Big-Data Business Models: A Critical Literature Review and Multi-Perspective Research Framework

M. Wiener, C. Saunders, Marco Marabelli
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引用次数: 7

Abstract

The emergence of ‘big data’ offers organizations unprecedented opportunities to gain and maintain competitive advantage. Trying to exploit the strategic business potential embedded in big data, many organizations have started to renovate their business models or develop new ones, giving rise to the phenomenon of big-data business models (BDBMs). Although BDBM research is still in its infancy, a significant number of studies on the topic have been published since 2014. We thus suggest it is time to perform a critical review and assessment of the literature at the intersection of business models and big data (analytics), thereby responding to recent calls for further research on and sustained analysis of BDBMs. In particular, our review uses three major criteria (BDBM types, dimensions, and deployment) to assess the state of the BDBM literature and identify shortcomings in this literature. On this basis, we derive and discuss five central research perspectives (supply chain, stakeholder, ethics, national, and process), providing guidance for future research and theory development in the area. These perspectives also have practical implications on how to address the current BDBM deployment gap.
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大数据商业模式:关键文献综述和多视角研究框架
“大数据”的出现为企业获得和保持竞争优势提供了前所未有的机会。为了挖掘大数据蕴含的战略商业潜力,许多组织开始更新或开发新的商业模式,从而产生了大数据商业模式(BDBMs)现象。尽管BDBM研究仍处于起步阶段,但自2014年以来,已经发表了大量关于该主题的研究。因此,我们建议现在是时候对商业模式和大数据(分析)交叉领域的文献进行批判性的审查和评估,从而回应最近对BDBMs进一步研究和持续分析的呼吁。特别是,我们的回顾使用了三个主要标准(BDBM类型、维度和部署)来评估BDBM文献的状态,并确定这些文献中的不足之处。在此基础上,我们推导并讨论了五个核心研究视角(供应链、利益相关者、伦理、国家和过程),为该领域未来的研究和理论发展提供指导。这些观点对于如何解决当前BDBM部署差距也具有实际意义。
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