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A recipe for big data value creation

机译：大数据价值创造秘诀

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摘要

Purpose The purpose of this paper is to present a process-theory-based model of big data value creation in a business context. The authors approach the topic from the viewpoint of a single firm. Design/methodology/approach The authors reflect current big data literature in two widely used value creation frameworks and arrange the results according to a process theory perspective. Findings The model, consisting of four probabilistic processes, provides a "recipe" for converting big data investments into firm performance. The provided recipe helps practitioners to understand the ingredients and complexities that may promote or demote the performance impact of big data in a business context. Practical implications - The model acts as a framework which helps to understand the necessary conditions and their relationships in the conversion process. This helps to focus on success factors which promote positive performance. Originality/value Using well-established frameworks and process components, the authors synthetize big data value creation-related papers into a holistic model which explains how big data investments translate into economic performance, and why the conversion sometimes fails. While the authors rely on existing theories and frameworks, the authors claim that the arrangement and application of the elements to the big data context is novel.
机译：目的本文的目的是介绍在业务环境中基于过程理论的大数据价值创造模型。作者从单个公司的角度来探讨该主题。设计/方法/方法作者在两个广泛使用的价值创造框架中反映了当前的大数据文献，并根据过程理论的观点安排了结果。调查结果该模型由四个概率过程组成，为将大数据投资转换为公司绩效提供了“配方”。提供的食谱可帮助从业人员了解在业务环境中可能促进或降低大数据对性能的影响的成分和复杂性。实际意义-该模型充当框架的角色，有助于理解转换过程中的必要条件及其关系。这有助于将重点放在促进积极绩效的成功因素上。原创性/价值使用完善的框架和流程组件，作者将与大数据价值创造相关的论文综合为一个整体模型，该模型解释了大数据投资如何转化为经济绩效，以及为何有时转化失败。尽管作者依赖现有的理论和框架，但作者声称元素在大数据上下文中的排列和应用是新颖的。

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