The paper sought to make contribution to youth entrepreneurship research field. This is because whilst youth entrepreneurship presents enormous socio-economic benefits, including economic growth, diversification, innovation and poverty elimination earlier research have paid more attention to adults' entrepreneurship with less attention been paid to youth entrepreneurship resulting in a compelling research gap following the present huge youth unemployment across the world. Consequently, the motivation of the paper is to guide public policy and practice on the promotion of youth entrepreneurship, especially in developing countries.
The study employs the survey research design based on logistic regression analysis as the key analytical technique to examine data. The choice of the logistic regression model is due to the fact that the main research question that informs the study is a dichotomous one. Hence it was found appropriate to select the logit regression model based on similar works in the field.
Over all, the results show that lack of financial support from one's family background, early entry into formal employment, as well as being born into entrepreneurial dominated families significantly predict the probability of a youth considering entrepreneurship as an attractive life venture.
The study is based on non-probability sampling method and so readers must bear that in mind when they are interpreting the results.
Following from the findings, one of the practical implications is that youth entrepreneurs must align the external influences to the internal capacity of the businesses to initiate and/or start sustainable entrepreneurial ventures.
The study sheds light from an under-explored and new geographical context to advance existing knowledge in the field.
The author wishes to acknowledge the financial support of the Research and Conference Committee of the University of Ghana Business School.
Damoah, O.B.O. (2020), "Strategic factors predicting the likelihood of youth entrepreneurship in Ghana: a logistic regression analysis", World Journal of Entrepreneurship, Management and Sustainable Development, Vol. 16 No. 4, pp. 389-401. https://doi.org/10.1108/WJEMSD-06-2018-0057
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