Proceedings of the Second International Conference On Economic and Business Management (FEBM 2017)

Measurement and statistical analysis of financing efficiency of listing companies —taking Shandong province as a case

Authors
Guizhen Meng
Corresponding Author
Guizhen Meng
Available Online October 2017.
DOI
https://doi.org/10.2991/febm-17.2017.137How to use a DOI?
Keywords
financing efficiency; principal component analysis; entropy method
Abstract
The thesis adopts the principal component analysis and entropy method to set up a model for calculating and carrying out a statistical analysis of the financing efficiency of listing companies within the jurisdiction of Shangdong Province. First, the thesis sets up a financing efficiency evaluation indicator system according to financing theories. Next, it adopts the principal component analysis to abstract five principal factors influencing the financing efficiency. Later, the thesis adopts the entropy method to analyze the total score of each sample. Later, it draws the conclusion that the listing companies within the jurisdiction of Shandong Province universally have a low financing efficiency. Lastly, the thesis analyzes the reason for drawing the conclusion and proposes relevant countermeasures.
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Proceedings
Second International Conference On Economic and Business Management (FEBM 2017)
Part of series
Advances in Economics, Business and Management Research
Publication Date
October 2017
ISBN
978-94-6252-423-1
ISSN
2352-5428
DOI
https://doi.org/10.2991/febm-17.2017.137How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Guizhen Meng
PY  - 2017/10
DA  - 2017/10
TI  - Measurement and statistical analysis of financing efficiency of listing companies —taking Shandong province as a case
BT  - Second International Conference On Economic and Business Management (FEBM 2017)
PB  - Atlantis Press
SN  - 2352-5428
UR  - https://doi.org/10.2991/febm-17.2017.137
DO  - https://doi.org/10.2991/febm-17.2017.137
ID  - Meng2017/10
ER  -