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Digital entrepreneurship is a highly topical, sub-specialist and contemporary branch of entrepreneurship which is providing ever-increasing range of platforms for pursuing entrepreneurship-related career options. While the academic discourses in this area are increasingly growing, there is an equal level of scant attention paid to inquire how proclivity toward this career choice is developed and influenced. In the present study, this gap has been addressed by identifying major antecedents of digital entrepreneurship intentions under the aegis of capital theory.

Using the survey data from 287 respondents, structural equation modeling was utilized to explore the association of four antecedents: digital entrepreneurial competence, innovative cognition, social media adroitness and digital entrepreneurship role models on the goal intentions. Subsequently the association between goal intention and implementation intention to start a digital venture was also examined.

The analysis confirms the significant impact of the identified antecedents on the digital entrepreneurial volition of potential entrepreneurs. Our results demonstrate that innovativeness has the greatest impact on the goal intentions to create new digital ventures followed by the presence of role models. Digital competence is also a significant contributor in enhancing the propensity to start digital ventures while being digitally adroit has the least impact on such inclination. Lastly, our study provides empirical evidence to the linkage between goal and implementation intentions.

This paper informs practice on entrepreneurship education especially the role of skill-based education programs to enhance the information technology–related knowledge of students and incubation support for hands-on-training on the various dimensions of digital ventures. At policy-level institutions providing entrepreneurial education can design special tasks and learning activities that are focused on acquainting students with design thinking perspectives and lean start-up approaches.

The impacts of institutional quality on entrepreneurship are well established. However, the effects of an external factor, such as the shadow economy, that moderates this relationship have largely been neglected in existing literature. As such, this paper investigates how the shadow economy moderates the effects of institutional quality on entrepreneurship in a global sample of 79 economies from 2006 to 2018, when the latest required data are available.

This paper utilizes the fixed-effect and generalized method of moments (GMM) estimation techniques. Various scenarios have been considered for the robustness of the analysis, including different estimation techniques, different estimates of the shadow economy and various subsamples of countries with different income levels.

Empirical findings indicate that improved institutional quality boosts entrepreneurship activities, while the extended shadow economy is associated with reduced entrepreneurship activities. Interestingly, the positive impacts of institutional quality on entrepreneurship will be lessened with a larger shadow economy. These findings have remained largely unchanged across samples of countries and different proxies and estimation techniques.

Findings from this paper offer policymakers the relationships between institutional quality, shadow economy and entrepreneurship and the moderating effects of shadow economy on the institutional quality–entrepreneurship nexus. The implication is that institutional quality should be strengthened while the shadow economy should be controlled to promote entrepreneurship initiatives.

To the best of the author's knowledge, this is the first empirical study to explore the moderating effects of the shadow economy on the institutional quality–entrepreneurship nexus.

This paper aims to: first, it studies expert opinions about the future of clean, decentralized energy technology in Australia; second, develop an interpretive and participatory foresighting methodology for a forthcoming study.

This paper reports a forecasting study about the future of clean energy. Driven mostly by economics and changing carbon policies, the energy sector is currently moving from fossil fuels to a variety of cleaner technologies. Energy experts have several incommensurate interpretations of how this change will happen. This paper describes the first phase of an ongoing study that foresight clean energy futures in Australia. By building on a participatory method in a scientific expert community, it describes the path from technological presumptions into four parallel yet interconnected scenarios. The paper also explores the social drivers behind these scenarios.

First, energy experts in Australia classify futures into four main scenarios: abundant, where energy will be mostly produced by solar cells; traded, where the future of energy lies in virtual power plants and microgrids; circular, which targets Australia’s NetZero goals through biomaterials, carbon capture and new powerful; secure, which secures the country’s energy supply through coal and nuclear energy. Second, they locate policy as the most important form of wildcards. The policy is multilayered from local to US politics and falls outside the scope of forecasting.

The most important limitations of the study are: first, its reliance on scientific and technological experts, which guarantees its scientific validity but may underrepresent the social drivers of energy; second, this study is a methodological pilot of a larger study that will target industrial, commercial and local drivers; third, its focus on Australia, where politics, the size of the country and climate shape the uptake of clean energy in specific ways, most notably in the case of rapid uptake of solar energy.

The main practical implications of the paper are its broad focus on clean energy futures and its participatory foresighting approach, which can be repeated in other studies.

The main social implication of the study is that it clearly shows that a technological perspective is necessary but not sufficient in understanding the future of clean energy. The paper also shows that local drivers importantly mold the future and should be taken into account in future studies and policy.

This paper makes two contributions. First, it organizes several technologies into four scenarios that clarify Australia’s clean energy futures better than a piecemeal study would do. Second, it developed and piloted an interpretive participatory methodology for studying futures by building on references from design research. This methodology will be used in subsequent studies.

Feature extraction from 3D datasets is a current problem. Machine learning is an important tool for classification of complex 3D datasets. Machine learning classification techniques are widely used in various fields, such as text classification, pattern recognition, medical disease analysis, etc. The aim of this study is to apply the most popular classification and regression methods to determine the best classification and regression method based on the geodesics.

The feature vector is determined by the unit normal vector and the unit principal vector at each point of the 3D surface along with the point coordinates themselves. Moreover, different examples are compared according to the classification methods in terms of accuracy and the regression algorithms in terms of R-squared value.

Several surface examples are analyzed for the feature vector using classification (31 methods) and regression (23 methods) machine learning algorithms. In addition, two ensemble methods XGBoost and LightGBM are used for classification and regression. Also, the scores for each surface example are compared.

To the best of the author’s knowledge, this is the first study to analyze datasets based on geodesics using machine learning algorithms for classification and regression.

In the context of exponential technological advancements in the economy and the role of entrepreneurial ventures in significantly contributing towards social and economic growth, this study aims to examine the influence of learning motivation and personal innovativeness (PI) on students’ entrepreneurship intention. The study gains relevance in the context of students in emerging economies like India, where the digital divide is still on the higher side. The study also seeks to understand the extent to which varying levels of technological self-efficacy moderate the interaction effects of human capital in the aforementioned relationship.

The sample for this study consisted of 330 students from various disciplines, including science, technology and management, who were selected randomly from different universities in India. A self-administered and structured questionnaire was used to obtain responses from the participants. The data were analysed using confirmatory factor analysis (IBM SPSS 23.0), and path analysis was performed using Hayes PROCESS Macro.

The study's results indicated that learning motivation and PI had a significant indirect effect on students’ entrepreneurship intention, mediated through human capital. However, interestingly, the relationships were varyingly influenced by technological self-efficacy as the moderator.

The contemporary student cohort consists of individuals known as “digital natives,” who possess a strong inclination towards digital learning and demonstrate innovative behaviour. The insights gained from this study underscore the crucial role of technological self-efficacy in shaping entrepreneurial intentions, indicating the necessity of incorporating technological training and skill development within international business education curricula. Also, the results of the study emphasize the need for integrating PI into business education programs, as it positively influences the entrepreneurial mindset and potential.

This study is pioneering in conceptualizing and testing a model that provides a more comprehensive understanding of student attitudes and outcomes. This understanding can be used to customize entrepreneurial programs to better meet the needs of students. Entrepreneurship fosters technological innovation and creates employment opportunities, making student venture creations a crucial factor in economic development and sustainability. For educators and university administrators, it is essential to comprehend how to enhance entrepreneurial intentions among students to design a learning environment that facilitates the creation of new ventures as a result of higher education.

Continuous advances in digital technology and business models digitalization have decisively altered the entrepreneurial landscape redefining the aims and the requirements of entrepreneurial education to suit the new digital reality in entrepreneurship. The purpose of this study is to shed light in a neglected niche in the intersection between digital entrepreneurship (DE) and entrepreneurship education and outline DE education as field of research. Given that the interdisciplinary growth of DE research outpaces instructional designs in terms of required knowledge and skills, it is important to document how entrepreneurship education responds to the ongoing integration of emerging digital technologies with the entrepreneurial process. Moreover, the introduction of a DE education conceptual framework would facilitate the discussion on theoretical and practical implications and promote new conceptualizations in future research, new educational approaches and new curriculum designs.

A concept-driven, semi-structured developmental literature review methodology, based on grounded theory and reinforced with increased systemization, was used for the identification and analysis of peer-reviewed articles. Previous literature reviews were used to define the search keywords. The articles from three databases were carefully selected, based on protocol and strict eligibility criteria. The papers in the final set were classified in four primary dimensions, synthesized from several sub-streams of research. Each sub-stream highlighting a different view of DE education emerged through open, axial and selective coding of articles. The combined perspectives of these dimensions resulted in a new DE conceptual framework.

Thematic interrelation between the studies examined, revealed an ample view of the various schools of thought in the research field, offering also a better understanding on how entrepreneurial education addresses the practical requirements of digital entrepreneurship. A four dimensional conceptual framework produced highlights pedagogy and learning, success factors and barriers, behavioral approach and ecosystems as the current trends of research. Also, directions for future research are proposed.

The classification framework proposed can serve as a roadmap for entrepreneurship educators seeking efficient pedagogical practices focused on the transfer of knowledge and training on the new skills required by DE and motivate future researchers aiming to propose novel educational interventions.

Although digital entrepreneurship research has gained significant momentum in recent years, little attention is paid to its increased educational requirements. The body of knowledge develops in an uncontrolled and fragmented manner, and the systematic study of the field from an educational perspective was missing. This study offers a representative picture of the topic, highlights current trends of research, synthesizes literature from different disciplinary origins, provides linkages between unconnected streams of research and points out research gaps. Finally, it proposes a conceptual framework to circumscribe DE education as a field of study and serve as a basis to help future research move forward.