Study of data governance evaluation in enterprises based on grouping method for combining evidence

Gang Wang; Yang Wang; Jue Wang; Shanlin Yang

doi:10.12011/1000-6788(2016)06-1505-12

Study of data governance evaluation in enterprises based on grouping method for combining evidence

Gang Wang
, Yang Wang
, Jue Wang
, Shanlin Yang

School of Management

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

In order to properly evaluate the level of data governance in enterprises, a data governance evaluation model based on a grouping method for combining evidence was proposed. Firstly, the evaluation index system of data governance is built and the indexes weights are determined. Secondly, in order to solve the "0 absolutization" problem and reduce the conflict of evidence, language evaluation sets and evidence grouping methods are used in this research. Then, the final results are gotten by combining the evidence twice within a group and between groups. Finally, the data governance of H commercial bank was selected to experiment. Empirical results verified the effectiveness and practicality of the proposed method.

Original language	English
Pages (from-to)	1505-1516
Number of pages	12
Journal	Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
Volume	36
Issue number	6
DOIs	https://doi.org/10.12011/1000-6788(2016)06-1505-12
State	Published - 25 Jun 2016

Keywords

Data governance evaluation
Evidence distance
Evidence theory
Grouping combination
Language evaluation sets

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10.12011/1000-6788(2016)06-1505-12

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title = "Study of data governance evaluation in enterprises based on grouping method for combining evidence",

abstract = "In order to properly evaluate the level of data governance in enterprises, a data governance evaluation model based on a grouping method for combining evidence was proposed. Firstly, the evaluation index system of data governance is built and the indexes weights are determined. Secondly, in order to solve the {"}0 absolutization{"} problem and reduce the conflict of evidence, language evaluation sets and evidence grouping methods are used in this research. Then, the final results are gotten by combining the evidence twice within a group and between groups. Finally, the data governance of H commercial bank was selected to experiment. Empirical results verified the effectiveness and practicality of the proposed method.",

keywords = "Data governance evaluation, Evidence distance, Evidence theory, Grouping combination, Language evaluation sets",

author = "Gang Wang and Yang Wang and Jue Wang and Shanlin Yang",

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AU - Wang, Gang

AU - Wang, Yang

AU - Wang, Jue

AU - Yang, Shanlin

PY - 2016/6/25

Y1 - 2016/6/25

N2 - In order to properly evaluate the level of data governance in enterprises, a data governance evaluation model based on a grouping method for combining evidence was proposed. Firstly, the evaluation index system of data governance is built and the indexes weights are determined. Secondly, in order to solve the "0 absolutization" problem and reduce the conflict of evidence, language evaluation sets and evidence grouping methods are used in this research. Then, the final results are gotten by combining the evidence twice within a group and between groups. Finally, the data governance of H commercial bank was selected to experiment. Empirical results verified the effectiveness and practicality of the proposed method.

AB - In order to properly evaluate the level of data governance in enterprises, a data governance evaluation model based on a grouping method for combining evidence was proposed. Firstly, the evaluation index system of data governance is built and the indexes weights are determined. Secondly, in order to solve the "0 absolutization" problem and reduce the conflict of evidence, language evaluation sets and evidence grouping methods are used in this research. Then, the final results are gotten by combining the evidence twice within a group and between groups. Finally, the data governance of H commercial bank was selected to experiment. Empirical results verified the effectiveness and practicality of the proposed method.

KW - Data governance evaluation

KW - Evidence distance

KW - Evidence theory

KW - Grouping combination

KW - Language evaluation sets

UR - https://www.scopus.com/pages/publications/84984604641

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SN - 1000-6788

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JO - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice

JF - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice

IS - 6

ER -

Study of data governance evaluation in enterprises based on grouping method for combining evidence

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Keywords

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