Assessing the impact of big data on firm innovation performance: Big data is not always better data

被引:222
|
作者
Ghasemaghaei, Maryam [1 ]
Calic, Goran [1 ]
机构
[1] McMaster Univ, DeGroote Sch Business, Hamilton, ON, Canada
关键词
Big data; Data velocity; Data variety; Data volume; Innovation performance; Firm performance; COMMON METHOD VARIANCE; DATA ANALYTICS; PRODUCT INNOVATION; ORGANIZATIONAL PERFORMANCE; SUPPLY CHAIN; BUSINESS INTELLIGENCE; LEARNING ORIENTATION; CAUSAL AMBIGUITY; DATA QUALITY; INFORMATION;
D O I
10.1016/j.jbusres.2019.09.062
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this study, we explore the impacts of big data's main characteristics (i.e., volume, variety, and velocity) on innovation performance (i.e., innovation efficacy and efficiency), which eventually impacts firm performance (i.e., customer perspective, financial returns, and operational excellence). To address this objective, we collected data from 239 managers and empirically examined the relationships in the proposed model. The results reveal that, while data variety and velocity positively enhance firm innovation performance, data volume has no significant impact. The finding that data volume does not play a critical role in enhancing firm innovation performance contributes novel insights to the literature by contradicting the prevalent belief that big data is better data. Moreover, the findings reveal that data velocity plays a more important role in improving firm innovation performance than other big data characteristics.
引用
收藏
页码:147 / 162
页数:16
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