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Abstract

To improve their practices, teachers need to regularly develop and practice teaching innovations. Hence, this study examines such practices via the relations between entrepreneurial teachers and their entrepreneurial ecosystem, including schools’ formal structures and informal collegiality. Exploratory and confirmatory factor analyses of the survey responses of 734 teachers from 30 Hong Kong primary and secondary schools examined the structure of their entrepreneurial attributes and competencies. The results revealed hierarchical structures for entrepreneurial attributes (Mitigating Risk and Contriving Humility) and competencies (Advocating Innovation and Seeking Resources). The entrepreneurial ecosystem has a two-factor structure, comprising formal structure and community. Structural equation modeling showed that entrepreneurial teachers’ attributes were linked to entrepreneurial teachers’ competencies, which in turn were linked to the entrepreneurial ecosystem’s formal structures and informal community. Further, teachers with more than 3 years of teaching experience had more teacher entrepreneurial competencies than less experienced teachers. This study offers insights into (a) how teachers foster innovative and entrepreneurial teams within EEs, (b) strategies to integrate entrepreneurial thinking and innovative practices, (c) promoting innovation, and (d) forming entrepreneurial teams.

Keywords

entrepreneurial ecosystem teacher entrepreneurialism sustainability learning community teacher development

Introduction

Continuous pedagogical improvement (CPI) can substantially improve student learning outcomes (Ion & Sirvent, 2022). Effective CPI relies on both evidence-based practices and innovations in teaching and learning (Ion & Sirvent, 2022). As teachers are central to students’ academic learning, they are best positioned to adapt innovative pedagogical initiatives to address students’ needs (Askell-Williams & Koh, 2020; Bellei et al., 2020; Benoliel & Schechter, 2017). Teachers, serving as active agents at the interface of curricula and students, can engage in CPI cycles (assessing, planning, implementing, and evaluating) of revising teaching and learning practices to improve student outcomes, ideally equitably. Hence, CPI requires teachers to regularly develop and actualize these innovations (Ho et al., 2021; Ion & Sirvent, 2022; Oude Groote Beverborg et al., 2020).

To enhance teacher engagement in pedagogical improvement and innovation, many teachers engage in active vision-building (Leithwood et al., 2020; Oude Groote Beverborg et al., 2020). In this approach, a school helps teachers build a clear understanding of its goals and objectives and involves them in decision-making, thereby fostering their ownership and agency to improve their school (Ho & Chen, 2026). Furthermore, developing suitable collaboration among teachers and gathering feedback help identify areas for improving their teaching practices (Bellei et al., 2020; Runhaar et al., 2014).

As entrepreneurial teachers spearhead innovative teaching and curricula, understanding their key competencies and attributes can help identify them and support their initiatives (Boon et al., 2013; Ho et al., 2022; Wu & Lin, 2020). These entrepreneurial teachers mentor and collaborate with teams of colleagues to expand innovations across diverse subjects within an entrepreneurial ecosystem (EE; Ho et al., 2021). EEs resemble professional learning communities (PLCs, Shirley & Hargreaves, 2021). Like PLCs, EEs can help improve school systems, their culture, and their teaching. Unlike PLCs, EEs specifically include individuals who shape their school environment and culture to nurture and promote specific initiatives (entrepreneurial teachers, ETs, Spigel & Harrison, 2018; Stam & van de Ven, 2021). However, past studies have not explicated ETs’ roles in EEs (Ho et al., 2012; Ho et al., 2022; Roundy, 2022). To address this knowledge gap, we examine how ETs operate within these ecosystems via formal or informal collegiality strategies. To focus the inquiry, we ask:

How do the attributes and competencies of entrepreneurial teachers shape the entrepreneurial ecosystems of schools, particularly the ecosystem’s formal structures and informal communities?

Theoretical Framework

Theoretical Lens – Entrepreneurial Ecosystem

EEs, as defined in the business literature, refer to a system of specialized and diverse individuals who collaborate to strategically nurture the development and use of innovations within organizations (Ács et al., 2014; Stam et al., 2021). By fostering motivation and leadership abilities, EEs empower individuals to become change agents, driving, and guiding transformations (Spigel & Harrison, 2018; Stam et al., 2021).

Entrepreneurial individuals often engage with others to discover, pursue, and scale up new initiatives into organic EEs (organizational EEs; Ács et al., 2014; Autio et al., 2014; Cavallo et al., 2019), thereby fostering conditions to continue or expand entrepreneurial practices (Cavallo et al., 2019; Spigel et al., 2018; Stam et al., 2021). Hence, ETs help foster conditions and a culture within an EE’s evolving and socially interactive system, to spur further entrepreneurial development within their school(s; Spigel et al., 2018; Stam et al., 2021).

Furthermore, an individual’s active involvement in an authentic, structured environment, (possibly online), coupled with community-based learning, significantly enhances the development of entrepreneurial attributes and competencies (Curtis et al., 2021; Moberg, 2021; Motoyama & Knowlton, 2017). Therefore, maintaining a well-structured environment and a supportive community is crucial for fostering entrepreneurial attitudes among teachers and their thoughtful individual reflection on their experiences (Jones et al., 2020). The structure and community support provided by these environments are essential to EEs.

An EE comprises actors, formal structures, and their community. Actors are individuals who cooperate to fulfill their organization’s interests (Autio et al., 2014). Formal structures are explicit operational supports (i.e. decision-making apparatus and organizational routines; Ho et al., 2012) for promoting entrepreneurial activities in the organization (Autio et al., 2014; Fernandes & Ferreira, 2022). The community comprises informal networks among actors based on their mutual trust and cooperative relationships to advance entrepreneurial activities (Fernandes & Ferreira, 2022; Spigel et al., 2018; Steidle et al., 2024). Within an EE, actors, formal structures, and the community have mutually dependent relationships across time (Stam et al., 2021). Organization leaders and actors form and shape an EE’s formal structure and community (EE environment, Cavallo et al., 2019; Fernandes & Ferreira, 2022; Stam et al., 2021).

In educational settings, the formal structures of an educational environment (such as routines, meeting protocols, and decision-making processes) and its community ties (including trust and collegial interaction) can generate recurring opportunities for collaborative inquiry and feedback. These opportunities facilitate teachers’ professional learning by supporting cycles of experimentation, evidence-based practice, and reflective dialog (central elements of improvement work and learning communities; Bryk et al., 2015; Shirley & Hargreaves, 2021). In this study, “reflection” is defined as practice-focused sensemaking that occurs through structured routines and collegial interaction, rather than as a philosophical assertion about ultimate truth. EE community is defined as informal, trust-based networks among school actors; collegiality is used only as a shorthand descriptor of cooperative interaction within that community, not as a definition of the community construct.

Actors – ETs

Unlike past EE studies that only focus on formal structures supporting organizational routines (Ács et al., 2014; Stam et al., 2021), our study also examines the roles of actors in promoting innovation. Actors are individuals who engage, liaise, or coordinate activities to support the EEs operation, drive their evolution, or facilitate the incubation of innovation (Cavallo et al., 2019; Stam et al., 2021). They include initiators, experts, facilitators, learners, and brokers, and so on. For instance, some actors help create an EE to introduce inventive ideas and change their organization’s working practices (Stam et al., 2021). Other actors seek to gain ideas from the EE (Nambisan & Baron, 2013). Whether actors play active or passive roles in an EE, they are biotic elements that promote a self-reinforcing, virtuous cycle (Spigel et al., 2018). The term “self-reinforcing cycle” refers to the process by which early entrepreneurial actions, such as piloting an innovation, foster relational trust, legitimacy, and access to resources. These outcomes subsequently lower barriers to further innovation and enhance participation, thereby generating a positive feedback loop within the ecosystem (Spigel & Harrison, 2018; Stam & van de Ven, 2021). The term “virtuous” is used here in a non-moral sense to indicate a beneficial feedback loop, in contrast to a vicious cycle that undermines trust and participation. Such actors, particularly those with entrepreneurial attributes or competencies, are crucial for advancing the development of EEs (Cavallo et al., 2019; Fernandes & Ferreira, 2022; Spigel et al., 2018).

ETs are actors within their schools’ EE (Ho et al., 2022; Jentoft, 2017). ETs initiate and actualize innovative instruction, curriculum, or pastoral care strategies (i.e. educators’ work supporting students’ wellbeing, guidance, and social–emotional development, often through mentoring, counseling referral, and home–school liaison; Borasi & Finnigan, 2010; Gupta, 2021; Ho et al., 2021). To actualize an innovation, an ET seizes innovation opportunities, realizes them, and scales them in schools (Ho et al., 2021, 2022). Typically, ETs seek approval from school authorities to support the piloting of innovative initiatives. Then, they pilot and formalize the innovative practices in their subject departments. Finally, they share their experiences of adopting innovative practices with other subject departments. As ETs help structure the entrepreneurial environment within their schools, this study examines how ETs contribute to EEs, by acting as transformative agents or practicing their agency.

Notably, the EntreComp framework (endorsed by the European Commission) established a robust foundation for understanding and measuring individual entrepreneurial literacy and skills (Baggen & Kaffka, 2022). These competencies, attitudes, skills, and behaviors across social, cultural, environmental, and financial domains, include perseverance, resilience, self-efficacy, creativity, teamwork, and ethical sensitivity (Bacigalupo et al., 2020). While the framework’s 15 competencies aim to empower European citizens for their labor markets and lifelong learning (Baggen & Kaffka, 2022; Higgins et al., 2023), educational contexts exhibit unique entrepreneurial behaviors, prioritizing social value over economic gains while navigating educational constraints (Ho et al., 2021; Keyhani & Kim, 2021). To address these differences, Ho and Lu (2024) developed the Teacher Entrepreneurial Behavior (TEB) scale to measure educators’ entrepreneurial attributes and competencies, and explored their impacts on fostering collaborative communities within schools. We detail ETs’ key attributes and competencies below.

ET Attributes

ET attributes and competencies underpin ET behaviors (Ho et al., 2021). ET attributes are inner qualities that comprise an extensive array of characteristics, including humanism, insight, persistence, vision, ethics, and collaboration (Borasi & Finnigan, 2010; Dennis & Parker, 2010; van Dam et al., 2010). Scholars have organized ET attributes into two major dimensions: mitigating risk and contriving humility (Gupta, 2021; Ho et al., 2021, 2022; Shen & Yang, 2022). Mitigating risk combines recognizing opportunities for new pedagogical ideas, willingness to risk trying them (Dennis & Parker, 2010; George et al., 2019; Jentoft, 2017), assessing the risk of these new ideas, and piloting them before full implementation (Arruti & Paños-Castro, 2020; Ho et al., 2021). In short, mitigating risk combines risk-taking with the prevention of unnecessary risks. Contriving humility combines the confidence to introduce new ideas with humbly gaining support from colleagues (Ho et al., 2021, 2022). ETs stay in touch with colleagues to cultivate collaboration opportunities, which allow them to access human resources to actualize their innovative ideas (Keyhani & Kim, 2021; Shen & Yang, 2022).

ET Competencies

ET competencies are the abilities that ETs use to implement their innovative ideas (George et al., 2019; Ho et al., 2021; Shen & Yang, 2022). ETs’ two primary competencies are advocating innovation and seeking resources (Arruti & Paños-Castro, 2020; Ho & Lu, 2024; van Dam et al., 2010). Advocating innovation refers to generating new ideas, helping colleagues to create innovative ideas (Ho et al., 2021, 2022; Jentoft, 2017; Oplatka, 2014), and integrating ETs’ professional knowledge and experience within their schools to help their colleagues implement their ideas (Ho et al., 2022; Gupta, 2021). Seeking resources refers to developing external relationships to access support (often financial) to aid the implementation of their innovative ideas (Ghazali et al., 2022; Jentoft, 2017; Keyhani & Kim, 2021). When seeking resources, ETs consult with experts both inside and outside their schools to gather materials and access funding (Ho et al., 2021).

Relationship Between Attributes and Competencies

Teachers with greater ET attributes may be more likely to use their ET competencies to implement innovations (Ho et al., 2021; Jentoft, 2017). However, no large empirical study has determined the relationship between entrepreneurial attributes and competencies (Gupta, 2021; Ho et al., 2022; Shen & Yang, 2022). In line with entrepreneurship theory (Baggen & Kaffka, 2022; George et al., 2019; Ho et al., 2021), we conceptualize entrepreneurial attributes as foundational dispositions that shape individuals’ readiness for innovation, whereas competencies represent actionable abilities through which these dispositions are expressed. This hierarchical distinction is aligned with the logic of entrepreneurial ecosystems: actors’ personal dispositions enable the development of higher-order competencies for engaging with and transforming formal and communal components of the ecosystem (Cavallo et al., 2019; Stam & van de Ven, 2021). Accordingly, ET attributes function as antecedent enablers of ET competencies, rather than parallel components, forming a coherent theoretical and empirical hierarchy. Hence, we propose the following hypothesis.

H1. ET attributes are positively related to ET competencies.

EE Environment – Formal Structure

Beyond a school’s hierarchical structure, an entrepreneurial environment with an official, formal structure systematically nurtures innovations and supports their use (Apa et al., 2017). Formal structures vary; they can include entrepreneurial incubators, mentoring programs, or partnerships with outsiders (Crick & Crick, 2018). By purposefully forming or joining these formal structures, EEs bring administrative guidance and resources to minimize obstacles and offset innovation failings (Crick & Crick, 2018; Jentoft, 2017). An EE’s formal structure requires actors to activate and maintain its sustainability (Apa et al., 2017; Cavallo et al., 2019; Stam et al., 2021). When actors advocate innovation, they often move beyond their assigned roles in an EE’s formal structure, using and modifying it to cooperate with other actors (possibly from other departments) to generate and actualize new initiatives (Cavallo et al., 2019; Kuratko et al., 2017).

Although some entrepreneurial principals and teachers have viewed ETs as self-directed learners who observe, experiment, interact with others, and self-reflect outside the formal structure (Boon et al., 2013), others view ETs as advocating innovation, generating new ideas, and implementing them by developing the formal structure of an EE (Eyal & Yosef-Hassidim, 2012; Ho & Lu, 2024; Wu & Lin, 2020). Some ETs seek more autonomy from their principals and ask them to modify the formal structure to fit their needs (Eyal & Yosef-Hassidim, 2012; Ho et al., 2021). Hence, many entrepreneurial principals and ETs intentionally structure innovative conditions by creating (a) a rigorous management structure, (b) a network to exchange information, or (c) a reward system to support their colleagues as they plan, execute, and monitor new initiatives (Demirbilek, 2024; Ho et al., 2021, 2022). Hence, we propose two more hypotheses:

H2a. ET attributes are positively linked to the formal structure of the EE.

H2b. ET competencies are positively linked to the formal structure of the EE.

EE’s Environment – Community

A community comprises interconnected and interdependent actors who nurture their relationships (Cowell et al., 2018), learn from one another, and cultivate innovative ideas (Stam et al., 2021). Actors, especially those with entrepreneurial competencies, contribute their knowledge, and resources to shape or influence their community’s interactions to support the creation of innovative initiatives (Cavallo et al., 2019; Spigel et al., 2018; Stam et al., 2021).

As ETs aim to mitigate risk, advocate innovation, and seek resources, they purposefully expand their social network within schools to involve more colleagues, sometimes forming teams that support and help implement innovation initiatives (Ho et al., 2021; Sachs, 2001). They engage colleagues to work on authentic cases enabling them to discuss and reflect on their feelings and emotions about their teaching experience (Martin et al., 2018; Peltonen, 2015). In doing so, ETs nurture colleagues’ professional growth while implementing innovative ideas (Ho et al., 2020; Roundy, 2022). ETs contrive humility to maintain idea diversity, trust, and cooperative relationships (Ho et al., 2022; Jentoft, 2017; Roundy, 2022). As ETs proactively structure high-quality interactive communities to encourage colleague collaboration and facilitate talent retention, they actively maintain such relationships to advance community cohesiveness and sustainability (Motoyama & Knowlton, 2017; Spigel et al., 2018; Steidle et al., 2024). Hence, such communities can inspire colleagues to become more innovative in their teaching (Ho et al., 2020; Roundy, 2022). Thus, we suggest that the following hypotheses regarding ET attributes’ and competencies’ links with EE community.

H3a. ET attributes are positively linked to the EE community.

H3b. ET competencies are positively linked to the EE community.

Formal Structure and Community

When its formal structure resonates well with an established community, the EE thrives (Fernandes & Ferreira, 2022; Stam et al., 2021). As actors perform their roles during the development of their EEs, they can help build cooperative and interdependent relationships between the formal structure and the community over time (Nambisan & Baron, 2013). For instance, a formal structure with apprenticeship models or flexible middle leaders (e.g. department heads) can empower teachers to build and expand their community (Bryant, 2019; Ho et al., 2022). Furthermore, ETs can guide others to practice innovative pedagogy and generate bottom-up changes. In fact, the business literature extends this analysis, showing that proactive concretization and (re)formulation for synergy supports the development of EEs (Björklund & Krueger, 2016). Proactive concretization involves taking tangible, immediate actions that outline collaboration opportunities, thereby attracting and securing resources through visible, immediate benefits/progress. Conversely, (re)formulation for synergy strategically adapts goals to emphasize mutual benefits and incorporate external inputs, enhancing alignment and interdependencies among participants (Khatami et al., 2022; Nabi et al., 2017). Together, these mechanisms attract initial support, and sustain engagement and resource allocation by continuously aligning the evolving interests and capabilities within the entrepreneurial ecosystem. These processes reinforce the formal structures and sense of community, which are essential for developing and sustaining entrepreneurial environments in educational settings. As formal structure and community can help develop and sustain an entrepreneurial environment in schools (Fernandes & Ferreira, 2022; Stam et al., 2021), we propose a fourth hypothesis.

H4. EE formal structure is positively associated with EE community.

Hypothetical Framework

The conceptual framework (Figure 1) illustrates how the research question guides the study’s hypothesized relationships. The framework positions entrepreneurial teacher attributes (mitigating risk and contriving humility) as foundational personal dispositions that influence entrepreneurial teacher competencies (advocating innovation and seeking resources; H1). These competencies, in turn, are theorized to affect two interrelated components of schools’ EE: the formal structure (H2b) and the community (H3b). In addition, ET attributes are posited to exert indirect effects on the EE’s formal structure (H2a) and community (H3a) through ET competencies. Finally, the model proposes that the EE’s formal structure and community are positively associated (H4), reflecting their mutually reinforcing nature. The figure clarifies the logical flow from the research question to the testable hypotheses, illustrating how teachers’ entrepreneurial dispositions and actions shape the broader school environment that sustains innovation. While EE formal structure and community may also shape teachers’ entrepreneurial development over time, this study tests the teacher-to-environment direction consistent with our research question and cross-sectional design.

Figure 1.

Conceptual framework linking teacher entrepreneurial attributes and competencies to school entrepreneurial ecosystem components.

Hong Kong Context

The Hong Kong government has long promoted teachers’ continuing professional development and the cross-fertilization of ideas and expertise through sharing and collaboration to achieve sustainable school development and transformation (Committee on Professional Development of Teachers and Principals, 2015; Legislative Council, Panel on Education, 2020). Its education policies emphasize teachers as reflective practitioners and collaborative innovators who contribute to both the formal structures and informal communities of their schools. The government’s professional standards further encourage teachers to act as role models, demonstrating professional autonomy, collegial leadership, and a commitment to collective growth (Education Bureau, 2018). Within this system, entrepreneurial behavior, particularly among elementary and secondary school teachers, is primarily interpreted as an educational and pedagogical endeavor rather than a commercial one. Teachers are expected to enhance their schools’ formal structures by reviewing vision and mission statements and by refining policies, procedures, and practices that sustain improvement (Ho et al., 2025). Simultaneously, they strengthen their schools’ informal communities by mentoring colleagues, leading collaborative learning, and co-designing innovations to address emerging challenges. Consequently, Hong Kong provides an ideal context for examining how entrepreneurial teachers contribute to both the structural and relational dimensions of school ecosystems through formal and informal collegial approaches.

Although Hong Kong’s education system is characterized by centralized curriculum standards and strong accountability mechanisms, teachers retain moderate yet meaningful autonomy in their pedagogical and collaborative work (Lau et al., 2024). Within established curricular frameworks, teachers are encouraged to design innovative learning activities, adapt teaching approaches to students’ needs, and initiate professional collaborations both within and beyond their schools (Ho et al., 2025). Many schools also support teachers in developing learning community, corporate, and university partnerships to promote knowledge exchange and professional growth (Vajen et al., 2023). This environment enables entrepreneurial teachers to exercise agency through adaptive decision-making, resource-seeking, and leadership in developing collaborative ecosystems, even within the constraints of a tightly regulated policy context.

Methodology

Sample

In this study, data were collected from 734 teachers across 30 primary and secondary schools who participated in a professional development seminar organized by the first author (see Table 1). The seminar, Leading Teams in a Time of High Teacher Mobility, focused on strategies for sustaining staff morale and retention amid workforce turnover. Schools were invited through a professional development network administered by the Education Bureau, reflecting a purposive sampling strategy aimed at recruiting institutions already engaged in innovation or leadership initiatives. The participating teachers were active practitioners seeking to enhance their professional capacity. They comprised three roughly equal – sized age cohorts – born between 1965 to 1980 (Generation X), 1981 to 1996 (Millennials), and after 1996 (Generation Z) – and 59% had 12 or more years of teaching experience.

Table 1.

Sample Characteristics (N = 734).

Characteristic	%
Gender
Male	62.9
Female	37.1
Age
Generation Z (Born after 1996)	32.0
Millennial Generation (Born from 1981 to 1996)	34.1
Generation X (Born from 1965 to 1980)	33.9
Education background
Bachelor	52.1
Master	47.5
Doctor	0.4
Teaching experience
1–3 years	13.1
4–7 years	15.0
8–11 years	12.9
12 years or above	59.0

Measurements

All survey items were measured on a six-point Likert-type scale ranging from “strongly disagree” (1) to “strongly agree” (6). As some teachers teach Chinese at school, we prepared bilingual surveys. Three experienced principals forward- and backward-translate the survey into Chinese. Then, an experienced teacher education scholar, reviewed the translation and made further adjustment. Participants could view both the original and translated texts.

EE’s Actors – ET

Ho & Lu’s (2024) scales measured ET attributes: (a) mitigating risk (four items; Cronbach’s α = .86; e.g. I enhance my colleagues’ understanding in my initiatives) and (b) contriving humility (three items; α = .87; e.g. I am humble listening to my colleagues’ suggestions). It also measured ET competencies: (c) advocating innovation (four items; α = .86; e.g. I proactively share my own views) and (d) seeking resources (four items; α = .89; e.g. I help my colleagues get professional advice from experts outside of our school).

EE’s Environment – Formal Structure and Community

Jansen et al.’s (2006) instrument measured EE’s formal structure (six items; α = .97; e.g. Our team frequently refines existing school management infrastructure and procedures) and community (six items; α = .96; e.g. Our team develops and experiments with new professional learning and collaboration strategies). Capturing the roles of actors creating EE’s formal structure and community, this scale purposefully measured whether staff proactively modify organization operational support or establish a learning community for continuous improvement.

All items demonstrated acceptable loadings on their respective factors (⩾0.6), and no cross-loadings or item eliminations were necessary.

Data Analysis

To analyze the survey responses, we addressed the following issues with specific statistics strategies: (a) similarities versus differences of teachers across schools with multilevel analysis (Hox et al., 2017), (b) survey measurement errors (e.g. for community construct) with multilevel factor analyses (Joreskog & Sorbom, 2018), (c) multiple outcomes with multivariate outcome multilevel analysis (Hox et al., 2017), and multilevel structural equation models (ML-SEM, Joreskog & Sorbom, 2018), (d) indirect, multi-level mediation effects with multilevel M-tests (MacKinnon et al., 2004) and ML-SEM, (e) hypotheses’ false positives with the two stage linear step-up procedure (Benjamini et al., 2006), (f) comparing effect sizes with Lagrange multiplier tests (Bertsekas, 2014), and (g) consistency of results across data sets (robustness) with separate multilevel, single outcome models and analyses of data subsets (Kennedy, 2008; Table 2). For a detailed description of the whole analysis, see Ahn et al. (2021).

Table 2.

Statistical Strategies Addressing Each Analytic Difficulty.

Analytic difficulty	Statistics strategy
Data set
• Nested data (teachers within schools)	• Multilevel analysis (aka Hierarchical linear modeling, Hox et al., 2017)
• Measurement errors on surveys	• Factor Analysis (Joreskog & Sorbom, 2018)
Outcome variables
• Multiple outcomes (Y₁, Y_{2, . . .})	• Multivariate outcome multilevel analysis (Hox et al., 2017)
• Multiple outcomes (Y₁, Y_{2, . . .})	• Multilevel Structural equation model (Joreskog & Sorbom, 2018)
Explanatory variables
• Indirect, multi-level mediation effects (X → M → Y)	• Multilevel M-test (MacKinnon et al., 2004)
• Indirect, multi-level mediation effects (X → M → Y)	• Multilevel structural equation model (Joreskog & Sorbom, 2018)
• Many hypotheses’ false positives	• Two-stage linear step-up procedure (Benjamini et al., 2006)
• Compare effect sizes (β₁ > β₂?)	• Lagrange multiplier tests (Bertsekas, 2014)
• Consistency of results across data sets (Robustness)	• Separate multilevel, single outcome models
• Consistency of results across data sets (Robustness)	• Analyses of subsets of the data (Kennedy, 2008)

Factor Analyses

We tested each construct’s survey items (e.g. community) for internal validity and minimized their measurement errors with multilevel factor analyses (Joreskog & Sorbom, 2018). Specifically, we tested whether each construct’s factor structure was: (a) single, (b) multiple, (c) hierarchical, or (d) nested (aka bi-factor, Heck & Thomas, 2020). Bartlett factor scores yielded unbiased estimates of factor score parameters (Joreskog & Sorbom, 2018). To assess CFA fit, we used the comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error approximation (RMSEA), and standardized root mean square residual (SRMR), which minimized Type I and Type II errors in many simulations (Hu & Bentler, 1999). We used two fit thresholds: good (CFI & TLI > 0.95; RMSEA < 0.06; SRMR < 0.08) and moderate (0.90 < CFI & TLI < 0.95; 0.06 < RMSEA < 0.10; 0.08 < SRMR < 0.10).

Explanatory Model

We modeled EE outcomes with a multivariate outcome, multilevel analysis, starting with a variance component model to test for significant differences at each level: teacher (level 1) and school (level 2; Hox et al., 2017).

E E_O u t c o m e s y_{ij} = β_{y} + e_{yij} + f_{yj}

(1)

In the vector of EE_Outcomes_yij, outcome y (EE formal structure, EE community) of teacher i in school i had a grand mean intercept, β_y, with unexplained components (residuals) at the teacher- and school-levels (e_yij, f_yj).

\begin{array}{l} E E_O u t c o m e s y_{ij} = β_{y} + e_{yij} + f_{yj} + β_{ywj} D e m o g r a p h i c s y_{ij} + β_{yxk} E T_a t t r i b u t e s y_{ij} \\ + β_{yzj} E T_c o m p e t e n c i e s y_{ij} \end{array}

(2)

Explanatory variables were entered in sequential sets to estimate the variance explained by each set and to test for mediation effects (Kennedy, 2008). Structural variables could have influenced malleable process variables, so we first entered Demographics (gender, age, education, teaching experience), followed by ET_attributes (mitigating risk, contrived humility, which tested hypotheses H2a and H3a) and ET_competencies (advocate innovation, seek resources, which tested hypotheses H2b and H3b). A nested hypothesis test (difference in chi-squared log likelihoods; Δχ²LL) determined the significance of a set of explanatory variables (Kennedy, 2008). For greater precision and less multicollinearity, we omitted non-significant variables (which do not cause omitted variable bias, Cinelli & Hazlett, 2020). We applied these tests to all vectors and used an alpha level of .05.

We used multi-level mediation tests to test H1 and to create a multi-level path analysis (Hox et al., 2017) for the ML-SEM (Joreskog & Sorbom, 2018). We then removed non-significant variables to yield the final model. The final model with only significant variables and interactions was the candidate ML-SEM. We removed non-significant parameters (if any) to yield the final ML-SEM. The correlation between the two EE outcomes (EE formal structure, EE community) tested H4. The total effect (TE) of an explanatory variable on the outcome was the sum of its direct effects (DE) and its indirect effects (IE). (The indirect effect of explanatory variable X on outcome Y via mediator M [namely, X → M → Y] was the product of the standardized parameter linking X to M multiplied by the total effect of M on Y [namely, (X → M) × (M → Y)].)

Results

As the differences across schools were not significant (10% variance; 0.1 intraclass correlation; p < .05), a multilevel model was not needed, so we used single-level analyses.

Exploratory Factor Analysis (EFA)

We performed EFA with the Kaiser–Meyer–Olkin (KMO) test, and then used principal factor analysis with varimax rotation to verify the factor structure of the measurement scales (Joreskog & Sorbom, 2018). Table 2 presents the EFA results. The KMO value is 0.9 and Cronbach’s alpha for all factors exceeded .8.

Confirmatory Factor Analysis (CFA)

The results presented in Tables 3 to 5 suggest that hierarchical models (M3) best fit the ET attributes and the ET competencies data, while the two-factor model (M2) best fit the EE’s environment data (Table 6).

Table 3.

Results of Exploratory Factor Analysis.

Factors	Factor loading	KMO value	Eigenvalues	% Of variance	Cronbach’s alpha
ET attributes		0.903
Mitigating risk			2.803	30.049	.856
Mitigating_risk_3	0.895
Mitigating_risk_1	0.855
Mitigating_risk_2	0.724
Mitigating_risk_4	0.668
Contriving humility			2.150	20.720	.867
Contriving_humility_1	0.845
Contriving_humility_3	0.835
Contriving_humility_1	0.629
ET competencies		0.936
Seeking resources			3.382	22.548	.885
Seeking_resources_2	0.822
Seeking_resources_1	0.832
Seeking_resources_3	0.795
Seeking_resources_4	0.732
Advocating innovation			2.823	17.839	.862
Advocating_innovation_1	0.861
Advocating_innovation_2	0.765
Advocating_innovation_3	0.726
Advocating_innovation_4	0.708
EE’s environment		0.947
EE’s formal structure			5.197	43.308	.969
Formal_structure_4	0.879
Formal_structure_1	0.873
Formal_structure_2	0.860
Formal_structure_6	0.849
Formal_structure_5	0.848
Formal_structure_3	0.821
EE’s community			4.926	41.053	.955
Community_4	0.867
Community_6	0.848
Community_5	0.842
Community_1	0.835
Community_2	0.792
Community_3	0.777

Table 4.

Model Fit Summary and Model Measure Comparison for ET Attributes (N = 734).

Model	χ²	df	p	GFI	CFI	NFI	RMSEA
One-factor model	80.293	20	<.001	0.861	0.892	0.875	0.172
Two-factor model	58.741	17	<.001	0.981	0.989	0.984	0.058
Hierarchical model	40.857	13	<.001	0.986	0.992	0.989	0.054
Nested model	25.756	9	<.010	0.991	0.995	0.993	0.050

Note. χ² = chi-square; df = degrees of freedom; GFI = goodness-of-fit index; CFI = comparative fit index; NFI = normed fit index; RMSEA = root-mean-square error of approximation.

Table 5.

Model Fit Summary and Model Measure Comparison for ET Competencies (N = 734).

Model	χ²	df	p	GFI	CFI	NFI	RMSEA
One-factor model	108.650	14	<.001	0.840	0.837	0.833	0.200
Two-factor model	88.650	11	<.001	0.961	0.961	0.957	0.110
Hierarchical model	42.194	6	<.001	0.991	0.994	0.991	0.060
Nested model	28.235	5	<.001	0.988	0.991	0.989	0.082

Note. χ² = chi-square; df = degrees of freedom; GFI = goodness-of-fit index; CFI = comparative fit index; NFI = normed fit index; RMSEA = root-mean-square error of approximation.

Table 6.

Model Fit Summary and Model Measure Comparison for EE’s Environment (N = 734).

Model	χ²	df	p	GFI	CFI	NFI	RMSEA
One-factor model	595.183	40	<.001	0.666	0.849	0.846	0.230
Two-factor model	230.305	39	<.001	0.945	0.981	0.978	0.052
Hierarchical model	191.066	32	<.001	0.891	0.946	0.943	0.154
Nested model	110.849	30	n.s.	0.986	0.979	0.978	0.110

Note. χ² = chi-square; df = degrees of freedom; GFI = goodness-of-fit index; CFI = comparative fit index; NFI = normed fit index; RMSEA = root-mean-square error of approximation.

The results in Tables 3 and 4 indicate that the hierarchical linear model of ET attributes data (RMSEA = 0.054; normed fit index = 0.989; CFI = 0.992; goodness-of-fit index (GFI) = 0.986; chi-square (χ²) [13] = 40.857, p < .001) and competencies (RMSEA = 0.060; normed fit index = 0.991; CFI = 0.994; goodness-of-fit index (GFI) = 0.991; chi-square (χ²) [6] = 42.194, p < .001) comprising two specific factors best fit the data. The Cronbach’s alpha of these factors exceeded .80. Table 5 shows that two factors, EE’s formal structure and EE’s community, were linked to EE’s environment (RMSEA = 0.052; normed fit index = 0.978; CFI = 0.981; goodness-of-fit index (GFI) = 0.945; chi-square (χ²) [39] = 230.305, p < .001). The Cronbach’s alphas of these factors all exceeded .95.

Correlation Analysis

ET attributes were positively correlated with ET competencies (r = .70), which in turn were positively correlated with EE’s formal structure (r = .44) and EE’s community (r = .54). EE’s formal structure and EE’s community were also positively correlated (r = .73). Notably, four demographic variables, namely, generation Z, generation X, teaching experience (0–3 years), and teaching experience (8 years or above), were positively correlated to ET competencies (Table 7).

Table 7.

Means (M), Standard Deviations (SDs), and Correlations Among All Variables.

	Variables	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1	1. Female	0.63	0.48
2	2. Generation Z	0.32	0.47	−.01
3	3. Generation M	0.34	0.47	.08	−.49
4	4. Generation X	0.34	0.43	−.07	−.39	−.40
5	5. Bachelor	0.52	0.50	−.02	.22	−.23	−.02
6	6. Master’s	0.48	0.50	.03	−.21	.23	.02	−.99
7	7. Doctor	0.00	0.06	−.04	−.04	.00	.01	−.07	−.06
8	8. Teaching experience (1–3 years)	0.13	0.33	−.07	.44	−.17	−.21	.19	−.19	.04
9	9. Teaching experience (4–7 years)	0.15	0.36	−.01	.51	−.24	−.20	.15	−.15	−.03	−.16
10	10. Teaching experience (8–11 years)	0.13	0.34	.07	.21	.02	−.17	−.09	.09	−.03	−.15	−.17
11	11. Teaching experience (12 or more years)	0.59	0.49	.01	−.82	.27	.40	−.18	.18	.01	−.46	−.50	−.47
12	12. ET attributes	4.75	0.97	.04	.01	.02	.01	−.01	.01	−.01	−.01	−.01	.04	−.02
13	13. ET competencies	4.26	0.68	−.01	−.16	.04	.12	−.07	.08	−.02	−.15	−.03	−.03	.15	.70
14	14. EE formal structure	4.03	0.62	.02	.03	.02	−.02	.02	−.02	−.03	.01	.05	.02	−.05	.42	.44
15	15. EE community	3.66	0.80	−.01	.03	.02	.01	−.01	.01	−.02	−.02	.05	.04	−.06	.50	.54	.73

Note. N = 734. Correlations of |.08| or higher are significant at α = .05.

SEM

The single-level SEM showed a good fit (SRMR = 0.064; CFI = 0.976; TLI = 0.961; RMSEA = 0.042; χ² [291] = 722; p < .001; IFI = 0.967; AGFI = 0.907; RFI = 0.952; Figure 2). Demographics and ET attributes were linked to ET competencies. Compared to other teachers, those with 1 to 3 years of experience showed fewer ET competencies (TE = DE = −0.345). Meanwhile, teachers with greater ET attributes showed greater ET competencies (TE = DE = 0.791), supporting hypothesis H1.

Figure 2.

Summary of standardized parameters for the structural equation model of entrepreneurial ecosystem (N = 734). For clarity of presentation, observed measures of each factor are not shown. Black and red arrows show positive and negative effect sizes, respectively. Thicker arrows show larger effect sizes.

Years of experience, ET attributes, and ET competencies were linked to EE formal structure. Teachers with greater ET attributes reported greater EE formal structure (TE = IE = 0.407 = 0.791 × 0.514 via TE competencies), supporting H2a. Likewise, teachers with greater ET competencies reported greater EE formal structure (TE = DE = 0.514), supporting H2b. However, compared to other teachers, those with 1 to 3 years of experience reported less EE formal structure (TE = IE = −0.177 = −0.345 × 0.514 via TE competencies).

Years of experience, ET attributes, and ET competencies were linked to EE community. Teachers with greater ET attributes reported greater EE community (TE = IE = 0.340 = 0.791 × 0.430 via TE competencies), supporting H3a. Likewise, teachers with greater ET competencies reported greater EE community (TE = DE = 0.430), supporting H3b. Compared to other teachers, those with 1 to 3 years of experience reported less EE community (TE = IE = −0.148 = −0.345 × 0.430 via TE competencies).

EE formal structure was positively correlated with EE community (0.347) supporting H4. Other relationships were not significant. This final model accounted for 78% of the variance in EE formal structure and 35% of the variance in EE community.

Discussion

Extending previous research on EE, our study examines how the attributes and competencies of entrepreneurial teachers shape the entrepreneurial ecosystems of schools, particularly the ecosystems’ formal structures and informal communities. The results supported all hypothesized relationships (H1–H4) and clarified the connections between entrepreneurial teachers and the school entrepreneurial ecosystem. Consistent with H1, entrepreneurial teacher (ET) attributes were strongly and positively associated with ET competencies (β = .791), supporting the interpretation that attributes serve as foundational dispositions expressed through actionable competencies. In accordance with H2a and H2b, ET competencies were positively linked to the entrepreneurial ecosystem’s (EE) formal structure (β = .514), while ET attributes demonstrated an indirect positive association with formal structure through competencies (IE = 0.407). Similarly, consistent with H3a and H3b, ET competencies were positively associated with the EE’s community (β = .430), and ET attributes again exerted an indirect effect via competencies (IE = 0.340). Finally, in support of H4, EE formal structure and EE community were positively correlated (r = .347), indicating that the structural and relational components of the ecosystem frequently co-occur in schools. Collectively, these findings indicate that teachers’ competencies, such as advocating innovation and seeking resources, represent the more immediate link to both ecosystem components, whereas attributes influence the ecosystem primarily by enabling these competencies.

These findings should be understood within the context of teachers’ professional autonomy in Hong Kong. While the schooling system maintains a relatively centralized curriculum and accountability framework, teachers still possess moderate autonomy in instructional planning, experimentation, and collaboration. This space for discretion allows them to adapt pedagogical strategies, initiate projects, and form partnerships with internal and external stakeholders, including community groups, NGOs, and universities, to advance innovation. However, such autonomy is uneven across schools and often mediated by leadership style, school culture, and resource availability (Kolho, 2024; Kolho et al., 2023). Consequently, teacher agency in Hong Kong reflects a “bounded autonomy” model, where entrepreneurial teachers operate creatively within, rather than outside, institutional constraints. This context helps explain why ET competencies in our study were strongly related to both EE formal structure and community: teachers exercise their entrepreneurial agency by reinterpreting systemic rules and leveraging existing structures to foster sustainable innovation.

Theoretical Implications

First, the result that less experienced teachers had weaker ET competencies suggests that the latter can be learned (Ho et al., 2022), suggesting that teachers may acquire ET competencies as they become more experienced. As advocating innovation and seeking resources are complex skills, teachers may require substantial time to learn them (Gupta, 2021; Ho et al., 2022). Both of these competencies are related to idea generation, implementation, and collaboration with internal and external parties (George et al., 2019; Ho et al., 2021; Shen & Yang, 2022). Their on-the-job socialization may help them learn to relate with other teachers and thereby advance their entrepreneurial ideas (Ho et al., 2022). As teachers gain experience, they not only accumulate a track record of successfully implementing new initiatives and expanding their networks to obtain resources (Benoliel & Schechter, 2017), but also attain organizational and peer legitimacy, enabling them to explore, innovate, and utilize the system more effectively to promote their entrepreneurial pursuits (Boyett & Finlay, 1993). These results are consistent with the view that teacher entrepreneurs neither work against nor for the system; instead, they collaborate with it to obtain legitimacy, a crucial component of school entrepreneurship (Ho et al., 2025). These results suggest that teachers need to secure legitimacy from both the system (structure) and their peers (community) to successfully advance their entrepreneurial endeavors. Future studies can explore how teachers with different years of teaching experience perform entrepreneurial competencies and their efforts to utilize and transform the educational ecosystem.

Second, teachers with greater ET competencies reported more EE formal structure and EE community. This result supports the theoretical notion that actors form and shape the EE environment in schools (Cavallo et al., 2019; Fernandes & Ferreira, 2022; Stam et al., 2021). Unlike Boon et al.’s (2013) study of teachers in the Netherlands showing that their ETs do not align with EE formal structure and act outside of it, our study of teachers in Hong Kong showed that those with greater ET competencies aligned with greater EE formal structure and their possible proactive modifications of it (Ho et al., 2012; Ho et al., 2021; Shen & Yang, 2022). Likewise, the alignment of ET competencies and EE environment is consistent with studies showing that ETs aim to nurture colleagues’ growth by forming a reflective learning community to support and sustain school improvement (Ho et al., 2020; Roundy, 2022; Steidle et al., 2024). These findings highlight the potential role of ETs in creating dynamic, high-quality communities that foster collaboration, retain talent, and sustain relationships through effective leadership (Motoyama & Knowlton, 2017; Spigel et al., 2018; Steidle et al., 2024). Future studies can explore how these dynamics influence student outcomes and possibly reshape innovations to better accommodate and leverage ET leadership in fostering stronger EE.

Third, in line with past studies, our results showed that EE’s formal structure and community were two separate, positively linked, environmental factors in school contexts (Bryant, 2019; Ho & Chen, 2026). This result also suggests that EE formal structure and EE community may influence each other. Actors not only shape or modify both elements, but their intervention might generate synergy between both EE elements, consistent with educational EE studies showing that an EE in a school is an organic system. When researchers explore the influence of EEs in schools, they can scrutinize the dynamic development of an EE’s formal structure and community. Exploring these influences in greater detail can help discern their mechanisms. Specifically, future studies can explore how formal structures and community impact each other, along with how actors in various roles shaping their relations. Additionally, future studies can investigate the specific proactive actions and strategic adaptations that schools implement to develop and sustain EEs (Björklund & Krueger, 2016). Understanding these elements can provide deeper insights into fostering effective school entrepreneurial environments.

Based on the study’s findings, the attributes and competencies of ETs appear indispensable for cultivating EE, which benefits CPI. To actualize their entrepreneurial predispositions, ETs mobilize their entrepreneurial attributes to perform their entrepreneurial competencies. In doing so, they gain legitimacy using their social capital, their legitimacy, their financial resources, and their knowledge resources – which in turn helps them proactively transform their school’s formal and informal culture (EE’s environment) to sustain their innovations. Hence, the ET’s proactive personal predisposition and resultant ET competencies can influence an EE’s environment. Using their competencies, ETs can interact with colleagues to realize their ideas. If their initiative succeeds, their colleagues take ownership of the innovation in their school, thereby advancing and sustaining the entrepreneurial spirit of the school (entrepreneurial ecosystem). In this way, individual entrepreneurial drive morphs into a collective propensity over and above a particular innovation.

Furthermore, although gender and other demographic variables do not significantly relate to other variables in our study of Hong Kong teachers, gender imbalances persist in the representation and participation within many entrepreneurial ecosystems (Moberg, 2021). Therefore, future studies can investigate the development of diverse and inclusive entrepreneurial ecosystems across different educational settings, including potential influences across national contexts and community actors (Steidle et al., 2024). These studies can also examine the structures of EEs, including those that actively promote gender equality and address barriers faced by women and other underrepresented groups in schools.

Practical Implications

Our study has three practical implications. First, as teachers with fewer years of experience often showed less ET competence, schools can formulate and assess policies and procedures to nurture the ET competencies of early career teachers (via mentors, workshops, support groups, etc.) to support school-wide innovation. Second, as teachers with greater ET attributes show greater ET competences, principals can develop and evaluate methods to identify such teachers during job interviews and hire them to create a stronger corps of teachers with ET competencies. Third, principals and other school staff can consider how to revise their formal structures to better support their EE community and cultivate superior EE community processes to improve their formal structure.

Limitations and Future Research

This study’s limitations include its narrowly representative sample and its single snapshot collection of data. Because participants volunteered for a professional development seminar focused on leadership and innovation, they may reflect a subgroup of teachers already predisposed toward entrepreneurial behaviors. This self-selection could inflate mean levels of entrepreneurial attributes; therefore, future research should recruit more heterogeneous samples across schools and contexts to test the robustness of these findings.

While we opted to use a scale more appropriate for the educational context (Ho & Lu, 2024), future research can explore the insights offered by a general, well-structured, entrepreneurship competencies framework (Baggen & Kaffka, 2022). Such studies might enhance our understanding of school teachers’ leadership roles and their influence on fostering an entrepreneurial environment within schools.

Given that the data are cross-sectional and derived from a purposive, self-selected professional development sample, the observed negative association between early-career status (1–3 years) and ET competencies may reflect both competency development with experience and selection processes, such as early-career attrition or differential participation in professional learning. Employing longitudinal designs that track cohorts over time, or utilizing linked administrative retention data, is necessary to differentiate developmental change from survivorship or selection effects.

Conclusion

In conclusion, this study showed that (a) ETs have specific attributes and competencies, (b) ET attributes were linked to ET competencies, and (c) ET competencies were positively aligned with both EE formal structure and community. Further, teachers with less teaching experience reported less ET competency. These findings provide opportunities for researchers to investigate the mechanisms through which teachers contribute to the development of innovative and entrepreneurial teams within EEs. These findings can inform strategies to effectively integrate entrepreneurial thinking and innovative practices within EEs. Pursuing such investigations will contribute to a comprehensive understanding of the underlying mechanisms for promoting innovation and forming entrepreneurial teams.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Chun Sing Maxwell Ho

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Creating Sustainable and Thriving Teams: Teachers’ Driven Entrepreneurial Ecosystem

Abstract

Keywords

Introduction

Theoretical Framework

Theoretical Lens – Entrepreneurial Ecosystem

Actors – ETs

ET Attributes

ET Competencies

Relationship Between Attributes and Competencies

EE Environment – Formal Structure

EE’s Environment – Community

Formal Structure and Community

Hypothetical Framework

Hong Kong Context

Methodology

Sample

Measurements

EE’s Actors – ET

EE’s Environment – Formal Structure and Community

Data Analysis

Factor Analyses

Explanatory Model

Results

Exploratory Factor Analysis (EFA)

Confirmatory Factor Analysis (CFA)

Correlation Analysis

SEM

Discussion

Theoretical Implications

Practical Implications

Limitations and Future Research

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References