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    Title: 專案團隊隱性知識管理之績效評估
    Performance Evaluation of Project Team Tacit Knowledge Management
    Authors: 謝佩璇
    Hsieh, Pei-Hsuan
    吳虹霓
    Wu, Hung-Ni
    Contributors: 資科系
    Keywords: 專案管理; 知識管理; 績效評估; 虛擬社群; 電子化企業
     Project Management ; Knowledge Management; Performance Evaluation ; Virtual Community ; E-Business
    Date: 2015-12
    Issue Date: 2020-03-27 15:35:02 (UTC+8)
    Abstract: 本研究從專案團隊(人員)、隱性知識(流程)以及虛擬社群(科技)三方面,評估專案團隊成員於各專案執行階段之隱性知識管理績效,並探討成員是否藉由虛擬社群提升其隱性知識管理能力。依知識螺旋理論及平衡計分卡構面,本研究採用層級分析法詢問專家意見,獲得隱性知識管理績效評估指標及相對應權重。接著,依評估指標發展問卷,調查專案團隊成員在專案各執行階段隱性知識管理績效,並分析是否藉由虛擬社群可提升隱性知識管理能力。研究發現專案團隊成員在起始階段有較高的隱性知識管理能力執行,專案成員藉由虛擬社群進行隱性知識管理有助於提升其團隊知識力。研究學術與實務意涵指出專案執行環境、團隊成員屬性及規劃前需求分析,皆影響隱性知識管理績效。
    This research draws on three aspects, i.e., project team (people), tacit knowledge (flow), and virtual communities (IT), to evaluate project team members’ tacit knowledge management ability in each phase of project operation. Whether the members’ abilities get enhanced by participating in the cloud computing virtual community is also examined. Based on the spiral theory of knowledge and the constructs of balance scorecard, this research uses the analytic hierarchy process to consult with expert opinions for determining indices and their corresponding weights for evaluating project team’s performance of tacit knowledge management. The project team members’ tacit knowledge management performance in each project phase is then investigated by a survey developed according to the evaluation indices. This research found that the project team members’ ability managing tacit knowledge at the initial stage perform higher than at other stages. The knowledge power of the project team can be enhanced as the project members participate in the virtual community. The academic and practical contributions of this research indicate that project operation context, team member attributes, and need analysis all before the project planning phase have influence on tacit knowledge management performance.
    Relation: 商略學報, Vol.7, No.4, pp.267-280
    Data Type: article
    Appears in Collections:[Department of Computer Science ] Periodical Articles

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