Reduction of Risk Control Indicators of ERP System Based on Rough Set

Zhi Heng Zhang; Yong Jun Hua

doi:10.4028/www.scientific.net/AMM.678.28

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 678Reduction of Risk Control Indicators of ERP System...

Reduction of Risk Control Indicators of ERP System Based on Rough Set

Abstract:

the risk evaluation indicator system by enterprise resource planning (ERP) system is characterized by excessive subjectivity, lack of reasonable basis for establishing, and redundancy. The paper adopts the rough set theory, proposes attribute reduction algorithm based on information entropy, and makes attribute reduction on risk control indicators for implementation of ERP system by integrating cases from 10 enterprises that have already implemented ERP systems. The resultsshow that attribute reduction algorithm based on rough set is effective and available on reduction of risk control indicator for implementation of ERP system.

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Periodical:

Applied Mechanics and Materials (Volume 678)

Pages:

28-34

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.678.28

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Cite this paper

Online since:

October 2014

Authors:

Zhi Heng Zhang*, Yong Jun Hua

Keywords:

ERP, Reduction Indicators, Risk Control, Rough Sets, System Implementation

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* - Corresponding Author

References

[1] Bai Haiqing, Mao Jiye. A Causation Model of the Key Factors that Impact on the Success of the Application of ERP[J]. MANAGEMENT WORLD, 2011(3), pp.102-111.

Google Scholar

[2] Zhu Zongqian, Ji Hao , YANG Dongmin. Model of Mining in Risk Estimation Information of ERP Implementation Based on Web[J], Computer Engineering, vol. 34-7(2008). pp.70-75.

Google Scholar

[3] Zhao Quanwu , Huang Zhizhong , Bu Xiangzhi . Emp irical study on impacts of ERP implementation on listed companies in China: Data from Shanghai stock exchange from 1993 to 2003[J], JOURNAL OF MANAGEMENT SCIENCES IN CH INA, Vol. 11-1(2008).

Google Scholar

[4] Zhu Zongqian, Zhang Shikui, Liao Xiuwu. Research on Evaluation Model of ERP Software Vendor and Consultant Based on QFD[J]. Industrial Engineering and Management, Vol. 17-3(2012), pp.8-15.

Google Scholar

[5] Chen Qingguang, Wang Kaikai. Risk Identification and Control in the ERP Implementation Based on Risk Matrix: a Case Study of Automobile Industry Company[J]. Journal of Intelligence, 2009(2), pp.84-89.

Google Scholar

[6] Z. Pawlak, Rough set[J]. International Journal of Computer Information Sciences, 1982, 11(5), pp.342-356.

Google Scholar

[7] Z. Pawlak，Rough set theory and its applications to data analysis[J]. Cybernetics and Systems, 1998, 29, pp.661-688.

DOI: 10.1080/019697298125470

Google Scholar

[8] Wang Xue-en，Han Chongzhao，Han Deqiang. A Survey of Rough sets Theory[J]. Control Engineering of China, Vol. 20-1(2003), pp.1-8.

Google Scholar