<abstract xmlns="http://www.w3.org/1999/xhtml">

This paper uses multivariate statistical analysis to explore the ordinary least squares regression algorithm, principal component regression algorithm, and partial least squares regression algorithm. Then, an index system for entrepreneurial management performance assessment was constructed with public innovation space, resource collocation and entrepreneurial performance indicators, and an entrepreneurial management performance mediation model was established with this. Finally, the quartiles of entrepreneurial performance's principal components were derived by studying the relationship between entrepreneurial performance assessment and each input. The results show that the first principal component <italic>Z</italic>1 of entrepreneurial performance is significant at all quartiles, while the second principal component <italic>Z</italic>2 is significant only at the 0.6 quartiles, and the constant terms are significant at the 0.6, 0.7, and 0.8 quartiles. Multivariate statistical analysis is employed in this paper to provide a reference for entrepreneurship management and to assess entrepreneurial performance more accurately.
</abstract>

This paper uses multivariate statistical analysis to explore the ordinary least squares regression algorithm, principal component regression algorithm, and partial least squares regression algorithm. Then, an index system for entrepreneurial management performance assessment was constructed with public innovation space, resource collocation and entrepreneurial performance indicators, and an entrepreneurial management performance mediation model was established with this. Finally, the quartiles of entrepreneurial performance's principal components were derived by studying the relationship between entrepreneurial performance assessment and each input. The results show that the first principal component Z1 of entrepreneurial performance is significant at all quartiles, while the second principal component Z2 is significant only at the 0.6 quartiles, and the constant terms are significant at the 0.6, 0.7, and 0.8 quartiles. Multivariate statistical analysis is employed in this paper to provide a reference for entrepreneurship management and to assess entrepreneurial performance more accurately.

A study of entrepreneurial management performance assessment method based on multivariate statistical analysis

Guilin University of Aerospace Technology

Guilin University of Electronic Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper uses multivariate statistical analysis to explore the ordinary least squares regression algorithm, principal component regression algorithm, and...

A study of entrepreneurial management performance assessment method based on multivariate statistical analysis

Publié en ligne: 28 oct. 2023

Pages: -

Reçu: 07 févr. 2023

Accepté: 08 mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00837

Mots clés
Multivariate statistical analysis, Principal component regression, Entrepreneurial management, Performance assessment, Quantile

© 2023 Zhiyuan Teng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A study of entrepreneurial management performance assessment method based on multivariate statistical analysis

Publié en ligne: 28 oct. 2023

Pages: -

Reçu: 07 févr. 2023

Accepté: 08 mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00837

Mots clésMultivariate statistical analysis, Principal component regression, Entrepreneurial management, Performance assessment, Quantile

© 2023 Zhiyuan Teng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Multivariate statistical analysis, Principal component regression, Entrepreneurial management, Performance assessment, Quantile