Notice of Retraction: Primarily Research on Knowledge Audit for Evaluating Enterprise Knowledge Management Capability

Bai-min, Suo; Wang, Jia-Bin; Han-bing, Zhang

doi:10.1109/icmss.2009.5302226

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…The tool was validated by various case studies from different industries. A combination of an enterprise knowledge management system based on an environmentprocess-capability and a knowledge audit model was presented by Suo Bai-min et al [20]. It was reported that such a tool enhanced the knowledge management capability of an enterprise.…”

Section: Communications Managementmentioning

confidence: 99%

A Softcomputing Knowledge Areas Model

Arafeh¹,

Mufid²

2015

J. Manage. Sci. Inform. Sys.

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Recently, ten knowledge areas (KAs) of project management have been published by the PMBOK® Guide. They comprise specific skills and experiences to ensure accomplishing project goals, and include management of: integration, scope, cost, time, quality, communications, procurement, risk, human resources and stakeholders. This research paper focuses on the ten required KAs for a project manager or a project to be successful. It aims at applying the Softcomputing modeling techniques to describe the relations between the 47 processes and the KAs. Such a model will enable users to predict the overall competencies of the project management. Thus, it provides an assessment tool to envisage, visualize and indicate the overall performance and competency of a project.The proposed Softcomputing Knowledge Areas Model (SKAM) is a two-stage model. The first stage involves ten models. Each model describes relations between a specific KA and its related processes. The outputs of these ten models will feed into the second stage that will represent the relationship between all the ten KAs and the overall predicted competencies of a project. A combination of Subtractive Clustering and Neurofuzzy modeling techniques are used. Three measures are used to validate the adequacy of the models: the mean average percentage errors, the correlation coefficient and the maximum percentage errors. The highest achieved values for these measures are0.5751, 0.9999 and 4.7283, respectively. However, although the preliminary findings of the proposed SKAM model are promising, more testing is still required before declaring the adequacy of applying the Softcomputing modeling approach in the project management field.

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Section: Communications Managementmentioning

confidence: 99%

A Softcomputing Knowledge Areas Model

Arafeh¹,

Mufid²

2015

J. Manage. Sci. Inform. Sys.

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“…It shows the questionnaire is reliable and can be used for the intended study. Table 1-Knowledge audit processes and activities Activity Sub-activity Perezsoltero [20] Cheung [21] Suo [22 ] Sharma [9] Jiuling [ 23] Lee [24] Wu [25] Ganasan [ 26] Knowledge Acquisition…”

Section: Proceedings Of the 2014 Ieee Ieemmentioning

confidence: 99%

Identifying knowledge components in software requirement elicitation

Taheri

Abdullah

et al. 2014

2014 IEEE International Conference on Industrial Engineering and Engineering Management

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This paper considers the importance of knowledge in software development organizations which are highly knowledge-intensive and focuses on knowledge audit in their requirement elicitation process. Requirement elicitation process involves a great deal of knowledge and there are several problems regarding eliciting and using the knowledge in this process. Misunderstanding, undefined scope, conflicting information and constant changes of requirements are some of the problems of requirement elicitation. A knowledge audit model is proposed in this paper to improve the requirement elicitation process by identifying knowledge components and knowledge sources existing in the requirement elicitation process as well as their relationships. A survey is then conducted to prove the validity of the model. The results support that the proposed knowledge components and knowledge audit model improves requirement elicitation.

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Cloud computing technology for the petroleum application

Chen

Chang

2016

2016 18th International Conference on Advanced Communication Technology (ICACT)

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Notice of Retraction: Primarily Research on Knowledge Audit for Evaluating Enterprise Knowledge Management Capability

Cited by 4 publications

References 2 publications

A Softcomputing Knowledge Areas Model

A Softcomputing Knowledge Areas Model

Identifying knowledge components in software requirement elicitation

Cloud computing technology for the petroleum application

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