Perceptions of Organizational Change Readiness for Sustainable Digital Transformation: Insights from Learning Management System Projects in Higher Education Institutions

Abstract

The adoption of Learning Management Systems (LMS) in Higher Education Institutions (HEI) offers a transformative potential to enhance educational quality, operational efficiency, and cost-effectiveness while promoting sustainable digital transformation. However, resistance to LMS implementation often undermines these benefits. Initial perceptions of an Organizational Change Readiness (OCR) play a crucial, as they shape attitudes and behaviors, often resulting in rumors, disengagement, and resistance. The objective of the study is to explore how attributes of change, leadership support, internal organizational context, and attributes of change targets impact OCR in the context of LMS implementation. Drawing from organizational change management and information systems literature, this study examines key factors influencing these early perceptions within LMS initiatives. A cross-sectional survey was conducted with 316 university personnel across seven public universities and three private colleges. Data were analyzed using partial least squares, revealing that vision clarity, change appropriateness, top-management support, project champion effectiveness, and organizational flexibility explaining 75% of the variance in perceived OCR. Conversely, factors such as change efficacy, organizational history of change, organizational conflicts, and group self-efficacy demonstrated limited influence. These findings underscore the importance of aligning LMS initiatives with institutional goals, fostering sustainable digital practices, and enhancing policy frameworks to facilitate smooth adoption. This study provides actionable insights for promoting sustainable educational transformation in HEIs, particularly in contexts where traditional teaching methods prevail and resistance to technological change is common.

1. Introduction

Higher Education Institutions (HEIs) are increasingly adopting Learning Management Systems (LMS) as part of their modernization efforts [1,2], to enhance digital learning, improve teaching efficiency, and enhance learning outcomes [3,4]. Despite these potential benefits, many institutions continue to face challenges related to technology acceptance and LMS usage [3,4,5], including resistance from university staff, limited resources, and low engagement with LMS features [5]. These barriers hinder the transformative potential of LMS and highlight the need for a deeper understanding of the factors influencing its adoption.

Researchers have applied various theoretical models to explain LMS adoption and usage, including the Technology Acceptance Model (TAM) [6,7], the Unified Theory of Acceptance and Use of Technology (UTAUT) [1], and the Theory of Planned Behavior (TPB) [8]. Each of these models highlights unique behavioral and organizational factors influencing technology acceptance. For example, TAM emphasizes perceived ease of use and usefulness [6,7], while UTAUT incorporates performance expectations and facilitating conditions [1]. TPB explores intention-based actions influenced by attitudes, subjective norms, and perceived behavioral control [8]. Explicating these theoretical foundations strengthens the conceptual underpinnings of LMS adoption in HEIs. Recent studies suggest that these models need to undergo certain changes to fully capture the organizational and behavioral factors that influence the adoption of LMS, specifically in environments marked by resistance to change [9,10]. Factors like change beliefs, resistance to change, and contextual influences [11,12] have become central to understanding how LMS adoption is perceived in such environments.

One major challenge identified in the literature is the resistance from university staff to adopting LMS. Lecturers and administrative personnel, who are expected to benefit most from these systems, often exhibit reluctance or employ neutralization techniques to justify their resistance [13]. Several case studies have identified contributing factors such as workload anxiety, perceived complexity, and misalignment with traditional workflow practices [1,13]. Ohemeng et al. [14] highlight that changing perceptions in developing countries often requires targeted sense-giving processes such as workshops, one-on-one communication, and meetings to address resistance and build alignment with organizational goals. In regions where traditional workflow dominate and digital literacy varies significantly, such as in many developing contexts, these challenges are further exacerbated. In Kosovo’s HEIs, resistance often stems from limited digital infrastructure, cultural preferences for traditional teaching methods, and insufficiently tailored LMS training programs [15]. Addressing these barriers is essential to ensure that LMS initiatives align with the United Nations’ 2030 Agenda for Sustainable Development, particularly its focus on education quality and inclusivity [12].

While much research has explored technology acceptance and individual user behaviors [6,13,16], few studies have focused on OCR as a critical determinant of LMS implementation success. Research by Holt et al. [17] and Ilyas [11] highlights the framework for understanding how organizational context, leadership, and staff perceptions shape the organizational readiness for technological change. Moreover, OCR is recognized as pivotal in fostering sustainable digital transformation, particularly within educational ecosystems that face entrenched resistance [18]. However, empirical research specifically investigating OCR in the context of LMS adoption remains scarce, especially in regions with unique challenges such as limited infrastructure, resource constrains, and traditional workflow dominance.

Furthermore, while studies emphasize the importance of resources and training, many overlook the pre-implementation phase, where early perceptions of OCR can critically shape the trajectory of LMS adoption [2,4]. Although technology acceptance models are widely applied, there is a lack of research on OCR in the specific context of LMS implementation within HEIs in Kosovo. Much of the existing literature emphasizes individual factors such as perceived usefulness and ease of use [6] while paying less attention to broader organizational dimensions, including leadership support, change history, and adaptability, known as key drivers of OCR [3]. Additionally, exploring how sustainable digital transformation aligns with institutional objectives offers a unique perspective for ensuring effective adoption strategies. To address this gap, this study aims to investigate the factors influencing OCR for LMS adoption within the context of HEIs in Kosovo. By utilizing organizational change management theories and focusing on sustainable digital transformation, this research seeks to provide actionable insights for effective LMS implementation in culturally unique educational contexts.

The manuscript is structured as follows: Section 2 develops the study’s hypotheses based on a review of relevant literature. Section 3 outlines the research methodology, including the survey design and data collection process. Section 4 presents the results, and Section 5 discusses the findings in the context of prior research. The manuscript concludes in Section 6 with practical recommendations, limitations, and directions for future research.

2. Hypotheses Development

This research studies the factors influencing personnel perceptions of OCR in LMS projects within HEIs. Drawing on organizational change management theories and the information systems literature, this study examines factors that influence early perceptions of OCR for implementing LMS projects [19,20]. Building on Holt et al. [17] and Paré et al. [19], the study categorizes variables into four main groups: attributes of the change, leadership support, internal organizational context, and attributes of change targets to assess OCR. These categories serve as a framework for assessing how well-prepared an institution is for LMS implementation. Furthermore, the inclusion of sustainability principles within the organizational context emphasizes the alignment of digital transformation efforts with long-term institutional goals [14,20]. The research model, illustrated in Figure 1, outlines each variable and its hypothesized links with OCR.

2.1. Attributes of the Change

Attributes of the change refer to the specific characteristics of a proposed organizational change, such as its purpose, scope, anticipated benefits, complexity, and alignment with organizational values [21]. These attributes influence how individuals perceive the change and affect their willingness to support and adopt it. Holt et al. [17] define the attributes of the change as the ‘what’ element of a change initiative. In LMS projects, these attributes extend beyond new technology implementation and involve significant shifts in pedagogical approaches, workflow adjustments, personnel responsibilities, and the overall organizational structure [22]. This shift requires university personnel to integrate LMS platforms into teaching practices, which often disrupts traditional practices in HEIs in Kosovo [15]. This study identifies several attributes that are likely to influence perceptions of organizational readiness for LMS based change, but also contribute to sustainable digital transformation by facilitating more resilient and adaptable educational practices [7].

2.1.1. Vision Clarity

Clear communication of the intended change is essential to building urgency and legitimacy [19,23,24,25]. A clearly communicated vision for LMS initiatives allows staff to better understand that the new system aligns with institutional goals and can ultimately improve teaching efficiency, enhance learning outcomes, and expand access to educational resources [26]. Findings from Altunoglu [20] underscore that clear communication of LMS benefits significantly shapes user engagement and initial perceptions of its appropriateness. Effective sense-giving processes, such as workshops and targeted communication, have been identified as critical for aligning individual and organizational goals during technology adoption [14]. In HEIs, particularly in those where traditional teaching methods are predominant, articulating this vision effectively is critical to overcoming resistance and skepticism toward new technology [27]. Without a clear vision, employees may perceive the change as disconnected from their objectives [9]. Conversely, a well-defined vision that communicates LMS advantages—like improved educational quality and operational efficiency—encourages personnel to support the initiative [28]. Ensuring that the rationale for change is effectively communicated is thus essential for establishing OCR in HEIs.

2.1.2. Change Appropriateness

Change appropriateness refers to the degree to which personnel see the change as an appropriate response to current challenges [19,29,30]. For LMS projects, it is essential that staff perceive the system as a solution to challenges faced by HEIs, including resource limitations, outdated pedagogical methods, and limited access to digital tools [22,31]. Research indicates that resistance from HEI personnel often arises from concerns over LMS compatibility with teaching practices or apprehensions regarding system complexity [1,32]. Staff are more likely to accept LMS if they see it as complementing, rather than disrupting, their established practices [1]. Altunoglu [20] further emphasizes that satisfaction with LMS depends significantly on the system’s ability to align with user-specific needs, including content quality, customization, and engagement.

2.1.3. Change Efficacy

Change efficacy, or the confidence in successful implementation, is also vital to OCR [33]. Personnel in HEIs need assurance that LMS adoption will succeed and yield meaningful educational improvements [31]. Perceived self-efficacy, or the belief in one’s capability to use the LMS effectively, is crucial for change efficacy [1,9]. Studies highlight that technical support, training, and positive examples from past implementations significantly shape perceptions of change efficacy [22,31]. Staff who receive adequate training and develop digital skills are more likely to feel confident in adopting LMS [3]. Conversely, past failures or insufficient support may hinder change efficacy and increase resistance [2].

Although there is extensive research on change attributes and their influencing factors, little evidence addresses how these elements specifically affect academic staff in Kosovo’s HEIs, where digital literacy levels vary, and traditional teaching methods remain prevalent [15]. The literature often addresses different contexts, leaving gaps in understanding the unique challenges Kosovo’s HEIs face during LMS implementation. Additionally, the impact of negative past experiences and inadequate support on change efficacy remains underexplored in this region. This highlights the need for research addressing the specific needs of academic staff in Kosovo. Based on this discussion, the following hypotheses are proposed:

Hypothesis 1.

Vision clarity positively relates to perceived OCR.

Hypothesis 2.

Change appropriateness positively relates to perceived OCR.

Hypothesis 3.

Change efficacy positively relates to perceived OCR.

2.2. Leadership Support

Researchers acknowledge leadership support as a critical factor in driving organizational change initiatives [29]. In LMS implementations within HEIs, leadership support entails the level of engagement from university leaders to ensure successful technology adoption [34]. Leaders contribute by allocating the necessary resources, promoting staff participation, and demonstrating a commitment to enhancing the educational experience through technology [35]. As noted by Ohemeng et al. [14], effective leadership in developing regions often employs sense-giving strategies such as targeted training and direct communication to align staff perceptions with organizational objectives. Effective leadership helps create an environment where staff members feel supported and inspired to engage with new technologies like LMS [29,36]. This role becomes particularly critical in HEIs where resistance to adopting technology is often common [1].

2.2.1. Top-Management Support

Senior leaders in HEIs play a pivotal role in influencing faculty attitudes toward LMS adoption. Proactive leadership can mitigate resistance by addressing apprehensions and providing a clear roadmap for sustainable digital transformation [14]. Their active involvement in promoting the initiative, addressing concerns, and providing essential resources helps shape the organizational climate, fostering acceptance [37,38]. Samara et al. [36] emphasize that strong leadership can mitigate uncertainties and reduce staff concerns, especially during transitions to new technologies like LMS. Leaders who offer resources such as training, infrastructure, and technical support significantly improve perceptions of OCR [39]. Studies on educational technology adoption highlight the importance of leadership in overcoming implementation barriers. For example, Lavidas et al. [1] stress that university leaders must show consistent support throughout the LMS project, encouraging faculty engagement during implementation. Similarly, Asamoah [32] emphasizes that ICT policies, driven by leadership, should ensure that faculty members are adequately trained and equipped to use the LMS effectively. Without active leadership involvement, LMS initiatives may face resistance and disengagement from academic staff. Moreover, Kohnke and Moorhouse [27] found that leadership’s dedication to communicate clearly and outline the benefits and goals of the LMS, positively shapes faculty perceptions of the change. This transparency builds trust, reduces uncertainty, and enhances perceived OCR [31]. Effective leadership does more than support the system; it motivates staff to embrace the transition, while also ensuring that the change aligns with broader institutional goals [40].

2.2.2. Presence of a Change Champion

Beyond top-management support, the presence of a change champion, someone who actively advocates for the change and its benefits, is crucial in influencing OCR [40]. Change champions serve as change agents within the institution, connecting management and staff by addressing concerns and communicating the system’s advantages [19,41]. Castro and Tumibay [9] suggest that change champions foster engagement by reducing resistance and building a positive attitude toward the LMS. These champions act as role models, demonstrating effective system use and helping colleagues overcome technical challenges [42]. This role is especially important in HEIs where faculty members may hesitate to adopt new technologies due to unfamiliarity or low digital confidence [3]. By offering personalized support, change champions help create a sense of collective efficacy among staff, which enhances their willingness to adopt the LMS [2].

Sakala and Chigona [13] further emphasize that change champions are instrumental in countering faculty resistance techniques, such as claims of insufficient training or incompatibility with teaching methods. Engaging staff and addressing their concerns reduces barriers to LMS adoption, leading to more positive attitudes toward the system.

Despite the established importance of leadership support in technology adoption, research has not fully explored how leadership involvement specifically impacts LMS implementation in HEIs within regions like Kosovo. Current studies highlight leadership’s role in providing resources and support, but there is limited investigation into how strategies like effective communication, transparency, and the appointment of change champions mitigate resistance and improve OCR among faculty. Additionally, the role of change champions in addressing faculty concerns and fostering engagement remains underexplored, particularly in settings where digital literacy varies and resistance to technological change is common. Connecting these dots is essential for understanding how leadership and change champions can drive LMS adoption in HEIs in Kosovo. To address these gaps, the following hypotheses are proposed:

Hypothesis 4.

Top-management support positively relates to perceived OCR.

Hypothesis 5.

The presence of a change champion positively relates to perceived OCR.

2.3. Internal Context

The organizational context in which change takes place significantly influences perceptions of OCR. Various internal factors, such as an institution’s history with previous change initiatives, levels of organizational conflict, and flexibility in adapting policies and practices, are crucial in shaping how employees view the feasibility of adopting new technologies like LMS [36,43]. Institutions that integrate sustainability principles into their policies tend to have more adaptable and resilient change environments, which can further bolster OCR [14,20].

2.3.1. Organizational History of Change

Previous change initiatives within an organization play a significant role in shaping staff perceptions of future change [44]. When institutions successfully implement educational technologies, staff tend to develop a more optimistic outlook on the organization’s ability to adopt future innovations [22]. On the other hand, if past experiences have involved insufficient support, failure, or significant challenges, staff may approach new initiatives, like LMS, with skepticism [45]. This aspect is particularly relevant for HEIs, where traditional teaching methods still dominate, and past experiences with digital technology adoption may have been limited or problematic [9].

Rodrigues et al. [28] argue that prior experiences with technological innovations shape faculty perceptions of future projects. For example, if previous LMS implementations were underfunded or poorly managed, academic staff might anticipate similar issues with new efforts. Lavidas et al. [1] highlight how negative past experiences with technology can lead to resistance, with staff viewing new initiatives as unnecessary disruptions. To enhance OCR, it is crucial that institutions address the lessons learned from previous implementations in the planning stages of new LMS projects.

2.3.2. Organizational Conflicts

LMS implementation within HEIs often encounters internal conflicts arising from differing priorities, interests, and objectives among key stakeholders, such as faculty, IT personnel, and administrators [13]. These conflicts may concern the system’s impact on teaching practices, workload distribution, and academic autonomy. Mumbi and Nyirenda [2] argue that when faculty goals and administrative decisions are not aligned, staff tends to feel excluded from the decision-making process, leading to a resistance to change.

Additionally, Asamoah [32] suggests that hierarchical structures and power struggles within HEIs can amplify these conflicts, especially when decisions about technology adoption are perceived as top-down initiatives with minimal contribution from academic staff. Failing to engage faculty members early in the process can result in entrenched resistance and perceptions that the institution is unprepared for the change [36]. To address these conflicts, through inclusive decision-making and communication between stakeholders is crucial for reducing resistance and enhancing OCR [13].

2.3.3. Organizational Flexibility

An OCR is largely determined by its ability to tailor its policies, practices, and structures to support new technologies [19,22,45]. HEIs that are able to adjust their policies to promote the integration of LMS are more likely to achieve successful implementation [31,39]. By promoting policies that encourage experimentation and innovation, HEIs can better align LMS initiatives with sustainability goals [20]. According to Kohnke and Moorhouse [27], an institution’s ability to provide support throughout this change by offering training and adjusting workloads is key for a successful implementation of LMS. Without such support, staff may become overwhelmed and resistant, which can lead to low engagement with the new system [22].

Lavidas et al. [1] highlight the importance of adaptive policies that promote experimentation with LMS, to allow university personnel to explore the platform without fear of penalties. However, institutions with rigid structures face stronger resistance to LMS adoption. As noted by Asamoah [32], inflexible administrative processes can hinder the swift adoption of new technologies, resulting in delays in implementation and reduced adoption rates.

While the literature acknowledges the significance of internal factors—such as the history of change, organizational conflicts, and flexibility—affecting OCR in HEIs, there is limited research on how these factors play out in regions like Kosovo. Issues such as past failures in technology adoption, internal conflicts, and rigid policies affecting LMS adoption in these settings remain underexplored [46]. Furthermore, little attention has been given to how organizational flexibility can encourage university personnel engagement with LMS in developing regions. Based on this discussion, the following hypotheses are proposed:

Hypothesis 6.

History of successful change experiences positively relates to perceived OCR.

Hypothesis 7.

Organizational conflicts negatively relate to perceived OCR.

Hypothesis 8.

Organizational flexibility positively relates to perceived OCR.

2.4. Attributes of the Change Targets

The attributes of the change targets refer to the characteristics of the individuals or groups within the organization who are responsible for adapting to the change [17]. In the context of LMS projects in HEIs, these change targets typically include academic staff, administrative personnel, and IT support teams, whose skills, attitudes, and beliefs significantly affect perceptions of OCR [47]. The individual characteristics of these staff members, such as self-efficacy, resistance to change, and collective efficacy, can either facilitate or hinder the successful implementation of LMS projects [1,13].

Group Self-Efficacy

Group self-efficacy reflects the collective confidence among staff members in their ability to work collaboratively and adopt new systems [19,47]. For academic staff, this extends beyond individual competence with LMS and includes a shared belief that their colleagues and the institution as a whole can successfully integrate LMS into teaching methods [9]. Research by Lavidas et al. [1] underscores that self-efficacy is a strong predictor of technology acceptance, which demonstrates its impact on OCR at both personal and group levels.

Low self-efficacy can negatively impact faculty engagement with LMS platforms, as staff may feel overwhelmed by the technical demands of the system [2]. Kohnke and Moorhouse [27] emphasize the importance of ongoing technical training and support, particularly in settings where digital literacy levels vary and traditional teaching practices are prevalent. Providing training and support is crucial for enhancing staff confidence in LMS usage, reducing overall resistance, and creating a more open-minded attitude towards change in the organization [1].

Resistance to change is a common challenge in educational environments when implementing new technologies, especially within established pedagogical practices [13,31]. Such resistance often stems from fears of increased workloads, concerns over job security, or disruptions to traditional teaching methods and can manifest as active resistance or passive disengagement [22,39]. Personal motivation and internal beliefs can also play a significant role in new system acceptance. Staff who feel their current methods are effective may view LMS as an added burden rather than a convenient tool [9]. Furthermore, digital literacy and technical proficiency can also affect OCR for LMS, as technological complexity can reduce engagement when staff feel hesitant about adopting the system into their routines [1].

Although previous studies have explored how attributes of the change targets shape OCR for LMS adoption, little is known about how these attributes affect Kosovo’s HEIs. Current literature often overlooks how varying levels of digital literacy impact collective efficacy in academic settings. Additionally, little research examines strategies to address resistance stemming from LMS implementation, which could be mitigated by early staff engagement and ongoing training. Based on this discussion, the following hypothesis is proposed:

Hypothesis 9.

Group self-efficacy positively relates to perceived OCR.

3. Methods

3.1. Sample

This study utilized a quantitative, cross-sectional survey design to explore the factors influencing OCR during LMS implementation across HEIs in Kosovo. A cross-sectional design was chosen as it allows the collection of data at a single point in time, providing a snapshot of current perceptions and experiences related to LMS adoption. This approach provided a snapshot of current perceptions and experiences related to LMS adoption.

Prior to the full survey distribution, a pre-test was conducted at the University of Applied Sciences in Ferizaj. This pre-test involved three administrative staff, an IT staff member, five academic staff familiar with LMS, and a project manager experienced in managing information systems. Participants completed the initial questionnaire and provided constructive feedback on clarity, comprehensiveness, and completion time. Overall, the pre-test indicated that the questionnaire was clear and easy to use. However, minor changes were made to adjust the wording and structure of the questionnaire to enhance presentation and usability.

The study included academic and administrative personnel from diverse disciplines and institutional structures across seven public universities and three private colleges in Kosovo. A convenience sampling approach was employed due to logistical constraints, allowing for the efficient collection of data from a diverse group of respondents across multiple institutions. Inclusion criteria required respondents to be actively involved in LMS implementation or use, ensuring that their responses reflected relevant experiences and perspectives. Administrative staff not directly engaged with LMS systems were excluded to maintain focus on targeted stakeholders.

Data for this study were collected through an online questionnaire administered via Google Forms. The data collection process adhered to a structured protocol, ensuring uniformity across all participating institutions. A total of 870 questionnaires were distributed across 10 HEIs in Kosovo. Of these, 316 valid responses were received, resulting in a response rate of 43.96%.

3.2. Measures

The survey instrument used in this study was designed to assess 10 dimensions grouped into four main variables, each aligned with the research model. The study employed a five-point Likert scale ranging from “strongly disagree” to “strongly agree” for all survey items, enabling a consistent and standardized measurement approach for all variables. The survey incorporated items to evaluate both the dependent and independent variables central to the study. To ensure content validity, survey items were developed based on an extensive review of literature and adapted from validated scales used in prior empirical studies. Construct validity was assessed during the pilot study through exploratory feedback from academic and administrative staff, refining items to better reflect the context of Kosovo’s HEIs. The reliability of the instrument was further verified through confirmatory factor analysis (CFA). The dependent variable, OCR, was measured using items adapted from Eby et al. [45] and Rafferty and Simons [48]. For the independent variables, vision clarity was assessed using a scale adapted from Armenakis et al. [29]. Change appropriateness and top-management support were measured using scales adapted from Holt et al. [17]. Change efficacy, organizational history of change, the presence of a change champion, and organizational conflicts were evaluated using scales adapted from Paré et al. [19]. Organizational flexibility was assessed through items adapted from Rush et al. [49] and Eby et al. [45]. Lastly, group self-efficacy was measured using a scale developed by Compeau and Higgins [50]. The detailed items utilized to assess all variables in this study can be found in Appendix A.

Control variables were carefully selected based on their potential influence on OCR, as identified in prior research. These included respondent age, gender, tenure, and level of IT literacy. The rationale for including these variables stems from their known associations with technology adoption and organizational change readiness in higher education contexts.

3.3. Ethical Considerations

Permission to conduct the study was obtained from the management of the HEIs participating in this study. Informed consent was secured from all participants, to ensure that they were fully aware of objectives of the study, their role, and the voluntary nature of their involvement. Data confidentiality and participant anonymity were strictly maintained throughout the research process. This ethical approach ensured compliance with institutional standards for human subject research and data protection.

3.4. Statistical Analysis

To verify the validity and reliability of the measurement instruments confirmatory factor analysis (CFA) was conducted, ensuring that the original scales’ factor structures matched the current sample. All factor loadings exceeded acceptable thresholds, confirming instrument suitability. Cronbach’s alpha values were calculated to assess internal consistency, and all variables demonstrated high reliability with alpha values exceeding 0.7. For hypothesis testing, the study employed Partial Least Squares Structural Equation Modeling (PLS-SEM), a variance-based structural equation modeling technique suitable for exploratory research and complex models with multiple constructs [51]. PLS-SEM was chosen due to its suitability for small to medium-sized samples and its robustness in handling complex models with multiple constructs. To ensure that multicollinearity does not distort the relationships among the independent variables, variance inflation factors (VIF) were calculated for all constructs in the model. The VIF values were below the commonly accepted threshold of 3.3, confirming no significant multicollinearity issues and ensuring the robustness of the model results.

4. Results

Table 1. Profile of respondents.

Characteristics		Frequency	Percentage (%)
Age	29 or less	13	4%
	30 to 39	41	13%
	40 to 49	149	47%
	50 to 59	100	32%
	60 and over	13	4%
Gender	Male	200	63%
	Female	116	37%
Education	High School	0	0%
	Bachelor	17	5%
	Master	70	22%
	PhD	229	72%
Tenure at institution	Less than 2 years	58	18%
	2–5 years	102	32%
	More than 5 years	156	49%
Position	Rector	5	2%
	Vice Rector	15	5%
	General Secretary	3	1%
	Dean	24	8%
	Vice Dean	16	5%
	Department Head	25	8%
	Professor	22	7%
	Associate Professor	48	15%
	Assistant Professor	56	18%
	Lecturer	16	5%
	Teaching Assistant	28	9%
	Researcher	0	0%
	Administrative Staff	58	18%
Level of IT literacy	No experience	0	0%
	Basic	46	15%
	Medium	140	44%
	Advanced	90	28%
	Expert	40	13%

summarizes the demographic characteristics of the 316 respondents in this study. Most participants were aged between 40 and 49 years (47%), followed by those aged 50 to 59 years (32%). Gender distribution showed 63% male and 37% female respondents. In terms of education, the largest proportion of respondents held a PhD (72%), with additional degrees distributed across master’s (22%) and bachelor’s levels (5%). Regarding institutional tenure, nearly half (49%) of respondents had more than five years of experience, while 32% had two to five years, and 18% had less than two years. Respondents’ positions were diverse, with academic roles comprising 54% (Assistant Professors 18%, Associate Professors 15%, Teaching Assistants 9%, Full Professors 7%, and Lecturers 5%), followed by administrative staff at 18%. Management and specialized roles made up 28%. Concerning IT literacy, 44% of respondents reported a medium level, with 28% at an advanced level and 15% at a basic level. 13% identified as experts, and none reported having no-experience indicating that all respondents possessed at least foundational digital skills.

4.1. Measurement Model

Confirmatory factor analyses were conducted to assess the reliability and validity of the measurement model.

Table 2. Confirmatory Factorial Analyses of instrument.

Instruments	χ2/df	CFI	TLI	RMSEA	CR	AVE
Organizational change readiness (OCR)	3.884	0.944	0.927	0.079	0.80	0.75
Attributes of the change (VC/CA/CE)	3.896	0.970	0.903	0.081	0.81/0.80/0.84	0.66/0.81/0.63
Leadership support (TLS/PEC)	3.924	0.923	0.941	0.078	0.79/0.82	0.74/0.83
Internal context (OHC/OC/OF)	3.856	0.952	0.902	0.083	0.89/0.92/0.96	0.69/0.71/0.82
Attributes of the change targets (CSE)	3.867	0.968	0.916	0.079	0.81	0.78

shows the results for all constructs involved in this study. For each construct, we evaluated the chi-square to degrees of freedom ratio (χ²/df), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), Composite Reliability (CR), and Average Variance Extracted (AVE).

For OCR, the fit indices suggested a good fit, with a χ²/df of 3.884, CFI of 0.944, TLI of 0.927, and RMSEA of 0.079. The CR and AVE values for this construct were 0.80 and 0.75, respectively. The construct for “Attributes of the Change” (which includes vision clarity, change appropriateness, and change efficacy) also demonstrated an acceptable fit, with a χ²/df of 3.896, CFI of 0.970, TLI of 0.903, and RMSEA of 0.081. The CR values for these dimensions ranged from 0.80 to 0.84, and the AVE values from 0.63 to 0.81. For leadership support (top-management support and the presence of an effective champion), fit indices were also satisfactory (χ²/df = 3.924, CFI = 0.923, TLI = 0.941, RMSEA = 0.078), with CR values of 0.79 and 0.82 and AVE values of 0.74 and 0.83, respectively. Constructs related to the internal context, which included organizational history of change, organizational conflicts, and organizational flexibility, showed solid factor structures with a χ²/df of 3.856, CFI of 0.952, TLI of 0.902, and RMSEA of 0.083. Their CR values ranged from 0.89 to 0.96, with AVE values between 0.69 and 0.82. Lastly, attributes of the change targets (group self-efficacy) demonstrated good reliability and validity, with a χ²/df of 3.867, CFI of 0.968, TLI of 0.916, RMSEA of 0.079, CR of 0.81, and AVE of 0.78.

We further evaluated the discriminant validity of the constructs by examining the variance shared between constructs. As displayed in

Table 3. Variance shared between research model constructs.

	OR	VC	CA	CE	TMS	PEC	OHC	OC	OF	GSE
Organizational change readiness (OCR)	0.84
Vision clarity (VC)	0.76 **	0.79
Change appropriateness (CA)	0.63 *	0.47 **	0.77
Change efficacy (CE)	0.37 *	0.42 **	0.62 *	0.81
Top-management support (TMS)	0.46 **	0.29 *	0.51 *	0.55 **	0.83
Presence of an effective champion (PEC)	0.55 *	0.59 **	0.69 *	0.53 ***	0.68 **	0.85
Organizational history of change (OHC)	0.61 **	0.64 **	0.69 **	0.65 **	0.68 **	0.71 **	0.81
Organizational conflicts (OC)	−0.31 *	−0.28 *	−0.47 **	−0.37 *	−0.51 **	−0.45 **	−0.48 **	0.88
Organizational flexibility (OF)	0.53 **	0.48 *	0.61 **	0.67 **	0.55 *	0.64 **	0.63 **	−0.43 **	0.83
Group self-efficacy (GSE)	0.48 **	0.71 **	0.49 **	0.51 **	0.62 **	0.76 **	0.45 *	−0.39 **	0.66 **	0.78

* Bolded values represent the square root of the Average Variance Extracted for each construct, indicating discriminant validity. Asterisks indicate significance levels: * p < 0.05, ** p < 0.01.

, the square root of the AVE for each construct (shown on the diagonal in bold) is greater than its correlation with other constructs, indicating strong discriminant validity.

To assess multicollinearity among the independent variables, variance inflation factors (VIF) were calculated for each construct in the research model.

Table 4. Multicollinearity Assessment (VIF Values).

Construct	VIF Value
Vision clarity (VC)	1.85
Change appropriateness (CA)	2.10
Change efficacy (CE)	1.45
Top-management support (TMS)	2.60
Presence of an effective champion (PEC)	2.95
Organizational history of change (OHC)	1.75
Organizational conflicts (OC)	1.90
Organizational flexibility (OF)	2.50
Group self-efficacy (GSE)	1.80

presents the VIF values, all of which fall below the commonly accepted threshold of 3.3, confirming that multicollinearity is not a concern in this study. The VIF values indicate that the predictors are independent and do not suffer from multicollinearity, ensuring that the model’s estimated path coefficients are robust and reliable.

4.2. Hypothesis Testing

The structural model was tested using partial least squares (PLS) path modeling. The path coefficients and the variance explained in the dependent variable (OCR) are presented in

Table 5. PLS results.

Path	Path Coefficients
Vision clarity (VC)	0.26 **
Change appropriateness (CA)	0.23 **
Change efficacy (CE)	0.06
Top-management support (TMS)	0.37 **
Presence of an effective champion (PEC)	0.45 **
Organizational history of change (OHC)	0.05
Organizational conflicts (OC)	0.07
Organizational flexibility (OF)	0.31 **
Group self-efficacy (GSE)	0.03
% of the variance explained in the dependent variable	0.75

Path coefficients marked with asterisks indicate statistical significance at different levels: ** p < 0.01.

. The model explains 75% of the variance in OCR. Vision clarity (β = 0.26, p < 0.01), change appropriateness (β = 0.23, p < 0.01), top-management support (β = 0.37, p < 0.01), presence of an effective champion (β = 0.45, p < 0.01), and organizational flexibility (β = 0.31, p < 0.01) were all positively associated with OCR. However, change efficacy (β = 0.06), organizational history of change (β = 0.05), organizational conflicts (β = 0.07), and group self-efficacy (β = 0.03) were not found to significantly influence OCR.

The PLS construct cross-loadings were also examined to ensure that each item loads more highly on its associated construct than on others. This confirms discriminant validity at the item level.

Table 6. PLS Construct cross-loadings of the research model.

Item	OR	VC	CA	CE	TMS	PEC	OHC	OC	OF	GSE
VC1	0.784	0.356	0.312	0.298	0.321	0.298	0.267	0.312	0.286	0.364
VC2	0.805	0.341	0.342	0.284	0.312	0.322	0.292	0.315	0.264	0.355
VC3	0.771	0.331	0.323	0.301	0.314	0.298	0.275	0.302	0.263	0.378
VC4	0.789	0.354	0.311	0.292	0.311	0.297	0.264	0.315	0.286	0.369
CA1	0.315	0.812	0.344	0.334	0.323	0.289	0.274	0.335	0.263	0.367
CA2	0.329	0.796	0.326	0.342	0.334	0.312	0.289	0.311	0.277	0.372
CA3	0.341	0.824	0.354	0.336	0.322	0.318	0.277	0.321	0.281	0.379
CA4	0.346	0.839	0.341	0.345	0.318	0.299	0.264	0.328	0.275	0.368
CE1	0.298	0.314	0.756	0.323	0.315	0.329	0.298	0.315	0.267	0.349
CE2	0.304	0.316	0.766	0.332	0.328	0.301	0.289	0.302	0.264	0.376
CE3	0.288	0.319	0.792	0.329	0.314	0.315	0.271	0.309	0.278	0.381
CE4	0.315	0.328	0.781	0.344	0.326	0.312	0.286	0.324	0.267	0.369
TMS1	0.297	0.314	0.312	0.807	0.322	0.335	0.312	0.326	0.289	0.368
TMS2	0.311	0.318	0.309	0.825	0.329	0.322	0.305	0.329	0.282	0.371
TMS3	0.289	0.306	0.298	0.794	0.304	0.308	0.298	0.307	0.267	0.366
TMS4	0.298	0.313	0.301	0.812	0.315	0.319	0.294	0.317	0.273	0.359
C1	0.276	0.298	0.282	0.305	0.788	0.324	0.292	0.309	0.271	0.372
C2	0.301	0.307	0.299	0.321	0.805	0.312	0.285	0.324	0.276	0.374
C3	0.288	0.294	0.287	0.311	0.774	0.298	0.276	0.312	0.263	0.367
OHC1	0.272	0.286	0.278	0.299	0.312	0.791	0.303	0.329	0.283	0.371
OHC2	0.288	0.294	0.284	0.312	0.319	0.774	0.298	0.317	0.276	0.363
OHC3	0.274	0.292	0.287	0.306	0.305	0.804	0.314	0.324	0.279	0.369
OHC4	0.281	0.303	0.292	0.316	0.312	0.817	0.309	0.332	0.282	0.375
OCP1	0.274	0.287	0.279	0.309	0.308	0.301	0.768	0.334	0.288	0.373
OCP2	0.269	0.291	0.283	0.304	0.312	0.298	0.781	0.327	0.286	0.364
OCP3	0.278	0.293	0.284	0.308	0.319	0.312	0.793	0.319	0.279	0.362
OF1	0.299	0.317	0.309	0.328	0.322	0.329	0.321	0.806	0.284	0.379
OF2	0.303	0.321	0.314	0.333	0.326	0.324	0.327	0.818	0.281	0.372
OF3	0.291	0.312	0.303	0.319	0.318	0.311	0.309	0.792	0.273	0.368
OF4	0.298	0.318	0.312	0.329	0.324	0.319	0.313	0.816	0.279	0.375
GSE1	0.263	0.281	0.268	0.294	0.299	0.302	0.278	0.286	0.761	0.373
GSE2	0.272	0.288	0.278	0.304	0.309	0.314	0.286	0.296	0.772	0.368
GSE3	0.267	0.279	0.271	0.297	0.304	0.308	0.281	0.289	0.756	0.362
GSE4	0.263	0.275	0.267	0.292	0.298	0.301	0.276	0.284	0.754	0.359
OR1	0.348	0.362	0.357	0.366	0.369	0.372	0.367	0.379	0.373	0.856
OR2	0.341	0.356	0.354	0.362	0.364	0.367	0.359	0.372	0.366	0.842
OR3	0.332	0.349	0.346	0.354	0.357	0.362	0.352	0.364	0.356	0.839
OR4	0.338	0.351	0.348	0.359	0.361	0.368	0.358	0.367	0.361	0.847

Bold values indicate the highest factor loadings for each construct, confirming convergent validity.

presents the cross-loadings for each construct which indicate that all items load more strongly on their respective constructs, thus supporting the distinctiveness of the constructs.

The hypotheses testing results, based on the PLS construct cross-loadings, confirm discriminant validity across all constructs. Each item loaded more strongly on its respective construct than on others which indicates the distinctiveness of the constructs. For Vision Clarity (VC), all items (VC1–VC4) had loadings between 0.771 and 0.805, confirming that the LMS vision was understood well by respondents. The results support Hypothesis 1, which states that vision clarity positively relates to perceived OCR. Similarly, Change Appropriateness (CA) items (CA1–CA4) loaded strongly, ranging from 0.812 to 0.839, reflecting positive perception toward the appropriateness of LMS adoption. This result supports Hypothesis 2: change appropriateness is positively related to OCR. Items for Change Efficacy (CE) (CE1–CE4) showed adequate loadings, ranging from 0.756 to 0.792, but the path coefficient (β = 0.06) indicates that Hypothesis 3 is not supported: change efficacy did not significantly influence OCR. Top-Management Support (TMS) items (TMS1–TMS4) had loadings between 0.794 and 0.825, and a significant path coefficient (β = 0.37, p < 0.01). These findings support Hypothesis 4, indicating that top-management support positively relates to OCR. For Presence of a Change champion (C), the item loadings ranged from 0.774 to 0.805, with a path coefficient of β = 0.45 (p < 0.01). This strongly supports Hypothesis 5, suggesting that the presence of a change champion positively influences OCR. Organizational History of Change (OHC) items (OHC1–OHC4) loaded between 0.774 and 0.817. However, the path coefficient (β = 0.05) indicates that Hypothesis 6 is not supported, as organizational history did not significantly impact OCR for LMS implementation. Organizational Conflicts (OC) items (OCP1–OCP3) showed strong loadings (0.768 to 0.793), but the path coefficient (β = 0.07) reveals that Hypothesis 7 is not supported, indicating that internal conflicts did not significantly affect OCR. Organizational Flexibility (OF) items (OF1–OF4) displayed loadings between 0.792 and 0.818, and the path coefficient (β = 0.31, p < 0.01) supports Hypothesis 8, affirming that flexibility positively influences OCR. Finally, Group Self-Efficacy (GSE) (GSE1–GSE4) loadings ranged from 0.754 to 0.772, but the path coefficient (β = 0.03) indicates that Hypothesis 9 is not supported: group self-efficacy did not significantly affect OCR.

5. Discussion

The main aim of this study was to explore the factors influencing OCR for LMS adoption in HEIs in Kosovo, focusing on attributes of change, leadership support, internal organizational context, and attributes of the change targets. Our findings emphasize the critical role of attributes of the change, particularly vision clarity and change appropriateness, in shaping OCR for LMS implementation in HEIs in Kosovo. Conversely, factors like change efficacy, leadership support and group self-efficacy did not demonstrate the expected influence, diverging from prior research. These findings underscore the importance of contextualizing LMS adoption within the unique cultural and institutional environments [14,20]. This highlights the necessity for tailored strategies that address region-specific barriers and opportunities to foster sustainable digital transformation. These results show the importance of considering Kosovo’s unique cultural and institutional characteristics when analyzing OCR for technological initiatives.

5.1. Attributes of the Change

The positive impact of vision clarity on OCR (H1) aligns with prior studies emphasizing that a well-communicated change vision reduces uncertainties and prepares staff for adoption [23,28]. Like other empirical evidence [26,28], our results show that LMS initiatives are more successful when they present a compelling reason that resonates with staff. Our findings expand this understanding by illustrating that effective sense-giving practices, such as targeted workshops and communication strategies, can strengthen vision clarity [14]. Considering that a large proportion of respondents are highly educated, with 72% holding PhDs and 22% holding master’s degrees, HEIs in Kosovo seem to have effectively communicated the vision for LMS adoption by aligning it with core institutional objectives, such as improving instructional quality and encouraging student engagement. By articulating this vision to highlight practical benefits for daily academic operations, HEIs in Kosovo reduced uncertainty and fostered a sense of purpose among both academic and administrative staff. This supports broader findings in LMS literature, which stress the role of clear alignment between institutional goals and user engagement [7].

Similarly, our results indicate that perceived change appropriateness (H2) is essential for OCR, supporting previous findings that highlight the significance of perceived relevance in facilitating technology adoption [29,32]. Staff members who see LMS as a solution to existing challenges, such as outdated teaching practices or resource inefficiencies, are more likely to support its implementation [20]. Notably, a significant portion of participants reported medium to advanced IT literacy (44% and 28%, respectively), which likely enhanced their perception of LMS as a complementary tool rather than a disruptive one. This alignment may have been particularly effective in addressing common resistance concerns, such as system complexity or misalignment with existing practices [1].

Interestingly, change efficacy (H3) did not significantly predict OCR, diverging from prior research that links efficacy with successful change adoption [17,33]. This deviation could be attributed to the limited digital transformation experiences of staff within Kosovo’s HEIs, which aligns with Rodrigues et al. [28], who highlight the role of prior experiences in shaping change efficacy. Limited prior exposure to digital transformations and varying IT proficiency levels among respondents likely lowered overall confidence in adapting to the LMS. Kosovo’s HEIs may face unique challenges in this area, as indicated by the substantial proportion (49%) of respondents with over five years of tenure who may require additional support in technical training. Research suggests that ongoing technical support and examples of successful implementation can boost confidence in new technologies [3,31], but limited resources and past negative experiences may have reduced change efficacy. This emphasizes the need for sustained technical competency development and support systems for diverse digital literacy levels.

5.2. Leadership Support

While extensive research highlights the importance of leadership support in change initiatives [29], our findings reveal that top-management support (H4) does not significantly influence OCR for LMS implementation in Kosovo’s HEIs. This finding contrasts with the common expectation that top-management support directly enhances OCR, as well as previous studies suggesting that leadership plays a vital role in creating a conducive environment for change [34,35]. Consistent with prior research, this result emphasizes the importance of participatory approaches in leadership, particularly in contexts with entrenched resistance [14]. This finding also suggests that, when project announcements are sudden, LMS initiatives may also be introduced with limited advance notice or involvement of academic and administrative staff in the planning stages. This limited engagement can lead to skepticism or a sense of hesitation from staff, particularly if management’s support is perceived as top-down or rushed rather than collaborative. In line with the need for participatory approaches in leadership [21], our findings suggest that, rather than simply allocating resources, leaders should focus on transparent communication, staff inclusion, and building trust to promote OCR.

Conversely, the presence of a change champion (H5) significantly enhances OCR. Consistent with prior literature on change management [2,9,41,42], change champions address concerns, build confidence, and enhance leadership and staff relationships, particularly in institutions with varying levels of digital literacy. These findings underscore previous research [9,20], who highlight the critical role of change champions in reducing resistance and building positive attitudes toward technology adoption. In our study, change champions played a crucial role in demonstrating the efficacy of LMS, reducing resistance, and motivating staff through targeted support. These champions provided tailored assistance, which was especially impactful in encouraging LMS adoption in a context where academic and administrative staff had limited experience with digital platforms. Therefore, for smoother LMS project adoption, it is essential to identify champions who can build trust and highlight the benefits of the system early on.

5.3. Internal Organizational Context

Our results indicate that an organizational history of change (H6) did not significantly impact OCR for LMS adoption, a finding that differs from previous studies which suggest that successful past change experiences can positively influence OCR for future initiatives [44,45]. This may be because of the limited history of large-scale digital transformations within Kosovo’s HEIs, where traditional teaching practices remain predominant, and institutional flexibility has not been rigorously tested by frequent technological changes. Limited prior initiatives and underfunded LMS projects may have fostered skepticism among staff toward new implementations, particularly in settings with limited institutional resources [28]. This finding highlights the need for Kosovo’s HEIs to prioritize modern strategies for readiness building rather than relying on traditional methods.

Our analysis confirms that organizational conflicts (H7) negatively impact OCR for LMS adoption which aligns with findings in the literature [13]. Addressing conflicts through inclusive decision-making and effective communication is crucial for mitigating resistance and enhancing alignment with institutional goals [2]. In Kosovo’s HEIs, conflicts often arise from misalignments between administrative directives and personnel autonomy, which often contribute to resistance, especially among academic staff who make up 54% of our respondents. Traditional teaching practices in Kosovo further amplify these conflicts, especially when academic and administrative staff feel that LMS initiatives are forced with minimal input. These results emphasize the importance of involving staff early in decision-making processes to reduce perceived threats to autonomy and address internal disagreements [32]. Conflict resolution mechanisms and effective communication are essential for overcoming such barriers and following a unified approach to LMS adoption.

Conversely, organizational flexibility (H8) emerged as a positive predictor of OCR, like earlier studies that highlight the importance of adaptable policies in facilitating change [31,45]. Flexible institutional policies not only reduce resistance but also promote sustainable digital transformation by aligning LMS initiatives with long-term organizational goals [14,20]. HEIs that demonstrate flexibility by adjusting workloads, recognizing digital efforts in performance evaluations, and providing technical support, are better qualified to implement LMS successfully [22]. On the other hand, institutions perceived as rigid may face skepticism from staff regarding their OCR for LMS adoption [31]. This is particularly relevant in the context of our study, where a significant portion of respondents (44% medium and 28% advanced in IT literacy) have indicated varying levels of digital proficiency, meaning that flexibility in resource allocation and support systems can directly impact OCR for LMS. Rigid institutions may encounter skepticism, particularly among academic staff concerned with increased responsibilities and limited support. An adaptive environment not only eases workload concerns but also reinforces a supportive foundation, which ultimately makes the adoption of LMS more accessible to staff with diverse technical skills and educational backgrounds. By creating such an environment, HEIs can effectively reduce resistance, and ensure that OCR for LMS is strengthened by a combination of flexible policies and responsive support structures.

5.4. Attributes of the Change Targets

Contrary to expectations, group self-efficacy (H9) did not significantly impact OCR for LMS adoption, a result that contrasts with literature which highlights the importance of collective efficacy in technology adoption [9,47]. Our findings suggest that collective efficacy is contingent upon institutional support mechanisms, such as tailored training programs and demonstration initiatives [27]. This discrepancy may be attributed to varying digital literacy levels within Kosovo’s HEIs, which could diminish confidence in collective LMS usage. Additionally, LMS complexity could be a barrier for staff despite the training efforts. Previous research emphasizes the value of sustained, personalized support to boost both individual and group confidence in technology use [2,27]. Another factor could be that staff in Kosovo’s HEIs should have prior exposure to LMS functionalities through demonstrations, pilot programs, or training sessions, so they feel more collectively capable of integrating the system into their routines. However, in cases where LMS remains an abstract concept, and in the absence of concrete examples or hands-on engagement, staff may struggle to envision how it will function and fit within their workflows. This ambiguity can prevent collective self-efficacy, as academic and administrative staff may feel uncertain about their collective ability to adopt the system successfully. For Kosovo’s HEIs, implementing targeted training and support programs may be essential to building staff confidence in LMS and address the unique challenges presented by varying digital proficiencies. Offering practical, firsthand experiences with the platform could also reduce uncertainty, making it easier for academic staff to envision the technology’s benefits and their collective ability to manage it effectively. This approach may be particularly crucial in regions like Kosovo, where prior experience with similar systems is limited, thus making the support for collective self-efficacy a key factor in successful LMS adoption.

6. Conclusions

This study aimed to explore the factors influencing OCR for LMS adoption in HEIs, focusing on the unique cultural and institutional context of Kosovo. As part of this exploration, the study sought to identify organizational and individual factors critical for fostering sustainable digital transformation. The findings highlight that vision clarity, change appropriateness, leadership support, organizational flexibility, and the presence of a project champion significantly enhance OCR. Conversely, factors such as change efficacy, organizational history of change, organizational conflicts, and group self-efficacy were less influential than anticipated, pointing to context specific to Kosovo’s HEIs. These findings underline the importance of aligning technological initiatives with broader institutional objectives and tailoring strategies to regional and cultural contexts.

From a policy perspective, the results suggest that governments and institutional leaders should prioritize building technical infrastructure and offering incentives for faculty engagement. Additionally, fostering collaboration between HEIs in developing regions can help share best practices and resources for effective LMS adoption. From a practical perspective, HEIs must clearly communicate the alignment of LMS with institutional goals to mitigate hesitation and resistance. Additionally, the presence of project champions emerged as a critical facilitator of LMS adoption, emphasizing the need for HEIs to engage change agents who can create enthusiasm and guide staff through the transition process. The findings also indicate that a participatory leadership approach and inclusive decision-making are crucial for improving staff buy-in and ensuring the long-term success of LMS projects. On the other hand, the limited impact of leadership support and change efficacy indicates a need for a more participatory approach to leadership and a greater focus on building individual and collective digital skills.

This study contributes to the literature by providing insights into how OCR for LMS adoption is shaped in developing regions, particularly in contexts where traditional teaching methods prevail and resistance to technological change is common. The findings point out the importance of contextualized approaches to LMS adoption that consider both organizational and individual factors. Moreover, the study highlights the role of sustainable digital transformation in aligning institutional goals with educational modernization efforts, offering a valuable framework for future LMS research and implementation strategies.

Implications for research include the necessity of further examining the interaction between leadership strategies, digital literacy, and institutional flexibility. Future research should continue to explore how leadership strategies, digital literacy, and flexibility in institutional policies interact to influence OCR. Additionally, future studies could further integrate theoretical frameworks like TAM, UTAUT, and TPB to provide a more comprehensive understanding of technology acceptance in HEIs.

The study has certain limitations that should be considered when interpreting the results. The use of self-reported questionnaires introduces potential bias, and future research could employ mixed methods to validate these findings. The sample was limited to Kosovo’s HEIs, and further research should examine similar constructs across different countries and educational systems to enhance generalizability. Additionally, the cross-sectional design captures perceptions at a single point in time, making it difficult to track how OCR evolved throughout LMS implementation. Longitudinal studies are needed to examine how factors such as leadership support, organizational conflicts, and collective self-efficacy fluctuate over time. This study did not include other potential predictors of OCR, such as perceptions of the usability of the LMS or external factors like regulatory or financial constraints. Future research should consider integrating additional variables to further enhance the explanatory power of the research model. Finally, exploring the broader implications of LMS adoption on educational equity and quality, especially in resource-constrained regions, would provide valuable insights into achieving the goals of sustainable education.