.png){kind=icon}
返回
Exploring big data traits and data quality dimensions for big data analytics application using partial least squares structural equation modelling
.png){kind=icon}
OA
AI
DOI：10.1186/s40537-021-00439-5.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The popularity of big data analytics (BDA) has boosted the interest of organisations into exploiting their large scale data. This technology can become a strategic stimulation for organisations to achieve competitive advantage and sustainable growth. Previous BDA research, however, has focused more on introducing more traits, known as Vs for big data traits, while ignoring the quality of data when examining the application of BDA. Therefore, this study aims to explore the effect of big data traits and data quality dimensions on BDA application. This study has formulated 10 hypotheses that comprised of the relationships of big data traits, accuracy, believability, completeness, timeliness, ease of operation, and BDA application constructs. This study conducted a survey using a questionnaire as a data collection instrument. Then, the partial least squares structural equation modelling technique was used to analyse the hypothesised relationships between the constructs. The findings revealed that big data traits can significantly affect all constructs for data quality dimensions and that the ease of operation construct has a significant effect on BDA application. This study contributes to the literature by bringing new insights to the field of BDA and may serve as a guideline for future researchers and practitioners when studying BDA application.
Keyword:
Big data analytics
Big data
Big data traits
Data quality dimensions
Partial least squares structural equation modelling
Survey questionnaire
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.4
论文数:
1.5K
被引数:
1.1W
机构
引用论文
Application of big data analytics and organizational performance: the mediating role of knowledge management practices大数据分析应用与组织绩效: 知识管理实践的中介作用.png)
JOURNAL OF BIG DATAOAAI
JOURNAL OF BIG DATAIF6.4
OAAI分享收藏Treatment of coking wastewater by an advanced Fenton oxidation process using iron powder and hydrogen peroxideChemosphere
ChemosphereIF0
PREAI
分享收藏Big data monetization throughout Big Data Value Chain: a comprehensive reviewJOURNAL OF BIG DATAOAAI
JOURNAL OF BIG DATAIF6.4
OAAI分享收藏
查看更多内容