Big data are a prominent source of value capable of generating competitive advantage and superior business performance. This paper represents the first empirical investigation of the theoretical model proposed by Grover et al. (2018), considering the mediating effects of four value creation mechanisms on the relationship between big data analytics capabilities (BDAC) and four value targets. The four value creation mechanisms investigated (the source of the value being pursued) are transparency, access, discovery, and proactive adaptation, while the four value targets (the impacts of the value creation process) are organization performance, business process improvement, customer experience and market enhancement, and product and service innovation. The proposed empirical validation of Grover et al.’s (2018) model adopts an econometric analysis applied to data gathered through a survey involving 256 BDA experts. The results reveal that transparency mediates the relationship for all the value targets, while access and proactive adaptation mediate only in case of some value targets, and discovery does not have any mediating effect. Theoretical and practical implications are discussed at the end of the paper.

大数据是能够产生竞争优势和卓越业务绩效的重要价值来源。本文代表了 Grover 等人提出的理论模型的第一次实证研究。（2018），考虑四种价值创造机制对大数据分析能力（BDAC）和四个价值目标之间关系的中介作用。所研究的四个价值创造机制（被追求的价值的来源）是透明度、访问、发现和主动适应，而四个价值目标（价值创造过程的影响）是组织绩效、业务流程改进、客户体验市场提升，产品和服务创新。Grover 等人提出的经验验证。的 (2018) 模型采用计量经济学分析，应用于通过涉及 256 名 BDA 专家的调查收集的数据。结果表明，透明度在所有价值目标的关系中起中介作用，而访问和主动适应仅在某些价值目标的情况下起中介作用，而发现没有任何中介作用。本文最后讨论了理论和实践意义。