Artikel

Cross-country analysis to high-growth business: Unveiling its determinants

High-growth businesses are a relevant phenomenon for economies as they represent an important driver for economic growth and an efficient allocation of resources that can be inductive of wealth creation. Despite the importance that has been given to this phenomenon, inequalities regarding the ability to trigger and manage the entrepreneurial activity remain. In light of previous research, where perceptions of specialists from different countries through the Global Entrepreneurship Monitor (GEM) were analyzed, this research aims to describe and account for the entrepreneurship levels, particularly those influencing the high growth of the businesses. In order to compare, real data contrasts the experts' perceptions confirming the conclusions found through the analysis of the firms across different countries. In order to achieve this goal, our database combines country data from three databases, namely: OECD database; EUROSTAT database and HOFSTEDE database; in which observations from more than 35 countries was subjected to several multivariate analysis techniques, in particular the multiple linear regression analysis. In general, our results show that the high growth of business is positively related to the size of firms, the power distance index and negatively related to masculinity.

Language
Englisch

Bibliographic citation
Journal: Journal of Innovation & Knowledge (JIK) ; ISSN: 2444-569X ; Volume: 4 ; Year: 2019 ; Issue: 3 ; Pages: 146-153 ; Amsterdam: Elsevier

Classification
Management
Subject
Entrepreneurship
EUROSTAT
High growth business
OCDE

Event
Geistige Schöpfung
(who)
Queirós, Maria
Braga, Vítor
Correia, Aldina
Event
Veröffentlichung
(who)
Elsevier
(where)
Amsterdam
(when)
2019

DOI
doi:10.1016/j.jik.2018.03.006
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Queirós, Maria
  • Braga, Vítor
  • Correia, Aldina
  • Elsevier

Time of origin

  • 2019

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