Proceedings of the 12th European Conference on Knowledge ...

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Halimah Abdul Manaf, Steven Armstrong and Alan Lawton Table 1: Reliability analysis for <strong>the</strong> KSP, TKIM and BFI Variables n Mean SD α KSP: 1. Mentoring Programme1 310 4 .48 0.867 (8) (Competence) 2. Mentoring Programme2 310 4 .59 0.770 (4) (Behaviour) 3. Individual Codification 310 3.7 .69 0.670 (2) 4. Individual Personalization 310 4.1 .58 0.646 (3) 5. Institutional Codification 310 3.9 .57 0.820 (5) 6. Institutional Personalization 310 4 .52 0.732 (4) 7. Knowledge Sharing Practices 310 3.9 .38 0.893 (26) TKIM: 1. Managing Tasks 310 1.27 0.544 0.749 (11) 2. Managing O<strong>the</strong>rs 310 1.26 0.534 0.848 (9) 3. Managing Self 310 0.83 0.468 0.663 (12) 4. Total Tacit Knowledge 310 1.02 0.334 0.777 (32) BFI: 1. Agreeableness 310 4.35 .59 0.890 (9) 2. Openness 310 4.00 .53 0.850 (8) 3. Conscientiousness 310 3.58 .73 0.671 (4) 4. Personality Traits 310 4.08 .42 0.856 (21) A correlation matrix <strong>of</strong> measures used in <strong>the</strong> study showing <strong>the</strong> correlation coefficient can be found in Table 2. Table 2: Correlation matrix <strong>of</strong> variables (n = 310) MEN MEN COD PER PER COD O<strong>the</strong> AGRE PER CON Variables IP 1 2 1 1 2 2 KS TK rs Task - Self E S OPEN S Individual .208* .216* 0.09 .198* .241* .236* - - .161* .322* .227 Performance (IP) 1 * * 9 * * .123* * .141* - .113* * .138* .286** * .185** ** Mentoring 1 (MEN 1)- .323* .195* .256* .250* .328* .382* .151* .148* 0.04 0.08 .254* .119 (competence) 1 * * * * * * * - * 3 2 .188** * .235** * Mentoring 2 (MEN 2)- .356* .352* .365* .334* .378* .185* 0.09 .179* .272* .217* 0.02 (behaviour) 1 * * * * * * 4 * * .239** * .157** 8 Individual .356* .273* .584* .363* .200* 0.06 0.07 0.08 .225* Codification (COD 1) 1 * * * * * 1 2 4 .139* * .247** 0.1 Individual - Personalization (PER .367* .362* .268* 0.02 0.04 0.00 0.08 .273* 0.08 1) Institutional 1 * * * 6 1 7 2 .191** * .296** 8 Personalization (PER .500* .382* 0.03 0.05 0.09 .217* 0.08 2) 1 * * 8 0.1 5 7 .161** * .209** 7 Institutional .415* 0.02 0.03 0.08 .256* .142 Codification (COD 2) 1 * .111* 8 1 8 .191** * .220** * - - Knowledge Sharing 0.10 0.05 - .183* .227* .166 (KS) 1 2 4 .144* * .129* * .214** ** - Tacit Knowledge (TK- .467* .507* .227* 0.02 LAMTK) 1 * * * 0.031 0.06 0.107 1 .487* .165* 0.07 0.01 O<strong>the</strong>rs 1 * * 0.054 5 0.086 4 0.03 0.02 Task 1 .121* 0.011 8 0.05 5 .150* 0.07 Self 1 0.07 * .186** 5 Agreeableness .814* .292 (AGREE) 1 * .331** ** .612 Personality (PERS) 1 .733** ** .256 Openness (OPEN) Conscientiousness 1 ** (CONS) 1 *p< 0.05, ** p< 0.01, *** p< 0.001 556
Halimah Abdul Manaf, Steven Armstrong and Alan Lawton Hypo<strong>the</strong>ses 1: There is a positive relationship between effective knowledge sharing mechanisms (KSM) and levels <strong>of</strong> accumulated managerial tacit knowledge (LAMTK). A correlation analysis revealed no significant relationship between LAMTK and institutional personalisation (r = -.038, p = .51), nor between LAMTK and individual personalisation (r = - .026, p = .643) sub-scales <strong>of</strong> KSM. There were, however, significant though weak correlations between LAMTK and both institutional codification (r = -.11, p = .025) and individual codification (r = -.2, p = .00) sub-scales. These results are similar to those <strong>of</strong> a previous study (Syed-Ikhsan & Rowland 2004) where some support was found for <strong>the</strong> claim that <strong>the</strong> better <strong>the</strong> sharing <strong>of</strong> <strong>the</strong> tacit knowledge from individuals through formal and informal discussions/meetings, <strong>the</strong> better <strong>the</strong> performance <strong>of</strong> knowledge transfer (r=0.279, p
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Proceedings <stron
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Contents Title Author(s) Picture <s
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Title Author(s) Picture of<
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Volume Two The Influence of
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The Symbolic Innovation of<
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Biographies of <st
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Jan Pawlowski works as Prof
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in academia. He holds the</
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Biomedical Engineering Research Cen
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Mathematics and Ph
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Thi Hai Hang Nguyen is a lecturer a
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Dan Savescu graduate TCM Faculty, p
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Teaches Business Computing and Stat
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Abdallah Al-Shawabkeh, Alexander K<
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Table 1: Inn-KM approach contents 2
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Knowledge Dynamics and Organisation
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Eckhard Ammann We distinguish three
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Eckhard Ammann quality dimension ar
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Eckhard Ammann The second cycle, Cy
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Figure 7: Supervised learning-by-do
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Identifying and Ranking the
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Manouchehr Ansari et al users <stro
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2.5 leadership and strategy Manouch
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Manouchehr Ansari et al conducted s
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Serious Games in the</stron
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Albena Antonova and Anandasivakumar
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Albena Antonova and Aniko Csepregi
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Seyed Esmaeil Asgharpour and Gholam
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Attitude of Senior
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4.5 Comparative Advantage Seyed Esm
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Contextual Adaptive Visualization E
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Xiaoyan Bai, David White and David
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Simona-Clara Bârsan, Mihaela-Georg
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2.4 Rights transfer Simona-Clara B
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A Framework for the</strong
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Leila Beig et al Additionally, Wei
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Leila Beig et al The proposed KM au
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Leila Beig et al source context Ele
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Leila Beig et al Figure 1: Learning
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Leila Beig et al Figure 3 visually
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Leila Beig et al based on collectiv
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Experiential Knowledge Creation Pro
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Didiosky Benítez et al Figure 1: E
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Didiosky Benítez et al meanings ac
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Didiosky Benítez et al In previous
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Didiosky Benítez et al Academic p
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Pavel Bogolyubov Figure 1: number <
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4. Results and discussion Pavel Bog
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Pavel Bogolyubov Knowledge Manageme
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Pavel Bogolyubov Table 3: Countries
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Pavel Bogolyubov McNamee, R. C., N.
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Ettore Bolisani, Francesca Gambarot
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Table 2: Synthesis
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Ettore Bolisani, Marco Paiola and E
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Strategies for Increasing Knowledge
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Constantin Bratianu, Adriana Agapie
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Klaus Bredl, Amrei Groß and Jane F
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Camelia Burja and Vasile Burja Appr
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∀ , i ≥ 0 v u i where: ui repre
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Camelia Burja and Vasile Burja Tabl
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Camelia Burja and Vasile Burja info
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Camelia Burja and Vasile Burja Jack
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Adriana Schiopoiu Burlea With respe
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Adriana Schiopoiu Burlea 3. ESF rol
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Adriana Schiopoiu Burlea In <strong
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3.2 Discussions Adriana Schiopoiu B
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Adriana Schiopoiu Burlea Nonaka, I.
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Simon Cadez and Vlado Dimovski with
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Simon Cadez and Vlado Dimovski scho
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Simon Cadez and Vlado Dimovski It i
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Why Should I Share my new ideas? Cu
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Francesco Calza, Rossella Canestrin
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José Manuel Cardenas and Mauro Spi
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Vincenzo Cavaliere and Daria Sarti
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National Knowledge Management Strat
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Behiye Çavuşoğlu and Mustafa Sag
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Implementing a work-life balance cu
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Juan-Gabriel Cegarra-Navarro, Mª E
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The Influence of R
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Huei-Fang Chen and Yi-Wen Lin outco
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3.2.4 Knowledge-sharing Huei-Fang C
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Huei-Fang Chen and Yi-Wen Lin that
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Huei-Fang Chen and Yi-Wen Lin Hair,
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2.1.2 Social capital Marguerite Cro
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Marguerite Cronk 2.3 Social capital
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Marguerite Cronk Figure 4: The rela
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An Exploratory Study of</st
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Françoise de Viron, Thomas Lederer
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4.1.2 The researchers Françoise de
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The Application of
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Nasser Easa and Robin Fincham 3. Th
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Nasser Easa and Robin Fincham knowl
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Nasser Easa and Robin Fincham <stro
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Network Management as a way to Mana
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Eva Eckenhofer An
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Eva Eckenhofer par
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Initiation Configuration Interessem
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Eva Eckenhofer Eve
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The Essence of Kno
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Emmanuel Innocents Edoun and Valden
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4. Case study and analysis Emmanuel
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2. The PUS-project Anandasivakumar
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Anandasivakumar Ekambaram and Agnar
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Jamal El-Den and Xin Zhou This rese
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Jamal El-Den and Xin Zhou includes
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Jamal El-Den and Xin Zhou Boyce, C.
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Tiit Elenurm development visions. C
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Tiit Elenurm companies the<
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References Tiit Elenurm Accorsi, F.
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Isaac Enakimio and Abdallah Al-Shaw
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A proposed Framework for Discoverin
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2.3 Knowledge mapping Mohamad Ali F
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Mohamad Ali Feyz, Babak Akhgar and
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Knowledge Workers: A Typology Frame
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Jiří Franek and Eva Grublova crea
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Jiří Franek and Eva Grublova Know
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Jiří Franek and Eva Grublova memb
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Middle Managers’ Maturity <strong
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Zoltán Gaál et al investigated m
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Zoltán Gaál et al Table 2: Total
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Charles Gagné et al This paper pre
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Charles Gagné et al attributable t
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Charles Gagné et al intermediary d
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Adoption of Knowle
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1.1.2 SMEs and KMS Tendayi Gondo an
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Tendayi Gondo and Edmore Kori ambit
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The Chain Value Process and Knowled
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4. What a biofeedb
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References Manel González-Piñero
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Nebojsa Graca and Ana Lucija Gojako
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creating new, added, essential qual
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Instance Schema Figure 4: Cyclic tr
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Receive suggestions Compare suggest
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The Not-Invented-Here Syndrome in A
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Opinion of colleag
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Appendix David Grosse Kathoefer and
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Individual Level Influencers on Tac
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Understanding Personal Knowledge De
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Intellectual Capital in Universitie
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Table 3: Opinions about Human Capit
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Developing a Knowledge Strategy Usi
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Harold Harlow knowledge to create c
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3.1 TKI Regression results Harold H
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Understanding the
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3.1 Acquire Ciara Heavin and Freder
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Key Knowledge Sharing Points: Explo
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Using Web 2.0 Technologies to Suppo
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Expert Knowledge: Does it Help or H
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Integration of Kno
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