Content area
This study aims to examine the key drivers influencing the digital entrepreneurial intention (DEI) of business students regarded as potential entrepreneurs. Using the EEM theory, the practical implications of the study are based on data collected from 400 business students at ten private universities in Bangladesh. To analyze the proposed hypotheses, a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was used. The results show that digital entrepreneurial education (DEE) enhances digital competency (DC) and has a positive influence on digital entrepreneurial intention (DEI). In addition, DC has a positive effect on DEI and plays a mediating role in the relationship between DEE and DEI. Our results emphasize the importance of digital competency as a mediator between digital entrepreneurial education and intention. The study's cross-sectional design limits causal inferences. The focus on business students may also affect the generalizability of the findings. Future research could benefit from longitudinal studies and more diverse samples, including cross-country comparisons to validate the outcomes in different contexts.
This study aims to examine the key drivers influencing the digital entrepreneurial intention (DEI) of business students regarded as potential entrepreneurs. Using the EEM theory, the practical implications of the study are based on data collected from 400 business students at ten private universities in Bangladesh. To analyze the proposed hypotheses, a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was used. The results show that digital entrepreneurial education (DEE) enhances digital competency (DC) and has a positive influence on digital entrepreneurial intention (DEI). In addition, DC has a positive effect on DEI and plays a mediating role in the relationship between DEE and DEI. Our results emphasize the importance of digital competency as a mediator between digital entrepreneurial education and intention. The study's cross-sectional design limits causal inferences. The focus on business students may also affect the generalizability of the findings. Future research could benefit from longitudinal studies and more diverse samples, including cross-country comparisons to validate the outcomes in different contexts.
Keywords: digital entrepreneurial intention, digital entrepreneurial education, digital competency, entrepreneurial event model, PLS-SEM
INTRODUCTION
The rapid advancement and adoption of digital technology have fundamentally reshaped the global landscape, influencing every facet of human life in both expected and unexpected manners. As the digital revolution accelerates, businesses worldwide are compelled to transform their methods of production and marketing of goods and services. Consequently, industries are revisiting and refining the traditional strategies they once relied on to compete in the market. As the business world undergoes a paradigm shift toward digitalization, entrepreneurs are increasingly motivated to utilize digital tools to bring their ideas to life. They also find it easier to adapt to a market that is increasingly focused on technology. The widespread use of digital tools by entrepreneurs has led to the emergence of a unique form of entrepreneurship known as digital entrepreneurship (DE), which differs from conventional entrepreneurship by integrating and heavily relying on modern technologies. DE is still largely unexplored despite its growing prominence in the tech-driven entrepreneurial environment. In particular, advancing this field requires understanding the entrepreneurial intention and the elements that induce engagement with DE. Thus, digital entrepreneurial intention (DEI), an individual's motivation and willingness to initiate and develop digital-based ventures (Elnadi & Gheith, 2023), has emerged as a key research area in understanding individuals' propensity to engage in DE (Depaoli et al., 2020; Duong et al., 2024a; Vu et al., 2024).
Through the adoption of digital technologies, DEI anticipates that people will be more willing and ready to step into business ventures that are managed and operated virtually. While prior studies have identified DEI as a crucial component of the literature on digital entrepreneurship (Nguyen & Nguyen, 2024), little research has explored how tech-driven entrepreneurship education (Galvao et al., 2018) can influence people's digital entrepreneurial intentions and provide them with the necessary skills to succeed in the digital entrepreneurial landscape.
A paradigm shifts in entrepreneurship education occurred due to the rapid advancement of technologies (Sulistianingsih, 2023; Kumar et al., 2023). Therefore, researchers have emphasized that digital entrepreneurship education (DEE) is a crucial learning approach that aims to equip individuals with the skills, knowledge, and abilities necessary to succeed in the digital business sphere (Rodrigues, 2022; Sitaridis & Kitsios, 2024). Due to its tech-oriented, unique character, DEE looks different from other conventional entrepreneurship pedagogies. That is why the focus of DEE on digital applications in business is more comprehensive than the focus of other contemporary entrepreneurship education approaches (Vu et al., 2024; Duong et al., 2024b; Wang et al., 2019). Due to its emphasis on digital business models, DEE is regarded as crucial for cultivating the entrepreneurial mindset necessary for recognizing and leveraging digital business opportunities (Nguyen & Nguyen, 2024; Vu et al., 2024). Under these circumstances, the question that needs to be answered is, "Does DEE positively affect DEI-technology-driven entrepreneurial intentions?"
As digitalization advances, the importance of developing digital skills through specialized educational programs is becoming increasingly pertinent in the emerging digital entrepreneurship landscape (Ghosh et al., 2022; Bican & Brem, 2020). In this landscape, recent studies (Ngoasong, 2018; Triyono et al., 2023) have brought up the necessity of digital competency (DEC)-an individual's potential to effectively utilize digital platforms to create, manage, and scale entrepreneurial ventures (Primario et al., 2022). However, while entrepreneurship digital education has been extensively researched, its integration with digital competencies remains insufficiently explored. Therefore, the role of DEC in navigating the relationships between DEE and DEI still demands comprehensive investigation. Building upon this framework, the study also aims to investigate two other critical questions: "Does DEE positively affect DEC?" And "in the DEE-DEI connection, does DEC serve as a mediator?"
Drawing on the existing literature on digital entrepreneurship and the Entrepreneurial Event Model (EEM), which outlines how perceived desirability, feasibility, and propensity to act influence digital entrepreneurship (Shapero & Sokol, 1982), this study intends to examine the aforementioned questions. By examining these questions, this study makes three significant contributions to the digital entrepreneurship literature. First, it contributes to the body of digital entrepreneurship literature by examining digital entrepreneurial pedagogy and its role in influencing individuals' tech-driven entrepreneurial mindsets. Second, it examines how digital entrepreneurial pedagogy influences tech-driven competencies, allowing people to remain agile in an ever-changing digital context. Third, this study explores the mediating effects of digital competencies on the relationship between digital entrepreneurship education and entrepreneurial intention.
In the following sections, this study presents a theoretical framework, including hypotheses, methodology, results, discussion, implications, limitations, recommendations, and conclusions.
THORETICAL BACKGROUND
The Entrepreneurial Event Model (EEM) posits that entrepreneurial intentions are a function of three components (Shapero & Sokol, 1982): perceived desirability, perceived feasibility, and the disposition to act on opportunities. The model implies that a triggering event (e.g., experience, educational attainment) can lead people to consider entrepreneurship (Shapero & Sokol, 1982; Krueger, 1993). Once triggered, people assess business prospects by focusing on desirability and feasibility. People only engage in entrepreneurial activities (demonstrate willingness) when (1) they perceive an opportunity as desirable and (2) they view it as feasible (Shapero, 1975). Digital entrepreneurship education (Vu et al., 2024; Nguyen & Nguyen, 2024) is recognized as one of the critical triggering factors in terms of digital entrepreneurship, developing individuals' digital competencies (Bachmann et al., 2024), and strengthening their digital entrepreneurial intentions. As students develop an understanding of digital entrepreneurship through their education, recognizing it as a viable and rewarding career path, their motivation to engage in entrepreneurial ventures increases (Herani & Pranandari, 2024; Ferri et al., 2019).
Digital Entrepreneurship Education (DEE) and Digital Entrepreneurial Intention (DEI)
DEE has evolved into a transformational platform designed specifically to empower individuals with the skills and knowledge necessary for success in the evolving landscape of digital entrepreneurship (Duong et al., 2024b; Alzahrani & Bhunia, 2024). DEE teaches people in a variety of methods, including online courses, coaching programs, and startup accelerators. By integrating theoretical knowledge with practical skills, students are equipped to meet the challenges of the digital economy (Nguyen & Nguyen, 2024). The new style of teaching entrepreneurship does not rely on traditional methods, and it merges technology with business-based concepts. This method makes learning more entertaining and encourages students to use digital instruments to search out business alternatives and begin new businesses (Ratten & Usmanij (2021).
Students who possess adequate knowledge of digital entrepreneurship are better equipped to create a business model canvas, manage resources effectively, utilize various digital marketing strategies, and assess the sustainability of a business (Sufyan et al., 2023). Through DEE, students comprehend how to enter the field of digital business; hence, they are keen to show their desire to engage with digital entrepreneurship (Choi & Markham, 2019).
Furthermore, students with knowledge of digital business are well-prepared to forecast and overcome forthcoming challenges in the process of establishing and managing a digital firm (Colombelli et al., 2023; Qermane & Mancha, 2021). Drawing on the EEM mode and the extant literature, we can say that students who receive digital entrepreneurship education may cultivate their positive intentions to engage with digital entrepreneurship. Thus, we propose following hypothesis:
H1: Digital entrepreneurship education is positively associated with digital entrepreneurial intention
Digital Entrepreneurship Education (DEE) and Digital Competency (DC)
DEC refers to the knowledge and skills required to explore and gather new information, understand and capitalize on entrepreneurial opportunities (Ngoasong, 2017). Moreover, DEC can be acquired through formal education, context-specific training, and some prior experience (Fayolle & Gailly, 2015). DEE as a knowledge transfer process, integrate digital knowledge and entrepreneurial skills (Permatasari & Anggadwita, 2019). In accordance with the current Industrial Revolution 4.0 (Darma et al., 2020), digital education can be utilized to develop individuals' skills and enhance their employability. DEE strengthens an individual's competency in utilizing digital tools, platforms, and technologies for entrepreneurial innovation (Nguyen & Nguyen, 2024). DEE encourages individuals to acquire digital skills that directly translate into the marketplace by combining theoretical knowledge and practical applications about different areas, such as digital marketing, e-commerce management, cybersecurity, data analytics, and digital finance, that are vital for the successful development and growth of digital entrepreneurship (Elia et al., 2020). DEE cultivates digital literacy skills to identify and seize digital economic and market potential opportunities through training, workshops, and other practical programs (Hajli et al., 2024; Pigola et al., 2024). Based on the EEM model and insights from existing literature, it can be said that DEE has the potential to enhance individuals' DEC. Therefore, we hypothesize the following:
H2: Digital entrepreneurship education (DEE) is positively associated with Digital competency (DC).
Digital Competency (DEC) and Digital Entrepreneurial Intention (DEI)
Becoming proficient in certain skills and competencies increases individuals' potential to identify and leverage entrepreneurial opportunities (Pennetta et al., 2024; Bachmann et al., 2024). Competency in the digital domain-encompassing data analytics, digital marketing, e-commerce management, and cybersecurity-provides individuals with the technical and strategic skills necessary for creating ventures (Guo & Kiratikarnkul, 2024). Individual adaptability to technology, strong digital competencies, a risk tolerance, and a capacity for innovation are essential components of entrepreneurial intention in digital business environments (Al-Qadasi et al., 2024; Fan et al., 2024). Prior research suggests that individuals with high digital skills are more likely to perceive digital entrepreneurship as practical, desirable, and attainable, resulting in an increased likelihood of them pursuing entrepreneurial opportunities (Sudirman, 2025).
Previous studies have shown that digital education, in connection with the use of technology and the internet (Nguyen & Nguyen, 2024; Duong et al., 2024b), can help individuals to foster their digital competencies, which in turn may motivate them to engage with developing and managing existing or new ventures (Bachmann et al., 2024; Biswal et al., 2024). Although DEE provides necessary knowledge, the effectiveness of entrepreneurship education in fostering entrepreneurial intention and how to apply acquired knowledge to the development and management of new ventures remains unclear (Nguyen & Nguyen, 2024; Duong et al., 2024a). Furthermore, education itself may not produce the expected results in fostering entrepreneurial intention if it does not lead to the acquisition of relevant digital competencies (Kolade et al., 2024). In the absence of digital competency, individuals may often lack the necessary technical skills and confidence to apply education to practical action (Antonelli et al., 2024; Lyu et al., 2024). Based on the EEM model and the current literature, we propose the following hypotheses:
H3: Digital competency is positively associated with digital entrepreneurial intention.
H4: Digital competency mediates the relationship between digital entrepreneurship education and digital entrepreneurial intention.
MATERIALS AND METHODS
Sample and Data Collection
This study focuses on business students enrolled in entrepreneurial education and training programs at private universities in Bangladesh. Business studies equip students with the skills and knowledge needed to start and manage their own businesses. Since business students learn how to establish and run a business during their academic careers, it is perceived that they are more likely to become entrepreneurs than students in other fields (Luthje & Franke, 2003).
Selecting business students as respondents aligns with the research focus on digital entrepreneurship and digital entrepreneurial intention. Business students' familiarity with business frameworks, digital tools, entrepreneurial aspirations, and representativeness of the digital generation makes them an insightful and suitable group for this study. Moreover, as students represent the future entrepreneurs of tomorrow, with opportunities to prepare themselves through tech-driven education in academic institutions, it is crucial to understand their tech-driven entrepreneurial intentions and how digital education equips them in this regard.
The data were collected from ten leading private universities in Bangladesh that specialize in business education. With the consent and collaboration of class instructors, the questionnaires were distributed among the students. Each student was allocated 20 minutes to complete the questionnaire. Respondents received gifts for completing the survey successfully.
Our survey instrument was structured into two sections. The first section contained a cover letter that outlined the purpose of the study, clarified that participation was voluntary, and assured participants of the confidentiality of their data. The second section comprised the main questionnaire, which included attention-check questions (e.g., "Please select 'Disagree'") along with a range of response options. Since data was collected from ten leading universities located at different places of Bangladesh, the data collection process took time and spanned two months, from November 10, 2024, to January 10, 2025.
This study employed a two-round survey design to minimize common method bias. In the first round (Time 1), 500 questionnaires were distributed, asking respondents to evaluate their level of digital entrepreneurial education. During this phase, data on demographic characteristics, including gender, age, and education, were also collected. After data cleaning-ensuring responses met attention-check criteria and questionnaire completeness-433 valid responses were obtained. In the second round (Time 2), conducted two week later, the same respondents were invited to rate their level of digital competency and digital entrepreneurial intention. Following a similar cleaning process, a final dataset of 400 (80%) valid responses was retained, ensuring completeness, reliability, and the absence of missing data.
The respondents identified as 53% (n=212) female and 47% (n=188) male. In terms of age, 32% (n=128) were between the ages of 18 and 20, 47% (n=189) were between the ages of 21 and 24, and 21% (n=83) were over 25 years old. In terms of family business background, 29% (n=115) of respondents reported having a family business, while 71% (n=285) indicated no family business background. In terms of education, 26% (n=105) respondents were first year students, 22% (n=88) were second year students, 19% (n=76) were third year students, and 27% (n=108) were fourth year students. Based on these demographic characteristics, we believe the study sample was sufficiently representative.
Measure
This study used validated items with strong psychometric properties to ensure high internal consistency, reliability, and convergent validity (Bryman, 2007; Fisher et al., 2016). Using a 7-point Likert scale from 1 ('strongly disagree') to 7 ('strongly agree'), all measures have been assessed in accordance with the existing scale validations. In this study, the 6-item digital entrepreneurship education (Hasan et al., 2017) scale was adapted. One sample statement is, "This university arranges digital entrepreneurial specialized program." To examine the hypotheses, we adapted the 8-item scale on digital entrepreneurial intention designed by Vejayaratnam et al. (2019). For example, one item reads, "My professional goal is becoming a digital entrepreneur." The study also relied on the 5-item digital competency scale of Rubach and Lazarides (2021), which was adapted for use. A sample item is, "I can independently use digital learning opportunities and appropriate tools."
Data Analysis
SmartPLS 4.1.0.9, a widely used PLS-SEM software tool was employed for factor structure and construct validation (Hair et al., 2019). The ability of Partial Least Squares Structural Equation Modelling (PLS-SEM), a causal-predictive technique, to successfully explain causal relationships through statistical models with complex topologies has drawn much attention from researchers. Moreover, instead of creating a theoretical covariance matrix, PLS-SEM increases the explained variance of the dependent latent variables (Hair et al., 2011).
Common Method Bias
This study used both ex-ante and ex-post methods to evaluate common method bias, including: (a) item randomization (Cooper et al., 2020), (b) the use of established scales with demonstrated psychometric qualities (Podsakoff et al., 2003), (c) three evenly distributed attention-check questions (e.g., "Please select 'Disagree') (Kung et al., 2018), and (d) Harman's single-factor test (one factor explains 41.91% of the variance in Harman's single factor test) (Kock et al., 2021). Based on the questionnaire design and the results of Harman's test, the data collected for this study doesn't show common method bias.
Model Assessment
Factor loadings were employed to measure the convergent validity. Convergent validity analyses require estimated item loadings to be equal to or greater than 0.5 (Hair et al., 1987). The item loadings in all three variables used in this study are greater than 0.5. Discriminant validity was measured by comparing the square roots of the average variance extracted (AVE) and the item correlations (Kock, 2015). Findings showed that the square root of the AVE for each latent variable was greater than any of the correlations involving that latent variable, thus satisfying the condition for adequate discriminant validity. Also, Heterotrait-Monotrait (HTMT) ratio was used to test for discriminant validity. HTMT value less than 1 indicates acceptable discriminant validity (Henseler et al., 2015). The results of the HTMT test showed that the ratios of the DEE, DEC, and DEI variables have values less than 0.90, indicating that the discriminant validity criterion is met.
In addition, this study confirmed the scale reliability through composite reliability (CR) and Cronbach's alpha analyses. The coefficient values for both are required to be equal or above 0.70 to be considered as acceptable (Nunnally, 1978). The findings indicated that all variables had a Cronbach's alpha above 0.70 and a CR value above 0.80. All measures reached the necessary threshold, indicating that the scales demonstrated adequate reliability (See Table 1). Another critical aspect of data analysis is to ensure that there is no multicollinearity between the variables. Variance Inflation Factors (VIFs) are typically used to assess potential multicollinearity. Thus, multicollinearity does not exist in this study, as the values of VIF were less than 3 (Kock, 2015).
RESULTS
This study utilized a PLS-SEM approach to evaluate the psychometric properties of the latent variables and to test the hypotheses outlined above. The causal-predictive nature of PLS-SEM enhances its suitability as a methodological choice (Hair et al., 2022). The construct correlations are shown in Table 2.
We then conducted hypothesis testing, with the results summarized in Table 3. This table presents coefficient estimates, statistical significance values, and confidence intervals, which provide critical insights into the stability of the coefficient estimates (Talukder & Atinc, 2024). Additionally, the analysis incorporated results derived through the bootstrapping method with 5000 samples (Streukens & Leroi-Werelds, 2016; Talukder & Prieto, 2025).
As shown in Table 3, digital entrepreneurship education has a positive effect on digital entrepreneurial intention (β = 0.549, p < 0.001). This result supports Hypothesis 1 since it poses that digital entrepreneurship education is positively associated with digital entrepreneurial intention. The relationship between digital entrepreneurship education and digital competency was positive (β = 0.524, p < 0.001). This result supports hypothesis 2, which posits that digital entrepreneurship education increases digital competency. The relationship between digital competency and digital entrepreneurial intention was positive (β = 0.628, p < 0.001). This result supports hypothesis 3, which suggests that digital competency increase digital entrepreneurial intention.
Lastly, H4 suggests that digital competency mediate the relationship between digital entrepreneurship education and digital entrepreneurial intention (DEE → DC → DEI). Result (β = 0.472, p < 0.001) support hypothesis 4. Moreover, the evaluation of the structural model, based on effect sizes (f-squared) and predictive relevance (Q-squared), demonstrates significant relationships among digital entrepreneurship education, digital entrepreneurial intention, and digital competency. The effect sizes (Table 4) of all associations are within the acceptable range of 0.02 to 0.35 (Cohen, 2013). Among these, two effect sizes are moderate, while one is large.
Additionally, the Q2 (Q-squared) values presented in Table 5 for digital competencies (0.429), digital entrepreneurship education (0.399), and digital entrepreneurial intention (0.470) indicate medium predictive relevance, as they fall within the 0.25 to 0.50 range (Hair et al., 2019). Since all Q2 values are greater than 0, the model exhibits predictive relevance for the endogenous constructs. The significant T-values and low P-values further confirm the relationships, reinforcing the model's robustness and its explanatory power in examining digital competency and digital entrepreneurial intention based on digital entrepreneurship education.
DISCUSSION
The study revealed a significant relationship between digital entrepreneurship education, digital competencies, and digital entrepreneurial intention. The finding for Hypothesis 1 further shows that digital entrepreneurship education has a positive effect on students' tendency to develop in the field of digital entrepreneurship (Nguyen & Nguyen, 2024). This means that digital education, such as business incubation centres, practical training, and mentoring for digital startups, can successfully encourage entrepreneurial intention. With the ever-changing digital landscape across the world, incorporating digital entrepreneurship education into university curricula can plays consequential role equipping students with the mindset and knowledge needed to explore entrepreneurial opportunities.
The hypothesis 2 is to find out the impact of digital entrepreneurship education on enhancing the individual's digital competency. It shows that universities can improve students' digital skills in areas such as digital marketing, e-commerce management, or fintech applications by providing tech-focused education. Hypothesis three notably reiterates that if individuals possess an appropriate level of digital competency, they will significantly enhance their propensity for digital entrepreneurship. These insights are consistent with the growing trend of businesses being built on digital platforms in Bangladesh, where the domains of e-commerce, freelancing, and tech-based ventures have been experiencing significant growth.
Moreover, the results of hypothesis 4 conclude that digital competency acts as a mediating factor between digital entrepreneurship education and digital entrepreneurial intention. If Entrepreneurial intention can be developed through conventional education, students need to be equipped with strong digital competencies so that they can convert their desires into successful entrepreneurial ventures. Highlighting the importance of digital entrepreneurship education in developing the entrepreneurial mind of students in Bangladesh with respect to the digital competency as one of the key outcomes. The results underscore the need for universities to continually update their courses to ensure they reflect new digital developments, and that graduates possess the skills and knowledge necessary to thrive in the digital economy. In future research, it would be interesting to investigate how external academic and market conditions, such as government policies, financial support, and market conditions, influence students' digital entrepreneurial intentions.
IMPLICATION
In terms of theoretical implications, this study contributes to the literature on digital entrepreneurship and entrepreneurship in general, with a particular emphasis on the concept of EEM and its applicability in developing countries, such as Bangladesh. Within the context of Bangladesh's rapidly evolving digital economy, the application of the Entrepreneurial Event Model (EEM) provides a nuanced perspective on how digitalization influences entrepreneurial motivation. This underscores the critical need for researchers to reevaluate and refine existing theoretical paradigms to ensure their continued relevance and robustness in addressing the complexities of the digital age. The Entrepreneurial Event Model (EEM) by Shapero & Sokol (1982) emphasizes that entrepreneurial intentions are not only determined by perceived desirability and perceived feasibility, but also by the propensity to act. This research extends the EEM by adding digital entrepreneurship education and digital competency as fundamental antecedents that influence students' entrepreneurial intentions in the digital space. In summary, this work confirms the significance of the EEM in terms of digital entrepreneurship, extended with digital education and digital competency as the major explanatory variables of entrepreneurial intention.
In addition, the results of this research provide several practical implications for policymakers, academics, and emerging digital entrepreneurs. The evidence of the significance of digital entrepreneurship in boosting economic growth and employment highlights the need to take a more structured and competency-oriented path when it comes to educating entrepreneurs. This knowledge could enable universities and other relevant actors to take effective and targeted measures to promote a more vibrant digital entrepreneurial ecosystem by understanding the influence of digital entrepreneurial education and digital competency on students' digital entrepreneurial intentions.
This study highlights that digital competency has a meaningful impact on entrepreneurial intentions; therefore, it is advisable to develop more practical training in digital marketing, fintech, blockchain, and e-commerce platforms. To minimize the gap between classroom instruction and real-world work activities, universities should collaborate with industry experts and successful digital entrepreneurs. Furthermore, associations with corporations and mentorship programs offer entrepreneurs the opportunity for inspiration through guidance and exposure to the industry. In addition, to develop the next generation of digital entrepreneurs, tech-driven corporations need to work with universities to create internship, mentorship, and funding opportunities for talented students. These initiatives can increase not only students' digital entrepreneurial intentions but also the digital economy development. Implementing these actionable recommendations may help countries, especially developing countries, create a more inclusive and tech-driven entrepreneurial ecosystem, opening the doors to innovation and increased job creation in the new digital era.
LIMITATION AND FURTHER DIRECTIONS
While this study offers valuable insights, it has certain limitations. First, the reliance on cross-sectional data limits the ability to establish definitive cause-and-effect relationships. Future research could employ experimental or longitudinal designs to further investigate the interplay between digital entrepreneurship education, digital competency, and entrepreneurial goals. Second, the study focuses exclusively on business graduates aspiring to start digital businesses. Expanding the scope to include individuals at different educational and employment stages would provide a more comprehensive understanding of factors influencing digital entrepreneurial intentions across diverse contexts. Finally, cross-country comparisons with similar developing economies could shed light on how institutional culture and economic conditions shape the motivations of digital entrepreneurs. Such comparative studies would enhance the reliability and generalizability of the findings, enriching the global discourse on digital entrepreneurship. Future research could further refine this theoretical model by exploring additional factors, such as technological infrastructure, social networks, and government policies, that influence digital entrepreneurial intentions in emerging economies.
CONCLUSION
Digital entrepreneurship plays a vital role in driving innovation and economic diversification across industries. This research aims to fill this gap in the literature by examining the determinants of engaging in digital entrepreneurship. Using a sample of business graduates from Bangladesh and the EEM framework, the study makes important contributions regarding the relations between determinants of digital entrepreneurial intention. The results underscore the importance of digital competency and entrepreneurship education in influencing individuals' decisions to launch digital entrepreneurial ventures. More precisely, this study focuses on education, self-efficacy, and attitudes as a whole, which collectively impact the intention of Bangladeshi business graduates toward digital entrepreneurship. The study has important implications for educators, policymakers, and entrepreneurs who intend to foster an atmosphere that enables innovation and digital entrepreneurship by examining these determinants. By mapping the essence of digital entrepreneurial intention among potential digital entrepreneurs, this study contributes to the emerging body of literature on digital entrepreneurship in developing countries and unveils the most significant and high-impact drivers for digital entrepreneurship intention in this region.
REFERENCES
Al-Qadasi, N., Zhang, G., Al-Jubari, I., Al-Awlaqi, M.A., & Aamer, A.M. (2024). Entrepreneurship education and entrepreneurial behaviour: Do self-efficacy and attitude matter? The International Journal of Management Education, 22(1), 100945. https://doi.org/10.1016/j.ijme.2024.100945
Alzahrani, S., & Bhunia, A.K. (2024). A serial mediation model of the relationship between digital entrepreneurial education, alertness, motivation, and intentions. Sustainability, 16(20), 8858. https://doi.org/10.3390/su16208858
Antonelli, G., Venesaar, U., Riviezzo, A., Kallaste, M., Dorożyński, T., & Kłysik-Uryszek, A. (2024). Find your limits and break them! Nurturing students' entrepreneurship competence through innovative teaching methods and self-assessment. Journal of Enterprising Communities: People and Places in the Global Economy, 18(1), 29-48. https://doi.org/10.1108/JEC-10-2022-0148
Bachmann, N., Rose, R., Maul, V., & Hölzle, K. (2024). What makes for future entrepreneurs? The role of digital competencies for entrepreneurial intention. Journal of Business Research, 174, 114481. https://doi.org/10.1016/j.jbusres.2023.114481
Bell, E., Harley, B., & Bryman, A. (2022). Business research methods (6th ed.). Oxford University Press. Biswal, B.K., Mishra, J., Palanivel, R.V., Uprikar, V., Landage, H., & Kayande, R.A. (2024). Advancing digital entrepreneurship: Exploring new business models and research opportunities. Library of Progress: Library Science, Information Technology & Computer, 44(3), 1-19. https://doi.org/10.48165/bapas.2024.44.2.1
Choi, J.I., & Markham, S. (2019). Creating a corporate entrepreneurial ecosystem: The case of entrepreneurship education in the RTP, USA. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 62-74. https://doi.org/10.3390/joitmc5030062
Cohen, J. (2013). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.
Colombelli, A., Paolucci, E., Raguseo, E., & Elia, G. (2023). The creation of digital innovative start-ups: The role of digital knowledge spillovers and digital skill endowment. Small Business Economics, 62(3), 917-937. https://doi.org/10.1007/s11187-023-00789-9
Cooper, B., Eva, N., Fazlelahi, F.Z., Newman, A., Lee, A., & Obschonka, M. (2020). Addressing common method variance and endogeneity in vocational behavior research: A review of the literature and suggestions for future research. Journal of Vocational Behavior, 121, 103472. https://doi.org/10.1016/j.jvb.2020.103472
Darma, D.C., Ilmi, Z., Darma, S., & Syaharuddin, Y. (2020). COVID-19 and its impact on education: Challenges from Industry 4.0. Aquademia, 4(2), 1-4. https://doi.org/10.29333/aquademia/8453
Daouk, A. (2025). Navigating the digital transformation landscape: Education, opportunities, and challenges for entrepreneurs. In Entrepreneurship-digital transformation, education, opportunities and challenges (p.113).
Depaoli, P., Za, S., & Scornavacca, E. (2020). A model for digital development of SMEs: An interaction-based approach. Journal of Small Business and Enterprise Development, 27(7), 1049-1068. https://doi.org/10.1108/JSBED-01-2019-0020
Duong, C.D., Le, T.T., Dang, N.S., Do, N.D., & Vu, A.T. (2024). Unraveling the determinants of digital entrepreneurial intentions: Do performance expectancy of artificial intelligence solutions matter? Journal of Small Business and Enterprise Development, 31(7), 1327-1356. https://doi.org/10.1108/JSBED-02-2024-0065
Elia, G., Margherita, A., & Passiante, G. (2020). Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process. Technological Forecasting and Social Change, 150, 119791. https://doi.org/10.1016/j.techfore.2019.119791
Elnadi, M., & Gheith, M.H. (2023). The role of individual characteristics in shaping digital entrepreneurial intention among university students: Evidence from Saudi Arabia. Thinking Skills and Creativity, 47, 101236. https://doi.org/10.1016/j.tsc.2023.101236
Fan, J., Hu, J., & Wang, J. (2024). How entrepreneurship education affects college students' entrepreneurial intention: Samples from China. Heliyon, 10(10), e30776. https://doi.org/10.1016/j.heliyon.2024.e30776
Fayolle, A., & Gailly, B. (2015). The impact of entrepreneurship education on entrepreneurial attitudes and intention: Hysteresis and persistence. Journal of Small Business Management, 53(1), 75-93. https://doi.org/10.1111/jsbm.12065
Ferri, L., Ginesti, G., Spano, R., & Zampella, A. (2019). Exploring factors motivating entrepreneurial intentions: The case of Italian university students. International Journal of Training and Development, 23(3), 202-220. https://doi.org/10.1111/ijtd.12158
Fisher, G.G., Matthews, R.A., & Gibbons, A.M. (2016). Developing and investigating the use of single-item measures in organizational research. Journal of Occupational Health Psychology, 21(1), 3- 23. https://doi.org/10.1037/a0039139
Galvão, A., Ferreira, J.J., & Marques, C. (2018). Entrepreneurship education and training as facilitators of regional development: A systematic literature review. Journal of Small Business and Enterprise Development, 25(1), 17-40. https://doi.org/10.1108/JSBED-05-2017-0178
Guo, T., & Kiratikarnkul, S. (2024). The influence of digital marketing literacy and self-efficacy on the intention to be an e-commerce entrepreneur. Maejo University Institutional Repository. Retrieved from http://ir.mju.ac.th/dspace/handle/123456789/2174
Hair, J., & Alamer, A. (2022). Partial least squares structural equation modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027
Hair, J.F., Anderson, R.E., & Tatham, R.L. (1987). Multivariate data analysis. Pearson. Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J.F., Ringle, C.M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
Hasan, S.M., Khan, E.A., & Nabi, M.N.U. (2017). Entrepreneurial education at university level and entrepreneurship development. Education & Training, 59(7), 888-906. https://doi.org/10.1108/ET-01-2016-0020
Hajli, N., Baydarova, I., & Nisar, T. (2024). Digital entrepreneurial ecosystem: The role of the sharing economy in driving innovation. Entrepreneurship & Regional Development, 10(2), 1-31. https://doi.org/10.1080/08985626.2024.2444908
Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Herani, R., & Pranandari, A. (2024). Promote or inhibit? Examining the influence of youth digital advocacy on digital social entrepreneurship. Social Enterprise Journal, 20(5), 654-677. https://doi.org/10.1108/SEJ-11-2023-0136
Kock, F., Berbekova, A., & Assaf, A.G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism Management, 86, 104330. https://doi.org/10.1016/j.tourman.2021.104330
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101
Kolade, S., Jones, P., Amankwah-Amoah, J., Ogunsade, A., & Olanipekun, K. (2024). Entrepreneurship education and entrepreneurial intention in a turbulent environment: The mediating role of entrepreneurial skills. International Review of Entrepreneurship, 21(3), 399-430. https://shura.shu.ac.uk/32517/
Krueger, N. (1993). The impact of prior entrepreneurial exposure on perceptions of new venture feasibility and desirability. Entrepreneurship Theory and Practice, 18(1), 5-21. https://doi.org/10.1177/104225879301800101
Kumar, R., Kaur, S., Erceg, Ž., & Mirović, I. (2023). Industry 4.0 and its impact on entrepreneurial ecosystems: An examination of trends and key implications. Journal of Organization Technology and Entrepreneurship, 1(1), 12-34. https://doi.org/10.56578/jote010102
Kung, F.Y., Kwok, N., & Brown, D.J. (2018). Are attention check questions a threat to scale validity? Applied Psychology, 67(2), 264-283. https://doi.org/10.1111/apps.12108
Lyu, J., Shepherd, D., & Lee, K. (2024). The impact of entrepreneurship pedagogy on nascent student entrepreneurship: An entrepreneurial process perspective. Studies in Higher Education, 49(1), 62-83. https://doi.org/10.1080/03075079.2023.2220722
Ngoasong, M.Z. (2018). Digital entrepreneurship in a resource-scarce context: A focus on entrepreneurial digital competencies. Journal of Small Business and Enterprise Development, 25(3), 483-500. https://doi.org/10.1108/JSBED-01-2017-0014
Nguyen, P.N.D., & Nguyen, H.H. (2024). Unveiling the link between digital entrepreneurship education and intention among university students in an emerging economy. Technological Forecasting and Social Change, 203, 123330. https://doi.org/10.1016/j.techfore.2024.123330
Nunnally, J.C. (1978). An overview of psychological measurement. In P. McReynolds (Ed.), Clinical diagnosis of mental disorders: A handbook (pp. 97-146). Springer.
Pennetta, S., Anglani, F., & Mathews, S. (2024). Navigating through entrepreneurial skills, competencies and capabilities: A systematic literature review and the development of the entrepreneurial ability model. Journal of Entrepreneurship in Emerging Economies, 16(4), 1144-1182. https://doi.org/10.1108/JEEE-09-2022-0257
Permatasari, A., & Anggadwita, G. (2019). Digital entrepreneurship education in emerging countries: Opportunities and challenges. In P. Ordóñez de Pablos, R. Tennyson, & M.D. Lytras (Eds.), Opening up education for inclusivity across digital economies and societies (pp. 156-169). IGI Global. https://doi.org/10.4018/978-1-5225-7473-6.ch008
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., & Podsakoff, N.P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-890. https://doi.org/10.1037/0021-9010.88.5.879
Pigola, A., Fischer, B., & Moraes, G.H.S.M.D. (2024). Impacts of digital entrepreneurial ecosystems on sustainable development: Insights from Latin America. Sustainability, 16(18), 7928. https://doi.org/10.3390/su16187928
Primario, S., Rippa, P., & Secundo, G. (2022). Rethinking entrepreneurial education: The role of digital technologies to assess entrepreneurial self-efficacy and intention of STEM students. IEEE
Transactions on Engineering Management, 71, 2829-2842. https://doi.org/10.1109/TEM.2022.3199709
Qermane, K., & Mancha, R. (2021). WHOOP, Inc.: Digital entrepreneurship during the COVID-19 pandemic. Entrepreneurship Education and Pedagogy, 4(3), 500-514. https://doi.org/10.1177/2515127420975
Ratten, V., & Usmanij, P. (2021). Entrepreneurship education: Time for a change in research direction? The International Journal of Management Education, 19(1), 100367. https://doi.org/10.1016/j.ijme.2020.100367
Rodrigues, A.L. (2022). Integrating digital technologies in accounting preservice teacher education: A case study in Portugal. International Journal of Technology and Human Interaction, 18(1), 1-19. https://doi.org/10.4018/IJTHI.293200
Rubach, C., & Lazarides, R. (2021). Addressing 21st-century digital skills in schools: Development and validation of an instrument to measure teachers' basic ICT competence beliefs. Computers in Human Behavior, 118, 106636. https://doi.org/10.1016/j.chb.2020.106636
Shapero, A. (1975). The displaced, uncomfortable entrepreneur. Psychology Today, 9(6), 83-88. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1506368
Shapero, A., & Sokol, L. (1982). The social dimensions of entrepreneurship. In C. Kent, D. Sexton, & K. H. Vesper (Eds.), The encyclopedia of entrepreneurship (pp. 72-90). Prentice-Hall.
Sitaridis, I., & Kitsios, F. (2024). Digital entrepreneurship and entrepreneurship education: A review of the literature. International Journal of Entrepreneurial Behavior & Research, 30(2/3), 277-304. https://doi.org/10.1108/IJEBR-01-2023-0053
Streukens, S., & Leroi-Werelds, S. (2016). Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Management Journal, 34(6), 618-632. https://doi.org/10.1016/j.emj.2016.06.003
Sudirman, N. (2025). Digital entrepreneurship and business innovation: Strategies for Indonesian SMEs in the era of Industry 4.0. Journal of Indonesian Scholars for Social Research, 5(1), 24-34. https://doi.org/10.59065/jissr.v5i1.170
Sufyan, M., Degbey, W.Y., Glavee-Geo, R., & Zoogah, D.B. (2023). Transnational digital entrepreneurship and enterprise effectiveness: A micro-foundational perspective. Journal of Business Research, 160, 113802. https://doi.org/10.1016/j.jbusres.2023.113802
Sulistianingsih, S. (2023). Use of digital technology to support the entrepreneurship education process. Indo-MathEdu Intellectuals Journal, 4(2), 347-361. https://doi.org/10.54373/imeij.v4i2.203
Talukder, M.F., & Prieto, L. (2025). Quiet quitting and job security: investigating the impacts of employee's capital and habitus. International Journal of Organizational Analysis (Advance online publication). https://doi.org/10.1108/IJOA-04-2025-5444
Talukder, M.F., & Atinc, G. (2024). Empowering commitment: Unraveling the impact of motivating language and the mediating role of trust. Corporate Communications: An International Journal. Advance online publication. https://doi.org/10.1108/CCIJ-12-2023-0196
Triyono, M.B., Mutohhar, F., Kholifah, N., Nurtanto, M., Subakti, H., & Prasetya, K.H. (2023). Examining the mediating-moderating role of entrepreneurial orientation and digital competence on entrepreneurial intention in vocational education. Journal of Technical Education and Training, 15(1), 116-127. https://doi.org/10.30880/jtet.2023.15.01.011
Vejayaratnam, N., Paramasivam, T., & Mustakim, S.S. (2019). Digital entrepreneurial intention among private technical and vocational education (TVET) students. International Journal of Academic Research in Business and Social Sciences, 9(12), 110-120.<https://doi.org/10.6007/IJARBSS/v9-i12/6678
Vu, T.H., Do, A.D., Ha, D.L., Hoang, D.T., Van Le, T.A., & Le, T.T.H. (2024). Antecedents of digital entrepreneurial intention among engineering students. International Journal of Information Management Data Insights, 4(1), 100233. https://doi.org/10.1016/j.ijimei.2024.100233
Wang, S.M., Yueh, H.P., & Wen, P.C. (2019). How the new type of entrepreneurship education complements the traditional one in developing entrepreneurial competencies and intention. Frontiers in Psychology, 10, 2048. https://doi.org/10.3389/fpsyg.2019.02048
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