A configurational perspective on comparative international entrepreneurship: a new approach to examining entrepreneurial activity combining clustering and qualitative comparative analysis

Abstract

Purpose For two decades, the Global Entrepreneurship Monitor (GEM) has collected survey and national expert data to better understand entrepreneurial activity and the country context within which this occurs. In this paper, we re-envision GEM’s country groupings, positing a novel approach to more fully understanding the nuances of entrepreneurial activity. Design/methodology/approach Using data from the GEM’s Entrepreneurial Framework Conditions (EFCs) (2017–2020), we employ an unsupervised machine learning method (clustering) to classify countries into distinct groups according to country-specific government policies, education, sociocultural, and entrepreneurship infrastructure support. Then, building on the identified two sets of distinct economies (termed as “matured” and “maturing” entrepreneurial economies) and using the GEM’s data on Entrepreneurial Behaviour and Attitudes (EBAs), fuzzy-set Qualitative Comparative Analysis (fsQCA) is applied to highlight the complex nature of entrepreneurial intentions and to identify configurations of possible conditions that confirm intention pathways in entrepreneurial activities in each cluster of economies. Findings Our key findings suggest that in “matured” economies, where entrepreneurship is well-supported, people are driven by opportunity and a supportive environment. Moreover, in “maturing” economies, where there is less support, factors like personal status and overcoming fear of failure play a bigger role in their motivations. This new perspective is crucial not just for understanding entrepreneurship but also for shaping policies that truly support budding entrepreneurs. The results suggest that governments should tailor their support for entrepreneurship based on their maturity level. Originality/value Historically, GEM grouped countries based on the level of economic development (efficiency, innovation and factor economies) and, more recently, used the level of income (high, medium and low). Both categorisations are essentially outcome factors reflecting economic progress. While it is useful to compare countries based on these dimensions, we propose grouping based on entrepreneurial framework or contextual conditions, enabling scholars and policy makers alike to better understand how context influences entrepreneurial activity.

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