Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
PurposeThis study aims to investigate the digital entrepreneurial intentions of Albanian youth, identify the obstacles they face in starting digital businesses and examine their preferences regarding the types of businesses they aspire to establish. The Theory of Planned Behavior (TPB) is used as a framework to analyze these factors.Design/methodology/approachPrimary data were collected via questionnaires distributed in public and private universities. In a sample of 325 students, Structural Equation Modeling with Confirmatory Factor Analysis, path analysis and machine learning-based text analysis were used.FindingsThis study reveals significant impacts of innovativeness, attitude towards entrepreneurship, subjective norms, perceived behavioral control and self-efficacy on digital entrepreneurial intentions among Albanian students. Additionally, text mining highlights a strong preference for digital entrepreneurship.Research limitations/implicationsThe theoretical contributions of this study include applying Structural Equation Modeling to reveal insights into the impact of entrepreneurial factors and obstacles. The findings can inform policymakers and educators in designing targeted interventions to support student entrepreneurship. Meanwhile, the limitations of this study encompass a small sample size, lack of time series and panel data and the absence of an evaluation of the impact of education system practices, along with the need to investigate the effects of young population emigration from Albania to the EU.Originality/valueThis research contributes to the understanding of digital entrepreneurial intentions and behavior by using TPB in the Albanian context, offering access to a diverse dataset from Albanian universities, testing the direct impact of innovativeness on entrepreneurial behavior and pioneering the use of machine learning techniques for text analysis. Thus, it provides novel insights into the entrepreneurial landscape in Albania. In addition, this work can drive initiatives to support student entrepreneurship and bridge the gap between academia and industry in Albania.
PurposeThis study aims to investigate the digital entrepreneurial intentions of Albanian youth, identify the obstacles they face in starting digital businesses and examine their preferences regarding the types of businesses they aspire to establish. The Theory of Planned Behavior (TPB) is used as a framework to analyze these factors.Design/methodology/approachPrimary data were collected via questionnaires distributed in public and private universities. In a sample of 325 students, Structural Equation Modeling with Confirmatory Factor Analysis, path analysis and machine learning-based text analysis were used.FindingsThis study reveals significant impacts of innovativeness, attitude towards entrepreneurship, subjective norms, perceived behavioral control and self-efficacy on digital entrepreneurial intentions among Albanian students. Additionally, text mining highlights a strong preference for digital entrepreneurship.Research limitations/implicationsThe theoretical contributions of this study include applying Structural Equation Modeling to reveal insights into the impact of entrepreneurial factors and obstacles. The findings can inform policymakers and educators in designing targeted interventions to support student entrepreneurship. Meanwhile, the limitations of this study encompass a small sample size, lack of time series and panel data and the absence of an evaluation of the impact of education system practices, along with the need to investigate the effects of young population emigration from Albania to the EU.Originality/valueThis research contributes to the understanding of digital entrepreneurial intentions and behavior by using TPB in the Albanian context, offering access to a diverse dataset from Albanian universities, testing the direct impact of innovativeness on entrepreneurial behavior and pioneering the use of machine learning techniques for text analysis. Thus, it provides novel insights into the entrepreneurial landscape in Albania. In addition, this work can drive initiatives to support student entrepreneurship and bridge the gap between academia and industry in Albania.
PurposeBased on the theory of planned behavior (TPB), the purpose of this study is to provide a well-supported explanation of how rural college students (RCS)’ entrepreneurial learning experiences (ELE) affect their returning home entrepreneurial intention (RHEI) through the three antecedents of TPB (Personal attitudes, PA; Subjective norms, SN and Perceived behavioral control, PBC).Design/methodology/approachAn extension of the TPB was proposed, including the additional constructs of entrepreneurial learning experiences(ELE). Data were collected from a sample of 986 rural college students from ten universities and colleges located in China using a survey questionnaire. SEM was used to test the hypotheses and the relationships between variables.FindingsRCS’ ELE significantly and positively influences the formation of their RHEI through the mediating effect of PBC. In addition, the three antecedents of TPB have direct and significant impact on RHEI, and PA, PBC indirectly mediate the relation between SN and RHEI.Practical implicationsThe results of this study have implications for entrepreneurship educators and policymakers by promoting RCS’ RHEI through optimize the content and methods of entrepreneurship education from the perspective of students learning, and strengthening publicity for rural entrepreneurship, increase support for returning home entrepreneurship.Originality/valueThe role of ELE in forming RCS' RHEI has been underestimated by previous studies. This study combines the push-pull theory with TPB to explore the formation mechanism of RCS’ RHEI, and helps to understand the role of ELE in shaping RHEI through the development of an extended TPB intention-based model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.