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Predicting the Entrepreneurial Behaviour of Starting Up a New Company: A Regional Study Using PLS-SEM and Data from the Global Entrepreneurship Monitor
Tipo: Artículo
Idioma: Inglés
Título:
Predicting the Entrepreneurial Behaviour of Starting Up a New Company: A Regional Study Using PLS-SEM and Data from the Global Entrepreneurship Monitor
It is essential to understand the variables that explain and predict the behaviour of starting up a new company in a regional context. This study aims to analyse the theoretical basis and predictive potential of the Global Entrepreneurship Monitor (GEM) data, considering the concerns and suggestions of other authors. In addition to an extensive literature review, a PLS-SEM methodology and data on variables and countries from the latest GEM report are used in this study. The results show that GEM reports have a sufficient theoretical foundation for quality studies in this field. In addition, a valid and reliable causal model is designed that includes all personal and contextual GEM variables. The hypotheses of the proposed model are based on the existing causal relationships in the literature, using GEM data in its formulation. The model is comprehensive and practical because it significantly predicts entrepreneurial behaviour, particularly entrepreneurial intention and action.
The usefulness of this study is high, both for researchers, practitioners and institutions wishing to understand better and further promote entrepreneurial behaviour at a regional (country) level.
Autores:
José Alberto Martínez-González
Carmen Dolores Álvarez-Albelo
Javier Mendoza-Jiménez
Urszula Kobylinska
Publicación:
A Regional Study Using
PLS-SEM and Data from the Global
Entrepreneurship Monitor.
Mathematics 2022, 10, 704.
DOI: https://doi.org/10.3390/math10050704
Año: 2022
Aportado por: José Carlos Sánchez García