The study aimed to assess the extent to which supervisory behaviour and the internal work environment influence EDI and creativity.

Innovation and creativity are closely linked to novelty, transformation, and value creation. Contemporary scholarship defines innovation as the intentional implementation of new or significantly improved products, processes, services, or practices that generate value for organisations and their stakeholders (Ritala, Kraus & Bouncken 2024). Employee-driven innovation positions employees as active contributors to idea generation and problem-solving, emphasising that innovation emerges through interaction between individuals, supervisory behaviour, and the organisational context in which work is performed (Berglund et al. 2024).

Creativity refers to the generation of ideas, solutions, or approaches that are both novel and useful within a particular organisational context (Madjar 2005). While creativity primarily concerns idea generation, innovation extends beyond ideation to include the implementation and application of creative ideas to produce organisational value (Dubina 2005). Creativity can therefore be regarded as a precursor to innovation, as innovative outcomes depend on generating ideas that are sufficiently original, relevant, and actionable. In organisational settings, employee creativity is shaped not only by individual capabilities, but also by supervisory support and environmental conditions that legitimise experimentation and idea sharing (Madjar 2005).

Innovative and creative capacity is not restricted to specific job levels or occupational roles; rather, all employees possess latent creative potential that can be mobilised under appropriate organisational and supervisory conditions (Kwon & Kim 2023; Montani, Vandenberghe & Khedhaouria 2024). Employees often hold deep, tacit knowledge of operational processes, customer needs, and inefficiencies, positioning them to identify improvement opportunities that may not be visible to senior management. As a result, EDI is increasingly conceptualised as a bottom-up process embedded in daily work activities rather than as a purely top-down strategic initiative (Bäckström, Bengtsson & Berglund 2022).

Foundational EDI scholarship emphasises that innovation frequently emerges from employees’ experiential knowledge and proximity to operational challenges (Kesting & Ulhøi 2010). Employees often identify inefficiencies, service gaps, and opportunities for improvement that may remain invisible at senior management levels. Consequently, EDI depends on organisational systems that encourage bottom-up participation, knowledge exchange, and experimentation. More recent scholarship reinforces this position by showing that structured managerial support, collaborative practices, and organisational learning mechanisms are critical for sustaining employee innovation over time (Flocco, Canterino & Cagliano 2022). In higher education institutions specifically, innovation increasingly depends on employees’ ability to adapt work practices, redesign service delivery processes, and contribute creative solutions within constrained institutional environments.

Unfortunately, formal innovation initiatives often prioritise top-down approaches and managerial control, with employee contributions frequently remaining undervalued or underutilised in the absence of supportive supervisory practices (Cerne et al. 2023). Supervisory behaviour, therefore, plays a pivotal role in determining whether employee ideas are encouraged, legitimised, and acted upon. Supervisory support, autonomy, and psychological safety have been consistently identified as key enablers of employees’ willingness to engage in creative behaviours and innovation-related risk-taking, linking EDI directly to the internal work environment (Rehman 2025).

Employee-driven innovation may take the form of incremental or radical innovation, each placing different demands on supervisory behaviour and environmental conditions. Incremental innovation involves small-scale, continuous improvements aligned with existing organisational routines and is often associated with lower risk and resource requirements (Berraies, Jabeur & Sassi 2023; Kraus et al. 2023; Ritala et al. 2024). Radical innovation, by contrast, challenges dominant assumptions and introduces solutions that are novel to the organisation, frequently emerging when employees question established ways of working (Raisch & Zimmermann 2023). In such cases, supervisors and middle managers are crucial in protecting, legitimising, and resourcing innovative initiatives, particularly in contexts characterised by uncertainty and risk (Montani et al. 2024).

Given the distinct benefits and risks associated with incremental and radical innovation, organisational ambidexterity, the capacity to pursue exploitation and exploration simultaneously, has become a necessity (Raisch & Zimmermann 2023). Consequently, organisations seeking long-term sustainability must create supervisory and environmental conditions that enable employees to contribute creatively across different forms of innovation.

Although innovation is frequently emphasised in strategic plans and managerial discourse as essential for organisational success, this commitment does not always translate into supportive supervisory behaviour. At the operational level, supervisors often respond cautiously to employee innovation because innovative activities introduce uncertainty, disrupt established routines, and require a partial relinquishment of control (Cerne et al. 2023; Raisch & Zimmermann 2023). As a result, supervisors may unintentionally constrain EDI and creativity by prioritising compliance, predictability, and short-term performance outcomes over experimentation and learning.

Empirical research consistently shows that supervisory behaviour exerts a proximal influence on employees’ motivation, attitudes, and discretionary behaviours related to innovation and creativity (Montani et al. 2024). Supervisors’ day-to-day leadership orientations shape whether employees perceive innovative behaviour as legitimate and worthwhile or as risky and unrewarded (Jin & Peng 2024). In this sense, supervisors act as operational gatekeepers who translate organisational intentions into practice, distinguishing their role from broader management-level structures and policies that shape innovation more distally (Kwon & Kim 2023).

Research on EDI further highlights the importance of relational exchanges between supervisors and employees. Hansen et al. (2017) argue that managerial support facilitates EDI by legitimising employee experimentation and creating opportunities for collaborative problem-solving. Similarly, Echebiri and Amundsen (2021) emphasise that leader-member relationships characterised by trust, communication, and mutual respect strengthen employees’ willingness to contribute innovative ideas. These relational dynamics are particularly important in bureaucratic settings where employees may otherwise perceive innovation as risky or misaligned with formal expectations.

Within this proximal role, empowering supervisory behaviour has been identified as a key antecedent of employee innovation and creativity. Empowering supervision enhances employees’ creative self-efficacy, intrinsic motivation, and willingness to engage in problem-solving and experimentation (Lee, Willis & Tian 2023; Montani et al. 2024). By granting discretion, encouraging exploration, and supporting learning from setbacks, supervisors create immediate conditions that legitimise innovation-related risk-taking and reduce the constraining effects of bureaucratic control (Berglund et al. 2024).

When supervisors demonstrate confidence in employees’ capabilities, allow flexibility in task execution, and provide constructive feedback and recognition, employees are more likely to pursue novel ideas and challenge existing practices (Jin & Peng 2024; Kwon & Kim 2023). Such supervisory behaviours support innovation by fostering autonomy and ownership at the task level. Conversely, controlling or risk-averse supervision discourages experimentation and reinforces conformity, thereby narrowing employees’ scope for creative engagement (Cerne et al. 2023).

Supervisors influence innovation not only through support and empowerment but also by balancing structure and flexibility. Mumford et al. (2002) found that leaders enhance creativity when they provide intellectual stimulation, constructive guidance, and access to resources while avoiding excessive control. Likewise, Rosing, Frese and Bausch (2011) emphasise the importance of ambidextrous leadership, whereby supervisors alternate between opening behaviours that encourage experimentation and closing behaviours that ensure coordination and implementation. Empirical evidence further demonstrates that supervisory support and encouragement positively influence employees’ innovative behaviour, particularly when employees possess confidence in their ability to innovate (Chen, Li & Leung 2016).

Overall, supervisory behaviour remains a critical proximal determinant of EDI, distinct from but complementary to management-level support and organisational systems. Supervisors who encourage idea generation, model learning-oriented behaviour, facilitate collaboration, and advocate for employee ideas play a central role in activating innovation at the operational level (Berglund et al. 2024). Such supervisory practices are essential for converting strategic commitments to innovation into sustained, employee-driven creative outcomes.

Innovative organisations deliberately cultivate internal work environments that function as learning systems, where ideas are embedded in everyday problem-solving and continuous improvement. Environments characterised by open communication, collaboration, and knowledge sharing legitimise idea generation as part of routine work, rather than as an exceptional activity, thereby strengthening employee innovation and creativity (Berglund et al. 2024; Ritala et al. 2024). Such environments signal organisational support for creativity and reinforce employees’ perceptions that innovation is both expected and valued.

The internal work environment comprises several interrelated dimensions that shape employees’ ability to innovate. Organisational innovation culture establishes norms regarding experimentation, collaboration, and openness to new ideas. Innovation mechanisms refer to formal structures and systems – such as suggestion schemes, collaborative forums, and idea evaluation processes – that facilitate the development and implementation of employee ideas. Innovation opportunities concern employees’ perceived availability of time, autonomy, and organisational support to explore improvements beyond routine work requirements. Risk-taking tolerance reflects the extent to which experimentation and failure are accepted as part of organisational learning, while dedication to innovation refers to the degree to which innovation is prioritised and supported within everyday organisational practices. Research by Dul and Ceylan (2014) demonstrates that workplace environments characterised by autonomy, resource availability, supportive leadership, and flexible work structures significantly strengthen creativity and innovation outcomes.

A core feature of innovation-supportive environments is the presence of psychological safety and trust, which enable employees to question existing practices, engage in constructive dissent, and experiment with alternative solutions without fear of negative repercussions (Cerne et al. 2023; Jin & Peng 2024). Work environments characterised by low power distance, task autonomy, meaningful and challenging work, and learning-oriented responses to failure encourage employees to both explore new ideas and leverage existing knowledge (Montani et al. 2024). These conditions are particularly salient for EDI, as they empower employees to take ownership of innovation beyond formal role expectations.

Internal work environments may contain structural and cultural constraints that inhibit innovation. Excessive workload pressures, rigid procedures, limited supervisory or senior management support, inadequate access to resources, and risk-averse cultures reduce employees’ capacity to experiment and engage creatively (Kraus et al. 2023; Raisch & Zimmermann 2023). In contrast, environments that provide visible managerial support, participative decision-making, collaborative and diverse workgroups, and systematic processes for idea development are more likely to foster sustained innovation (Berglund et al. 2024; Montani et al. 2024).

Research further suggests that interactions among environmental dimensions are more important than any single factor in isolation. Dul and Ceylan (2014) argue that creativity-supportive work environments emerge through a combination of autonomy, resource availability, supportive leadership, and organisational flexibility. Consequently, innovation opportunities are more likely to translate into EDI when accompanied by a culture that tolerates risk, visible supervisory support, and mechanisms that facilitate idea implementation.

Organisational culture constitutes a central dimension of the internal work environment, shaping employees’ willingness and ability to innovate. Cultural attributes related to adaptability, collaboration, and support for creativity are closely linked with enabling conditions such as risk tolerance, innovation opportunities, and effective team processes (Bogale & Debela 2024). Cultures that normalise experimentation and view failure as a learning opportunity encourage employees to propose novel ideas and challenge established practices (Kraus et al. 2023; Raisch & Zimmermann 2023).

Communication patterns and social interaction further influence the innovative capacity of the work environment. Open communication, cooperative teamwork, and strong interdepartmental collaboration facilitate the exchange and integration of diverse knowledge, which is essential for creative problem-solving and EDI (Berglund et al. 2024; Cerne et al. 2023). Reward systems also play a signalling role: recognition of innovative efforts reinforces the value placed on creativity, while punitive responses to failure or a lack of meaningful rewards can discourage employees from engaging in innovation-related activities (Lee et al. 2023).

Access to adequate resources represents another critical environmental condition for innovation. Employees are more likely to experiment creatively and take calculated risks when sufficient financial, technological, informational, and human resources are available (Berglund et al. 2024; Montani et al. 2024). Time is particularly decisive: while moderate time pressure may support execution, sustained urgency and excessive time constraints undermine reflection, collaboration, and idea development, thereby constraining EDI (Jin & Peng 2024; Montani et al. 2024).

In summary, the internal work environment shapes employee innovation through the interaction of cultural norms, structural conditions, social dynamics, and resource availability. Innovation-supportive environments are characterised by learning-oriented cultures, psychological safety, supportive supervisory and managerial practices, accessible innovation mechanisms, and adequate time and resources. Conceptually, these elements operate as an integrated system: organisational culture and structures establish the boundaries for innovation, while day-to-day work conditions and resources determine whether employees are able and willing to translate creative ideas into innovative outcomes.

The study adopted a positivist research paradigm, which assumes that organisational phenomena can be objectively measured and analysed to identify patterns and relationships among variables. A positivist approach was considered appropriate because the study sought to examine measurable relationships between supervisory behaviour, the internal work environment, EDI, and creativity using statistical analysis (Creswell & Creswell 2018). Quantitative methods were therefore employed to facilitate hypothesis testing, relational analysis, and the empirical examination of mediating effects across constructs. A cross-sectional, descriptive, exploratory, and explanatory research design was employed to examine how supervisory behaviour and the internal work environment influence EDI and creativity in a South African ODeL institution. The study employed a census survey, and 624 participants completed a self-developed questionnaire, yielding a response rate of 15%. Inferential statistical analysis was employed to evaluate the concurrent effects of supervisory behaviour and the work environment on employee innovation and creativity.

The study targeted the entire population of 4206 academic and administrative employees at a South African higher education institution, with 624 usable questionnaires returned, representing a 15% response rate. Although modest, the 15% response rate is not uncommon in voluntary electronic surveys conducted in large organisational and higher education settings, where online participation rates are often comparatively lower (eds. Vannette & Krosnick 2018). The achieved sample size was sufficient to support robust multivariate analyses, including correlation analysis and structural equation modelling (SEM), thereby ensuring adequate statistical power for examining relationships between constructs.

The demographic profile of the sample generally aligned with that of the population. African (black) employees constituted a smaller share of the sample (47.6%) than of the population (63.2%), whereas female employees were marginally more prevalent in the sample (64.3%) than in the population (60%). Employees from administrative departments or units were also over-represented in the sample (60.6%) compared to their proportion in the population (48%), as were individuals occupying supervisory positions (30.4% vs. 22.6%). In addition, respondents with postgraduate qualifications accounted for a larger proportion of the sample (66.2%) than of the population (51%). Notwithstanding these discrepancies, the sample adequately represents the population across the main demographic characteristics, supporting its overall representativeness. While non-response bias cannot be entirely ruled out, participation was achieved across all major employee categories and occupational levels. The study focused on relational analysis rather than population estimation, for which sample size and variability are more critical than response rate alone.

The Supervisor-Internal Environment Questionnaire (SIEQ) was developed for the study, with questionnaire items derived from an extensive review of the literature, including academic articles and specialised texts on supervisory behaviour, leadership, the internal work environment, and EDI and creativity.

The questionnaire consisted of four sections: (1) demographic information; (2) supervisory behaviour, including statements on supervisory support and factors influencing EDI and creativity; (3) the internal work environment, encompassing organisational innovation culture, innovation mechanisms, innovation opportunities, risk-taking tolerance, and commitment to innovation and creativity; and (4) supervisory support, which included items related to management support, innovation management, innovative leadership, and team innovation. Exploratory factor analysis (EFA) was conducted to determine the underlying factor structure of the constructs. Subsequent statistical analyses confirmed the reliability and validity of the measuring instrument, indicating that it was appropriate for assessing the constructs included in the study. Internal consistency reliability was established using acceptable Cronbach’s alpha coefficients (Cronbach’s α > 0.70 across constructs).

Ethical clearance to conduct this study was obtained from the University of South Africa College of Economic and Management Sciences Research Ethics Review Committee (No. 2018_CRERC_011[FA]). The questionnaire was administered electronically via the Lime Survey platform, with participants accessing it via a dedicated web link. Informed and voluntary consent was implied through participants’ completion and submission of the survey. Anonymity of responses was guaranteed, and no identifying information was collected. The survey was closed once enough completed questionnaires had been obtained. Appropriate measures were taken to ensure confidentiality and data integrity, including password-protected storage and the secure retention of data in a locked location.

The results of the correlation analysis, which examined the strength and direction of the relationships between the constructs of supervisory behaviour and the internal work environment, are presented in Table 1.

Table 1 shows that supervisory support was significantly and positively related to most internal work environment variables. The strongest relationship was observed with innovation opportunities (r = 0.63, p < 0.01; large practical effect), followed by risk-taking tolerance (r = 0.47, p < 0.01; medium effect), innovation mechanisms (r = 0.37, p < 0.01; medium effect), and organisational innovation culture (r = 0.36, p < 0.01; medium effect). No statistically significant relationship was found between supervisory support and dedication to innovation (r = 0.067, p = 0.096).

Supervisory support also demonstrated consistent, significant associations with all supervisory behaviour (management) factors, including innovation management (r = 0.47, p < 0.01), team innovation (r = 0.36, p < 0.01), innovative leadership (r = 0.33, p < 0.01), and management support (r = 0.30, p < 0.01), all reflecting medium practical effects. These results indicate strong linkages between supervisory support and broader management practices associated with innovation (Leach 2020).

Organisational innovation culture showed strong and significant relationships with both internal work environment and supervisory behaviour variables. Large practical effects were observed with innovation management (r = 0.69, p < 0.01) and team innovation (r = 0.54, p < 0.01), while medium effects were evident for innovative leadership (r = 0.48, p < 0.01) and management support (r = 0.41, p < 0.01). Organisational innovation culture also correlated strongly with innovation opportunities (r = 0.59, p < 0.01), risk-taking tolerance (r = 0.55, p < 0.01), and innovation mechanisms (r = 0.54, p < 0.01), all of which reflect large practical effects (Leach 2020).

Significant relationships were further identified among key internal work environment factors. Innovation opportunities were strongly related to innovation mechanisms (r = 0.54, p < 0.01; large effect) and risk-taking tolerance (r = 0.54, p < 0.01; large effect). Innovation mechanisms also showed significant associations with innovation management (r = 0.46, p < 0.01), innovative leadership (r = 0.30, p < 0.01), team innovation (r = 0.35, p < 0.01), and management support (r = 0.19, p = 0.008), indicating that all supervisory behaviour factors were significantly related to the processes that initiate innovation (Leach 2020).

Risk-taking tolerance demonstrated significant relationships with innovation management (r = 0.50, p < 0.01; large effect), innovative leadership (r = 0.44, p < 0.01), management support (r = 0.40, p < 0.01), and team innovation (r = 0.36, p < 0.01), reflecting medium to large practical effects. In addition, dedication to innovation was positively related to risk-taking tolerance (r = 0.20, p < 0.01; small effect) and innovation opportunities (r = 0.18, p < 0.01; small effect) (Leach 2020).

Finally, strong inter-relationships were observed among supervisory behaviour (management) factors. Management support was strongly associated with innovative leadership (r = 0.79, p < 0.01), team innovation (r = 0.60, p < 0.01), and innovation management (r = 0.54, p < 0.01). Innovation management was also strongly related to innovative leadership (r = 0.62, p < 0.01) and team innovation (r = 0.65, p < 0.01). In contrast, innovative leadership was strongly associated with team innovation (r = 0.65, p < 0.01). These results indicate a high degree of alignment among supervisory behaviour factors associated with innovation (Leach 2020).

The initial Structural Equation Modelling (SEM) model tested a comprehensive set of relationships between supervisory and management-related factors and multiple dimensions of the internal work environment. Although Model 1 demonstrated an acceptable overall fit, inspection of the structural paths revealed estimation challenges, including several standardised regression coefficients exceeding unity. Further diagnostic analysis identified substantial multicollinearity between key exogenous constructs, specifically between team innovation and management support, and between innovation management and innovative leadership. These high intercorrelations indicated conceptual and empirical overlap, justifying the consolidation of constructs and the re-specification of the model.

To address these issues and improve model parsimony and interpretability, a second SEM model was developed, combining the highly correlated constructs into two higher-order exogenous variables: management support teams and innovative management and leadership. The revised model (Model 2) showed a slightly improved and clearly acceptable fit, with all key goodness-of-fit indices meeting recommended thresholds. This supported the adequacy of the respecified model in explaining the structural relationships underlying employee innovation and creativity. The second SEM model, which integrates both measurement and structural relationships, is presented in Figure 1. The goodness-of-fit indices associated with Model 2 are reported in Table 2.

The model demonstrated a good fit, as reflected by the CMIN/df ratio of 1.927, which was lower than the recommended benchmark value of 3. Root Mean Square Error of Approximation (RMSEA) should ideally be below 0.05 for a good fit, and below 0.08 for an adequate fit (Hu & Bentler 1999). The RMSEA value of 0.070, with lower and upper confidence intervals of 0.066–0.074, indicated acceptable model fit. Furthermore, the Comparative Fit Index (CFI) (0.841), Tucker-Lewis Index (TFI) (0.833), and Incremental Fit Index (IFI) (0.842) values exceeded the 0.80 threshold, indicating an adequate level of fit. Collectively, the recommended fit indices support the conclusion that Model 2 demonstrates an acceptable fit. The structural parameter estimates are presented in Table 3.

Table 3 indicates that management support teams demonstrated strong, statistically significant positive relationships with several endogenous variables. The largest standardised effects were observed for innovation mechanisms (β = 0.922), risk-taking tolerance (β = 0.836), and supervisory support (β = 0.678). No statistically significant relationship was found between management support teams and innovation dedication.

In contrast, innovative management and leadership showed a different pattern of relationships. Statistically significant negative relationships were observed with organisational innovation culture (β = −0.363) and innovation opportunities (β = −0.420). A statistically significant positive relationship was found between innovative management and leadership and risk-taking tolerance (β = 0.549). No statistically significant relationships were identified between innovative management and leadership and supervisory support, dedication to innovation, or innovation mechanisms.

The findings provide partial support for the hypothesised relationships between supervisory behaviour, the internal work environment, and EDI and creativity. Consistent with Hypothesis 2, supervisory and management-related factors demonstrated significant positive relationships with several internal work environment variables, particularly innovation mechanisms, risk-taking tolerance, and supervisory support. These results indicate that supportive supervisory and managerial practices foster environments conducive to innovation and creativity.

Hypothesis 3, which proposed a positive relationship between the internal work environment and EDI and creativity, received indirect support through the significant structural relationships observed among innovation culture, innovation opportunities, risk-taking tolerance, and supervisory support. However, not all internal work environment variables demonstrated equally strong effects. For example, dedication to innovation showed weaker, statistically non-significant relationships across several pathways, suggesting that employee commitment to innovation may depend on additional contextual or individual factors.

Finally, Hypothesis 4, which proposed a mediating role of the internal work environment, was supported. The findings indicate that supervisory behaviour influences employee innovation primarily through its impact on internal environmental conditions rather than through direct effects alone. This suggests that supervisors shape innovation indirectly by influencing organisational culture, innovation opportunities, risk-taking tolerance, and supportive mechanisms that enable employees to engage creatively.

This study makes a theoretical contribution by extending leadership–innovation frameworks that emphasise direct leadership effects. Instead, the study demonstrates that supervisory influence on EDI is largely indirect, mediated by internal work environment factors such as innovation culture, risk-taking tolerance, and innovation mechanisms. In challenging linear leadership–innovation models, the findings support a contextualised perspective in which supervisors shape innovation by configuring the conditions under which employees engage creatively. This complements and extends research on empowering leadership by empirically foregrounding the mediating role of organisational context (Lee et al. 2023; Montani et al. 2024).

From a practical perspective, the findings confirm that supervisors are the most immediate leverage point for fostering innovation in educational institutions. Developing supervisors as facilitators of innovation, through encouragement, constructive feedback, and visible support for new ideas, enables strategic innovation aspirations to be enacted in daily practice. Empowering supervisory behaviours, including autonomy, legitimised experimentation, and protection from punitive responses to failure, enhance employees’ willingness to engage creatively (Lee et al. 2023; Montani et al. 2024).

The study further highlights that innovation depends on an enabling internal work environment characterised by risk-taking, open communication, and collaborative problem-solving. Practical interventions, such as safe forums for idea sharing and learning-oriented responses to failure, foster psychological safety and knowledge exchange, which are essential for sustaining EDI (Berglund et al. 2024; Cerne et al. 2023; Figueiredo, Rodrigues & Diogo 2025; Nonyana, Mmako & Skosana 2025).

Beyond cultural support, structured innovation mechanisms are required to translate ideas into implementation. Clear processes, supported by supervisors, help balance incremental and transformative innovation, preventing creative potential from remaining underutilised (Kraus et al. 2023; Raisch & Zimmermann 2023).

Finally, the study highlights the importance of addressing constraints on time, autonomy, and resources. While accountability is necessary, excessive control and workload pressures undermine creative engagement. When autonomy, supportive leadership, and realistic resource allocation are aligned, employee innovation and creativity are more likely to be sustained over time (Jin & Peng 2024; Montani et al. 2024).

Several limitations should be acknowledged. Firstly, the study focused on supervisory behaviour and the internal work environment from an organisational innovation perspective and did not account for individual determinants, including personality, cognition, and motivation, which may also shape EDI and creativity. Secondly, the study was conducted within a single ODeL institution in South Africa. Given the distinctive structural, managerial, and operational characteristics associated with ODeL institutions, the results may not necessarily be transferable to conventional, comprehensive, or research-intensive universities, where organisational dynamics and supervisory practices may differ. Finally, because the study relied on self-reported survey data, the possibility of social desirability bias cannot be excluded, as respondents may have provided responses perceived as socially acceptable or organisationally favourable (Bernardi 2023).

Future studies could replicate this research across different categories of higher education institutions in South Africa, including traditional, comprehensive, and research-intensive universities, to determine whether institutional context influences EDI and creativity differently. Comparative studies between higher education institutions and private-sector organisations may further strengthen understanding of sector-specific innovation dynamics.

Future research should also investigate the role of individual-level variables, including personality, intrinsic motivation, cognitive orientation, and psychological capital, to provide a more comprehensive explanation of employee innovation and creativity. Furthermore, considering the distinct responsibilities associated with academic and administrative work environments, these contexts should be examined separately to determine whether different supervisory and organisational factors shape EDI and creativity across occupational groups.

Longitudinal or mixed-methods research designs may further strengthen understanding of causal relationships and provide richer insight into how supervisory behaviour and organisational conditions evolve to support employee innovation over time.