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  • 标题:A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL
  • 本地全文:下载
  • 作者:LUISA M. STRAUSS ; NORBERTO HOPPEN
  • 期刊名称:RAM. Revista de Administração Mackenzie
  • 印刷版ISSN:1518-6776
  • 电子版ISSN:1678-6971
  • 出版年度:2019
  • 卷号:20
  • 期号:4
  • 页码:1-27
  • DOI:10.1590/1678-6971/eRAMR190182
  • 出版社:Universidade Presbiteriana Mackenzie
  • 摘要:Purpose: The article presents the development of a framework to analyze the use of big data and analytics in organizations. The framework is based on affordance theory and actor-network theory (ANT). Originality/value: Big data and analytics are a set of tools and techniques that are not new, but recently have received much attention from the media and academia. The media promotes big data and analytics while the academia addresses the fact that there are still implementation obstacles and the process of using big data analytics is not well understood. Design/methodology/approach: We used a qualitative approach, in the form of a theoretical essay. We analyzed papers that related affordance theory with IT and, in particular, with big data and analytics. Further, in order to create the resulting framework, an illustrative case study was conducted. Findings: Affordance theory, allied to the translation concept of ANT, can be useful when analyzing the process of using big data and analytics in organizations, because it contemplates individual and organizational aspects, covering the perception of utility, necessary sociotechnical transformations in processes, people and structures, actual use and organizational effects. As the main contribution, we proposed a framework that includes elements of translation to guide future research.
  • 关键词:Big data; Analytics; Affordances; Actor-network theory; Framework
  • 其他关键词:Big data; Analytics; Affordances; Teoria ator-rede; Framework.
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