DocumentCode :
2990891
Title :
System method of evaluating core competence of Enterprise based on artificial neural network
Author :
Gao Xi-chao ; Fan Li-li ; Deng Yu
Author_Institution :
Sch. of Econ. & Manage., Southwest Jiaotong Univ., Chengdu, China
fYear :
2012
fDate :
20-22 Sept. 2012
Firstpage :
257
Lastpage :
269
Abstract :
Core competence of the enterprise is a complete system, which is composited by all sorts of related resources or ability correlated with each other. According to the Resource-Theory and Capability-Theory, the source of core competence can be concluded to seven aspects, which are Plan Ability, Organization Ability, Human Resources, Intellectual Property, Enterprise Culture, Market Capacity and Production Capacity. It´s necessary to look at each component of core competence from different perspectives for a comprehensive understanding. So the evaluation index system is designed in multidimension such as Value, Sustainability, Inimitability. This article evaluates the core competence of the enterprise by using artificial neural network, and uses the idea of AHP to solve the problem of determining the output of training sample in the neural network. Lastly, there is an empirical research by the BP neural network method, which evaluates the core competence of motor listed companies.
Keywords :
analytic hierarchy process; human resource management; neural nets; organisational aspects; AHP; BP neural network method; artificial neural network; capability-theory; enterprise core competence; enterprise culture; human resources; intellectual property; market capacity; motor listed companies; organization ability; plan ability; production capacity; resource-theory; Capacity planning; Companies; Data models; Indexes; Neural networks; Training; Analytic Hierarchy; Artificial Neural Network; core competence; evaluation approach;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering (ICMSE), 2012 International Conference on
Conference_Location :
Dallas, TX
ISSN :
2155-1847
Print_ISBN :
978-1-4673-3015-2
Type :
conf
DOI :
10.1109/ICMSE.2012.6414192
Filename :
6414192
Link To Document :
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