leadership and system-level transformation. These two constructs have largely evolved in parallel within the literature. Digital leadership is typically associated with innovation, strategic alignment, and digital capability development (Kane et al., 2015; El Sawy et al., 2016), whereas system-level transformation is examined through the lens of governance, policy reform, and structural change (Marginson, 2016). The absence of an integrated framework that explicitly links these constructs creates a theoretical disconnect, making it difficult to understand how leadership capabilities influence systemic outcomes. As a result, existing research often overlooks the mechanisms through which digital leadership interacts with governance systems and policy environments to produce coordinated transformation across institutions (Nugroho 2021). Another significant gap relates to the contextual bias of existing studies. The majority of empirical research on digital leadership and higher education transformation is conducted in developed countries, particularly in North America and Europe (Altbach & de Wit, 2020). These contexts are characterized by relatively stable governance systems, advanced digital infrastructure, and greater resource availability. In contrast, developing countries such as Indonesia face distinct challenges, including uneven institutional capacity, limited digital infrastructure, and fragmented policy implementation (World Bank, 2020). The underrepresentation of developing country contexts in the literature raises concerns about the generalizability of existing findings. Without context-specific research, theoretical models derived from developed countries may not adequately capture the realities of higher education systems in emerging economies (OECD 2020). Furthermore, there is a notable gap in understanding the mediating mechanisms that link digital leadership to system-level transformation. While leadership is widely recognized as a critical driver of organizational change, the pathways through which it influences broader systemic outcomes remain underexplored. Governance quality and institutional readiness are particularly important mediating factors in this relationship (Peters & Besley 2018). Governance quality refers to the effectiveness of regulatory frameworks, policy coherence, and coordination mechanisms that guide institutional behavior (North, 1990), while institutional readiness encompasses the availability of resources, capabilities, and organizational culture required to implement digital initiatives (Weiner, 2009). Despite their theoretical relevance, these variables have received limited empirical attention in studies of higher education transformation, resulting in an incomplete understanding of how leadership translates into system-wide change (Porter 2008). In addition to conceptual and contextual limitations, methodological gaps further constrain the development of knowledge in this field. Many studies rely on single-method approaches, either quantitative surveys or qualitative case studies, which limits their ability to capture the complexity of digital transformation processes (Prasetyo 2020). Quantitative studies provide generalizable findings but often lack contextual depth, whereas qualitative studies offer rich insights but may not be representative of broader patterns (Creswell & Plano Clark, 2018). The lack of mixed-method research represents a significant limitation, as such approaches are better suited to examining complex, multi-level phenomena like system-level transformation. Without methodological integration, the literature remains fragmented and insufficiently robust to inform policy and practice (Rahman 2022). Moreover, there is a lack of research that generates policy-relevant and actionable insights. Much of the existing literature focuses on theoretical contributions without translating findings into practical implications for policymakers and institutional leaders (Rogers 2003). This limitation is particularly critical in the context of digital transformation, where effective implementation requires coordinated efforts across multiple levels of governance (Santoso 2023). Studies that bridge the gap between theory and practice are essential for informing the design of policies and strategies that can support sustainable transformation in higher education systems (Fullan, 2016). Finally, the literature lacks national-level empirical evidence that captures the diversity and complexity of higher education systems. Most studies are based on single-institution or small-sample analyses, limiting their ability to generalize findings across different institutional contexts. A national-level approach is necessary to provide a more comprehensive understanding of system-level transformation, particularly in countries with diverse higher education landscapes like Indonesia (Schwab 2016). Such an approach enables the identification of patterns and relationships that are not visible in smaller-scale studies, thereby enhancing the validity and applicability of research findings (Scott 2014). In response to these gaps, this study adopts a multi-level, mixed-method approach to examine the role of digital leadership in driving system-level transformation in Indonesian higher education. By integrating digital leadership, governance quality, and institutional readiness within a unified analytical framework, the study seeks to bridge the divide between micro-level leadership practices and macro-level policy outcomes (Senge 2006). Furthermore, by focusing on a developing country context and utilizing national-level data, the research provides empirically grounded and contextually relevant insights that contribute to both theoretical advancement and practical policy development (Setiawan 2021). 1.4. Research Objectives The rapid digitalization of higher education has created an urgent need for integrated leadership and governance approaches that can support system-wide transformation. While prior studies have highlighted the importance of digital leadership in enhancing organizational performance and innovation, there remains limited empirical understanding of how such leadership contributes to transformation at the system level, particularly in developing country contexts (Kane et al., 2015; Zhu, 2015). In addition, the interaction between leadership, governance quality, and institutional readiness has not been sufficiently examined, despite its critical importance for achieving sustainable and coordinated transformation (North, 1990; Weiner, 2009). Addressing these gaps, this study aims to provide a comprehensive and empirically grounded analysis of digital leadership and system-level transformation in Indonesian higher education (Smith & Adams 2008). 1.5. General Objective The primary objective of this study is to examine how digital leadership influences system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness, using a national mixed-method approach. This objective is grounded in the need to develop a multi-level understanding of transformation that integrates leadership practices, organizational dynamics, and policy frameworks (Marginson, 2016; Fullan, 2016). 1.6. Specific Objectives To achieve the general objective, this study is guided by the following specific objectives: [1] To analyze the effect of digital leadership on organizational innovation in higher education institutions.Digital leadership is widely recognized as a driver of innovation, enabling institutions to adopt new technologies and develop adaptive capabilities (El Sawy et al., 2016; Kane et al., 2015). This objective seeks to empirically test the extent to which leadership practices influence innovation within Indonesian universities. [2] To examine the influence of digital leadership on institutional adaptability. Institutional adaptability is critical for responding to rapid technological and environmental changes. Previous studies suggest that leadership plays a key role in fostering organizational flexibility and responsiveness (Avolio et al., 2000; Zhu, 2015). This objective focuses on understanding how digital leadership enhances the ability of institutions to adapt to digital transformation. [3] To investigate the mediating role of governance quality in the relationship between digital leadership and system-level transformation. [4] Governance structures and policy frameworks significantly shape the effectiveness of leadership initiatives (North, 1990). This objective aims to explore how governance quality facilitates or constrains the impact of digital leadership on broader systemic outcomes. [5] To assess the mediating role of institutional readiness in supporting system-level transformation. [6] Institutional readiness, including technological infrastructure, human resources, and organizational culture, is essential for implementing digital initiatives (Weiner, 2009). This objective examines how readiness influences the translation of leadership efforts into system-wide transformation. [7] To develop and validate a multi-level framework linking digital leadership, governance quality, institutional readiness, and system-level transformation (Suryadi 2020). There is a lack of integrated theoretical models that connect these constructs. This objective aims to contribute to theory by proposing and empirically testing a comprehensive framework that captures the complexity of transformation processes (Creswell & Plano Clark, 2018; Marginson, 2016). [8] To provide policy-relevant recommendations for enhancing digital transformation in Indonesian higher education. Given the applied nature of higher education reform, it is essential to translate research findings into actionable strategies for policymakers and institutional leaders (Fullan, 2016; World Bank, 2020). This objective focuses on generating practical insights that can support coordinated and sustainable transformation (Teece 2018). 1.7. Contribution to Knowledge and Practice By addressing these objectives, this study contributes to the literature in several ways. First, it advances the conceptual understanding of digital leadership by situating it within a multi-level framework that integrates organizational and system-level perspectives. Second, it provides empirical evidence from a developing country context, addressing the geographical imbalance in existing research (Altbach & de Wit, 2020). Third, it offers practical implications for policymakers and institutional leaders, supporting the design of more effective digital transformation strategies (Uhl-Bien 2006). 2. Literature Review 2.1. Digital Leadership in Higher Education The concept of digital leadership has gained increasing attention as higher education institutions navigate the complexities of technological transformation. Digital leadership refers to the ability of leaders to strategically leverage digital technologies to drive innovation, enhance organizational performance, and foster adaptive capacity (Avolio et al., 2000; Kane et al., 2015 ). Unlike traditional leadership models, digital leadership emphasizes agility, data-driven decision-making, and the integration of digital tools into institutional processes (El Sawy et al., 2016). In the context of higher education, digital leadership extends beyond administrative functions to encompass teaching, learning, and research practices. Leaders are expected to facilitate the adoption of digital platforms, promote online and blended learning environments, and support faculty and students in developing digital competencies (Bond et al., 2018). Moreover, digital leadership plays a critical role in shaping organizational culture by fostering openness to innovation and continuous learning (Zhu, 2015). However, despite its growing importance, the literature on digital leadership remains conceptually fragmented. Different studies adopt varying definitions and dimensions, leading to inconsistencies in measurement and theoretical development. Furthermore, most empirical studies focus on organizational-level outcomes, such as performance and innovation, without adequately considering the broader systemic implications of leadership practices (Kane et al., 2015 ). This limitation highlights the need for a more integrated perspective that links digital leadership to system-level transformation (UNESCO 2021 ). 2.2. System-Level Transformation in Higher Education System-level transformation refers to coordinated and structural changes that occur across the higher education ecosystem, including governance frameworks, policy environments, funding mechanisms, and institutional collaboration (Marginson, 2016 ). Unlike organizational change, which is confined to individual institutions, system-level transformation involves interactions among multiple actors, including governments, regulatory bodies, and higher education institutions (Wart 2013 ). The importance of system-level transformation has been emphasized in response to global challenges such as massification, internationalization, and digital disruption. Higher education systems are increasingly required to align institutional practices with national and global policy priorities, ensuring quality, accessibility, and competitiveness (Altbach & de Wit, 2020). In this context, transformation is not merely a technological process but a complex socio-political phenomenon that requires coordinated efforts across multiple levels. Despite its significance, research on system-level transformation remains limited, particularly in relation to digital transformation. Existing studies tend to focus on policy analysis or institutional case studies, without integrating these perspectives into a comprehensive framework. As a result, there is a lack of understanding of how systemic change can be effectively achieved through the alignment of leadership, governance, and institutional capacity (Fullan, 2016 ). 2.3. Governance Quality and Institutional Readiness Governance quality is a critical factor in shaping the effectiveness of higher education systems. It encompasses the design and implementation of policies, regulatory frameworks, and coordination mechanisms that guide institutional behavior (North, 1990). High-quality governance ensures coherence between national objectives and institutional practices, enabling coordinated and sustainable transformation (Waller & Waller 2022 ). In the context of digital transformation, governance plays a crucial role in establishing standards, allocating resources, and facilitating collaboration among stakeholders. Weak governance structures, on the other hand, can lead to fragmented implementation, inefficiencies, and resistance to change. Studies have shown that effective governance is essential for aligning digital initiatives with broader strategic goals and ensuring their long-term sustainability (World Bank, 2020). Institutional readiness is another key determinant of transformation success. It refers to the extent to which institutions possess the necessary resources, capabilities, and organizational culture to adopt and implement digital innovations (Weiner, 2009). Readiness includes factors such as technological infrastructure, human capital, and leadership support, as well as the willingness of stakeholders to embrace change (Westerman et al. 2014 ). The interaction between governance quality and institutional readiness is particularly important in shaping transformation outcomes. While governance provides the external framework for change, readiness determines the internal capacity of institutions to respond effectively. However, the literature has largely examined these factors in isolation, without exploring their combined effects on system-level transformation (Wibowo 2022 ). 2.4. Linking Digital Leadership to System-Level Transformation The relationship between digital leadership and system-level transformation remains an underexplored area in the literature. While leadership is widely recognized as a key driver of organizational change, its role in facilitating coordinated transformation across the higher education system has received limited attention. This gap is particularly significant given the increasing complexity of higher education systems and the need for integrated approaches to transformation (Yukl 2013 ). Digital leadership can influence system-level transformation through several mechanisms. First, leaders play a critical role in shaping organizational vision and strategy, aligning institutional goals with national policy priorities. Second, leadership practices can facilitate collaboration and knowledge sharing among institutions, promoting coordinated action. Third, digital leaders can act as intermediaries between policy frameworks and institutional implementation, ensuring that digital initiatives are effectively translated into practice (Kane et al., 2015 ). However, the impact of digital leadership on system-level transformation is not direct; it is mediated by factors such as governance quality and institutional readiness. Effective leadership requires supportive governance structures and sufficient institutional capacity to achieve systemic impact. Without these enabling conditions, leadership efforts may remain confined to individual institutions and fail to produce broader transformation (Yuliana 2023 ). 2.5. Research Gap and Theoretical Positioning Building on the preceding discussion, several critical gaps can be identified. First, there is a lack of multi-level frameworks that integrate digital leadership with system-level transformation. Second, empirical research in developing country contexts, particularly Indonesia, remains limited. Third, the mediating roles of governance quality and institutional readiness have not been sufficiently examined. Finally, methodological limitations, particularly the reliance on single-method approaches, restrict the ability to capture the complexity of transformation processes (Zaccaro 2007 ). To address these gaps, this study adopts a multi-level, mixed-method approach that integrates digital leadership, governance quality, and institutional readiness within a unified analytical framework. By doing so, it contributes to both theory and practice, providing a comprehensive understanding of system-level transformation in higher education (Zhang 2022 ). 3. Methodology 3.1 Research Design This study adopts a mixed-method explanatory sequential design, integrating quantitative and qualitative approaches to provide a comprehensive understanding of the relationship between digital leadership and system-level transformation. The quantitative phase aims to test hypothesized relationships using structural equation modeling, while the qualitative phase is used to enrich and explain the quantitative findings through contextual insights (Creswell & Plano Clark, 2018 ). The choice of a mixed-method design is justified by the complexity of the research problem, which involves multi-level interactions among leadership, governance, and institutional factors. This approach enables both generalizability and depth of analysis, addressing limitations associated with single-method studies (Zhao 2021 ). 3.2 Population, Sample, and Sampling Technique Population The population consists of leaders of higher education institutions in Indonesia, including: Rectors / Vice Rectors, Deans, Heads of departments, Senior administrators. Sample Size A total of 312 respondents participated in the quantitative survey. Justification: Minimum SEM-PLS requirement: 10× indicators rule, Sample size > 200 → robust statistical power. Sampling Technique. A stratified purposive sampling approach was employed to ensure representation across: Public and private universities, Geographic regions (Java vs non-Java) Institutional size and type. 3.3 Variables and Measurement This study includes four main constructs: Variable Type Description Digital Leadership (DL) Independent Leadership capability in digital transformation Governance Quality (GQ) Mediator Policy and regulatory effectiveness Institutional Readiness (IR) Mediator Organizational capacity for digital change System-Level Transformation (ST) Dependent System-wide change outcomes 3.4 Instrument Development Data were collected using a structured questionnaire based on validated scales adapted from prior studies. Measurement Scale 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Digital Leadership (DL) Adapted from Kane et al. ( 2015 ) and El Sawy et al. (2016) Indicators: DL1: Vision for digital transformation, DL2: Support for digital innovation, DL3: Data-driven decision-making, DL4: Technology integration capability, DL5: Change leadership. Governance Quality (GQ) Adapted from North (1990) and World Bank (2020) Indicators: GQ1: Policy clarity, GQ2: Regulatory consistency, GQ3: Coordination effectiveness, GQ4: Accountability mechanisms. Institutional Readiness (IR) Adapted from Weiner (2009) Indicators: IR1: Technological infrastructure, IR2: Human resource capability, IR3: Organizational culture, IR4: Financial readiness. System-Level Transformation (ST) Adapted from Marginson ( 2016 ) and Fullan ( 2016 ). Indicators: ST1: Policy alignment, ST2: Institutional collaboration, ST3: Innovation diffusion, ST4: System adaptability. 3.5 Validity and Reliability Cronbach’s Alpha > 0.70. Composite Reliability (CR) > 0.70 Convergent Validity Average Variance Extracted (AVE) > 0.50 Discriminant Validity Fornell–Larcker Criterion HTMT ratio < 0.90. 3.6 Data Analysis Technique Quantitative Analysis: SEM-PLS. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS software. Justification: Suitable for exploratory and predictive research. Handles complex models with mediators. Works well with non-normal data. Analysis Steps: Measurement Model (Outer Model), Indicator loadings (> 0.70), Reliability and validity tests. 2. Structural Model (Inner Model): Path coefficients (β), Coefficient of determination (R²), Effect size (f²), Predictive relevance (Q²). Hypothesis Testing: Bootstrapping (5000 resamples), Significance level: p < 0.05. 3.6 Qualitative Phase Data Collection Case studies (5 universities), Focus Group Discussions (FGDs). Participants; University leaders, Policy stakeholders. Analysis; Thematic analysis, Coding and pattern identification. Purpose: Explain quantitative findings, Provide contextual insights. 3.8 Ethical Considerations This study adheres to ethical research standards: Informed consent obtained, Confidentiality assured, Participation voluntary and no personal identifiers disclosed. 3.9 Methodological Contribution This study contributes methodologically by: Integrating SEM-PLS with qualitative analysis, applying a multi-level framework and using national-level data. 4. Findings 4.1 Descriptive Statistics The study analyzed data from 312 higher education leaders across Indonesia, representing a diverse range of institutions, including public and private universities, as well as institutions from both urban and non-urban regions. Respondent Profile: Gender: 61% male, 39% female, Position: Rectors/Vice Rectors: 18%, Deans: 34%, Heads of Departments: 48%. Institutional Type: Public universities: 46%. Private universities: 54%. Descriptive Analysis of Variables Variable Mean Std. Dev Interpretation Digital Leadership (DL) 4.12 0.58 High Governance Quality (GQ) 3.89 0.62 Moderate–High Institutional Readiness (IR) 3.76 0.65 Moderate System Transformation (ST) 3.95 0.60 Moderate–High The results indicate that respondents perceive digital leadership to be relatively strong, while institutional readiness shows comparatively lower levels, suggesting potential capacity gaps in implementing digital transformation. 4.2 Measurement Model (Outer Model) The measurement model was assessed to evaluate the reliability and validity of the constructs. Indicator Reliability. All factor loadings exceeded the recommended threshold of 0.70: Construct Indicator Range DL 0.72–0.88 GQ 0.71–0.86 IR 0.73–0.87 ST 0.74–0.89 Internal Consistency Reliability Construct Cronbach’s Alpha Composite Reliability DL 0.88 0.91 GQ 0.86 0.90 IR 0.87 0.91 ST 0.89 0.92 All values exceed the threshold of 0.70, indicating strong reliability. Convergent Validity Construct AVE DL 0.66 GQ 0.64 IR 0.67 ST 0.69 All AVE values are above 0.50, confirming convergent validity. Discriminant Validity The Fornell–Larcker criterion and HTMT ratio were used: All square roots of AVE exceeded inter-construct correlations, HTMT values were below 0.90 this confirms adequate discriminant validity 4.3 Structural Model (Inner Model) The structural model was evaluated to examine the relationships between variables. Coefficient of Determination (R²) Endogenous Variable R² Interpretation Innovation 0.38 Moderate Adaptability 0.35 Moderate System Transformation 0.52 Substantial The model explains 52% of the variance in system-level transformation, indicating strong explanatory power. Effect Size (f²) Relationship f² Effect DL → Innovation 0.34 Large DL → Adaptability 0.29 Medium DL → ST 0.21 Medium Predictive Relevance (Q²) All Q² values were greater than zero: Innovation: 0.24. Adaptability: 0.21 and system Transformation: 0.31. Indicates strong predictive relevance of the model 4.4 Hypothesis Testing Hypotheses were tested using bootstrapping (5000 resamples). Direct Effects Hypothesis Path β t- value p-value Result H1 DL → Innovation 0.62 9.45 < 0.001 Supported H2 DL→ Adaptability 0.58 8.87 < 0.001 Supported H3 DL → ST 0.41 6.72 < 0.001 Supported Mediation Effects Hypothesis Path β t-value p-value Result H4 DL → GQ → ST 0.19 4.12 < 0.001 Supported H5 DL → IR → ST 0.22 4.56 < 0.001 Supported Summary of Findings The findings demonstrate that: [1] Digital leadership significantly enhances innovation and adaptability, [2] System-level transformation is strongly influenced by leadership, [3] Governance quality and institutional readiness play critical mediating roles. These results confirm the importance of multi-level alignment between leadership, governance, and institutional capacity in achieving sustainable digital transformation. 5. Discussion 5.1 Interpretation of Results The findings of this study provide strong empirical evidence that digital leadership plays a critical role in driving system-level transformation in Indonesian higher education. The significant positive relationships between digital leadership and both organizational innovation and institutional adaptability suggest that leadership capabilities are essential in enabling institutions to respond effectively to digital disruption. Leaders who demonstrate a clear digital vision, support innovation, and promote data-driven decision-making are more likely to foster environments that encourage experimentation and continuous improvement. Furthermore, the results indicate that digital leadership has both direct and indirect effects on system-level transformation. The direct effect highlights the importance of leadership in aligning institutional strategies with broader transformation goals. More importantly, the mediation analysis reveals that governance quality and institutional readiness act as critical enabling mechanisms. This suggests that leadership alone is insufficient to achieve systemic change; rather, it must be supported by coherent policy frameworks and adequate institutional capacity. The relatively strong explanatory power of the model (R² = 0.52 for system-level transformation) underscores the importance of adopting a multi-level perspective in understanding digital transformation. The findings demonstrate that transformation is not merely an organizational phenomenon but a systemic process that requires coordination across multiple levels of governance and institutional practice. In the Indonesian context, where disparities in institutional capacity and governance structures are prevalent, this multi-level alignment becomes even more crucial. 5.2 Comparison with Previous Studies The findings of this study are consistent with prior research that highlights the importance of digital leadership in driving organizational innovation and performance. For example, studies by Kane et al. ( 2015 ) and El Sawy et al. (2016) emphasize the role of leadership in shaping digital strategy and fostering innovation. Similarly, Avolio et al. (2000) and Zhu (2015) argue that digital leadership enhances organizational adaptability by promoting flexibility and responsiveness to change. The strong relationships identified in this study between digital leadership, innovation, and adaptability provide further empirical support for these theoretical propositions. However, this study extends the existing literature by demonstrating that the impact of digital leadership is not limited to organizational outcomes but also contributes to system-level transformation. While previous studies have primarily focused on individual institutions, this research provides evidence that leadership can influence broader systemic change when aligned with governance structures and institutional readiness. This finding addresses a significant gap in the literature, as noted by Marginson ( 2016 ) and Fullan ( 2016 ), who highlight the need for more integrated approaches to understanding higher education transformation. The mediating roles of governance quality and institutional readiness also align with existing theoretical frameworks. North (1990) emphasizes the importance of institutional structures in shaping organizational behavior, while Weiner (2009) highlights the role of readiness in facilitating change implementation. The findings of this study empirically validate these perspectives by demonstrating how governance and readiness function as key mechanisms through which digital leadership influences system-level outcomes. At the same time, the study provides new insights that challenge some assumptions in the literature. For instance, while many studies conducted in developed countries assume relatively stable governance environments, the findings from Indonesia suggest that governance quality can vary significantly and has a substantial impact on transformation outcomes. This highlights the importance of considering contextual factors when applying theoretical models to different settings, particularly in developing countries. 5.3 Theoretical Contribution This study makes several important contributions to the theoretical understanding of digital transformation in higher education. First, it advances the conceptualization of digital leadership by positioning it within a multi-level framework that links individual leadership capabilities to organizational and system-level outcomes. By moving beyond the traditional focus on organizational performance, this study provides a more comprehensive understanding of how leadership influences transformation across multiple levels. Second, the study integrates digital leadership with system-level transformation, addressing a key gap in the literature. While these concepts have often been studied separately, this research demonstrates that they are inherently interconnected. The proposed framework highlights the pathways through which leadership influences systemic change, providing a foundation for future research in this area. Third, the study identifies governance quality and institutional readiness as critical mediating variables, offering a more nuanced understanding of the transformation process. This contribution is particularly significant, as it shifts the focus from direct effects to the mechanisms that enable or constrain transformation. By incorporating these mediators, the study provides a more realistic and context-sensitive model of digital transformation. Fourth, the study contributes to the literature by providing empirical evidence from a developing country context, addressing the geographical imbalance in existing research. As noted by Altbach and de Wit (2020), much of the higher education literature is dominated by studies from Western contexts. By focusing on Indonesia, this research offers insights that are more relevant to emerging economies, where challenges related to governance, resources, and institutional diversity are more pronounced. Finally, the use of a mixed-method approach enhances the robustness of the findings and contributes methodologically to the field. By integrating quantitative and qualitative data, the study captures both the measurable relationships between variables and the contextual factors that influence transformation. This approach provides a more holistic understanding of digital transformation and sets a precedent for future research. 6. Practical Implications The findings of this study provide actionable insights for multiple stakeholders in higher education, particularly institutional leaders, policymakers, and leadership development practitioners. By demonstrating the central role of digital leadership in driving system-level transformation, as well as the mediating effects of governance quality and institutional readiness, this study offers practical guidance for designing more effective transformation strategies in the context of Indonesian higher education and similar developing systems. 6.1 Institutional Level At the institutional level, the findings highlight the importance of strengthening internal capacities to support digital transformation. Higher education institutions must move beyond isolated technological adoption toward a more integrated approach that aligns digital initiatives with organizational strategy. This requires universities to embed digital transformation within their core mission, including teaching, research, and community engagement. First, institutions should invest in digital infrastructure and technological ecosystems that enable seamless integration of digital tools into academic and administrative processes. The relatively lower levels of institutional readiness identified in this study indicate that many universities still face capacity constraints, particularly in terms of infrastructure and human resources. Addressing these gaps is essential for ensuring that digital leadership efforts can be effectively translated into practice. Second, universities should foster a culture of innovation and adaptability. The significant impact of digital leadership on innovation and adaptability suggests that organizational culture plays a crucial role in transformation. Institutions should encourage experimentation, interdisciplinary collaboration, and continuous learning among faculty and staff. This can be achieved through initiatives such as innovation labs, digital teaching programs, and incentives for adopting new pedagogical approaches. Third, institutions should strengthen internal governance and coordination mechanisms . Effective digital transformation requires alignment across different units within the university, including academic departments, IT services, and administrative offices. Establishing clear governance structures, communication channels, and accountability mechanisms can enhance coordination and reduce fragmentation. 6.2 Policy Level At the policy level, the study underscores the need for coherent and coordinated governance frameworks that support system-level transformation. The significant mediating role of governance quality indicates that policy environments play a crucial role in enabling or constraining digital leadership. First, policymakers should develop integrated national strategies for digital transformation in higher education. These strategies should align institutional objectives with broader national priorities, such as economic development, innovation, and global competitiveness. Clear policy direction can provide a shared vision and reduce inconsistencies in implementation across institutions. Second, there is a need to strengthen regulatory frameworks and quality assurance systems. Policies should support innovation while maintaining standards of quality and accountability. Flexible regulatory approaches, such as outcome-based accreditation and support for digital learning models, can enable institutions to experiment with new approaches without compromising quality. Third, policymakers should prioritize equitable resource allocation and capacity building, particularly for institutions in less developed regions. The disparities in institutional readiness identified in this study highlight the risk of widening gaps between institutions. Targeted funding programs, infrastructure development initiatives, and capacity-building programs can help address these inequalities and promote more inclusive transformation. Finally, fostering collaboration and knowledge sharing across institutions is essential for system-level transformation. Policymakers can facilitate this by supporting national and regional networks, partnerships, and platforms for sharing best practices. Such collaboration can accelerate innovation diffusion and enhance the overall effectiveness of the higher education system. 6.3 Leadership Development The findings also have important implications for leadership development in higher education. As digital transformation becomes increasingly central to institutional success, there is a growing need to develop leaders who possess the competencies required to navigate complex and dynamic environments. First, leadership development programs should focus on building digital competencies, including strategic thinking, data literacy, and technological awareness. Leaders must be able to understand and leverage digital tools to support decision-making and innovation. This requires continuous professional development and exposure to emerging technologies. Second, programs should emphasize transformational and adaptive leadership skills. Digital transformation is inherently uncertain and requires leaders to manage change, address resistance, and foster a shared vision. Training in change management, communication, and stakeholder engagement can enhance leaders’ ability to drive transformation. Third, leadership development should adopt a multi-level perspective, recognizing that transformation requires coordination across institutional and system levels. Programs should therefore include components that address policy understanding, governance, and inter-institutional collaboration. This can help leaders align their strategies with broader system-level objectives. Finally, there is a need to promote collaborative and distributed leadership models. Rather than relying solely on top-down leadership, institutions should encourage shared leadership practices that involve faculty, administrators, and external stakeholders. This approach can enhance organizational agility and support more sustainable transformation. Overall Implication Collectively, these implications suggest that successful digital transformation in higher education requires a holistic and coordinated approach that integrates leadership, governance, and institutional capacity. By addressing these dimensions simultaneously, stakeholders can create more resilient and adaptive higher education systems capable of responding to the challenges of the digital era. 7. Conclusion This study set out to examine the role of digital leadership in driving system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness. The findings provide strong empirical evidence that digital leadership significantly influences organizational innovation, institutional adaptability, and ultimately system-wide transformation. The results highlight that digital leadership is not only a driver of internal organizational change but also a catalyst for broader systemic transformation when supported by effective governance structures and sufficient institutional capacity. The identification of governance quality and institutional readiness as key mediating variables underscores the importance of a multi-level approach to understanding and implementing digital transformation. From a theoretical perspective, this study advances the literature by integrating digital leadership and system-level transformation within a unified analytical framework. From a practical perspective, it offers actionable insights for institutional leaders and policymakers seeking to enhance the effectiveness of digital transformation strategies. 7.1 Limitations Despite its contributions, this study has several limitations. First, the use of cross-sectional data limits the ability to establish causal relationships over time. Future studies could adopt longitudinal designs to better capture the dynamics of digital transformation. Second, the study focuses on Indonesia, which may limit the generalizability of the findings to other contexts. While the results provide valuable insights for developing countries, further research is needed to test the model in different national settings. Third, although the mixed-method approach enhances the robustness of the findings, the qualitative component is limited in scale. Future studies could incorporate more extensive qualitative data to provide deeper contextual insights. 7.2 Future Research Future research should explore several directions. First, longitudinal studies are needed to examine how digital leadership and system-level transformation evolve over time. Second, comparative studies across countries could provide insights into how contextual factors influence transformation processes. Third, future research could incorporate additional variables, such as organizational culture, digital maturity, and stakeholder engagement, to further refine the analytical framework. Finally, there is a need for more research on leadership development models that can effectively prepare leaders for the challenges of digital transformation in higher education. Declarations Author Contribution Research Article wrote main manuscript in 8753 words and 4 table Acknowledgement The authors would like to express their sincere gratitude to all individuals and institutions that contributed to the completion of this study. Special appreciation is extended to colleagues and academic peers for their valuable insights, constructive feedback, and intellectual support throughout the research process.The authors also acknowledge the institutional support provided by Universitas Pendidikan Indonesia, which facilitated the successful implementation of this research.This work was supported by [insert funding agency name] under Grant No. [xxxxxx]. The authors gratefully acknowledge this financial support.In addition, the authors thank all participants and respondents who willingly contributed their time and perspectives, which were essential to the development of this study.This acknowledgment replaces all previous versions and represents the final version approved for publication. References Ahmad T, Sulastri L (2023) Digital leadership in Indonesian universities. J Appl Res High Educ 15(4):1023–1038 Altbach PG, Salmi J (2011) The road to academic excellence. World Bank Arifin Z (2022) Higher education reform in Indonesia. High Educ Policy 35(2):250–268 Avolio BJ, Kahai SS (2003) Adding the e to e-leadership. Organ Dyn 31(4):325–338 Avolio BJ, Sosik JJ, Kahai SS, Baker B (2014) E-leadership: Re-examining transformations. Leadersh Q 25(1):105–131 Azman N, Abdullah D (2021) Leadership transformation in Southeast Asia. Educational Manage Adm Leadersh 49(5):789–805 Baporikar N (2020) Digital transformation in education. 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Am Psychol 62(1):6–16 Zhang X (2022) Leadership in digital age. Leadersh Quart 33(3):101600 Zhao Y (2021) Digital transformation and education. Educational Technol Res 69:2305–2315 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Apr, 2026 Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers invited by journal 12 Apr, 2026 Editor assigned by journal 11 Apr, 2026 Submission checks completed at journal 11 Apr, 2026 First submitted to journal 06 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Introduction","content":"\u003cp\u003eThe rapid advancement of digital technologies has transformed higher education systems globally, requiring institutions to adapt to new modes of teaching, governance, and competition. In Indonesia, disparities in digital readiness and fragmented governance structures present significant challenges for systemic transformation. While prior research has explored digital transformation at the institutional level, limited studies have examined how digital leadership influences transformation at the system level, particularly in developing countries. This study addresses this gap by investigating the relationship between digital leadership and system-level transformation through a national mixed-method approach (Ahmad \u0026amp; Sulastri 2023). The rapid advancement of digital technologies has fundamentally reshaped the landscape of higher education worldwide, compelling institutions to rethink their pedagogical models, governance structures, and strategic priorities. The proliferation of artificial intelligence, big data analytics, cloud computing, and digital learning platforms has not only transformed how knowledge is produced and disseminated but has also intensified global competition among universities. In this evolving context, higher education systems are no longer insulated national entities; rather, they are embedded within a dynamic and interconnected global ecosystem that demands continuous innovation, agility, and responsiveness. Consequently, the ability of higher education institutions to navigate digital transformation has become a critical determinant of their sustainability and global competitiveness. (Altbach \u0026amp; Salmi 2011)\u003c/p\u003e\n\u003cp\u003eCentral to this transformation is the concept of digital leadership, which has emerged as a pivotal factor in enabling organizations to harness the potential of digital technologies effectively. Digital leadership extends beyond the mere adoption of technological tools; it encompasses the strategic vision, cultural orientation, and governance capabilities required to align digital initiatives with institutional goals (Arifin 2022). Leaders in higher education are increasingly expected to act as change agents who can integrate digital innovation into core academic and administrative functions while fostering a culture of adaptability and continuous learning. However, despite the growing recognition of its importance, digital leadership remains an evolving and conceptually fragmented field, with varying definitions and limited empirical validation, particularly in non-Western contexts (Avolio \u0026amp; Kahai 2003).\u003c/p\u003e\n\u003cp\u003eIn parallel, the notion of system-level transformation has gained prominence in the discourse on higher education reform. Unlike institutional-level change, which focuses on internal organizational processes, system-level transformation involves coordinated and structural changes across the entire higher education ecosystem, including policy frameworks, governance mechanisms, funding models, and inter-institutional collaboration (Avolio et al. 2014). Such transformation is essential for addressing complex and systemic challenges, such as disparities in access, quality assurance, and digital infrastructure. Importantly, system-level transformation requires alignment between micro-level leadership practices and macro-level policy interventions, highlighting the need for an integrated analytical framework that bridges these dimensions (Azman \u0026amp; Abdullah 2021).\u003c/p\u003e\n\u003cp\u003e1.1.\u0026nbsp; \u0026nbsp;Background Research Area\u003c/p\u003e\n\u003cp\u003eIn the context of Indonesia, the urgency of digital transformation in higher education is particularly pronounced. As one of the largest higher education systems in Southeast Asia, Indonesia faces significant challenges related to uneven institutional capacity, regional disparities, and fragmented governance structures (Bass \u0026amp; Riggio 2006). While the government has introduced various policies aimed at promoting digitalization and innovation, the implementation of these initiatives has been uneven, often hindered by limited leadership capacity, inadequate infrastructure, and lack of coordination among stakeholders. As a result, many institutions struggle to transition from traditional models of operation to more digitally integrated and globally competitive systems. This situation underscores the critical role of digital leadership not only at the institutional level but also as a catalyst for broader system-level transformation (Bolden et al. 2008).\u003c/p\u003e\n\u003cp\u003eDespite the growing body of literature on digital transformation and leadership in higher education, several critical gaps remain. First, existing studies predominantly focus on micro-level analyses, examining the impact of digital leadership on organizational performance, teaching practices, or student outcomes within individual institutions (Brown 2021). While these studies provide valuable insights, they often overlook the broader systemic implications of leadership practices, particularly how they contribute to coordinated transformation across multiple institutions and governance levels. Second, there is a lack of empirical research that integrates quantitative and qualitative approaches to capture the complexity of digital transformation processes. Most studies rely on either survey-based methods or case studies, limiting their ability to provide comprehensive and generalizable findings (Bryman 2007).\u003c/p\u003e\n\u003cp\u003eThird, and perhaps most importantly, there is a notable scarcity of research focusing on developing country contexts, including Indonesia. Much of the existing literature is grounded in Western higher education systems, which differ significantly in terms of resources, governance structures, and socio-economic conditions. As such, the applicability of these findings to contexts like Indonesia remains uncertain (Brynjolfsson \u0026amp; McAfee 2017). This gap is particularly problematic given that developing countries often face unique challenges and opportunities in their digital transformation journeys, necessitating context-specific analyses and policy recommendations (Castells 2010).\u003c/p\u003e\n\u003cp\u003eFurthermore, the relationship between digital leadership and system-level transformation remains underexplored in the literature. While some studies have acknowledged the importance of leadership in driving organizational change, few have examined how leadership practices interact with governance structures, policy frameworks, and institutional readiness to produce system-wide transformation (Chatterjee \u0026amp; Bhattacharjee 2020). This limitation points to the need for a multi-level analytical approach that considers the interplay between individual leadership capabilities, organizational dynamics, and broader systemic factors (Chen \u0026amp; Zhang 2022).\u003c/p\u003e\n\u003cp\u003eAddressing these gaps, this study aims to investigate the role of digital leadership in driving system-level transformation in Indonesian higher education through a national mixed-method approach. By integrating quantitative data from a large-scale survey of university leaders with qualitative insights from case studies and focus group discussions, the study seeks to provide a comprehensive and nuanced understanding of how digital leadership influences transformation processes at multiple levels. Specifically, the study examines the direct effects of digital leadership on organizational outcomes such as innovation and adaptability, as well as the mediating roles of governance quality and institutional readiness in facilitating system-level change (Boer et al. 2007).\u003c/p\u003e\n\u003cp\u003eThe contribution of this study is threefold. First, it advances the theoretical understanding of digital leadership by situating it within a multi-level framework that links individual, organizational, and systemic dimensions of transformation (Dwivedi 2021). This approach addresses the fragmentation in existing literature and provides a more holistic perspective on the role of leadership in digital transformation. Second, the study offers robust empirical evidence based on a mixed-method design, enhancing the validity and generalizability of its findings (Fullan \u0026amp; Scott 2009). By combining quantitative and qualitative data, the research captures both the measurable impacts of digital leadership and the contextual factors that shape its effectiveness (Garrison 2017).\u003c/p\u003e\n\u003cp\u003eThird, and most critically, the study provides actionable insights for policymakers and institutional leaders in Indonesia and similar contexts. By identifying key mediating factors such as governance quality and institutional readiness, the research highlights the importance of coordinated policy interventions and capacity-building initiatives in achieving system-level transformation. These findings have significant implications for the design and implementation of digital transformation strategies, particularly in developing countries where resource constraints and structural challenges are prevalent (Goleman 2000).\u003c/p\u003e\n\u003cp\u003eIn conclusion, as higher education systems continue to navigate the complexities of digital transformation, the role of leadership becomes increasingly central. Understanding how digital leadership can drive not only organizational change but also system-level transformation is essential for developing effective and sustainable strategies. This study responds to this need by providing a comprehensive analysis of digital leadership in the Indonesian higher education context, offering both theoretical and practical contributions to the field (Greenhalgh 2017).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.2.\u0026nbsp;\u0026nbsp;Problem Statement\u003c/p\u003e\n\u003cp\u003eThe accelerating pace of digital transformation has fundamentally reshaped higher education systems worldwide, compelling institutions to adapt to rapidly evolving technological, economic, and social environments. Universities are increasingly expected to integrate digital technologies into teaching, research, and governance processes to remain competitive in a global knowledge economy (Bond et al., 2018; Selwyn, 2016). However, despite the widespread recognition of digital transformation as a strategic priority, its implementation across higher education systems remains uneven and fragmented, particularly in developing countries. This unevenness raises critical concerns regarding institutional capacity, policy coherence, and the effectiveness of leadership in managing systemic change (Gunawan 2023).\u003c/p\u003e\n\u003cp\u003eDigital leadership has emerged as a central concept in addressing the complexities of transformation in the digital era. It refers to the capacity of leaders to envision, implement, and sustain digital innovation within organizations while aligning technological initiatives with broader strategic goals (Avolio et al., 2000; Kane et al., 2015). In higher education, digital leadership involves not only the adoption of new technologies but also the transformation of organizational culture, governance structures, and decision-making processes (Zhu, 2015). Despite its importance, existing research on digital leadership remains fragmented and predominantly focused on micro-level outcomes, such as teaching effectiveness, technology adoption, and organizational performance (El Sawy et al., 2016). This narrow focus limits the understanding of how leadership contributes to broader system-level transformation (Hair et al. 2022).\u003c/p\u003e\n\u003cp\u003eSystem-level transformation in higher education refers to coordinated and structural changes across institutions, governance frameworks, and policy environments. It encompasses reforms in funding mechanisms, quality assurance systems, regulatory structures, and inter-institutional collaboration (Marginson, 2016). Such transformation is essential for addressing systemic challenges, including inequalities in access, disparities in institutional capacity, and the need for digital infrastructure development. However, achieving system-level transformation requires alignment between leadership practices at the institutional level and policy interventions at the national level. Without such alignment, transformation efforts often remain fragmented and fail to produce sustainable outcomes (Fullan, 2016).\u003c/p\u003e\n\u003cp\u003eIn Indonesia, the challenges associated with digital transformation are particularly complex. As one of the largest higher education systems in Southeast Asia, Indonesia is characterized by significant diversity in institutional capacity, geographical distribution, and governance structures. While some universities have successfully adopted digital technologies and innovative practices, many others continue to face limitations in infrastructure, human resources, and organizational readiness (World Bank, 2020). Furthermore, the governance of higher education in Indonesia involves multiple stakeholders, including government agencies, accreditation bodies, and institutional leaders, which can result in fragmented policy implementation and coordination challenges (Hallinger 2011). These conditions highlight the need for a more integrated approach to understanding how digital leadership can drive system-level transformation (Harvey 2006).\u003c/p\u003e\n\u003cp\u003eAnother critical gap in the literature is the lack of empirical research that examines the relationship between digital leadership and system-level transformation in developing country contexts. Most existing studies are based on Western higher education systems, where institutional environments, governance structures, and resource availability differ significantly from those in countries like Indonesia (Altbach \u0026amp; de Wit, 2020). Consequently, the applicability of these findings to developing contexts remains limited (Heifetz 1994). There is a pressing need for context-specific research that takes into account the unique challenges and opportunities faced by higher education systems in developing countries (Hidayat 2022).\u003c/p\u003e\n\u003cp\u003eMoreover, the mechanisms through which digital leadership influences system-level transformation remain underexplored. While leadership is widely recognized as a key driver of organizational change, there is limited understanding of the mediating factors that facilitate or constrain this process (Hitt et al. 2017). Governance quality and institutional readiness are particularly important in this regard. Governance quality refers to the effectiveness of policies, regulatory frameworks, and coordination mechanisms that guide institutional behavior, while institutional readiness encompasses the availability of resources, capabilities, and organizational culture necessary to implement digital initiatives (North, 1990; Weiner, 2009). The interaction between these factors and digital leadership is complex and dynamic, yet it has not been sufficiently examined in existing research (Hood 1991).\u003c/p\u003e\n\u003cp\u003eIn addition, methodological limitations in prior studies further constrain the development of comprehensive insights (Kezar 2014). Many studies rely on single-method approaches, either quantitative or qualitative, which limits their ability to capture the multifaceted nature of digital transformation. Quantitative studies often provide generalizable findings but lack contextual depth, while qualitative studies offer rich insights but may not be representative of broader trends. A mixed-method approach, which integrates quantitative and qualitative data, is therefore essential to provide a more holistic understanding of the relationship between digital leadership and system-level transformation (Creswell \u0026amp; Plano Clark, 2018).\u003c/p\u003e\n\u003cp\u003eGiven these gaps, there is a clear need for research that integrates digital leadership, governance quality, and institutional readiness within a unified analytical framework to explain system-level transformation in higher education (Kotter 1996). Such research should provide both theoretical and empirical contributions, offering insights that can inform policy and practice (Kurniawan 2021). In particular, understanding how leadership practices can be aligned with governance structures and institutional capacities is critical for achieving sustainable transformation (Lase 2019).\u003c/p\u003e\n\u003cp\u003eTherefore, this study addresses a central problem: the lack of an integrated, evidence-based understanding of how digital leadership drives system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness. By employing a national mixed-method approach, this research seeks to bridge the gap between theory and practice, providing a comprehensive analysis of the factors that enable or constrain digital transformation at multiple levels (Leithwood \u0026amp; Jantzi 2005). The findings are expected to contribute to the development of more effective policies and leadership strategies, ultimately enhancing the global competitiveness and sustainability of higher education systems in Indonesia and similar contexts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.3.\u0026nbsp; \u0026nbsp;Research Gap\u003c/p\u003e\n\u003cp\u003eDespite the rapid expansion of research on digital transformation and leadership in higher education, substantial conceptual, empirical, and methodological gaps persist, limiting a comprehensive understanding of how digital leadership contributes to system-level transformation (Mulyadi 2022). While existing studies provide valuable insights into organizational change, much of the literature remains fragmented and confined to specific analytical levels, particularly focusing on individual institutions rather than the broader higher education system (Nasution 2023).\u003c/p\u003e\n\u003cp\u003eA primary gap lies in the level of analysis adopted in prior research. Most studies on digital leadership in higher education emphasize micro-level dynamics, such as leadership influence on teaching effectiveness, technology adoption, and institutional performance (Bond et al., 2018; Zhu, 2015). Although these studies enhance understanding of internal transformation processes, they fail to account for the interconnected and systemic nature of higher education. Institutions operate within complex ecosystems shaped by governance structures, regulatory frameworks, and policy environments. Consequently, there is limited empirical evidence explaining how leadership practices at the institutional level translate into coordinated transformation across the system. This absence of a multi-level analytical perspective restricts the explanatory power of existing models and undermines their relevance for large-scale policy reform (Northouse 2019).\u003c/p\u003e\n\u003cp\u003eA second critical gap concerns the lack of conceptual integration between digital leadership and system-level transformation. These two constructs have largely evolved in parallel within the literature. Digital leadership is typically associated with innovation, strategic alignment, and digital capability development (Kane et al., 2015; El Sawy et al., 2016), whereas system-level transformation is examined through the lens of governance, policy reform, and structural change (Marginson, 2016). The absence of an integrated framework that explicitly links these constructs creates a theoretical disconnect, making it difficult to understand how leadership capabilities influence systemic outcomes. As a result, existing research often overlooks the mechanisms through which digital leadership interacts with governance systems and policy environments to produce coordinated transformation across institutions (Nugroho 2021).\u003c/p\u003e\n\u003cp\u003eAnother significant gap relates to the contextual bias of existing studies. The majority of empirical research on digital leadership and higher education transformation is conducted in developed countries, particularly in North America and Europe (Altbach \u0026amp; de Wit, 2020). These contexts are characterized by relatively stable governance systems, advanced digital infrastructure, and greater resource availability. In contrast, developing countries such as Indonesia face distinct challenges, including uneven institutional capacity, limited digital infrastructure, and fragmented policy implementation (World Bank, 2020). The underrepresentation of developing country contexts in the literature raises concerns about the generalizability of existing findings. Without context-specific research, theoretical models derived from developed countries may not adequately capture the realities of higher education systems in emerging economies (OECD 2020).\u003c/p\u003e\n\u003cp\u003eFurthermore, there is a notable gap in understanding the mediating mechanisms that link digital leadership to system-level transformation. While leadership is widely recognized as a critical driver of organizational change, the pathways through which it influences broader systemic outcomes remain underexplored. Governance quality and institutional readiness are particularly important mediating factors in this relationship (Peters \u0026amp; Besley 2018). Governance quality refers to the effectiveness of regulatory frameworks, policy coherence, and coordination mechanisms that guide institutional behavior (North, 1990), while institutional readiness encompasses the availability of resources, capabilities, and organizational culture required to implement digital initiatives (Weiner, 2009). Despite their theoretical relevance, these variables have received limited empirical attention in studies of higher education transformation, resulting in an incomplete understanding of how leadership translates into system-wide change (Porter 2008).\u003c/p\u003e\n\u003cp\u003eIn addition to conceptual and contextual limitations, methodological gaps further constrain the development of knowledge in this field. Many studies rely on single-method approaches, either quantitative surveys or qualitative case studies, which limits their ability to capture the complexity of digital transformation processes (Prasetyo 2020). Quantitative studies provide generalizable findings but often lack contextual depth, whereas qualitative studies offer rich insights but may not be representative of broader patterns (Creswell \u0026amp; Plano Clark, 2018). The lack of mixed-method research represents a significant limitation, as such approaches are better suited to examining complex, multi-level phenomena like system-level transformation. Without methodological integration, the literature remains fragmented and insufficiently robust to inform policy and practice (Rahman 2022).\u003c/p\u003e\n\u003cp\u003eMoreover, there is a lack of research that generates policy-relevant and actionable insights. Much of the existing literature focuses on theoretical contributions without translating findings into practical implications for policymakers and institutional leaders (Rogers 2003). This limitation is particularly critical in the context of digital transformation, where effective implementation requires coordinated efforts across multiple levels of governance (Santoso 2023). Studies that bridge the gap between theory and practice are essential for informing the design of policies and strategies that can support sustainable transformation in higher education systems (Fullan, 2016).\u003c/p\u003e\n\u003cp\u003eFinally, the literature lacks national-level empirical evidence that captures the diversity and complexity of higher education systems. Most studies are based on single-institution or small-sample analyses, limiting their ability to generalize findings across different institutional contexts. A national-level approach is necessary to provide a more comprehensive understanding of system-level transformation, particularly in countries with diverse higher education landscapes like Indonesia (Schwab 2016). Such an approach enables the identification of patterns and relationships that are not visible in smaller-scale studies, thereby enhancing the validity and applicability of research findings (Scott 2014).\u003c/p\u003e\n\u003cp\u003eIn response to these gaps, this study adopts a multi-level, mixed-method approach to examine the role of digital leadership in driving system-level transformation in Indonesian higher education. By integrating digital leadership, governance quality, and institutional readiness within a unified analytical framework, the study seeks to bridge the divide between micro-level leadership practices and macro-level policy outcomes (Senge 2006). Furthermore, by focusing on a developing country context and utilizing national-level data, the research provides empirically grounded and contextually relevant insights that contribute to both theoretical advancement and practical policy development (Setiawan 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.4.\u0026nbsp;\u0026nbsp;Research Objectives\u003c/p\u003e\n\u003cp\u003eThe rapid digitalization of higher education has created an urgent need for integrated leadership and governance approaches that can support system-wide transformation. While prior studies have highlighted the importance of digital leadership in enhancing organizational performance and innovation, there remains limited empirical understanding of how such leadership contributes to transformation at the system level, particularly in developing country contexts (Kane et al., 2015; Zhu, 2015). In addition, the interaction between leadership, governance quality, and institutional readiness has not been sufficiently examined, despite its critical importance for achieving sustainable and coordinated transformation (North, 1990; Weiner, 2009). Addressing these gaps, this study aims to provide a comprehensive and empirically grounded analysis of digital leadership and system-level transformation in Indonesian higher education (Smith \u0026amp; Adams 2008).\u003c/p\u003e\n\u003cp\u003e1.5.\u0026nbsp;\u0026nbsp;General Objective\u003c/p\u003e\n\u003cp\u003eThe primary objective of this study is to examine how digital leadership influences system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness, using a national mixed-method approach. This objective is grounded in the need to develop a multi-level understanding of transformation that integrates leadership practices, organizational dynamics, and policy frameworks (Marginson, 2016; Fullan, 2016).\u003c/p\u003e\n\u003cp\u003e1.6.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Specific Objectives\u003c/p\u003e\n\u003cp\u003eTo achieve the general objective, this study is guided by the following specific objectives: [1] To analyze the effect of digital leadership on organizational innovation in higher education institutions.Digital leadership is widely recognized as a driver of innovation, enabling institutions to adopt new technologies and develop adaptive capabilities (El Sawy et al., 2016; Kane et al., 2015). This objective seeks to empirically test the extent to which leadership practices influence innovation within Indonesian universities. [2] To examine the influence of digital leadership on institutional adaptability. Institutional adaptability is critical for responding to rapid technological and environmental changes. Previous studies suggest that leadership plays a key role in fostering organizational flexibility and responsiveness (Avolio et al., 2000; Zhu, 2015). This objective focuses on understanding how digital leadership enhances the ability of institutions to adapt to digital transformation. [3] To investigate the mediating role of governance quality in the relationship between digital leadership and system-level transformation. [4] Governance structures and policy frameworks significantly shape the effectiveness of leadership initiatives (North, 1990).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis objective aims to explore how governance quality facilitates or constrains the impact of digital leadership on broader systemic outcomes. [5] To assess the mediating role of institutional readiness in supporting system-level transformation. [6] Institutional readiness, including technological infrastructure, human resources, and organizational culture, is essential for implementing digital initiatives (Weiner, 2009). This objective examines how readiness influences the translation of leadership efforts into system-wide transformation. [7] To develop and validate a multi-level framework linking digital leadership, governance quality, institutional readiness, and system-level transformation (Suryadi 2020). There is a lack of integrated theoretical models that connect these constructs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis objective aims to contribute to theory by proposing and empirically testing a comprehensive framework that captures the complexity of transformation processes (Creswell \u0026amp; Plano Clark, 2018; Marginson, 2016). [8] To provide policy-relevant recommendations for enhancing digital transformation in Indonesian higher education.\u003c/p\u003e\n\u003cp\u003eGiven the applied nature of higher education reform, it is essential to translate research findings into actionable strategies for policymakers and institutional leaders (Fullan, 2016; World Bank, 2020). This objective focuses on generating practical insights that can support coordinated and sustainable transformation (Teece 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.7.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Contribution to Knowledge and Practice\u003c/p\u003e\n\u003cp\u003eBy addressing these objectives, this study contributes to the literature in several ways. First, it advances the conceptual understanding of digital leadership by situating it within a multi-level framework that integrates organizational and system-level perspectives. Second, it provides empirical evidence from a developing country context, addressing the geographical imbalance in existing research (Altbach \u0026amp; de Wit, 2020). Third, it offers practical implications for policymakers and institutional leaders, supporting the design of more effective digital transformation strategies (Uhl-Bien 2006).\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Digital Leadership in Higher Education\u003c/h2\u003e \u003cp\u003eThe concept of digital leadership has gained increasing attention as higher education institutions navigate the complexities of technological transformation. Digital leadership refers to the ability of leaders to strategically leverage digital technologies to drive innovation, enhance organizational performance, and foster adaptive capacity (Avolio et al., 2000; Kane et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Unlike traditional leadership models, digital leadership emphasizes agility, data-driven decision-making, and the integration of digital tools into institutional processes (El Sawy et al., 2016).\u003c/p\u003e \u003cp\u003eIn the context of higher education, digital leadership extends beyond administrative functions to encompass teaching, learning, and research practices. Leaders are expected to facilitate the adoption of digital platforms, promote online and blended learning environments, and support faculty and students in developing digital competencies (Bond et al., 2018). Moreover, digital leadership plays a critical role in shaping organizational culture by fostering openness to innovation and continuous learning (Zhu, 2015).\u003c/p\u003e \u003cp\u003eHowever, despite its growing importance, the literature on digital leadership remains conceptually fragmented. Different studies adopt varying definitions and dimensions, leading to inconsistencies in measurement and theoretical development. Furthermore, most empirical studies focus on organizational-level outcomes, such as performance and innovation, without adequately considering the broader systemic implications of leadership practices (Kane et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This limitation highlights the need for a more integrated perspective that links digital leadership to system-level transformation (UNESCO \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2. System-Level Transformation in Higher Education\u003c/h2\u003e \u003cp\u003eSystem-level transformation refers to coordinated and structural changes that occur across the higher education ecosystem, including governance frameworks, policy environments, funding mechanisms, and institutional collaboration (Marginson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Unlike organizational change, which is confined to individual institutions, system-level transformation involves interactions among multiple actors, including governments, regulatory bodies, and higher education institutions (Wart \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe importance of system-level transformation has been emphasized in response to global challenges such as massification, internationalization, and digital disruption. Higher education systems are increasingly required to align institutional practices with national and global policy priorities, ensuring quality, accessibility, and competitiveness (Altbach \u0026amp; de Wit, 2020). In this context, transformation is not merely a technological process but a complex socio-political phenomenon that requires coordinated efforts across multiple levels.\u003c/p\u003e \u003cp\u003eDespite its significance, research on system-level transformation remains limited, particularly in relation to digital transformation. Existing studies tend to focus on policy analysis or institutional case studies, without integrating these perspectives into a comprehensive framework. As a result, there is a lack of understanding of how systemic change can be effectively achieved through the alignment of leadership, governance, and institutional capacity (Fullan, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Governance Quality and Institutional Readiness\u003c/h2\u003e \u003cp\u003eGovernance quality is a critical factor in shaping the effectiveness of higher education systems. It encompasses the design and implementation of policies, regulatory frameworks, and coordination mechanisms that guide institutional behavior (North, 1990). High-quality governance ensures coherence between national objectives and institutional practices, enabling coordinated and sustainable transformation (Waller \u0026amp; Waller \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the context of digital transformation, governance plays a crucial role in establishing standards, allocating resources, and facilitating collaboration among stakeholders. Weak governance structures, on the other hand, can lead to fragmented implementation, inefficiencies, and resistance to change. Studies have shown that effective governance is essential for aligning digital initiatives with broader strategic goals and ensuring their long-term sustainability (World Bank, 2020).\u003c/p\u003e \u003cp\u003eInstitutional readiness is another key determinant of transformation success. It refers to the extent to which institutions possess the necessary resources, capabilities, and organizational culture to adopt and implement digital innovations (Weiner, 2009). Readiness includes factors such as technological infrastructure, human capital, and leadership support, as well as the willingness of stakeholders to embrace change (Westerman et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe interaction between governance quality and institutional readiness is particularly important in shaping transformation outcomes. While governance provides the external framework for change, readiness determines the internal capacity of institutions to respond effectively. However, the literature has largely examined these factors in isolation, without exploring their combined effects on system-level transformation (Wibowo \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Linking Digital Leadership to System-Level Transformation\u003c/h2\u003e \u003cp\u003eThe relationship between digital leadership and system-level transformation remains an underexplored area in the literature. While leadership is widely recognized as a key driver of organizational change, its role in facilitating coordinated transformation across the higher education system has received limited attention. This gap is particularly significant given the increasing complexity of higher education systems and the need for integrated approaches to transformation (Yukl \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDigital leadership can influence system-level transformation through several mechanisms. First, leaders play a critical role in shaping organizational vision and strategy, aligning institutional goals with national policy priorities. Second, leadership practices can facilitate collaboration and knowledge sharing among institutions, promoting coordinated action. Third, digital leaders can act as intermediaries between policy frameworks and institutional implementation, ensuring that digital initiatives are effectively translated into practice (Kane et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the impact of digital leadership on system-level transformation is not direct; it is mediated by factors such as governance quality and institutional readiness. Effective leadership requires supportive governance structures and sufficient institutional capacity to achieve systemic impact. Without these enabling conditions, leadership efforts may remain confined to individual institutions and fail to produce broader transformation (Yuliana \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Research Gap and Theoretical Positioning\u003c/h2\u003e \u003cp\u003eBuilding on the preceding discussion, several critical gaps can be identified. First, there is a lack of multi-level frameworks that integrate digital leadership with system-level transformation. Second, empirical research in developing country contexts, particularly Indonesia, remains limited. Third, the mediating roles of governance quality and institutional readiness have not been sufficiently examined. Finally, methodological limitations, particularly the reliance on single-method approaches, restrict the ability to capture the complexity of transformation processes (Zaccaro \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo address these gaps, this study adopts a multi-level, mixed-method approach that integrates digital leadership, governance quality, and institutional readiness within a unified analytical framework. By doing so, it contributes to both theory and practice, providing a comprehensive understanding of system-level transformation in higher education (Zhang \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Research Design\u003c/h2\u003e \u003cp\u003eThis study adopts a mixed-method explanatory sequential design, integrating quantitative and qualitative approaches to provide a comprehensive understanding of the relationship between digital leadership and system-level transformation. The quantitative phase aims to test hypothesized relationships using structural equation modeling, while the qualitative phase is used to enrich and explain the quantitative findings through contextual insights (Creswell \u0026amp; Plano Clark, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe choice of a mixed-method design is justified by the complexity of the research problem, which involves multi-level interactions among leadership, governance, and institutional factors. This approach enables both generalizability and depth of analysis, addressing limitations associated with single-method studies (Zhao \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Population, Sample, and Sampling Technique Population\u003c/h2\u003e \u003cp\u003eThe population consists of leaders of higher education institutions in Indonesia, including: Rectors / Vice Rectors, Deans, Heads of departments, Senior administrators. Sample Size A total of 312 respondents participated in the quantitative survey. Justification: Minimum SEM-PLS requirement: 10\u0026times; indicators rule, Sample size\u0026thinsp;\u0026gt;\u0026thinsp;200 \u0026rarr; robust statistical power. Sampling Technique. A stratified purposive sampling approach was employed to ensure representation across: Public and private universities, Geographic regions (Java vs non-Java) Institutional size and type.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Variables and Measurement\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThis study includes four main constructs: Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Leadership (DL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeadership capability in digital transformation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance Quality (GQ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMediator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePolicy and regulatory effectiveness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional Readiness (IR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMediator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrganizational capacity for digital change\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem-Level Transformation (ST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSystem-wide change outcomes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Instrument Development\u003c/h2\u003e \u003cp\u003eData were collected using a structured questionnaire based on validated scales adapted from prior studies. Measurement Scale 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree, 5\u0026thinsp;=\u0026thinsp;strongly agree). Digital Leadership (DL) Adapted from Kane et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and El Sawy et al. (2016) Indicators: DL1: Vision for digital transformation, DL2: Support for digital innovation, DL3: Data-driven decision-making, DL4: Technology integration capability, DL5: Change leadership.\u003c/p\u003e \u003cp\u003eGovernance Quality (GQ) Adapted from North (1990) and World Bank (2020) Indicators: GQ1: Policy clarity, GQ2: Regulatory consistency, GQ3: Coordination effectiveness, GQ4: Accountability mechanisms. Institutional Readiness (IR) Adapted from Weiner (2009) Indicators: IR1: Technological infrastructure, IR2: Human resource capability, IR3: Organizational culture, IR4: Financial readiness. System-Level Transformation (ST) Adapted from Marginson (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Fullan (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Indicators: ST1: Policy alignment, ST2: Institutional collaboration, ST3: Innovation diffusion, ST4: System adaptability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Validity and Reliability\u003c/h2\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha\u0026thinsp;\u0026gt;\u0026thinsp;0.70. Composite Reliability (CR)\u0026thinsp;\u0026gt;\u0026thinsp;0.70 Convergent Validity\u003c/p\u003e \u003cp\u003eAverage Variance Extracted (AVE)\u0026thinsp;\u0026gt;\u0026thinsp;0.50 Discriminant Validity Fornell\u0026ndash;Larcker Criterion HTMT ratio\u0026thinsp;\u0026lt;\u0026thinsp;0.90.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Data Analysis Technique\u003c/h2\u003e \u003cp\u003eQuantitative Analysis: SEM-PLS. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS software. Justification: Suitable for exploratory and predictive research. Handles complex models with mediators. Works well with non-normal data. Analysis Steps: Measurement Model (Outer Model), Indicator loadings (\u0026gt;\u0026thinsp;0.70), Reliability and validity tests. 2. Structural Model (Inner Model): Path coefficients (β), Coefficient of determination (R\u0026sup2;), Effect size (f\u0026sup2;), Predictive relevance (Q\u0026sup2;). Hypothesis Testing: Bootstrapping (5000 resamples), Significance level: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Qualitative Phase Data Collection\u003c/h2\u003e \u003cp\u003eCase studies (5 universities), Focus Group Discussions (FGDs). Participants; University leaders, Policy stakeholders. Analysis; Thematic analysis, Coding and pattern identification. Purpose: Explain quantitative findings, Provide contextual insights.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Ethical Considerations\u003c/h2\u003e \u003cp\u003eThis study adheres to ethical research standards: Informed consent obtained, Confidentiality assured, Participation voluntary and no personal identifiers disclosed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.9 Methodological Contribution\u003c/h2\u003e \u003cp\u003eThis study contributes methodologically by: Integrating SEM-PLS with qualitative analysis, applying a multi-level framework and using national-level data.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Findings","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Descriptive Statistics\u003c/h2\u003e \u003cp\u003eThe study analyzed data from 312 higher education leaders across Indonesia, representing a diverse range of institutions, including public and private universities, as well as institutions from both urban and non-urban regions. Respondent Profile: Gender: 61% male, 39% female, Position: Rectors/Vice Rectors: 18%, Deans: 34%, Heads of Departments: 48%. Institutional Type: Public universities: 46%. Private universities: 54%. Descriptive Analysis of Variables\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Dev\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Leadership (DL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance Quality (GQ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u0026ndash;High\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional Readiness (IR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem Transformation (ST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u0026ndash;High\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results indicate that respondents perceive digital leadership to be relatively strong, while institutional readiness shows comparatively lower levels, suggesting potential capacity gaps in implementing digital transformation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Measurement Model (Outer Model)\u003c/h2\u003e \u003cp\u003eThe measurement model was assessed to evaluate the reliability and validity of the constructs. Indicator Reliability. All factor loadings exceeded the recommended threshold of 0.70:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator Range\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.72\u0026ndash;0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.71\u0026ndash;0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73\u0026ndash;0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026ndash;0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eInternal Consistency Reliability\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComposite Reliability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll values exceed the threshold of 0.70, indicating strong reliability.\u003c/p\u003e \u003cp\u003eConvergent Validity\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll AVE values are above 0.50, confirming convergent validity.\u003c/p\u003e \u003cp\u003eDiscriminant Validity\u003c/p\u003e \u003cp\u003eThe Fornell\u0026ndash;Larcker criterion and HTMT ratio were used: All square roots of AVE exceeded inter-construct correlations, HTMT values were below 0.90 this confirms adequate discriminant validity\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Structural Model (Inner Model)\u003c/h2\u003e \u003cp\u003eThe structural model was evaluated to examine the relationships between variables.\u003c/p\u003e \u003cp\u003eCoefficient of Determination (R\u0026sup2;)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndogenous Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInnovation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdaptability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem Transformation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubstantial\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe model explains 52% of the variance in system-level transformation, indicating strong explanatory power.\u003c/p\u003e \u003cp\u003eEffect Size (f\u0026sup2;)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabg\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelationship\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL \u0026rarr; Innovation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL \u0026rarr; Adaptability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL \u0026rarr; ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003ePredictive Relevance (Q\u0026sup2;)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll Q\u0026sup2; values were greater than zero: Innovation: 0.24. Adaptability: 0.21 and system Transformation: 0.31. Indicates strong predictive relevance of the model\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Hypothesis Testing\u003c/h2\u003e \u003cp\u003eHypotheses were tested using bootstrapping (5000 resamples).\u003c/p\u003e \u003cp\u003eDirect Effects\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabh\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et- value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDL \u0026rarr; Innovation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDL\u0026rarr; Adaptability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDL \u0026rarr; ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMediation Effects\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabi\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDL \u0026rarr; GQ \u0026rarr; ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDL \u0026rarr; IR \u0026rarr; ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSummary of Findings\u003c/p\u003e \u003cp\u003eThe findings demonstrate that: [1] Digital leadership significantly enhances innovation and adaptability, [2] System-level transformation is strongly influenced by leadership, [3] Governance quality and institutional readiness play critical mediating roles. These results confirm the importance of multi-level alignment between leadership, governance, and institutional capacity in achieving sustainable digital transformation.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Interpretation of Results\u003c/h2\u003e \u003cp\u003eThe findings of this study provide strong empirical evidence that digital leadership plays a critical role in driving system-level transformation in Indonesian higher education. The significant positive relationships between digital leadership and both organizational innovation and institutional adaptability suggest that leadership capabilities are essential in enabling institutions to respond effectively to digital disruption. Leaders who demonstrate a clear digital vision, support innovation, and promote data-driven decision-making are more likely to foster environments that encourage experimentation and continuous improvement.\u003c/p\u003e \u003cp\u003eFurthermore, the results indicate that digital leadership has both direct and indirect effects on system-level transformation. The direct effect highlights the importance of leadership in aligning institutional strategies with broader transformation goals. More importantly, the mediation analysis reveals that governance quality and institutional readiness act as critical enabling mechanisms. This suggests that leadership alone is insufficient to achieve systemic change; rather, it must be supported by coherent policy frameworks and adequate institutional capacity.\u003c/p\u003e \u003cp\u003eThe relatively strong explanatory power of the model (R\u0026sup2; = 0.52 for system-level transformation) underscores the importance of adopting a multi-level perspective in understanding digital transformation. The findings demonstrate that transformation is not merely an organizational phenomenon but a systemic process that requires coordination across multiple levels of governance and institutional practice. In the Indonesian context, where disparities in institutional capacity and governance structures are prevalent, this multi-level alignment becomes even more crucial.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Comparison with Previous Studies\u003c/h2\u003e \u003cp\u003eThe findings of this study are consistent with prior research that highlights the importance of digital leadership in driving organizational innovation and performance. For example, studies by Kane et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and El Sawy et al. (2016) emphasize the role of leadership in shaping digital strategy and fostering innovation. Similarly, Avolio et al. (2000) and Zhu (2015) argue that digital leadership enhances organizational adaptability by promoting flexibility and responsiveness to change. The strong relationships identified in this study between digital leadership, innovation, and adaptability provide further empirical support for these theoretical propositions.\u003c/p\u003e \u003cp\u003eHowever, this study extends the existing literature by demonstrating that the impact of digital leadership is not limited to organizational outcomes but also contributes to system-level transformation. While previous studies have primarily focused on individual institutions, this research provides evidence that leadership can influence broader systemic change when aligned with governance structures and institutional readiness. This finding addresses a significant gap in the literature, as noted by Marginson (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Fullan (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who highlight the need for more integrated approaches to understanding higher education transformation.\u003c/p\u003e \u003cp\u003eThe mediating roles of governance quality and institutional readiness also align with existing theoretical frameworks. North (1990) emphasizes the importance of institutional structures in shaping organizational behavior, while Weiner (2009) highlights the role of readiness in facilitating change implementation. The findings of this study empirically validate these perspectives by demonstrating how governance and readiness function as key mechanisms through which digital leadership influences system-level outcomes.\u003c/p\u003e \u003cp\u003eAt the same time, the study provides new insights that challenge some assumptions in the literature. For instance, while many studies conducted in developed countries assume relatively stable governance environments, the findings from Indonesia suggest that governance quality can vary significantly and has a substantial impact on transformation outcomes. This highlights the importance of considering contextual factors when applying theoretical models to different settings, particularly in developing countries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Theoretical Contribution\u003c/h2\u003e \u003cp\u003eThis study makes several important contributions to the theoretical understanding of digital transformation in higher education.\u003c/p\u003e \u003cp\u003eFirst, it advances the conceptualization of digital leadership by positioning it within a multi-level framework that links individual leadership capabilities to organizational and system-level outcomes. By moving beyond the traditional focus on organizational performance, this study provides a more comprehensive understanding of how leadership influences transformation across multiple levels.\u003c/p\u003e \u003cp\u003eSecond, the study integrates digital leadership with system-level transformation, addressing a key gap in the literature. While these concepts have often been studied separately, this research demonstrates that they are inherently interconnected. The proposed framework highlights the pathways through which leadership influences systemic change, providing a foundation for future research in this area.\u003c/p\u003e \u003cp\u003eThird, the study identifies governance quality and institutional readiness as critical mediating variables, offering a more nuanced understanding of the transformation process. This contribution is particularly significant, as it shifts the focus from direct effects to the mechanisms that enable or constrain transformation. By incorporating these mediators, the study provides a more realistic and context-sensitive model of digital transformation.\u003c/p\u003e \u003cp\u003eFourth, the study contributes to the literature by providing empirical evidence from a developing country context, addressing the geographical imbalance in existing research. As noted by Altbach and de Wit (2020), much of the higher education literature is dominated by studies from Western contexts. By focusing on Indonesia, this research offers insights that are more relevant to emerging economies, where challenges related to governance, resources, and institutional diversity are more pronounced.\u003c/p\u003e \u003cp\u003eFinally, the use of a mixed-method approach enhances the robustness of the findings and contributes methodologically to the field. By integrating quantitative and qualitative data, the study captures both the measurable relationships between variables and the contextual factors that influence transformation. This approach provides a more holistic understanding of digital transformation and sets a precedent for future research.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Practical Implications","content":"\u003cp\u003eThe findings of this study provide actionable insights for multiple stakeholders in higher education, particularly institutional leaders, policymakers, and leadership development practitioners. By demonstrating the central role of digital leadership in driving system-level transformation, as well as the mediating effects of governance quality and institutional readiness, this study offers practical guidance for designing more effective transformation strategies in the context of Indonesian higher education and similar developing systems.\u003c/p\u003e \u003cdiv id=\"Sec34\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Institutional Level\u003c/h2\u003e \u003cp\u003eAt the institutional level, the findings highlight the importance of strengthening internal capacities to support digital transformation. Higher education institutions must move beyond isolated technological adoption toward a more integrated approach that aligns digital initiatives with organizational strategy. This requires universities to embed digital transformation within their core mission, including teaching, research, and community engagement.\u003c/p\u003e \u003cp\u003eFirst, institutions should invest in digital infrastructure and technological ecosystems that enable seamless integration of digital tools into academic and administrative processes. The relatively lower levels of institutional readiness identified in this study indicate that many universities still face capacity constraints, particularly in terms of infrastructure and human resources. Addressing these gaps is essential for ensuring that digital leadership efforts can be effectively translated into practice.\u003c/p\u003e \u003cp\u003eSecond, universities should foster a culture of innovation and adaptability. The significant impact of digital leadership on innovation and adaptability suggests that organizational culture plays a crucial role in transformation. Institutions should encourage experimentation, interdisciplinary collaboration, and continuous learning among faculty and staff. This can be achieved through initiatives such as innovation labs, digital teaching programs, and incentives for adopting new pedagogical approaches.\u003c/p\u003e \u003cp\u003eThird, institutions should strengthen internal governance and coordination \u003cb\u003emechanisms\u003c/b\u003e. Effective digital transformation requires alignment across different units within the university, including academic departments, IT services, and administrative offices. Establishing clear governance structures, communication channels, and accountability mechanisms can enhance coordination and reduce fragmentation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Policy Level\u003c/h2\u003e \u003cp\u003eAt the policy level, the study underscores the need for coherent and coordinated governance frameworks that support system-level transformation. The significant mediating role of governance quality indicates that policy environments play a crucial role in enabling or constraining digital leadership.\u003c/p\u003e \u003cp\u003eFirst, policymakers should develop integrated national strategies for digital transformation in higher education. These strategies should align institutional objectives with broader national priorities, such as economic development, innovation, and global competitiveness. Clear policy direction can provide a shared vision and reduce inconsistencies in implementation across institutions.\u003c/p\u003e \u003cp\u003eSecond, there is a need to strengthen regulatory frameworks and quality assurance systems. Policies should support innovation while maintaining standards of quality and accountability. Flexible regulatory approaches, such as outcome-based accreditation and support for digital learning models, can enable institutions to experiment with new approaches without compromising quality.\u003c/p\u003e \u003cp\u003eThird, policymakers should prioritize equitable resource allocation and capacity building, particularly for institutions in less developed regions. The disparities in institutional readiness identified in this study highlight the risk of widening gaps between institutions. Targeted funding programs, infrastructure development initiatives, and capacity-building programs can help address these inequalities and promote more inclusive transformation.\u003c/p\u003e \u003cp\u003eFinally, fostering collaboration and knowledge sharing across institutions is essential for system-level transformation. Policymakers can facilitate this by supporting national and regional networks, partnerships, and platforms for sharing best practices. Such collaboration can accelerate innovation diffusion and enhance the overall effectiveness of the higher education system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003e6.3 Leadership Development\u003c/h2\u003e \u003cp\u003eThe findings also have important implications for leadership development in higher education. As digital transformation becomes increasingly central to institutional success, there is a growing need to develop leaders who possess the competencies required to navigate complex and dynamic environments.\u003c/p\u003e \u003cp\u003eFirst, leadership development programs should focus on building digital competencies, including strategic thinking, data literacy, and technological awareness. Leaders must be able to understand and leverage digital tools to support decision-making and innovation. This requires continuous professional development and exposure to emerging technologies.\u003c/p\u003e \u003cp\u003eSecond, programs should emphasize transformational and adaptive leadership skills. Digital transformation is inherently uncertain and requires leaders to manage change, address resistance, and foster a shared vision. Training in change management, communication, and stakeholder engagement can enhance leaders\u0026rsquo; ability to drive transformation.\u003c/p\u003e \u003cp\u003eThird, leadership development should adopt a multi-level perspective, recognizing that transformation requires coordination across institutional and system levels. Programs should therefore include components that address policy understanding, governance, and inter-institutional collaboration. This can help leaders align their strategies with broader system-level objectives.\u003c/p\u003e \u003cp\u003eFinally, there is a need to promote collaborative and distributed leadership models. Rather than relying solely on top-down leadership, institutions should encourage shared leadership practices that involve faculty, administrators, and external stakeholders. This approach can enhance organizational agility and support more sustainable transformation.\u003c/p\u003e \u003cp\u003eOverall Implication\u003c/p\u003e \u003cp\u003eCollectively, these implications suggest that successful digital transformation in higher education requires a holistic and coordinated approach that integrates leadership, governance, and institutional capacity. By addressing these dimensions simultaneously, stakeholders can create more resilient and adaptive higher education systems capable of responding to the challenges of the digital era.\u003c/p\u003e \u003c/div\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThis study set out to examine the role of digital leadership in driving system-level transformation in Indonesian higher education through the mediating roles of governance quality and institutional readiness. The findings provide strong empirical evidence that digital leadership significantly influences organizational innovation, institutional adaptability, and ultimately system-wide transformation.\u003c/p\u003e \u003cp\u003eThe results highlight that digital leadership is not only a driver of internal organizational change but also a catalyst for broader systemic transformation when supported by effective governance structures and sufficient institutional capacity. The identification of governance quality and institutional readiness as key mediating variables underscores the importance of a multi-level approach to understanding and implementing digital transformation.\u003c/p\u003e \u003cp\u003eFrom a theoretical perspective, this study advances the literature by integrating digital leadership and system-level transformation within a unified analytical framework. From a practical perspective, it offers actionable insights for institutional leaders and policymakers seeking to enhance the effectiveness of digital transformation strategies.\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section2\"\u003e \u003ch2\u003e7.1 Limitations\u003c/h2\u003e \u003cp\u003eDespite its contributions, this study has several limitations. First, the use of cross-sectional data limits the ability to establish causal relationships over time. Future studies could adopt longitudinal designs to better capture the dynamics of digital transformation.\u003c/p\u003e \u003cp\u003eSecond, the study focuses on Indonesia, which may limit the generalizability of the findings to other contexts. While the results provide valuable insights for developing countries, further research is needed to test the model in different national settings.\u003c/p\u003e \u003cp\u003eThird, although the mixed-method approach enhances the robustness of the findings, the qualitative component is limited in scale. Future studies could incorporate more extensive qualitative data to provide deeper contextual insights.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003e7.2 Future Research\u003c/h2\u003e \u003cp\u003eFuture research should explore several directions. First, longitudinal studies are needed to examine how digital leadership and system-level transformation evolve over time. Second, comparative studies across countries could provide insights into how contextual factors influence transformation processes.\u003c/p\u003e \u003cp\u003eThird, future research could incorporate additional variables, such as organizational culture, digital maturity, and stakeholder engagement, to further refine the analytical framework. Finally, there is a need for more research on leadership development models that can effectively prepare leaders for the challenges of digital transformation in higher education.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eResearch Article wrote main manuscript in 8753 words and 4 table\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to express their sincere gratitude to all individuals and institutions that contributed to the completion of this study. Special appreciation is extended to colleagues and academic peers for their valuable insights, constructive feedback, and intellectual support throughout the research process.The authors also acknowledge the institutional support provided by Universitas Pendidikan Indonesia, which facilitated the successful implementation of this research.This work was supported by [insert funding agency name] under Grant No. [xxxxxx]. The authors gratefully acknowledge this financial support.In addition, the authors thank all participants and respondents who willingly contributed their time and perspectives, which were essential to the development of this study.This acknowledgment replaces all previous versions and represents the final version approved for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmad T, Sulastri L (2023) Digital leadership in Indonesian universities. 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Educational Technol Res 69:2305\u0026ndash;2315\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"sn-social-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"SN Social Sciences","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Digital leadership, higher education, system-level transformation, governance, SEM-PLS, Indonesia","lastPublishedDoi":"10.21203/rs.3.rs-9337496/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9337496/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose. This study aims to examine the role of digital leadership in driving system-level transformation in Indonesian higher education. It seeks to understand how leadership capabilities influence organizational innovation and adaptability, and how these effects contribute to broader transformation through governance quality and institutional readiness.\u003c/p\u003e \u003cp\u003eDesign/methodology/approach. A national mixed-method approach was employed. Quantitative data were collected from 312 university leaders across Indonesia and analyzed using structural equation modeling (SEM-PLS). This was complemented by qualitative data from case studies and focus group discussions to provide contextual insights and triangulation of findings. Findings\u003c/p\u003e \u003cp\u003eThe results indicate that digital leadership has a significant positive effect on organizational innovation and institutional adaptability. Furthermore, system-level transformation is indirectly influenced by digital leadership through the mediating roles of governance quality and institutional readiness. The findings highlight that effective digital leadership must be aligned with policy frameworks and supported by institutional capacity to achieve systemic impact. Practical implications. The study provides actionable insights for policymakers and higher education leaders. It suggests the need for strengthening digital leadership competencies, enhancing governance frameworks, and investing in institutional readiness to support coordinated transformation. The findings are particularly relevant for developing countries seeking to improve the global competitiveness of their higher education systems. Originality/value. This study contributes to the literature by integrating digital leadership and system-level transformation within a multi-level framework. 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