東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

An enterprise knowledge-sharing mode...

Small, Cynthia Taylor.

Linked to FindBook

Google Book

Amazon

博客來

An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing.

Record Type:	Electronic resources : Monograph/item
Title/Author:	An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing./
Author:	Small, Cynthia Taylor.
Description:	330 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1150.
Contained By:	Dissertation Abstracts International66-02B.
Subject:	Engineering, System Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3163738
ISBN:	0496982141

An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing.
Small, Cynthia Taylor.

An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing. - 330 p.

Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1150.

Thesis (Ph.D.)--George Mason University, 2005.

Knowledge sharing (KnS), which contributes to an enterprise's ability to create and leverage knowledge, relates to the diffusion of knowledge at the individual, group, enterprise, and inter-enterprise levels. Enterprises that have successfully implemented KnS practices and technologies report improved enterprise performance and enhanced competitiveness. Enhancing knowledge sharing is often a major goal of enterprise knowledge management initiatives. Previous KnS studies and research have resulted in the identification of factors within the KnS environment (e.g., leadership, behavior of peers, culture, KnS technology, and rewards & recognition) that influence KnS behavior, but generally provide minimum insight into the extent of influence of these factors.

ISBN: 0496982141Subjects--Topical Terms:

1018128
Engineering, System Science.

An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing.
LDR:03377nmm 2200289 4500 001 1845489
005 20051101074958.5
008 130614s2005 eng d
020 $a 0496982141
035 $a (UnM)AAI3163738
035 $a AAI3163738
040 $a UnM $c UnM
100 1 $a Small, Cynthia Taylor. $3 1933645
245 1 3 $a An enterprise knowledge-sharing model: A complex adaptive systems perspective on improvement in knowledge sharing.
300 $a 330 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1150.
500 $a Director: Andrew P. Sage.
502 $a Thesis (Ph.D.)--George Mason University, 2005.
520 $a Knowledge sharing (KnS), which contributes to an enterprise's ability to create and leverage knowledge, relates to the diffusion of knowledge at the individual, group, enterprise, and inter-enterprise levels. Enterprises that have successfully implemented KnS practices and technologies report improved enterprise performance and enhanced competitiveness. Enhancing knowledge sharing is often a major goal of enterprise knowledge management initiatives. Previous KnS studies and research have resulted in the identification of factors within the KnS environment (e.g., leadership, behavior of peers, culture, KnS technology, and rewards & recognition) that influence KnS behavior, but generally provide minimum insight into the extent of influence of these factors.
520 $a The purpose of this research is to develop a complex adaptive systems (CAS) based model for enterprise knowledge sharing that can provide knowledge management (KM) leaders and KM practitioners with enhanced understanding of KnS behavior and its influences. The premise of this research is that enhanced understanding of KnS behavior is needed to better identify and prioritize the diverse KM courses of action that can lead to improved knowledge sharing for enhanced organizational effectiveness. Enterprise KnS behavior is investigated from the individual knowledge worker perspective to gain insight into the extent of KnS influences, to determine if KnS behavior and its influences are related to the attributes of the knowledge worker, and to describe how best to utilize this information for KM enhancement. KnS behavior is modeled as having three major influences: enterprise KnS environment, KnS behavior of other knowledge workers, and attributes of the knowledge worker.
520 $a This research contributes a CAS-based enterprise KnS model and a methodology that guides KM leadership and practitioners in the use the model. The CAS-based enterprise KnS methodology incorporates the use of the CAS-based KnS Framework, the CAS-based enterprise KnS characterization instruments, and the multi-agent KnS simulation model developed as part of this research. The CAS-based model and methodology were evaluated in two cases studies conducted in operational KnS environments. The results of the case studies support the validity of the model and its effectiveness in providing KM leadership and practitioners with enhanced understanding of enterprise KnS behavior and its influences.
590 $a School code: 0883.
650 4 $a Engineering, System Science. $3 1018128
690 $a 0790
710 2 0 $a George Mason University. $3 1019450
773 0 $t Dissertation Abstracts International $g 66-02B.
790 1 0 $a Sage, Andrew P., $e advisor
790 $a 0883
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3163738