@ARTICLE{26543116_508618847_2021, 
	author = {Marta Gancarczyk and Sławomir Konopa}, 
	keywords = {, entrepreneurial ecosystems, high-growth enterprises, governanceproductive entrepreneurship},
	title = {<p class="text">Exploring the Governance of Entrepreneurial Ecosystems for Productive High Growth</p>},
	journal = {Foresight and STI Governance},
	year = {2021},
	volume = {15},
	number = {4},
	pages = {9-21},
	url = {https://foresight-journal.hse.ru/en/2021-15-4/508618847.html},
	publisher = {},
	abstract = {This paper aims to empirically identify the characteristics and governance types of regional entrepreneurial ecosystems (EEs) associated with productive high-growth entrepreneurship (PHGE). We developed a unique database comprised of public statistics on high-growth enterprises and regional EEs in Poland over the course of 2011-2018. The Hierarchical Clustering on Principal Components and a taxonomic analysis were used to identify how different types of EE governance relate to varying levels of high-growth enterprises&rsquo; performance. We have identified and described the relationships between PHGE and diverse clusters of EE governance and evolution stages toward developed structures. Two clusters proved similarly effective in generating PHGE and they represent alternative EE governance solutions as well as the most advanced evolutionary phases. The proposed conceptualizations of productive high-growth entrepreneurship and EE governance types advance the understanding and measurement of these phenomena. The profiling and configurational approach adopted in this research reflects the heterogeneity of EE governance types and outcomes and can be further replicated in other research settings.},
	annote = {This paper aims to empirically identify the characteristics and governance types of regional entrepreneurial ecosystems (EEs) associated with productive high-growth entrepreneurship (PHGE). We developed a unique database comprised of public statistics on high-growth enterprises and regional EEs in Poland over the course of 2011-2018. The Hierarchical Clustering on Principal Components and a taxonomic analysis were used to identify how different types of EE governance relate to varying levels of high-growth enterprises&rsquo; performance. We have identified and described the relationships between PHGE and diverse clusters of EE governance and evolution stages toward developed structures. Two clusters proved similarly effective in generating PHGE and they represent alternative EE governance solutions as well as the most advanced evolutionary phases. The proposed conceptualizations of productive high-growth entrepreneurship and EE governance types advance the understanding and measurement of these phenomena. The profiling and configurational approach adopted in this research reflects the heterogeneity of EE governance types and outcomes and can be further replicated in other research settings.}
}