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迈向大数据时代的业务流程创新:大数据知识管理的中介作用。

Toward Business Process Innovation in the Big Data Era: A Mediating Roles of Big Data Knowledge Management.

机构信息

Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan.

Department of Business Administration, National Taiwan University of Science and Technology, Taipei, Taiwan.

出版信息

Big Data. 2020 Dec;8(6):464-477. doi: 10.1089/big.2020.0140. Epub 2020 Nov 20.

Abstract

While recent debate recognizes the importance of big data (BD) and knowledge management (KM) in firm performance, there has been a paucity of literature regarding big data analytics technological (BDAT) and knowledge exploration-exploitation capabilities (KEEC) in the context of business process innovation (BPI). This study aims to identify whether BD and KM can be established in these emerging issues. We used a survey questionnaire to collect data from various firms and industries. We used structural equation modeling (SmartPLS and SPSS) to validate the research model with a sample of 155 companies in a developing country such as Indonesia. The result demonstrates a positive relationship between KEEC and BPI, followed by several significant findings such as BDAT with KEEC; KEEC on big data knowledge management (BDKM); BDKM and BPI; and BDAT on BDKM. In contrast, BDAT is nonsignificant for direct relationship on BPI, and interestingly, it becomes a significant result after mediated by BDKM. Similarly, BDKM has successfully mediated the relationship between KEEC and BPI. The management level ideally develops and increases such a knowledge creation/acquisition practices and BDAT in an organization to gain more meaningful benefits from these two capabilities. BDAT, KEEC, and BDKM simultaneously are a clear antecedent approach, which ultimately results in flexibility, effectiveness, and effectivity of BPI. The cases of this research are profit firms in a developing country such as Indonesia. A future study could be considered in different settings such as type of industries or more specific company's type, the economy level of countries (comparing between developed and developing countries), and environmental dynamical. A novel field of study is the inclusion of knowledge exploration-exploitation and BDAT that drives BPI.

摘要

虽然最近的争论认识到大数据 (BD) 和知识管理 (KM) 在公司绩效中的重要性,但在业务流程创新 (BPI) 背景下,关于大数据分析技术 (BDAT) 和知识探索-利用能力 (KEEC) 的文献很少。本研究旨在确定 BD 和 KM 是否可以在这些新兴问题中建立。我们使用问卷调查从不同的公司和行业收集数据。我们使用结构方程模型 (SmartPLS 和 SPSS) 验证了来自印度尼西亚等发展中国家的 155 家公司样本的研究模型。结果表明,KEEC 与 BPI 之间存在正相关关系,随后还有一些重要发现,例如 KEEC 与 BDAT;KEEC 对大数据知识管理 (BDKM);BDKM 和 BPI;以及 BDAT 对 BDKM。相比之下,BDAT 与 BPI 之间没有直接关系,有趣的是,在经过 BDKM 中介后,它成为了一个显著的结果。同样,BDKM 成功地调解了 KEEC 和 BPI 之间的关系。管理层理想地在组织中发展和增加这种知识创造/获取实践和 BDAT,以从这两种能力中获得更有意义的收益。BDAT、KEEC 和 BDKM 同时是一种明确的前因方法,最终使 BPI 具有灵活性、有效性和效率。本研究的案例是印度尼西亚等发展中国家的盈利公司。未来的研究可以考虑在不同的环境中进行,例如行业类型或更具体的公司类型、国家的经济水平(比较发达国家和发展中国家)以及环境动态性。一个新的研究领域是包括知识探索-利用和 BDAT 在内的驱动 BPI 的方法。

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