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Title The Impact of Green Entrepreneurship on Social Change and Factors Influencing AMO Theory
ID_Doc 68477
Authors Mia, MM; Rizwan, S; Zayed, NM; Nitsenko, V; Miroshnyk, O; Kryshtal, H; Ostapenko, R
Title The Impact of Green Entrepreneurship on Social Change and Factors Influencing AMO Theory
Year 2022
Published Systems, 10, 5
Abstract This study analyses the importance of the entrepreneurial intention of university students to promote social change by green entrepreneurship in regard to the three most vibrant components of AMO (Ability, Motivation, and Opportunity) theory, developed by the partial least square structural equation model (PLS-SEM). The entrepreneurial intention among students is identified via a deductive approach and this approach is developed using a PLS-SEM. The literature exploited and the methodology used comprise a full exploratory analysis technique to collect empirical data to find the predictor variables that influence the promotion of social changes connected to the mediating variable of green entrepreneurship. The survey data were collected from a total of 302 respondents through survey questionnaires from the students. The data were examined statistically to demonstrate the hypotheses predicted from the literature review. The outcomes of the hypothesis association showed that AMO theory influences the predictor variables of skills, incentives, and entrepreneurship education, and that these skills are statistically significant and accepted towards green entrepreneurship. However, the importance of a green entrepreneurship strategy is influenced by the entrepreneurial intention that encourages the promotion of social change. Therefore, the present study helps researchers to find the structural relationship between different wings connecting AMO theory with the entrepreneurial intention that incurs and develops sustainable business performance to create jobs, instead of searching for jobs. Secondly, this study also indicates a mixed approach where participants can openly discuss their opinion and understanding. Ultimately, this study encourages the use of the covariance-based structural equation model (CB-SEM) by confirming its theory, and testing the confirmatory factor analysis in particular.
PDF https://www.mdpi.com/2079-8954/10/5/132/pdf?version=1662004106

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