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Understanding the impact of big data on firm performance: The necessity of conceptually differentiating among big data characteristics

机译:了解大数据对公司性能的影响:大数据特征概念上区分的必要性

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摘要

This study uses the resource-based view to explore the impact of data volume, data velocity, and data variety, which are the main characteristics of big data, on firm performance and the mediating roles of data value and data veracity on these relationships. To test the research model, we collected data from 143 top and middle level managers in the United States. The findings show that data variety positively improves data value generation, whereas data volume and data velocity do not impact it. Additionally, while data volume negatively impacts data veracity, data velocity and data variety positively impact it. Findings indicate the necessity of conceptually differentiating among big data characteristics in investigating their impacts on firm outcomes instead of treating big data as a holistic variable. The study provides useful insights for researchers and managers willing to better understand the role of big data characteristics in influencing firm performance.
机译:本研究使用基于资源的视图来探讨数据量,数据速度和数据变化的影响,这是大数据的主要特征,以及数据价值和数据值的中介角度和数据准则对这些关系的介面。为了测试研究模式,我们从美国的143名顶级和中级经理收集数据。该研究结果表明,数据品种积极提高数据值,而数据量和数据速度不会影响它。此外,虽然数据卷产生负面影响数据速度,数据速度和数据品种积极影响它。调查结果表明,在调查其对坚实的成果的影响方面,概念上区分的必要性而不是将大数据视为整体变量。该研究为研究人员和管理人员提供了有用的见解,愿意更好地了解大数据特征在影响公司性能方面的作用。

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