Proceedings of the 3rd International Conference on Economy, Management and Entrepreneurship (ICOEME 2020)

Research on the Construction of Model and Measurement Index System for Evolution Process of High-tech Industrial Cluster

Authors
Xinjie Zhang, Yitao Zhang
Corresponding Author
Xinjie Zhang
Available Online 8 September 2020.
DOI
10.2991/aebmr.k.200908.025How to use a DOI?
Keywords
emerging technologies, industrial cluster, measurement index, logistic model
Abstract

Emerging technologies have significant characteristics of biological species, and the evolution of emerging technology industrial clusters conforms to the evolutionary law of biological life cycles. This paper builds and derives the evolution model of emerging technology industrial cluster based on the Logistic model in bio-mathematics, and establishes a measurement index system for the evolution process of high-tech industrial cluster based on the model, so as to propose targeted management strategies.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 3rd International Conference on Economy, Management and Entrepreneurship (ICOEME 2020)
Series
Advances in Economics, Business and Management Research
Publication Date
8 September 2020
ISBN
978-94-6239-052-2
ISSN
2352-5428
DOI
10.2991/aebmr.k.200908.025How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinjie Zhang
AU  - Yitao Zhang
PY  - 2020
DA  - 2020/09/08
TI  - Research on the Construction of Model and Measurement Index System for Evolution Process of High-tech Industrial Cluster
BT  - Proceedings of the 3rd International Conference on Economy, Management and Entrepreneurship (ICOEME 2020)
PB  - Atlantis Press
SP  - 150
EP  - 154
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200908.025
DO  - 10.2991/aebmr.k.200908.025
ID  - Zhang2020
ER  -