Research Article

Determination and classification of entrepreneurial efficiency of countries: Data envelopment analysis and hierarchical clustering analysis

Volume: 17 Number: 1 January 31, 2024
EN TR

Determination and classification of entrepreneurial efficiency of countries: Data envelopment analysis and hierarchical clustering analysis

Abstract

Entrepreneurship initiatives have undeniable effects on national economies. States and governments produce various strategies and policies to increase the contribution of entrepreneurship to the country's economy. Entrepreneurship levels of countries are determined by various organizations. Country entrepreneurship scores and rankings are regularly published by the “Global entrepreneurship monitor (GEM)”. Countries, on the other hand, understand their current level of entrepreneurship according to these reports. In this research, it is aimed to determine the entrepreneurial activity efficiency levels (EAE) of the countries with the data obtained from the GEM 2021 reports and to cluster them according to their activity levels. In this context, forty-two country data of five indicators presented in the 2021 GEM report were used. The research was carried out in two stages. In the first stage, four output-oriented data envelopment (DEA) models were created and the EAE were determined. In the second stage, the clustering of countries according to their EAEs was carried out by hierarchical clustering analysis. According to the research findings, 21 countries were at full efficiency in the DEA-1 model, 22 countries were at full efficiency in the DEA-2 model, and 18 countries were at full efficiency in the DEA-3 and DEA-4 models. In the hierarchical clustering analysis, the countries are clustered in three groups. Twenty-two countries were included in Cluster-1, seven countries in Cluster-2, and thirteen countries in Cluster-3. Cluster-1, Cluster-2 and Cluster-3 were characterized as high, middle, and low efficiency levels, respectively. As a result of the research, suggestions were made to countries to improve their entrepreneurial activities.

Keywords

National Entrepreneurship , Country Entrepreneurship Efficiency , Data Envelopment Analysis , Hierarchical Cluster Analysis

References

  1. Ács, Z. J., Autio, E., & Szerb, L. (2014). National systems of entrepreneurship: Measurement issues and policy implications. Research policy, 43(3), 476-494. https://doi.org/10.1016/j.respol.2013.08.016
  2. Aldrich, H. E., & Cliff, J. E. (2003). The pervasive effects of family on entrepreneurship: Toward a family embeddedness perspective. Journal of business venturing, 18(5), 573-596. https://doi.org/10.1016/S0883-9026(03)00011-9
  3. Aparicio, S., Turro, A., & Noguera, M. (2020). Entrepreneurship and intrapreneurship in social, sustainable, and economic development: opportunities and challenges for future research. Sustainability, 12(21), 8958. https://doi.org/10.3390/su12218958
  4. Arafat, M. Y., & Saleem, I. (2017). Examining start-up Intention of Indians through cognitive approach: a study using GEM data. Journal of Global Entrepreneurship Research, 7(1), 1-11. https://doi.org/10.1186/s40497-017-0073-3
  5. Baggen, Y., Lans, T., Biemans, H. J., Kampen, J., & Mulder, M. (2016). Fostering Entrepreneurial Learning On‐the‐Job: evidence from innovative small and medium‐sized companies in Europe. European Journal of Education, 51(2), 193-209. https://doi.org/10.1111/ejed.12171
  6. Bergmann, H., & Stephan, U. (2013). Moving on from nascent entrepreneurship: Measuring cross-national differences in the transition to new business ownership. Small business economics, 41(4), 945-959. https://doi.org/10.1007/s11187-012-9458-4
  7. Bosma, N. (2013). The Global Entrepreneurship Monitor (GEM) and its impact on entrepreneurship research. Foundations and Trends® in Entrepreneurship, 9(2), 143-248. http://dx.doi.org/10.1561/0300000033
  8. Bosma, N. S., & Levie, J. (2010). Global Entrepreneurship Monitor 2009 Executive Report. Utrecht University Repository.
  9. Caliendo, M., Fossen, F., & Kritikos, A. S. (2014). Personality characteristics and the decisions to become and stay self-employed. Small Business Economics, 42(4), 787-814. https://doi.org/10.1007/s11187-013-9514-8
  10. Callegari, B., & Nybakk, E. (2022). Schumpeterian theory and research on forestry innovation and entrepreneurship: The state of the art, issues and an agenda. Forest Policy and Economics, 138, 102720. https://doi.org/10.1016/j.forpol.2022.102720
APA
Kaygısız, E., Sahin, B., & Kara, K. (2024). Determination and classification of entrepreneurial efficiency of countries: Data envelopment analysis and hierarchical clustering analysis. Academic Review of Economics and Administrative Sciences, 17(1), 85-112. https://doi.org/10.25287/ohuiibf.1316415