This systematic literature review examines data saturation in qualitative research within the context of entrepreneurship studies from 2004 to 2024. Data saturation, a critical concept in ensuring the rigor of qualitative research, remains inadequately defined in terms of sample size and assessment criteria across various studies. This review synthesizes 11 empirical studies, focusing on strategies such as stopping criterion, code frequency counts, and comparative methods for determining saturation. It identifies sample sizes ranging from 7 to 39 interviews, with an average saturation occurring between 10 and 12 interviews. Furthermore, the study explores the influence of different sampling methods and homogeneity of study populations on saturation outcomes. Despite the reliability of existing methods, the findings underscore the need for greater transparency and consistency in reporting saturation criteria. The review offers valuable insights for entrepreneurial researchers aiming to design qualitative studies, emphasizing the importance of tailored saturation standards based on research objectives and methodologies. This research contributes to a clearer understanding of data saturation in entrepreneurial studies and highlights the necessity for further empirical investigation into saturation across diverse qualitative methods.

The development and expansion of economies depend heavily on entrepreneurship, and Malaysia is no exception. Understanding the underlying elements that impact the success or failure of user adoption behaviour of online shopping activities is significant since entrepreneurship is critical in driving economic growth and innovation. The study includes 73 articles published from 2004 to the last of 2023 from Science Direct, Scopus, Google Scholar, and Web of Science. We utilised qualitative methods and systematic review issues through the findings of “qualitative” studies as the last step inside a systematic review using Nvivo14. Our study’s result illustrated that applying the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) in Malaysian e-commerce validates the relevance of established theoretical frameworks. This study explores the relationship between 20 independent variables and five mediator factors, with dependent variables, e-commerce in Malaysia. The results highlight the intricate relationships between these variables and their importance for companies, decision-makers, and other stakeholders involved in Malaysian infrastructure financing. This review provides legislators, educators, researchers, and businesspeople with new knowledge in Malaysia so that decision-makers, investors, and aspiring entrepreneurs can make informed decisions.

This article explores the landscape of entrepreneurship education in Indonesia amid the wave of digital transformation. The research method uses Systematic Literature Review (SLR) to review research results sourced from journals indexed in Sinta or nationally accredited journals in Indonesia which can be accessed on Google Scholar. The conclusion, (i) Digital transformation-based entrepreneurship education creates a new learning model in colleges with the aim of developing entrepreneurial attitudes and values among young people, especially students, so as to produce entrepreneurial intentions. (ii) Higher education as an entrepreneur education provider must follow the progress of digital transformation in the teaching process of entrepreneurship education so that digital literacy among lecturers and students is getting better. (iii) The participation of stakeholders, the Government, college and the business world, is expected to provide support in policy making, especially curriculum changes in accordance with current circumstances in creating new business actors or entrepreneurial intentions.

Technological management has promoted distinctive characteristics in the socio-productive development of the regions. Its usefulness in entrepreneurial activity is studied to design the architecture of a technological observatory as an intelligent system for entrepreneurship in Latin America. Using a descriptive-explanatory method, data obtained from the application of two instruments directed to 18 experts in information and communication technologies and 174 entrepreneurs distributed 92 in Lima-Peru and 82 in Santiago de Cali-Colombia are processed. The findings show informational and training barriers and a weak or non-existent technological platform for effective entrepreneurial development. Added to the low development of plans and alliances mediated by technologies, whose experience supports public policies that strengthen entrepreneurship as an emerging economy. The architecture supports the functional and operational aspects of the system. Its scalability in other regions dynamizes the services-processes required prior to the detection of needs directed towards the projection of sustainable entrepreneurship.

The Malaysian government’s heightened focus on Technical and Vocational Education and Training (TVET) reflects a strategic move towards economic and social development, particularly in addressing youth unemployment. Recognizing the potential of TVET to contribute to these goals, there is a specific emphasis on enhancing the marketability of women in the workforce from the current 62 percent to an ambitious 95 percent. However, a notable gender gap persists in entrepreneurial pursuits within the TVET sector in Malaysia, with female representation lagging. To bridge this gap, this study aims to construct a comprehensive framework that nurtures future-ready female TVETpreneur talent. This initiative aligns with the Malaysian Higher Education Blueprint, 2021–2025, i.e., fostering a diverse and innovative workforce. An extensive literature survey was conducted to identify the factors influencing female TVET students’ entrepreneurial intention. The literature revealed that social psychological and organizational approaches are commonly used to explore and analyze the relationship between the influence of female TVET students’ talents and behavior, their exposure to entrepreneurship, mentorship and support programs, role models in TVET, curriculum design, and access to resources. A comprehensive theoretical framework was developed based on these findings, which offers significant insights related to enhancing TVET opportunities for women and advancing Malaysia’s economic and social development goals in a sustainable way.

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.