How creative self efficacy foster entrepreneurial intention through creative process engagement in entrepreneurial higher education ecosystem

Abstract

Efforts to enhance entrepreneurial intention among students entail a complex learning process. Understanding the function of the entrepreneurial education ecosystem (EEE) based on social interactions, learning demands, and supportive resources is essential. The aim of this study is to elucidate the influence of the EEE on entrepreneurial intention through creative self-efficacy (CSE) and creative process engagement (CPE) in higher education. Using a causal study with a survey utilizing questionnaires on 354 randomly selected students who have undergone entrepreneurship education in private university. Inferential analysis employing covariant structural equation modeling (SEM). Research findings indicate that the design of the EEE, including curriculum, practices, research, culture, and entrepreneurship infrastructure in higher education, enhances CSE. The availability of CSE as a personal resource enables students to effectively meet the demands of entrepreneurial learning and engage in the entrepreneurial learning process in the long term. EEE influences CSE, which in turn fosters engagement in the creative process required to support entrepreneurial intentions among university students. The theoretical implication is study of demand-resources (SDR) expands the understanding of the complexity of interactions between entrepreneurial education demands, resources, and entrepreneurial intentions. Practical implication is focused on the development of EEE and CSE based on the study demand-resources approach for enhancing entrepreneurial intention among individuals. Originalities value is expanding the understanding of the demand-resources (DR) model based on research findings regarding the role of EEE positions as environmental resources on the availability of personal resources, namely CSE, and its influence on CPE and entrepreneurial intention.

Impact statement

This study expands the scope of the JD-R theory within the context of entrepreneurship learning by demonstrating the importance of learning resources as factors shaping psychological meaning for students. To enhance entrepreneurial intention, entrepreneurship education in universities can adopt the study demand resources approach to realize active learning involving students directly in creative activities, business simulations, and entrepreneurial projects to boost entrepreneurial intention.

Keywords:

• Creative process engagement
• entrepreneurial education ecosystem
• creative self-efficacy
• entrepreneurial intention

Reviewing Editor:

• Dr Chris Jones, Economics, Finance & Entrepreneurship, Aston University, Birmingham, United Kingdom of Great Britain and Northern Ireland

Subjects:

• Education - Social Sciences
• School Leadership, Management & Administration
• Educational Research

Introduction

Exploration of the position of creative self-efficacy (CSE) in fostering the growth of entrepreneurial intentions (EI) in higher education is an important things to do, as indicated by Abulela (2024), Green et al. (2024), Jiatong et al. (2021), Mou (2024) and Tantawy et al. (2021). CSE serves as a resource enabling students to engage in a process that demands cognitive and physical burdens, such as learning. While CSE contributes to individual development in learning, as proposed by Tantawy et al. (2021), it has not been thoroughly explored as a construct influencing entrepreneurial thinking and motivating EI, especially in the context of higher education. Ferreira-Neto et al. (2023) add that entrepreneurial intention is a complex concept influenced by numerous factors.

Generally, research findings underscore the importance of understanding cognitive social processes related to relationships. In line with social cognitive theory (Bandura, 1997), CSE focuses on individuals’ beliefs in their ability to perform specific tasks. Miao et al. (2023) explain that CSE refers to an individual’s belief in their ability to generate and implement creative ideas effectively. He et al. (2020) define the level of confidence in an individual’s ability to generate new and original ideas. CSE emphasizes the importance of motivation in creative work and personal creation (Tantawy et al., 2021).

To further understand the mechanism linking CSE and EI, an understanding of the Entrepreneurial Education Ecosystem (EEE) is needed (Reaz, 2022). CSE is related to the social environment, and EEE serves as a social environment supporting CSE. Liu et al. (2021) explain EEE as a form of recognition increasingly vital in the entrepreneurial education process. However, the existence of EEE has not fully received attention as part of the design of entrepreneurship education systems in higher education to enhance entrepreneurial intentions. EEE, as a central component of the University-Based entrepreneurship ecosystem, focuses on entrepreneurial activities directly (Brush, 2014). Knowledge about EEE remains fragmented, although it can be used to build assumptions, drive development, and facilitate the dissemination of entrepreneurial knowledge in universities (Belitski & Heron, 2017).

EEE has the potential to be a resource in the entrepreneurial education process and support CSE in explaining changes in entrepreneurial intention. EEE has evolved to support various "to" and "through" learning activities, focusing on engagement with various actors in the ecosystem to achieve entrepreneurial education goals (O’Brien et al., 2019). Entrepreneurial education plays a crucial role in the entrepreneurial creation process for students, along with the importance of developing students’ entrepreneurial social networks (Maritz et al., 2022). Explaining how these factors interact and how EEE can influence CSE through engagement in the creative process, ultimately enhancing entrepreneurial intention, is crucial for designing strategies for the development of entrepreneurship education ecosystems in higher education.

On the other hand, concerning entrepreneurial intention, Tantawy et al. (2021) explain that creative process engagement (CPE) serves as a potential mediator to expand understanding of the relationship mechanism between CSE and entrepreneurial intention. Tan et al. (2016) state that engagement in the creative process reflects active participation in various stages of the creative process, contributing to the generation of innovative solutions. CPE has been extensively studied in the context of work as a mediating variable for creative performance (Chen et al., 2020; Yuan et al., 2017; W. Zhang et al., 2020). In the context of entrepreneurship education, CPE is part of the entrepreneurial learning process to foster entrepreneurial intentions. The mechanism of how CPE acts as a mediating variable for CSE and entrepreneurial intention requires further study. From the JD-R perspective, as stated by Bakker et al. (2023) and Schaufeli (2015), engagement requires personal resources such as self-efficacy and results in effective performance output. The application of the Job Demands-Resources (JD-R) framework to the university context requires further study (Lesener et al., 2020), where learning is considered psychologically as work. Most research has tested the JD-R model in the workplace environment, but limited research has been conducted to assess its validity in the education environment, especially in more specific contexts such as engagement in creative activities for entrepreneurship (Liu, 2023). The JD-R model provides a comprehensive understanding of the complex interactions between educational demands, resources, and students.

Therefore, empirical studies are needed to explain the positions of EEE and CPE in the relationship between CSE and entrepreneurial intention in entrepreneurship education, such as in Indonesia. Explaining the relationship between variables based on a perspective that places EEE as a resource (Study Demand Resources) to enhance CSE through social learning processes in higher education will help understand how to design entrepreneurship education by integrating EEE with classroom learning.

Research contribution involves expanding perspectives based on resources to support understanding the effectiveness of entrepreneurship education implementation in shaping CSE and processes to enhance entrepreneurial intention in the past, understanding the realities in learning and interactions to achieve higher entrepreneurial intentions, and shaping a vision for entrepreneurship education in higher education. The research aim is to explain the influence of the EEE on Entrepreneurial Intention through CSE and CPE in Indonesia.

Theoretical background

Creative self-efficacy (CSE)

CSE encompasses an individual’s confidence in their skills and willingness to take risks (Newman et al., 2018). CSE describes an individual’s overall belief in their abilities in the workplace, including learning outcomes and processes. CSEis a specific type of self-efficacy that refers to an individual’s perception that they can achieve creative outcomes (Tantawy et al., 2021). CSE is an extension of Bandura’s broader self-efficacy concept, defined as the belief in one’s ability to produce creative outcomes (Bicer et al., 2020). CSE refers to an individual’s belief in their ability to tackle problems that require creative and functional thinking (Yang et al., 2020). It is a crucial factor as a prerequisite for creating creative works or ideas (Huang et al., 2020).

This personal attribute is defined as self-judgment or self-assessment of one’s creative abilities. This concept first emerged within Bandura’s self-efficacy framework. In the contexts of work and education, CSE is deemed crucial for individual creative performance (Lin & Wang, 2021; Yang & Hsu, 2020). Stolz et al. (2022) emphasize the significant role of CSE in developing individual creativity, acting as the individual’s belief in their ability to creatively accomplish specific tasks within a given context and level.

Creative process engagement

Student engagement in education is a process. Engagement is characterized by high energy levels and a strong identification with the work. Bakker (2017) and Schaufeli et al. (2002) define engagement as "a positive, satisfying state of mind related to work, marked by vigor, dedication, and absorption." CPE involves construction and development, information searching and encoding, and generation of alternative ideas (Zhang et al., 2020; Zhang & Bartol, 2010). The concept of student engagement emphasizes the active, participative, and affective aspects of students’ involvement in the learning process, recognizing that it involves more than mere attendance and entails a deeper connection with the educational experience (Bilro & Loureiro, 2020). Tantawy et al. (2021) explain that CPE is defined as an individual’s involvement in methods or processes relevant to creativity, including (1) problem identification, (2) information searching and encoding, and (3) generation of ideas and alternatives.

Entrepreneurial education ecosystem

The entrepreneurial ecosystem is formed by stakeholders, with their interactions focused on the educational process (Wraae & Thomsen, 2018). The entrepreneurship education ecosystem in higher education is a complex system (Wang et al., 2021). EEE encompasses entrepreneurship curriculum, entrepreneurship practice, entrepreneurship research, entrepreneurship culture, and entrepreneurship infrastructure (Brush, 2014; Wang et al., 2021). EEE refers to an environment involving various elements and components that interact to support the development of entrepreneurship among students or participants in higher education. This ecosystem includes numerous factors and elements contributing to instilling entrepreneurial spirit, skill development, and fostering entrepreneurial culture in the university environment, such as entrepreneurship curriculum, entrepreneurship practice, entrepreneurship research, entrepreneurship culture, and entrepreneurship infrastructure.

Belitski and Heron (2017) describe the pillars of EEE as crucial for knowledge exchange and commercialization by scientists and entrepreneurs. Liu et al. (2021) add that EEE can be divided into two categories. First, as a subsystem of the broader entrepreneurship ecosystem, with entrepreneurship education as a subsystem within the larger entrepreneurship ecosystem. Second, universities play a central role in the development of the global economy by providing infrastructure, resources, and facilities to cultivate entrepreneurial communities.

Entrepreneurial intention

Entrepreneurial intention is a behavioral tendency. Generally, intention is influenced by three factors in the Theory of Planned Behavior (TPB) concept, namely attitude, subjective norm, and self-efficacy (Al-Mamary & Alraja, 2022; Martins et al., 2022; Tseng et al., 2022). In the process of entrepreneurship education in higher education, intention is influenced by the educational process, both through direct interactions in learning and through interactions with the surrounding environment. Pascucci et al. (2022) expand the concept of entrepreneurial intention, not only encompassing the desire for personal economic success but also emphasizing awareness of social and environmental responsibilities in entrepreneurial activities. This intention not only includes a desire to achieve personal economic goals but also to create organizations that are rich, dynamic, and innovative, capable of generating wealth with a constructive approach to society.

Social learning theory

The foundation for understanding CSE lies in the Social Cognitive Theory (SCT), which draws from the work of various theorists. SCT differs from other learning theories due to its focus on the central role played by cognition in the dynamic triadic interaction between oneself, the environment, and behavior (Newman et al., 2018; Tantawy et al., 2021). One expert who developed SCT is Bandura (1997). Social Learning Theory has made a significant contribution to our understanding of how individuals learn from the social environment and how behavior is influenced by observation, imitation, and reinforcement.

Job demands-resources (JD-R) model

The Job Demands-Resources (JD-R) theory is a framework used to understand, explain, and predict the influence of various workplace factors on well-being and performance (Bakker et al., 2004; Bakker & Demerouti, 2014). This model goes beyond mechanistic views by highlighting the importance of personal resources as predictors of motivation and demonstrating that personal resources can protect against the negative effects of job demands, adding a dynamic element to the relationship between job characteristics and individuals (Bakker et al., 2019, 2022). On the other hand, individuals are motivated to preserve their resources and will attempt to expand these resources if possible (Bakker & Demerouti, 2017). In a more specific context, Jagodics and Szabó (2022) explain JD-R as a comprehensive framework to elucidate how students interact with their work as learners. The JD-R model has various applications related to the educational context (Hodge et al., 2017; Martin et al., 2023; Pachler et al., 2019; Siddiqi, 2019). Liu (2023) describe how the application of JD-R explains engagement and predicts student performance, particularly in entrepreneurship. (Lesener et al., 2020; van der Ross et al., 2022) developed a framework based on JD-R to explain the health and well-being of students, namely SD-R (Study Demand Resources).

Hypotheses development

Entrepreneurial education ecosystems influence CSE through CPE

The development of self-efficacy is a function of self-assessment and social construction, interacting with the social environment (Bandura, 1997; Elnadi & Gheith, 2021). EEE can influence CSE. EEE enhances individuals’ access to educational opportunities, training, and resources for solving entrepreneurial problems, thereby promoting CSE and engagement in the creative process. EEE expands networks, sharpens collaborations, and thus reinforces the positive impact of CSE on engagement in the creative process. The EEE aims to create an environment that stimulates the development of an entrepreneurial mindset, provides practical knowledge, and empowers students to become successful entrepreneurs (Wang et al., 2021).

Ha1: Entrepreneurial education ecosystem influences creative self-efficacy.

Entrepreneurial education ecosystem influences CPE

The EEE serves as an environmental resource that facilitates the exchange of ideas and enhances engagement in the creative process. EEE influences individuals to participate in creative engagement processes, necessitating personal resource support to encourage student engagement in creative processes. In general, resources promote engagement (Bakker et al., 2004, 2023; Bakker & Demerouti, 2017). Study Demand Resources drive engagement (Lesener et al., 2020). Liu et al. (2021) emphasize that entrepreneurial education programs are concrete manifestations within the EEE. As a resource, EEE contains these programs, disseminating entrepreneurial skills, knowledge, guidance, assistance, and information to various students. The JD-R model evolves by incorporating the individual’s role in modifying the impact of job demands and resources on motivation and energy, through the support of environmental resources that promote high engagement, including specific processes such as creativity (Bakker & de Vries, 2021; Demerouti et al., 2019).

Ha2: Entrepreneurial education ecosystem influences creative process engagement.

Creative self-efficacy mediates the influence of EEE on CPE

Creative self-efficacy is viewed as the result and interaction of individual efforts with contextual factors that serve as long-term resources for individual engagement in their work, ultimately enhancing performance. Individuals with high CSE can perceive opportunities rather than obstacles, persisting in the face of challenging situations to create value (Tantawy et al., 2021). EEE enables students to develop individual strategies in the learning process to creatively understand problems and generate new ideas as solutions. Students strive to overcome the unfavorable effects of learning characteristics, aiming to maximize the beneficial effects of learning by taking cognitive and mental advantages and improving the engagement process. EEE, as a resource, facilitates two psychological processes that play a role in reducing the health impairment process, indicating that high job demands or jobs with chronic demands can deplete students’ mental and physical resources. This can lead to a decrease in self-efficacy. EEE ensures the motivational process, resulting in high work engagement. The proposed hypothesis is

Ha3: Creative Self-efficacy mediates the influence of entrepreneurial education ecosystem on creative process engagement intention.

Creative self-efficacy has an influence on entrepreneurial intention

Self-efficacy formed through entrepreneurial education processes has a significant effect on entrepreneurial intention (H. Liu et al., 2021; Wu & Tian, 2022). Liu (2023) and Maheshwari and Kha (2022) emphasize the importance of self-efficacy in efforts to foster high entrepreneurial intentions. Kumar and Shukla (2022) assert that self-efficacy has been widely used in entrepreneurship research to predict and explain entrepreneurial intentions and behaviors. Creativity self-efficacy serves as a resource for engagement in specific activities. Ferreira-Neto et al. (2023) argue that creativity self-efficacy cannot be separated from the process of forming entrepreneurial intentions.

Ha4: Creative self-efficacy influences entrepreneurial intention.

Creative self-efficacy has an influence on entrepreneurial intention, both directly and through CPE

The JD-R model recognizes the role of personal resources, including positive self-evaluation in work, supporting the motivational process and health impairment process that drive high engagement (Bakker et al., 2023; Schaufeli, 2017). Personal resources have a positive relationship with engagement, including in education (Hodge et al., 2017). CSE can foster enthusiasm, dedication, and absorption, prompting individuals to start their own businesses. CSE encourages creative engagement and enhances entrepreneurial intentions. Lesener et al. (2020) state that, similar to work, students face two crucial processes in their activities: health impairment process and motivational process. Both require the support of resources and personal resources, such as CSE acquired through education, to enhance student engagement and orientation toward entrepreneurship choices. Tantawy et al. (2021) affirm that CSE through entrepreneurship courses can contribute to higher levels of CPE, ultimately influencing entrepreneurial intentions. The proposed model in this research shown in Figure 1.

Figure 1. Proposed model.

Ha5: Creative self-efficacy influences entrepreneurial intention through creative process engagement.

Entrepreneurial intention is influenced by intrinsic motivational processes and health impairment processes driven by personal resources such as CSE within a supportive EEE. CSE also mediates the ecosystem’s function in supporting CPE, ultimately enhancing entrepreneurial intention.

Research method

In accordance with Sekaran and Bougie (2016), this study employs the hypothetico-deductive method. This method provides a systematic approach useful for generating knowledge to solve basic and managerial problems. The research design is conducted by surveying 354 randomly selected students in West Java and Banten. The survey is conducted with a one-shot study based on considerations of efficiency, data density, cost support, and time while ensuring that no changes or trends in entrepreneurial intentions are found over time during the data collection process. The data collection process utilized a questionnaire with closed-ended questions, administered through Google Form. Questionnaire distribution took place over a 2-week period, resulting in a dataset of 354 responses out of the 800 questionnaires distributed.

Entrepreneurial education ecosystem was measured based on Wang et al. (2021), including: (1) Entrepreneurship Curriculum, providing subjects and educational programs covering aspects such as business management, business planning, and other practical skills. (2) Entrepreneurship Practice, offering opportunities for students to directly experience entrepreneurial activities through projects, internships, or simulations. (3) Entrepreneurship Research. (4) Entrepreneurship Culture. (5) Entrepreneurship Infrastructure, encompassing facilities and resources supporting entrepreneurship activities, including business incubators, innovation centers, and other facilities. The indicators used were highly adequate, showing good fit with the data and the theory used, with Goodness of Fit (GOF) values of CMIN/DF = 2.905, GFI = 0.937, CFI = 0.977, PNFI = 0.78, RMSEA = 0.073, and SRMR = 0.020.

Creative self-efficacy was measured based on Tantawy et al. (2021), consisting of three statements: (1) Self-Efficacy for Generating Ideas (SEGI), including the belief that one can actively create new and innovative ideas. (2) Self-Efficacy for Recognizing Opportunities (SERO), covering the belief that one can identify situations or problems that can be creatively solved. (3) Self-Efficacy for Benefiting Others (SEBO), the belief that creative ideas generated by individuals have the potential to provide positive benefits. The indicators used were highly adequate, with Goodness of Fit (GOF) values of CMIN/DF = 2.59, GFI = 0.937, CFI = 0.953, PNFI = 0.714, RMSEA = 0.076, and SRMR = 0.024.

Creative process engagement was measured based on Tantawy et al. (2021), with dimensions such as problem identification, information searching and encoding, and idea generation, among others. The indicators used were highly adequate, showing good fit with the data and the theory used, with Goodness of Fit (GOF) values of CMIN/DF = 1.558, GFI = 0.966, CFI = 0.990, PNFI = 0.78, RMSEA = 0.040, and SRMR = 0.016.

Entrepreneurial intention was measured based on Pascucci et al. (2022), supported by Azim and Islam (2022) consisting of 8 statement items. Responses to closed-ended questions in the questionnaire were expressed through a rating scale of 1-5, ranging from "strongly disagree" to "strongly agree." Data analysis was conducted using Structural Equation Modeling (SEM) with Maximum Likelihood Estimation. Model-data fit was evaluated using Goodness of Fit (GOF) indicators. Additionally, steps were taken to evaluate and improve interpretation, and hypothesis testing was performed to ensure that the obtained results could be accurately interpreted according to the research objectives.

Results

The description of the research variables is as follows (see Table 1).

Table 1. Description statistic.

Variable	Mean	Standard deviation
Entrepreneurial Education Ecosystem	4.0	0.74
Creative Self-Efficacy	3.9	0.65
Creative Process Engagement	3.8	0.67
Entrepreneurial Intention	3.8	0.70

Source: Data processing (2023).

Based on descriptive analysis, the level of design of the EEE is quite adequate, with several important aspects fulfilled, although improvement is needed based on a standard deviation of 0.74. It would be better to lower this standard deviation and enhance entrepreneurship methodology to address the increasingly specific literature developments in entrepreneurship according to business fields. Entrepreneurship curriculum requires continuous adjustment to have a high link and match with entrepreneurship practices. The average CSE, at 3.9, falls under the adequate category on a scale of 1 to 5. Data indicates that CPE and entrepreneurial intention are sufficiently adequate, with averages of 3.8. However, given various changes in post-graduation student orientations, with more opting for the job market, the high level of Entrepreneurial Intention requires reinforcement from various aspects, particularly family support and a more adequate entrepreneurial ecosystem in society. The results of the model test shown in Figure 2.

Figure 2. The results of the standardized regression weight test for the research model.

The results of the Confirmatory Factor Analysis (CFA) testing indicate that the observed variables can reflect their respective latent variables. The factor weight test results show that each observed variable can explain changes in its respective latent variable. The test results indicate that each factor’s weight is accepted, and the relationships between the constructed variables in the study emphasize the importance of the organizational resources’ position, such as distributive leadership. The success of performance is based on motivational and health impairment processes.

The standardized regression weight values for the latent variable EEE range from 0.770 to 0.845. The factor weight values for the observed variable CSE range from 0.677 to 0.847. The factor weight values for the observed variable CPE range from 0.740 to 0.791. The factor weight values for the observed variable entrepreneurial intention range from 0.770 to 0.810. Each factor weight value for the observed variable is acceptable for explaining the latent variable. The AVE, composite reliability, and discriminant validity test results are as follows (see Table 2).

Table 2. The test results for AVE, composite reliability, and discriminant validity.

Variables	AVE	Composite reliability	1	2	3	4
Entrepreneurial Education Ecosystem	0.674	0.956
Creative Self-Efficacy	0.589	0.951	0.158
Creative Process Engagement	0.588	0.947	0.137	0.109
Entrepreneurial Intention	0.624	0.948	0.238	0.23	0.227

According Table 2, the AVE values for the EEE, CSE, CPE, and entrepreneurial intention are 67.4, 58.9, 58.8, and 62.4%, respectively. These results indicate that the observed variable constructs in this study have a sufficiently good level of validity, although there is a slight difference in the validity levels between these constructs. Adequate validity suggests that these measurements can be relied upon to evaluate identification characteristics in election organizers. The composite reliability values are all above 0.70, with the highest being for EEE at 0.956 and the lowest for CPE at 0.947. The discriminant validity testing results show that each observed variable can distinguish the latent variables well, and the discriminant validity is acceptable.

The normality test results, using the Kolmogorov-Smirnov method with a 95% confidence level, indicate that our data has a normal distribution. This is evidenced by the P-value of 0.505, which is greater than 0.05. No issues were found in identifying the model according to the tool used. Assumptions about multicollinearity (strong relationships between predictors) and singularity (linear dependence issues) are met. In the multivariate extreme data test, with a significance level of P less than 0.001, the results show that the Mahalanobis D-squared values in the AMOS calculation are lower than the chi-square values at a significance level of 0.001. This indicates the absence of multivariate outliers in the data. Next is the testing of the goodness of fit for the model with the following results (see Table 3).

Table 3. Model test results.

GOF parameters	Stage first	Cut of value	Conclusion
Absolute fit measure:
P-value (Sig.)	0.00	≥ 0.05	Moderate
CMIN	1.251	≤ 2.00	Fit
GFI (Goodness of Fit)	0.894	≥ 0.9	Moderate Fit
RMSEA (Root Mean square Error of Approximation)	0.027	0.08	Fit
Incremental fit measure:
AGFI (Adjusted Goodness of Fit Index)	0.881	≥ 0.90	Moderate Fit
CFI (Comparative Fit Index)	0.983	≥ 0.95	Fit
Incremental Fit Index (IFI)	0.983	≥ 0.95	Fit
Relative Fit Index (RFI)	0.915	≥ 0.95	Moderate Fit
Parsimonious fit measure:
PNFI (Parsimonious Normed Fit Index)	0.864	0.6	Fit
PGFI (Parsimonious Goodness of Fit Index)	0.797	0.9	Moderate

Source: Data processing (2023).

According to the test results, it is evident that the goodness of fit criteria, such as absolute fit indices, incremental fit indices, and parsimony indices, have been met. The data collected in the field aligns with the constructed research model.

Subsequently, hypothesis testing is based on the data analysis results, yielding the following outcomes (see Table 4).

Table 4. Causality test results regression weight.

Path			Estimate	S.E	C.R	P	Standarized regression weight
CSE	<---	EEE	0.304	0.041	7421	***	0.446
CPE	<---	CSE	0.335	0.08	4202	***	0.265
CPE	<---	EEE	0.16	0.052	3087	0.002	0.186
Intention	<---	CPE	0.362	0.05	7203	***	0.342
Intention	<---	CSE	0.776	0.081	9631	***	0.581

Source: Regression weight Data processing (2023); Note. *** = 0.000.

The test results indicate a significant relationship between variables. The critical ratio values fall within the region of accepting the one-sided hypothesis (>1.95). Additionally, the P value < 0.05 suggests a significant relationship for each variable. Next is to examine the mediating variables, as shown in Table 5.

Table 5. The results of the mediation test.

Path					Estimate
CPE	<---	CSE	<---	EEE	0.118
Intention	<---	CSE	<---	EEE	0.363
Intention	<---	CPE	<---	CSE	0.091

Source: The data processing results using Structural Equation Modeling (SEM).

The test results indicate that each mediator variable partially mediates the respective exogenous variable. CSE partially mediates the influence of EEE on CPE with an estimate of 0.118. CSE also partially mediates the influence of EEE on Entrepreneurial Intention with an estimate of 0.363. CPE partially mediates the influence of CSE on Entrepreneurial Intention with an estimate of 0.091. The next step is to test the hypotheses (see Table 6).

Table 6. The hypothesis test results Standarized regression weight.

Hypothesis	Estimate	Conclusion
Entrepreneurial education ecosystem influences creative self-efficacy	0.446	Supported
Entrepreneurial education ecosystem influences creative process engagement	0.186	Supported
Creative self-efficacy mediates the influence of entrepreneurial education ecosystem on creative process engagement	0.363	Supported
Creative self-efficacy influences entrepreneurial intention	0.581	Supported
Creative self-efficacy influences entrepreneurial intention through creative process engagement	0.091	Supported

Source: Results of standardized regression weight data analysis (2023).

The study results indicate that Ha1, Ha2, Ha3, Ha4, Ha5 are supported, consistent with previous studies. The difference in this research lies in the role of EEE and CSE as resources that ensure CPE.

Discussion

Creative self-efficacy as social learning process

The study highlights the importance of CSE in the learning process, even in specific contexts such as entrepreneurship education. Viewed from the perspective of social cognitive theory (Abulela, 2024; Bandura, 1997), CSE entails an individual’s belief in their ability to generate new and useful ideas, comprising two main components: Creative Thinking Self-Efficacy and Performance Self-Efficacy (CPSE). In contrast to previous studies, this study focuses on CSE with its main dimensions being creative thinking and the willingness to take risks by choosing to become an entrepreneur. CSE, as suggested by Bakker et al. (2023), Bicer et al. (2020), Newman et al. (2018) and Tantawy et al. (2021), is a personal resource that continues to evolve as individuals interact more with entrepreneurship curricula designed to meet the needs of students to become entrepreneurs. These curricula provide opportunities for entrepreneurship practice, encourage various interactions between students and entrepreneurship research, and foster an entrepreneurial culture. Furthermore, universities provide entrepreneurship infrastructure, such as business incubators and access to innovation, to support creativity in entrepreneurship learning.

The study results indicate that the EEE supports the engagement process through CSE. EEE significantly increases students’ efficacy in creative thinking. This influence can be explained based on students’ involvement in the creative process and the opportunities given to them to create problem-solving solutions until the end. This creative process is considered a meaningful experience by students, leading to the intention to become entrepreneurs, in line with Lin and Wang (2021). The interaction between individual CSE and EEE creates a unique experience that stimulates students’ confidence to actively engage in creating multiple solutions to a problem. The EEE model provides a comprehensive framework to analyze and understand various dimensions contributing to the effectiveness and development of the EEE. Each dimension plays a crucial role in shaping the overall entrepreneurial learning experience and nurturing an environment supporting the intention to become an entrepreneur. The EEE serves as a resource for informal and non-formal entrepreneurial learning.

Creative self-efficacy has a positive influence on entrepreneurial intention. CSE grows and develops based on student interactions in the formal learning process at the university. In this learning process, CSE acts as a personal resource that has the capacity to enhance CPE in the long run. CSE encourages CPE, ultimately leading to an increase in entrepreneurial intentions among students. Consistent with previous studies, CSE serves as a foundational factor.

Creative self-efficacy, as a personal resource, ensures that the motivational and health impairment processes support entrepreneurial intentions. Together, they form a unity that enhances students’ cognitive understanding of each stage of the process to become entrepreneurs. The expected entrepreneurs from higher education are those described by Pascucci et al. (2022), who possess social and environmental awareness realized through business. The process to realize this intention requires the support of personal and environmental resources in line with various current issues. The concept of entrepreneurial intention cannot be separated from the context where sustained demands seem deeper and more authentic than ordinary entrepreneurial intentions.

Creative Process Engagement (CPE) mediates the impact of CSE on entrepreneurial intention. CPE provides experiences while building mental capabilities to solve both structured and unstructured problems using different processes. CPE offers a learning experience that instills enthusiasm among students for addressing problems and engaging in entrepreneurship. In line with Tantawy et al. (2021), it is emphasized that internal and environmental resource support is necessary to foster engagement in identifying both structured and unstructured problems, searching and encoding information used as a reference for problem-solving, and generating ideas and alternatives based on various considerations, whether theoretical or empirical.

Consistent with previous studies, the learning resources (meaning) from the social environment such as the EEE have a strong relationship with engagement, followed by the availability of personal resources, namely CSE, which reduces learning demands, ensuring high engagement. Students perceive this engagement as a challenge leading to the entrepreneurial process, aligning with van der Ross et al. (2022). This study provides insights into how CSE can influence the intention to become an entrepreneur through the mechanisms of engagement in creativity supported by EEE, as well as directly. This contribution has implications for mechanisms and processes to encourage entrepreneurial intentions among university students. The availability of individual and ecosystem resources ensures CPE, ultimately influencing entrepreneurial intention. The research findings broaden our understanding that learning resources protect against the negative effects of learning demands, adding a dynamic element to the interaction between individuals and EEE, in line with (Bakker et al., 2019, 2022).

Entrepreneurial education ecosystem as environmental resources for engagement

In line with the resource perspective as outlined in the JD-R theory (Bakker et al., 2023; Schaufeli, 2017), creative engagement in entrepreneurship learning demands the availability of personal resources to generate positive outputs. In the context of entrepreneurship education in higher education, the EEE serves not only as an environmental resource that directly ensures creative engagement but also can foster CSE as a personal resource that ensures long-term involvement. The confirmed position of EEE as a resource aligns with Lesener et al. (2020) and van der Ross et al. (2022), who discuss demand resource studies. EEE serves as an environmental resource for students to actively engage in the creative process, guiding them toward higher entrepreneurial intentions. At a macro level, EEE is not just a subsystem of the entrepreneurial ecosystem in general; it plays a central role in higher education in the development of the global economy by providing infrastructure, resources, and facilities to cultivate sustainable entrepreneurial communities. In the context of this study, EEE serves as a short-term resource for students for CPE at the individual level.

The EEE primarily operates on a short-term basis in supporting engagement; therefore, mechanisms to realize engagement leading to high entrepreneurial intention involve fostering personal resources. As suggested in the JD-R theory, personal resources have a longer-term impact on driving engagement compared to non-personal resources. EEE influences CSE and creative process management. Each variable plays a role in increasing entrepreneurial intention. The EEE influences entrepreneurial intention through CPE. Aligned with Wang et al. (2021), the components of the EEE form a unified system in the governance of educational provision that supports both formal and non-formal processes of entrepreneurial education. EEE reduces pressure and expands the space for creativity. The EEE ensures CPE in groups of students with both low and moderate levels of CSE, as emphasized by Liu et al. (2021). The EEE is depicted as a complex and dynamic system, confirming its role as a resource for active student engagement in the creative process.

The interaction between students and the EEE is described as a process that supports independent learning, where students optimize EEE as a learning resource. In line with van der Ross et al. (2022) and Lesener et al. (2020). On the other hand, EEE ensures a reduction in processes that hinder student engagement in creativity, such as mental pressure and cognitive load. Health impairment processes decrease, while motivational processes increase. EEE fulfills various needs necessary for involvement in the CPE.

Conclusion

CSE serves as the key to ensuring long-term CPE. The existence of CSE requires environmental resources, namely The EEE, for its formation through social learning processes. The EEE serves as a learning resource (meaning) that promotes the enhancement of personal resources, guaranteeing well-being in CPE. Ultimately, EEE continues to play a significant role in supporting the enhancement of entrepreneurial intention through various mechanisms, both directly and indirectly. EEE influences CSE and CPE, and all three function as a unified entity that enhances students’ cognitive understanding of the stages in becoming entrepreneurs. EEE serves not only as a resource for informal and non-formal entrepreneurial learning but also centrally provides individual resources as long-term assets necessary to support the process of creative engagement in entrepreneurial activities through CSE. CSE has a positive influence on entrepreneurial intention, and CPE mediates the relationship between CSE and entrepreneurial intention. The availability of individual and ecosystem resources ensures CPE, which, in turn, influences entrepreneurial intention.

Theoretical implications

This study expands the scope of the JD-R theory within the context of entrepreneurship learning by demonstrating the importance of learning resources as factors shaping psychological meaning for students. Additionally, it highlights personal resource factors that influence student engagement in the creative process and entrepreneurial intention, namely CSE. CSE holds a crucial position as it can influence the intention to undertake entrepreneurship through the mechanism of engagement in creativity supported by the EEE. The EEE is designed as a social entrepreneurship learning process for students, comprising a curriculum tailored to the field, meaningful practical experiences, entrepreneurship research to enhance methodological skills in seeking entrepreneurial knowledge, entrepreneurial culture, and infrastructure. The SD-R developed based on several propositions about personal and environmental resources opens up a comprehensive understanding of the complexity of interactions between educational demands, resources, and entrepreneurial intentions. By identifying the vital role of resources, this model can assist in designing an EEE that supports CSE, CPE, and entrepreneurial intention.

Practical implications

Practically, to enhance entrepreneurial intention, entrepreneurship education in universities can adopt the study demand resources approach to realize active learning involving students directly in creative activities, business simulations, and entrepreneurial projects to boost entrepreneurial intention. CSE can be strengthened through instructional design that promotes high self-efficacy and engagement in creativity. This process involves practical projects, innovative challenges, and a collaborative learning environment. CSE acts as a positive predictor of Entrepreneurial Intention. By reinforcing CSE through entrepreneurship education interventions, the enhancement of students’ intention to undertake entrepreneurship becomes higher. EEE and CSE serve as resources to support entrepreneurial intention in universities. Understanding the role of CSE and how EEE can support it as a long-term resource provides valuable guidance for designing EEE to enhance the creative engagement process and increase entrepreneurial intention. Focus on developing EEE and CSE based on SD-R (Study Demand Resources) such as experiences, curriculum, and entrepreneurial culture, including leadership. Resources are expected to ensure the healthy and sustainable development of increased entrepreneurial intention.

Limitations and further research

This research was conducted in the regions of West Java and Banten, so the results may not be directly applicable to the student population in other regions or different contexts, especially in universities with a high focus on entrepreneurial education. The data collected through self-reporting, where students may experience bias, as respondents might tend to provide answers considered desirable rather than truthful responses. Therefore, to enhance the external validity of the study, it is recommended to replicate this study in different geographical areas or among student populations with different characteristics. Future longitudinal research is suggested, with periodic data collection to provide a better understanding of the development of entrepreneurial attitudes and intentions, as well as entrepreneurial behavior. Further research could consider contextual factors that may influence entrepreneurial intentions, such as regional economic conditions or family support as resources for realizing entrepreneurial intentions.

Author’s contributions

Conception and design, or analysis and interpretation of the data: AW, DH; The drafting of the paper, revising it critically for intellectual content: MYA; The final approval of the version to be published: SZ; All authors agree to be accountable for all aspects of the work.

Ethics statement

The procedures used in this study adhere to the tenets of the Declaration of Helsinki. Ethics approval was obtained from the Ethics Committee of Telkom University. In addition, Participants in this study were informed in detail about the study’s purpose, procedures, potential risks, and benefits. Each participant provided written consent before participating in the study. Participant data’s Privacy and confidentiality are fully guaranteed per applicable regulations.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, AW, upon reasonable request.

Additional information

Funding

No funding was received.