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  • 标题:Designing Knowledge Sharing System for Statistical Activities in BPS-Statistics Indonesia
  • 本地全文:下载
  • 作者:Dana Indra Sensuse ; Viktor Suwiyanto ; Sofian Lusa
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2021
  • 卷号:6
  • 期号:5
  • 页码:48-64
  • DOI:10.3390/data6050048
  • 出版社:MDPI Publishing
  • 摘要:Statistics of Indonesia’s (BPS) performance are not optimal since there is a lack of integration among business processes. This has resulted in unsynchronized data, unstandardized business processes, and inefficient IT investment. To encourage more qualified and integrated business processes, BPS should optimize the knowledge sharing process (KSP) among government employees in statistical areas. This study designed a Knowledge Sharing System (KSS) to facilitate KSP in BPS towards knowledge sharing improvement. The KSS manifested a hypothesis that the design of qualified knowledge management can facilitate an organization to overcome the lack of integration among business processes. Hence, BPS can avoid repetitive mistakes, improve work efficiency, and reduce the risk of failure. This study generated a business process-oriented KSS by combining soft system methodology with the B-KIDE (Business process-oriented Knowledge Infrastructure Development) Framework. It delivered research artifacts (a rich picture, CATWOE analysis (costumer, actor, transformation, weltanschauung, owner, environment), and conceptual model) to capture eight mechanisms of knowledge, map them into the knowledge process, and define the applicable technology. The KSS model has perceived a score of 0.40 using the Kappa formula that indicates the stakeholders’ acceptance. Therefore, BPS can leverage a qualified KSS towards the integrated business processes statistically while the hypothesis was accepted.
  • 关键词:knowledge sharing; knowledge management; soft system methodology; B-KIDE framework; design science research knowledge sharing ; knowledge management ; soft system methodology ; B-KIDE framework ; design science research
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