推动项目成功的大数据分析:知识共享和创新绩效的中介作用

IF 1 Q4 MANAGEMENT
Diego Norena-Chavez
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引用次数: 0

摘要

目的:利用基于资源的观点(RBV)和动态能力理论(DCT),本研究旨在探讨大数据分析(BDA)通过知识共享(KS)和创新绩效(IPF)对项目成功(PS)的影响。设计/方法:从IT公司的422名高级员工中收集调查数据,并使用SMART-PLS 4结构方程建模工具评估所提出的关系。研究结果表明,大数据分析通过知识共享对项目成功具有积极而显著的间接影响。IPF在IT企业BDA和PS之间具有显著中介作用。原创性/价值:这项研究是第一个将大数据分析视为项目成功的先决条件的研究之一。在大数据分析、知识共享、创新绩效和组织绩效之间的相互关系研究很少或没有相关研究的情况下,本研究探讨了知识共享和创新绩效在企业绩效管理与企业绩效之间的中介作用。启示:本研究以RBV和DCT为基础,通过KS和IPF考察企业绩效管理对企业绩效的影响。影响包括BDA的战略作用、KS和IPF的中介作用以及基于实践和研究的见解。研究结果指导BDA整合、协作文化和持续成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fueling big data analytics for project success: Mediating role of knowledge sharing and innovation performance
Purpose: Drawing on the Resource Based View (RBV) and Dynamic Capabilities Theory (DCT), the study seeks to investigate the impact of Big Data Analytics (BDA) on Project Success (PS) through Knowledge Sharing (KS) and Innovation Performance (IPF). Design/Methodology: Survey data were collected from 422 senior-level employees in IT companies, and the proposed relationships were assessed using the SMART-PLS 4 Structural Equation Modeling tool. Findings: The results show a positive and significant indirect effect of big data analytics on project success through knowledge sharing. IPF significantly mediated the relationship between BDA and PS in IT companies. Originality/Value: This study is one of the first to consider big data analytics as an essential antecedent of project success. With little or no research on the interrelationship of big data analytics, knowledge sharing, innovation performance, and organizational performance, the study investigates the mediating role of knowledge sharing and innovation performance on the relationship between BDA and PS. Implications: This study, grounded in RBV and DCT, investigates BDA’s influence on PS through KS and IPF. Implications encompass BDA’s strategic role, KS and IPF mediation, and practical and research-based insights. Findings guide BDA integration, collaborative cultures, and sustained success.
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来源期刊
CiteScore
1.00
自引率
14.30%
发文量
13
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