DocumentCode
2731223
Title
Notice of Retraction
Research on Chinese cities comprehensive competitiveness based on principal component analysis and factor analysis in SPSS
Author
Niu Dongxiao ; Tian Jie ; Ji Ling
Author_Institution
Dept. of Bus. & Adm. Manage., North China Electr. Power Univ., Beijing, China
fYear
2011
fDate
15-17 July 2011
Firstpage
868
Lastpage
871
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Factor analysis and principal component analysis are commonly used in multivariate statistical analysis. This paper has shown similarities and differences of principal component analysis and factor analysis in mathematical model and solution procedure. And we select some important indexes of Chinese cities comprehensive competitiveness, use economics software SPSS to carry on the principal component analysis and factor analysis, and get comprehensive score. At last, we analyze the influential factors of cities competitiveness to provide support and protection for the development of cities.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Factor analysis and principal component analysis are commonly used in multivariate statistical analysis. This paper has shown similarities and differences of principal component analysis and factor analysis in mathematical model and solution procedure. And we select some important indexes of Chinese cities comprehensive competitiveness, use economics software SPSS to carry on the principal component analysis and factor analysis, and get comprehensive score. At last, we analyze the influential factors of cities competitiveness to provide support and protection for the development of cities.
Keywords
principal component analysis; town and country planning; Chinese cities comprehensive competitiveness; SPSS; economics software SPSS; factor analysis; multivariate statistical analysis; principal component analysis; Cities and towns; Correlation; Eigenvalues and eigenfunctions; Indexes; Loading; Principal component analysis; Software; SPSS; city competitiveness; factor analysis; principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2011 IEEE 2nd International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-9699-0
Type
conf
DOI
10.1109/ICSESS.2011.5982478
Filename
5982478
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