TY - GEN
T1 - Drivers of Entrepreneurial Activity at Micro and Meso Levels
T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2021
AU - Kinnunen, Jani
AU - Georgescu, Irina
AU - Hosseini, Zahra
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021/8/24
Y1 - 2021/8/24
N2 - The implications of entrepreneurial conditions, opportunities, and attitudes for total entrepreneurial activity (TEA) are under study. The data is obtained from the Global Entrepreneurship Monitor and Heritage Foundation for ten European Union countries, which had long enough time-series data available. The set of indicators include variables to determine the difficulty to start a business, motivations, ambitions, and attitudes of citizens towards entrepreneurship, and economic freedoms from which 7 key indicators were selected. The target variable is TEA and time-period is 2011–2019. The applied time-series analysis compares firstly linear regression accounting for autoregression by classical crisp model, possibilistic least squares linear model with crisp inputs and fuzzy outputs, and fuzzy multi-objective linear model with fuzzy inputs and outputs; secondly, the analysis is complemented by vector error correction model to study long-run causality of the key drivers of TEA. The results extend studies on the connections of entrepreneurial activity and economic freedoms by accounting for behavioral and attitude factors: entrepreneurial finance, grants and subsidies together with established entrepreneurial community support risk-taking of new entrepreneurs, who have identified business opportunities; further, entrepreneurial female/male ratio showed short-run effects, while statistically significant long-run causalities could not be established.
AB - The implications of entrepreneurial conditions, opportunities, and attitudes for total entrepreneurial activity (TEA) are under study. The data is obtained from the Global Entrepreneurship Monitor and Heritage Foundation for ten European Union countries, which had long enough time-series data available. The set of indicators include variables to determine the difficulty to start a business, motivations, ambitions, and attitudes of citizens towards entrepreneurship, and economic freedoms from which 7 key indicators were selected. The target variable is TEA and time-period is 2011–2019. The applied time-series analysis compares firstly linear regression accounting for autoregression by classical crisp model, possibilistic least squares linear model with crisp inputs and fuzzy outputs, and fuzzy multi-objective linear model with fuzzy inputs and outputs; secondly, the analysis is complemented by vector error correction model to study long-run causality of the key drivers of TEA. The results extend studies on the connections of entrepreneurial activity and economic freedoms by accounting for behavioral and attitude factors: entrepreneurial finance, grants and subsidies together with established entrepreneurial community support risk-taking of new entrepreneurs, who have identified business opportunities; further, entrepreneurial female/male ratio showed short-run effects, while statistically significant long-run causalities could not be established.
KW - Economic freedoms
KW - Entrepreneurial activity
KW - Entrepreneurial conditions
KW - Fuzzy time-series analysis
KW - VECM
U2 - 10.1007/978-3-030-85577-2_50
DO - 10.1007/978-3-030-85577-2_50
M3 - Conference contribution
AN - SCOPUS:85115249060
SN - 978-3-030-85576-5
T3 - Lecture Notes in Networks and Systems
SP - 423
EP - 430
BT - Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
A2 - Kahraman, Cengiz
A2 - Cebi, Selcuk
A2 - Cevik Onar, Sezi
A2 - Oztaysi, Basar
A2 - Tolga, A. Cagri
A2 - Sari, Irem Ucal
PB - Springer
Y2 - 24 August 2021 through 26 August 2021
ER -