Introduction

Universities are complex organizations composed of various actors from different disciplines and departments, each pursuing their own teaching, research, and administrative agendas (Becher & Trowler, 2001; Mokher et al., 2019; Musselin, 2007; Weick, 1976). Historically, change within universities has been challenging (Lane, 2007; Meister-Scheytt & Scheytt, 2005), especially in areas such as teaching and research, which fall under the jurisdiction of academic freedom and professor autonomy (Kalfa et al., 2018; Kezar, 2001). Educational technology (EdTech) intersects with these protected domains, making its adoption complex. EdTech refers to the integration of technology into learning, encompassing tools such as Learning Management Systems (e.g., Blackboard, Moodle, Canvas), interactive devices like digital projectors and student response systems, and hybrid, blended, and remote teaching formats that combine online and in-person instruction for flexible learning environments.

The use of EdTech challenges traditional pillars of the university classroom in regards to course design, student participation, and teachers’ roles and responsibilities (Liu et al., 2017; Yamagata-Lynch et al., 2015). Most recently, these challenges to university life were intensely felt by instructors during the rapid digital transformation in the wake of the COVID-19 pandemic (Alhumaid et al., 2020; de Oliveira Durso et al., 2021). University leaders tasked with fostering digital change are understandably confronted with challenges such as tensions between management and teachers (Bygstad et al., 2022), disciplinary differences regarding the need and use of technology (Racovita-Szilagyi et al., 2018; Tyebally & Dong, 2021), varying levels of digital literacy (Ocak, 2011) and even resistance (Watty et al., 2016).

Our study examines not only the adoption of EdTech but also how trust and leadership dynamics influence its effective implementation. Previous research has highlighted EdTech's potential to transform educational practices and the challenges associated with its integration, emphasizing the need for supportive leadership (Moser, 2007; Singha & Singha, 2024). Also in the broader context of organizational innovation, leadership, trust, and technology adoption are critical factors influencing an organization's ability to innovate (Damanpour & Schneider, 2006). While EdTech refers to the use of technology to enhance teaching and learning, it must be emphasized at this point that innovation in education can occur independently of technology and that conversely, not all uses of EdTech are inherently innovative. We distinguish between EdTech adoption and true pedagogical innovation, suggesting EdTech can foster innovation through catalyzing new teaching methods and approaches. This paper aims to understand the conditions under which EdTech drives innovation in higher education institutions (HEIs).

Generally, innovation within HEIs is driven by the need to enhance teaching and learning outcomes, improve operational efficiency, and remain competitive in a digital world (Schneckenberg, 2009). Our study examines how trust in staff's abilities to utilize EdTech can foster an innovative culture within HEIs. This aligns with existing research that highlights the importance of leadership in driving institutional innovation (Li et al., 2017; Uy et al., 2024). Therefore, despite the difficulties associated with this task, educational leaders have been found to play important roles in shaping innovation in their institutions (Al-Husseini et al., 2021; Buyukgoze et al., 2022; Deacon et al., 2022; Kılınç et al., 2022; Sauphayana, 2021; Tsai et al., 2019). For example, university leaders have been found to be a driving force for institutional innovation through their ability to promote stability, open communication, provide financial support and offer clear direction (Sauphayana, 2021). In addition, leaders can motivate faculty members to innovate by creating a vision and providing intellectual stimulation, an exploratory way of thinking, which helps faculty members feel valued (Al-Husseini et al., 2021), committed (Kılınç et al., 2022) as well as help overcome barriers for innovation (e.g. by offering training) (Tsai et al., 2019), influencing the emergence of creativity (Rae, 2023) and guide the exploration of new technologies (Tsai et al., 2019).

Unpacking the concept of trust, the literature also shows that it is important for leaders to trust their staff members with space to experiment and innovate with technology (Al-Mansoori & Koç, 2019; Elsholz et al., 2021; Ng’ambi & Bozalek, 2013). Elsholz and colleagues (2021) stress that university management needs to practice ‘organized freedom,’ which involves providing teachers with a balance of guidance and infrastructure as well as freedom to innovate with technology. This resonates with Al-Mansoori and Koç’s (2019) who emphasize the importance of university leaders recognizing employee expertise and implementing incentive schemes to foster innovation. Similarly, Ng’ambi & Bozalek (2013) suggest that university leaders should collaborate with informal technology leaders to promote widespread technology adoption. These studies indicate how trust contributes to staff members' innovation (Al-Mansoori & Koç, 2019; Ng’ambi & Bozalek, 2013) as well as the crucial role leaders play in implementing EdTech strengthening digital change in a complex environment (Elsholz et al., 2021; Watty et al., 2016). However, ‘trust’ has rarely been the subject of investigation in this literature. Therefore we define and operationalize organizational trust in this context to capture the elements of a relationship between trustor and trustee (for a detailed discussion on organizational trust—see section “Organizational Trust and Innovation” and the “Research Methods”).

In response to this predicament, university leadership often walks a tightrope between both needing to steer innovation and support freedom to innovate. This paper aims to unpack the complex role university leaders play and how they can best steer and support the use of EdTech at their institutions. Specifically, through talking to both leaders and staff within the same HEIs, we aim to understand the nuanced relationship between leadership trust in staff's abilities to use EdTech and its contribution to innovation in their institutions, posing the following research question:

How Does a University Leader’s Trust in their Staff’s Abilities to Use EdTech Contribute to Innovation in their Institutions?

To theoretically frame our study, we draw on the complexity leadership theory (CLT) (Uhl-Bien & Arena, 2018; Uhl-Bien et al., 2007) and organizational trust (Mayer et al., 1995). The CLT conceptualizes leadership as three intertwined leadership types—operational, entrepreneurial, and enabling. Operational leadership refers to the carrying out of administrative procedures; whereas entrepreneurial leadership is about creating innovative ideas and enabling leadership focuses on balancing administrative tasks and supporting innovation. We aim to investigate how these leadership types convey organizational trust (Mayer et al., 1995) and how trust contributes to digital innovation. Innovation, we understand as the creation of new ideas, knowledge, processes and practices. The relationship between leadership, trust, and innovation will be explored through the analysis of eight European study programs that used EdTech to varying extents.

This paper aims to further our understanding of how university leaders can best steer and support digital change at the university. From the literature, we can surmise that leaders play an essential role in implementing technological innovation in a complex environment (Elsholz et al., 2021; Ng’ambi & Bozalek, 2013; Watty et al., 2016). However, the role trust plays in this relationship has only been marginally researched and merits further investigation.

Complexity Leadership Theory

CLT provides a framework to examine the multifaceted role leadership plays in contributing to the adaptivity of complex systems (Uhl-Bien, 2021; Uhl-Bien & Arena, 2018; Uhl-Bien et al., 2007). An organization is considered ‘complex’ when it cannot be understood through analyzing its individual components; rather a comprehensive understanding is only reached when examining dynamic interactions between agents, structures, and the larger environment (Uhl-Bien, 2021). HEIs have been described as complex organizations (Bradshaw & Fredette, 2009; Dawson et al., 2018; Meister-Scheytt & Scheytt, 2005; Tsai et al., 2019), with scholars having noted the specific nature of universities (Musselin, 2007) with such features as loose coupling (Sapir & Oliver, 2017; Weick, 1976), autonomous professors (Enders, 2001), and disciplinary and departments subcultures (Becher & Trowler, 2001; Lee, 2007). CLT takes this complexity into account in its conceptualization of leadership, which departs from the traditional focus on the actions of individual leaders to a broader understanding of leadership—a dynamic interactive process occurring throughout an organization. To untangle this complexity, CLT focuses on three types of leadership: operational, entrepreneurial, and enabling (Uhl-Bien & Arena, 2018).

Operational leadership refers to the actions of individuals who are in formalized leadership positions within an organization. This form of leadership is tasked with maintaining control and fulfilling organizational goals. For example, operational leadership is responsible for organizational planning, creating strategies, allocating resources and managing crises when they arise as well as incorporating new changes into organizational operations. While operational leadership is linked to the hierarchy of the organization and formalized positions in contrast, entrepreneurial leadership is emergent and can occur within any level of an organization. This form of leadership functions “to create new knowledge, skills, products and processes to sustain the future viability of the firm (i.e. exploration)” (Uhl-Bien & Arena, 2018, p. 10). For example, a university instructor who is interested in pursuing new technologies may emerge as an entrepreneurial leader in their faculty without being formally recognized as one. However, in order for entrepreneurial leadership to emerge the appropriate organizational conditions need to be in place. This is accomplished through enabling leadership which consists of “creating structure and processes … to trigger and amplify emergence (i.e., innovation, adaptive responses) into [a] new adaptive order” of an organization (Uhl-Bien & Arena, 2018, p. 10). This can include organizing physical space (e.g. workspace), virtual space (e.g. online formats), dedicating time (e.g. meetings, sprints) and thinking time (e.g. time set aside for brainstorming). Enabling leadership often overlaps with operational leadership, as creating an enabling environment often goes hand in hand with individuals having sanctioned authority within an organization to make such changes.

These three types of leadership facilitate the adaptivity of organizations: entrepreneurial leadership is about bringing forth new ideas, operational leadership underwrite innovation by providing the necessary support and mainstreaming innovative practices into core operations and enabling leadership creates the conditions for innovation to thrive. However, these types of leadership can also work in conflict with each other: operational leadership can fail to practice enabling leadership by imposing strict bureaucratic control which in turn diminishes the space for entrepreneurial leadership to emerge. Moreover, individuals can practice different types of leadership simultaneously in response to the context, e.g. in different instances organizational leaders can practice enabling as well as entrepreneurial leadership.

CLT has been applied to a limited extent to study leadership structures in higher education (Dawson et al., 2018; Dumulescu & Muţiu, 2021; Mäkinen, 2018; Tsai et al., 2019). For example, Dawson et al. (2018) and Tsai et al. (2019) used CLT to investigate the implementation and adoption of learning analytics (LA). In their study of LA adoption challenges in 21 HEIs located in the United Kingdom, Tsai et al. (2019) found that tension arose between operational and entrepreneurial leaders as there was not enough ‘adaptive space’ to engage in innovation and create a common vision. Dawson et al. (2018) examined complex leadership as it related to LA adoption at 26 Australian universities. In 32 interviews with senior managers, the authors identified two LA adoption processes (top-down and bottom-up) driven by university leadership. The top-down approach failed to provide enough creative space for staff to innovate with LA while the bottom-up approach led to a lack of networking and collaboration between separate groups within the institutions. These studies highlight the complexity involved in implementing technological innovation at the university and indicate the importance of balancing different leadership types.

Finding the right balance between these different leadership types has proven to be a difficult task as demonstrated in a study from Mäkinen (2018). In the examination of leadership roles in a transdisciplinary science research center, Mäkinen found that academic leaders often used different leadership practices depending on the needs of the context. For example, leaders practiced enabling leadership when the research center was forming and later focused more on operational leadership. However, shifting between these roles and finding a balance between them proved to be a main challenge. In addition, in a recent study, Dumulescu and Muţiu (2021) coupled leadership strategies with trust and empowerment. They used the CLT as a lens to understand the complexity driving leadership strategies at a Romanian university during the first semester of the COVID-19 pandemic. The authors identified how the personal attributes of academic leaders (e.g., previous experience, responsibility, and adaptability) were key in the central leadership’s strategy of “unity through decentralization” (Dumulescu & Muţiu, 2021, p. 6). This strategy empowered deans with trust and delegated them the responsibility of plotting their own courses of action for their faculties during the crisis.

These studies show how CLT situates leadership as a dynamic process occurring across a complex organization, like universities (Dawson et al., 2018; Tsai et al., 2019). Moreover, this conceptualization is inherently built on trust—that is, leaders must first have trust in their employees’ abilities, before they engage in enabling leadership and sponsor the emergence of entrepreneurial leaders (Dumulescu & Muţiu, 2021). In the following section, we explore the concept of organizational trust and its connection to leadership and innovation.

Organizational Trust and Innovation

We draw upon the organizational trust definition from Mayer and colleagues, who define organizational trust as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party” (Mayer et al., 1995, p. 712). This definition in contrast to other conceptualizations (Saruhan, 2013; Zaheer et al., 1998), takes into consideration both the characteristics of the “trustor” and “trustee” (Mayer et al., 1995). Research indicates there is a connection between organizational trust and innovation (Ellonen et al., 2008; Krot & Lewicka, 2011; Pučėtaitė, 2014; Sankowska, 2013; Savolainen, 2008; Yu et al., 2018). For instance, Ellonen et al. (2008) explored the relationship between organizational trust and organizational innovativeness, a term used to describe an organization’s ability to innovate products, market, processes, and strategy. In a survey of three large multinational companies, they found that trust in an organization's strategy, policies and leadership significantly influenced an organization's innovativeness. Similarly, Yu et al. (2018) drawing on questionnaires from 63 Chinese companies, identify that organizational trust is a central contributor for innovative employee behavior (e.g. problem identification, idea generation and implementation). They recommended such behaviors be fostered through a supportive work environment, demonstrating investment in employees as well as ensuring that employees feel integrated in the organization. The interconnection of trust and innovation was further articulated by Sankowska (2013), who in their investigation of innovation in 202 Polish companies, concluded, “trust should be treated as the cornerstone to the innovativeness [of the organization].” (Sankowska, 2013, p. 95). These studies underline that trust is a foundational principle in providing an environment that allows and supports innovation.

This maxim also holds true in the context of higher education (Johan, 2021; Lin & Shin, 2021; Oliver et al., 2020; Yusuf, 2020). For example, Lin and Shin (2021) investigated the innovative behavior, e.g. the creation and implementation of new ideas, of 271 professors at Chinese sports universities. Their findings demonstrate that organizational trust is closely linked to innovative behavior and increases innovation creation. In a related study, Oliver et al. (2020) in their study of university-industry collaborations, found that trust established on individual and organizational levels were key to the success of these collaborations. Specifically, trust was fostered between collaborating scientists through such factors as professional reputation and shared background, commitment towards the project and upholding scientific standards and possessing a flexible mindset. Additionally, Yusuf (2020) in their study on lecturer satisfaction and trust in private universities in Indonesia, found that lecturers' trust in their institutional leaders and organization was related to their freedom to innovate (e.g. experiment, take risks, look for new opportunities). Johan (2021) supports this finding in his survey of 74 lecturers working at a private Indonesian university, and found that lecturers’ trust in their leader improved their initiative and willingness to engage in innovation, e.g. create new ideas, processes, products or procedures.

These studies highlight the interconnected relationship between organizational trust and innovation (Ellonen et al., 2008; Oliver et al., 2020; Sankowska, 2013; Yu et al., 2018) and the crucial role organizational leaders can play in facilitating this relationship (Johan, 2021; Yusuf, 2020). Furthermore, they provide a foundational understanding that complements our investigation of trust and innovation within higher education, underscoring the universal principles of trust's impact on innovation across different sectors.

Research Methods

In line with the comparative case study approach from Bartlett and Vavrus (2017), we selected eight heterogeneous study programs within HEIs as our cases. Each of the eight study programs represent a distinct 'case' based on a specific academic program at a particular university. The study programs diverged in various ways (see Table 1 in the appendix): some study programs had extensive experience with EdTech while others were in the process of mainstreaming it into their curricula. Focusing on study programs enables a deeper exploration of contextual factors and dynamics influencing EdTech adoption and innovation. Our case study approach involves interviewing stakeholders and analyzing organizational structures, decision-making processes, and contextual conditions to identify specific patterns, challenges, and opportunities within each case. This selection of heterogeneous cases aims to elucidate how factors like funding, institutional identity, system-level trends, and societal discourse shape staff experiences with EdTech in higher education.

Our methodological approach is based on the Interactive Research Model, in which research participants are included in various stages of the research process with the purpose of gathering greater insight into relevant issues and challenges as well as providing research-based recommendations (Ellström et al., 2020). In this regard, we had an Open Call for Case Studies, in which interested parties could apply to be part of our study and hosted knowledge transfer workshops with the research participants. While the open call for applications can lead to a bias towards applications from people who are already highly motivated and experienced in using EdTech, we tried to counteract this imbalance by deliberately enriching the selection with cases that were less experienced and explicitly reported challenges. We were also able to counteract this by explicitly asking to also interview people who are critical towards digital development. In total 68 staff members were interviewed who were connected to the selected study programs in different ways—teaching staff, technical, support, administrative staff and institutional leadership / management. This sampling strategy captured how different levels / units at the university interact.

To address our research question, we developed interview questions grounded in our theoretical framework and relevant literature. Leadership types, such as operational, entrepreneurial, and enabling, were operationalized through targeted questions: operational leadership explored hierarchical structures and formal control mechanisms, entrepreneurial leadership focused on motivation and innovation, and enabling leadership centered on balancing administrative tasks with fostering creative experimentation. Broad topics explored organizational conditions influencing EdTech adoption including digitalization strategies, innovative culture, technical and pedagogical support, and organizational identity. In relation to leadership, we posed questions such as, “Who or what do you think is driving the use of digital education at your university?” and, “How hierarchical is the organization of digital teaching at your university, and where do you see specific responsibilities?” Additionally, interviewees were asked to elaborate on the roles different leadership positions play in the implementation of online teaching. The questionnaire included core questions for consistency across interviews and additional queries tailored to specific roles (e.g., leaders vs. teaching staff), ensuring both comparability and capturing diverse stakeholder perspectives. Interviews were conducted across eight HEIs with leaders, administrative staff, and teaching staff. On average, interviews lasted approximately one hour, were recorded, transcribed, and anonymized.

Thematic analysis (Williams & Moser, 2019) guided our analysis of interview data. A collaborative effort produced a codebook incorporating both theory-driven and data-driven codes. Initial open coding identified themes from textual indicators and recurring material, generating a preliminary list of codes. These codes were then refined in axial coding, linking them to our theoretical framework on leadership types and trust. For instance, trust was conceptualized in terms of the trustor-trustee relationship. Additional codes related to elements such as experimentation, innovation, leadership styles (formal and informal), academic freedom, and opportunities were analyzed for trust-related dimensions. Selective coding further refined these themes to ensure coherence and validity. MAXQDA software facilitated coding for consistency. The research team conducted joint coding of a sample of interview data to establish a shared understanding of the codebook, with regular meetings to address discrepancies.

Findings

Using CLT and the concept of organizational trust, we reflect on the triad relationship between leadership, trust, and digital innovation by drawing on interviews from university leaders, (e.g. vice rectors, deans) and from teachers, technical and administrative staff working in connection to the same case study. We also detail features of the cases to contextualize leadership approaches and staff experiences.

Our analysis revealed that university leaders were often positioned as ‘gatekeepers’ of digital innovation as they regulated key administrative procedures such as funding, quality assurance, strategy, and work contracts. In numerous examples, they demonstrated trust in their employees' abilities to select and implement EdTech effectively, often accompanied by enabling leadership. This trust led to positive outcomes like increased motivation, innovation, and the emergence of entrepreneurial leaders; individuals voluntarily taking on leadership roles based on their intrinsic motivation. However, our findings also revealed a darker side, where trust was limited to a select few, creating tension within institutions or used as a means to assign extra work without providing support.

Trusting Individuals & Sharing Responsibility

University leaders demonstrated trust towards individuals by delegating or collaborating on decision-making regarding digital innovations. The practice of sharing responsibility was most apparent in four case studies: two were study programs located in institutions in the United Kingdom, one a private university of applied sciences with close links to industry and the other a public research university. The other two study programs were located in institutions in Austria and Germany. The former in a public Austrian university of applied sciences and the latter in a private German university of applied sciences. These institutions shared some contextual similarities that may explain why university leaders within these cases emphasized trusting individuals and sharing responsibility for technological innovations. Most prominently, across the aforementioned cases, we saw a common goal of running efficient and competitive organizations equipped to respond to market demands and to varying degrees dependent on tuition fees as means of funding. Notably, within this commonality of sharing trust and responsibilities connected to decisions regarding EdTech, at the same time different contextual features of a case lead to trust being directed to different levels within a university. Both British institutions for example followed more pronounced New Public Management (NPM) principles, emphasizing streamlined management structures. This aligns with a system level trend and with the UK government's efforts to reorganize universities based on NPM and treating them like private companies (Chandler et al., 2002; Lapsley & Miller, 2024). Here we identified a focus being placed on fostering innovation through enabling leadership by trusting teaching staff. The study program within the Austrian university was considered an ‘outlier’ compared to the rest of the university's programs as it was conducted online and designed for working professionals. This meant it also provided a “cash-flow” for the university and catered to the needs of a specific clientele similar to a private university. This context again had an impact on how, why and to whom trust was allocated to, leading in this case to trust being allocated to the study program due to its unique nature and operational model that distinguishes it from other traditional programs. At the German private university, there was a more pronounced hierarchy compared to its British and Austrian counterparts, leading to trust being conveyed specifically to middle management as central-level university leaders shared decision-making about the use of digital tools only with mid-level leaders such as deans and study program leaders instead of teachers. In sum, the shared orientation across all four cases, despite targeting different levels, kept administrative procedures agile and the university competitive.

Trusting Teachers

At the two British universities, university leaders similarly practiced enabling leadership by delegating decision-making about technological innovations to teachers themselves.

At the private applied university, a trustful relationship with teachers was prioritized as a means to spark innovation. In this regard, a senior manager explained the necessity for leaders to create space for teachers to experiment with digital teaching:

I think the first one [condition] is probably a reasonable amount of freedom. And that is the freedom to experiment, to have ownership of their own classes, to not feel that they are going to get in trouble if something does not work out in some way. (Senior manager at a British university)

This senior manager understood their authority position as a means to practice enabling leadership: their role was to foster an organizational culture that promoted experimentation with digital tools and formats and mistakes were taken in stride. This sentiment was echoed by a deputy dean at the same institution, who explained, “we trusted our tutors to think of the best solutions for what they were doing. So, over a period of time, there was more diversification in how we did in teaching.”

This trust also resulted in a “flat hierarchy” at the institution and collaborative approach between university leaders and teaching staff implementing technological innovation:

… [there is a] feedback loop from teachers and tutors at the coalface who are sharing their learning and that's filtering up and people are listening to it and then trying to find solutions which accommodate these new thoughts and ideas. (Dean at a British university)

Trusting staff's tech abilities, a program leader continued to explain, was linked to their industrial experience. The university marketed their connection to industry as a ‘selling point’ to prospective students and thus valued the industry expertise of staff members, which translated into trusting them to determine the appropriate technologies for their courses. This collaborative approach aligns with enabling leadership as it allowed for the emergence of entrepreneurial leaders at the university, individuals with digital expertise taking on leading roles without being formally appointed. However, at the same time, it led to some ambiguity and confusion concerning who should take on certain responsibilities as well as pressure for staff to assume leadership roles.

At the other UK institution, a research university, the shared approach to decision-making and the importance teachers played when innovating with EdTech was described as followed:

...quite a bit of innovation and change always comes from the bottom-up. People wanting to try something and then communicating the experience of others and spreading it that way. (Teacher at a British university)

This teacher further described how the university had a “relatively light touch approval system” regarding digital tools, however a digital examination format would need approval from university administration. This teacher’s experience was mirrored in accounts from the middle-management. For example, a dean from the same faculty commented, “generally, we've got a pretty free flowing conversation, we can give feedback, our concerns and comments. And I think the university does a pretty good job in responding.” This assessment matched an account of another interviewee positioned at a central administrative unit, who remarked that decision-making was often allocated to individual schools:

… our university isn't very hierarchical anyway, it's … [a] very devolved university. So, it's just decision-making and budgets set primarily at the school level … So, if the school really wants to pursue a particular path … they will do it. (Assistant Director of Digital Education at a British university)

The school, several interviewees expressed, had a powerful role in deciding matters related to the use of technologies due to their budgetary control and oversight of the study programs. However, this shared responsibility was not always upheld across the board and central administration maintained competencies in some areas, specially during the COVID-19 crisis. This led to some clashes and frustration for teachers:

There are these top level decisions, for instance, on what type of [digital] tool to use, that as a sort of limited input from our side … these types of decisions are taken centrally and that can sometimes result in clashes with the local expertise. (Teacher at a British University)

At this university unlike the one above, there were more formal pathways and procedures. Decision-making involved multiple actors with their own spheres of influence: teachers had some freedom using technology in their teaching but were limited to available digital tools and faced restrictions when organizing digital examinations. Likewise, schools were granted a great deal of autonomy and budgetary oversight, but also answered to the central administration. This complexity arose from competing management structures: the central administration performed operational leadership hierarchically, while the school worked collaboratively with teachers in a flatter hierarchy resembling enabling and entrepreneurial leadership. Balancing these leadership types was crucial to harness teacher innovation in this environment.

Trusting the Study Program

University leaders in the Austrian university of applied sciences took a different approach to conveying trust to their staff members. Trust involved delegating the responsibility of technical innovation to the study program level. The above described contextual features of the study program being an ‘outlier’ and functioning similar to a private university allowed the study program to operate mostly autonomously:

… we are our own company, our own enterprise, the university is de facto outside in these things. In the operational implementation in the daily work that is all the [study program], the university plays no role here. (Teacher at an Austrian university)

This assemblage, the interviewee went on to elaborate, granted the study program certain privileges enabling it to respond flexibly to meet demands of the market. This mentality mirrors entrepreneurial leadership, as it empowered team members to collectively make decisions for their study program. Moreover, this flat hierarchy negotiated within the sphere of the study program, as one teacher explained, led to managers practicing enabling leadership.

… you don't necessarily need a manager who manages everything from above, but rather a leader who enables the team members to do their work well. That's how it works [here]. (Teacher at an Austrian university)

This enabling leadership structure led to the teaching staff being given a high level of autonomy and trust from their study program coordinator, a privilege that also came with its workload as illustrated by another staff member working in administration:

… so, to speak, management trusts us a lot, but of course also challenges us accordingly … so we have a lot in our hands that we are allowed to do ourselves, and as long as the work is done, so to speak, we are rarely interfered with. (Study Advisor at an Austrian university)

In this environment, motivation was high and innovation occurred naturally through interactions between colleagues and anyone—regardless of rank—was able to bring to discussion an idea for a new product, tool or course.

…it's relatively relaxed here, we can exchange ideas relatively quickly … and say: "Hey, I have an idea …. that's how ideas often develop and I think that's actually very cool because we help each other … together we often come up with even cooler ideas or even cooler things on how to implement something … so we are not so stuck, but still have the freedom to really think about what really makes sense here... (Teacher at an Austrian university)

Although the culture of the study program was informal and nonhierarchical, the university hierarchy still played a role in ‘green-lighting’ more comprehensive changes. However, negotiating within this hierarchy was considered a minor hurdle and sometimes more of a formality. In this case study, the three leadership types—operational, enabling and entrepreneurial—appeared to find the right balance of providing organizational support and freedom for innovation.

Trusting the Middle Management

At the private German university, conveying trust and sharing responsibility was practiced differently. We found that central-level university leaders shared decision-making about the use of digital tools with mid-level leaders such as deans and study program leaders instead of teachers. While central administration seemed to start and guide the process, the responsibility to implement EdTech rested with the faculties. In the quote below a teacher describes this division of labor.

I think the university management and also the management of the dean's office were basically trying to get everything started [with online teaching] … at the end of the day, we in the faculty have also adapted to it. (Teacher at a German university)

However, although central-level leaders entrusted the faculties with power to determine their own EdTech agendas, this trust did not extend to teachers. Instead university leaders feared losing oversight when their teachers worked online. This fear of losing control, another teacher explained was due to private universities being run more like companies:

The fact that mistrust arose, without good reason by the way, on the part of the management and the rectorate, this is a double structure in private universities, and also not easy, whether we [teachers] really are all working. And then such instruments as attendance lists are introduced, these are control instruments where we are supposed to register when we work, where and on what … these structures are ultimately labor-intensive … that keep us from doing what we really want to do. (Teacher at a German university)

Although NPM is less prevalent in German higher education compared to the United Kingdom (Hüther & Krücken, 2013), competition for resources remains crucial for private institutions. One teacher highlighted that they were only compensated for teaching units, leaving no time or opportunity for innovative thinking about digital teaching. The institution's reliance on tuition fees may have increased pressure on university leaders to control teaching output and ensure quality. This focus on operational leadership limited the emergence of entrepreneurial leaders and hindered the provision of space for experimentation and training by only partially providing enabling leadership in their relationship with middle managers.

Trust in the Organizational Culture

The other four universities, three public German universities and an Estonian public university, share the organizational orientation that responsibilities regarding EdTech and trust in teacher expertise were integral to their organizational cultures. Notably, the three German universities emphasized 'trust' as part of academic freedom, a belief that allows teaching staff to determine their own class content and use of digital tools. Academic freedom is deeply ingrained in the Humboldtian university model followed in the German higher education system alongside a very decentralized structure. These contextual particularities hold the possibility of fostering innovation but also come with the danger of teaching staff being left alone as leaders are often taking themselves completely out of teaching matters. Especially one of the three German institutions described here very strongly positioned itself as a campus university providing in person teaching leading to lacking support and even the hindrance of digital development through mistrust. In the Estonian institution, 'trust' was also fundamental, building a key aspect alongside ‘autonomy’ to the organizational culture. The organizational stance was also connected to broader societal values and its own unique historical context related to high level of trust and a nationally shared value system. This open and non-hierarchical structure was also related to Estonia being a small country, another characteristic adding to a supportive environment for digital innovation. In sum, these contextual features center around topics of institutional identity and societal discourse shaping the way the allocation of trust and the responsibilities around technological innovation play out.

Academic Freedom

For the three German public institutions, academic freedom appeared to cast a long shadow over all issues related to teaching. For example, a university leader at a larger German research university remarked, “in principle, every teacher can offer digital teaching, which is quite normal in the freedom of teaching.” This emphasis on freedom, the university leader went on to explain, also meant that teachers had to find their own support in this area.

A study program coordinator at the same institution remarked that self-reliance and appreciation of academic freedom was an integral part of the disciplinary culture. However, this lone-wolf mentality created an environment in which innovation was not always a welcomed guest:

So, in general, [our] mentality is not: "How can we solve this together? But this classic [stance]: "We've never done it like this before.” or “We've always done it this way." (Teacher at a German university)

In this case study, we found that university leaders practiced solely operational leadership with the expectation that innovation would emerge naturally based on interest from individual teachers.

Academic freedom was also sometimes embedded in the institutional structure. For example, the president of a small German university of applied sciences, clarified how academic freedom was coupled with their decentralized university structure. According to the interviewee, this structure cultivates individual motivation and agency to engage with digital tools:

We have a very decentralized organizational structure. We have assigned a lot of competencies to the departments and the departments in turn have passed on a lot of competencies to the individual study areas and the individual teachers. The goal is to increase motivation and identification and that each person can say, ”I did that myself”, and not, “I had to apply something that others somewhere gave me.” (President of a German university)

However, with this decentralized structure and the task of teaching falling into the individual study areas, a dean stated: That means that I, as dean, ultimately have nothing to do with this [teaching], removing himself from the teaching process.

This conscious separation of operational leaders from the teaching process allowed for the emergence of entrepreneurial leaders, however also had some negative side effects. As illuminated in the quote below, this stance led to confused perspectives on digital teaching, which hindered innovation:

… what I also notice over and over again is, there are very different understandings [of digital teaching]. And there are also perspectives that are not evidence-based: What actually constitutes good digital teaching? When is digital teaching really good? And there, too, is a real lack of exchange between colleagues... (Teacher at a German university)

A direct result of this lacking discourse, the interviewee went on to explain, led to “no wide interest in developing an innovative university culture” as knowledge about digital teaching and best practices were kept within the domains of individual teachers. Thus, although there were high levels of trust within the organizational culture, failure of the operational leaders to embrace enabling leadership was detrimental to technological innovation. This is not to say that the German system generally lacks innovative capacity, but here the potential for innovating with EdTech is shown to be inhibited by inherent complex structures that value operational leadership over enabling leadership and thus fail to integrate the important voices and discourses of university teachers. The inherent barrier of controlling the actions of others through operational leadership type mechanisms leads to minimized trust towards university staff.

The embeddedness of academic freedom was also present at the last German institution, a large research university and again, we found that teachers were often left to their own devices when it came to EdTech. This freedom resulted in the natural emergence of entrepreneurial leaders often younger faculty members with intrinsic motivation to use EdTech:

I think the younger researchers like me and also the doctoral students, i.e. all those who are not professors and are sitting in professorships, were much more creative [ with educational technology] and I think they were the ones who really pushed it forward. (Research assistant with teaching duties at a German university)

Similarly, to the small applied university in Germany described above, university leaders at this institution were absent from teaching issues. One teacher explained “I would say that formal managers don’t really appear at all … there is actually no influence”.

However, the university leaders' laissez-faire approach had its limits. During the COVID-19 pandemic, when staff were forced to teach online due to government lockdowns, the university leadership expressed distrust and associated online teaching with laziness. This attitude was exemplified by a vice president's statement that teachers should not rely on digital teaching for convenience:

Digital teaching because it makes didactic sense and improves teaching, yes, we gladly welcome it. Digital teaching for the sake of convenience, because it's so nice [for teachers] to lay on their sofas 500 kilometers away, no. (Vice president at a German university)

This reaction may stem from the institution's identity as a campus university, with a strong preference for in-person teaching as another university leader explained “We see ourselves as a presence university and we will remain that way.” Consequently, EdTech was seen as a temporary solution tied to the pandemic, rather than a long-term strategy. As a result, administrative processes were not adapted to support and sustain digitization efforts. This created a division between the innovative culture and entrepreneurial leadership at the program level and the hierarchical culture of the central administration, which focused solely on operational leadership.

Freedom as a Societal Value

At the Estonian university, despite having some regulations, teachers were given significant academic freedom to decide their own approaches with EdTech. A teacher explained this administrative approach which centers on trust is “typical Estonian” a behavior he contrasted with other European universities, saying:

I also have German colleagues. And the stories that they told me, quite frightening [regarding university bureaucracy]. Come on, I mean, you can't do anything, basically [in German universities]. So, we are more free. But at the same time, there are also downsides. Because there are [university] rules, I mean, you just hit the wall [with certain rules]. And that's it. And you can't change [these regulations]. (Teacher at an Estonian university)

Another interviewee expanded on this theme, explaining that ‘trust’ is embedded within Estonian society and key in the shared value system.

… when people are asked to sort of explain why and how e-Estonia works, it’s because of the high level of trust. High level of trust in institutions, high level of trust in government. (Teacher at an Estonian university)

This high level of trust, the interviewee explained was accompanied by an “advocacy from above” which translated into funding opportunities for new professorships and a push from the university management to deliver digitally savvy graduates.

Moreover, interviewees highlighted their institute, a subunit within the university, as the main driver and supporter of technological advancements. Specific offices within the institute offered pedagogical and technical support for teachers involved in online teaching and teachers expressed a sense of being well-supported by their institute, which was described as a "non-hierarchical" environment. This atmosphere was attributed to the small size of Estonia as a country:

I would say that our institute is all but hierarchical … compared to other experiences I had in Italy, Norway, Turkey, and in the UK, I would say that [the institute] is probably the least hierarchical environment I know. I would say that this [is related to] Estonia. Estonia is a very small country. … so, it's a very flat and non-hierarchical country in general. (Academic staff member at an Estonian university)

The institute's support for technological innovation was further enhanced by the central administration, which allocated additional funds for hardware and software and established incentive programs with monetary rewards to encourage teacher involvement with EdTech. These incentives made teachers feel valued and recognized for their efforts.

The central administration in this case study appeared to work in tandem by practicing both operational leadership by taking care of the technical and didactic aspects necessary for EdTech as well as enabling leadership, providing staff members with the space, recognition and streamlined administrative procedures, with minimal barriers, to realize the benefits of technological innovations. In turn, this approach allowed teachers to become co-owners of EdTech and entrepreneurial leaders in their own right.

Discussion & Conclusions

In this study, we explored how university leaders foster innovation by trusting their staff's ability to use EdTech. Through the lens of CLT and organizational trust, we gained insight into how leadership styles influence innovation. For instance, at an Austrian university of applied sciences, enabling leadership cultivated an innovative culture where staff, regardless of rank, could contribute ideas. This approach was complemented by operational leadership from university administration, harmonizing with program leaders. In contrast, at a private UK university, leaders empowered teachers to innovate with EdTech, though this sometimes blurred lines of responsibility. Conversely, at three German public universities, academic freedom did not universally translate to EdTech innovation. Leadership styles varied: some institutions embraced bottom-up innovation led by early-career staff, while others exhibited hands-off approaches that hindered EdTech adoption. In one case, leadership skepticism towards EdTech undermined staff morale and implementation.

Our findings align with literature highlighting leaders' pivotal role in technology uptake and innovation (Dawson et al., 2018; Dumulescu & Muţiu, 2021; Singha & Singha, 2024; Tsai et al., 2019). Furthermore, we identified how leaders face complex challenges when steering innovation in their institutions, a finding which echoes previous work characterizing universities as complex systems (Bradshaw & Fredette, 2009; Sapir & Oliver, 2017; Tsai et al., 2019). We found when university leaders understood the complexity of their roles and were able to interchangeably practice different leadership types, this resulted in an innovative organizational culture that empowered staff members to embrace EdTech. Conversely, inadequate leadership stifled innovation and left staff feeling unsupported. Thus, leaders need to be able to adapt to their contexts, essentially be able to wear different leadership ‘hats’, a finding that resonates with recommendations made by Tsai et al. (2019) and Dawson et al. (2018).

We further unpack the relationship between university leaders, trust and innovation, a premise that has only been explored to a limited extent in higher education institutions (Johan, 2021; Uy et al., 2024; Yusuf, 2020). We identified diverse ways leaders demonstrate trust, including joint decision-making and incentivizing experimentation with EdTech. Trust, deeply embedded in organizational culture and societal values like academic freedom, was generally positive but required guidance, infrastructure, and funding for sustainability. Our findings suggest simply adopting the ‘right’ kind of leadership (operational, enabling, entrepreneurial)—is insufficient to foster innovation at universities. Building and nurturing trustful relationships with staff members is crucial for them to feel valued, heard, and supported in their creative processes with EdTech.

While our study offers insights into leadership's role in fostering EdTech innovation through trust, it has limitations. Our comparative approach may not fully capture the depth and specificity of each context. The broad scope of eight cases, each representing a unique program at different institutions with its own contextual factors, limited the extent to which we could explore the rich data from each site in detail. Although we believe the inclusion of all eight case studies strongly contributes to our results, future research might benefit from focusing on fewer cases in greater depth to fully understand the unique dynamics at play.

Further studies can advance CLT in higher education by building on our findings. Longitudinal analyses could investigate how leadership types and their impact on trust and innovation evolve over time, providing a deeper understanding of how sustained enabling leadership cultivates a culture of trust and continuous innovation. Examining micro-level interactions between leaders and staff could uncover mechanisms of trust-building in complex educational environments. Additionally, further exploring trust manifestations by leaders in different higher education systems through ethnography or further case studies would provide valuable insights. It would also be beneficial for future studies to examine specific innovation metrics and how university leaders influence EdTech use. Broadening the scope, investigating the relationship between trust and resistance towards EdTech could also provide further understanding. And because of the uncertain environment due to multiple crises affecting the university as an organization, the capacity to adapt to circumstances and disruptions become a mechanism in order to secure the resilience of universities (Young et al., 2023). Considering this aspect, CLT can be paired with resilience theory focussing on the capacity to flexibly combine the selection of leadership types within the scope of action required due to crisis impulses (Schophuizen et al., 2023). Continued research in this area will enhance our knowledge of how universities and their staff can effectively navigate the increasingly digitized world.

For practical applications, our study provides insights into leveraging CLT, especially enabling leadership, to foster trust in HEIs. Firstly, leadership development programs should train leaders in CLT principles, emphasizing open communication, collaborative problem-solving, and supporting innovation through workshops, mentoring, and coaching. These initiatives focus on active listening, transparent communication, conflict resolution, and empowering individuals in simulated scenarios. Mentorship programs pairing experienced with new leaders guide balancing operational and entrepreneurial styles. Secondly, institutional policies should promote enabling leadership by fostering cross-departmental collaboration, recognizing innovative teaching practices, and funding professional development in digital teaching. This includes establishing grants for faculty developing EdTech solutions, encouraging interdisciplinary projects with dedicated resources, and creating platforms to share practices, fostering an innovative culture. Thirdly, robust feedback mechanisms are crucial. Implementing regular surveys, focus groups, and anonymous suggestion boxes allows staff to share experiences and ideas openly. Open forums where leadership discusses feedback enhance transparency and trust-building. Lastly, support structures should integrate EdTech and innovative teaching methods. This involves providing technical and pedagogical support, such as an EdTech center offering consultations and workshops. Online forums, meet-ups, and communities of practice facilitate faculty collaboration and continuous improvement.

As a closing remark, we would like to highlight that while our findings are rooted in European contexts, they offer adaptable insights globally. CLT resonates universally, yet its implementation varies due to cultural, organizational, and contextual factors. For instance, leaders in the USA, like their European counterparts, can cultivate trust through open communication, collaborative problem-solving, and supporting innovation. However, the American higher education system's nuanced NPM structure contrasts with Europe's (except for the UK), influencing operational, entrepreneurial, and enabling leadership. This structure supports top-down initiatives with robust financial backing and entrepreneurial collaborations, whereas European institutions, navigating more bureaucratic challenges and financial constraints, may face barriers to bottom-up innovations. Hence, while our framework illuminates leadership dynamics and promotes organizational trust and innovation, its adaptation across diverse settings demands consideration of local cultural norms, organizational contexts, and educational landscapes to ensure effectiveness.