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ACHIEVING EFFECTIVE USE WHEN DIGITALIZING WORK: THE ROLE OF REPRESENTATIONAL COMPLEXITY

机译:在数字化工作时实现有效使用:代表复杂性的作用

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摘要

In times of accelerated digital transformation, many organizations still struggle to put enterprise systems to effective use quickly. While prior work suggests either system or task complexity as a source for these difficulties, this case study of a major system implementation at a European bank reveals the most important source to be the complexity arising from co-dependency between the system and the task. We conceptualize this co-dependency as inherent in system-enabled tasks by proposing system dependency (the extent to which a task is supported by a system) and semantic dependency (the degree to which semantic understanding is required for task completion). Together, these dependencies create representational complexity, which constrains users from achieving effective use in system-enabled tasks and can explain differences in achieving effective use through variations in learning effort. The concepts and insights emerging from this study provide researchers and practitioners with a deeper understanding of what complexity means and why, in some contexts, learning how to use systems effectively takes longer.
机译:在加速数字转型时,许多组织仍然努力将企业系统迅速努力。虽然事先工作表明系统或任务复杂性作为这些困难的源头,但这种情况研究欧洲银行的主要系统实施揭示了最重要的来源,以实现系统和任务之间的共同依赖性的复杂性。我们通过提出系统依赖性(系统支持的任务支持的程度)和语义依赖(任务完成所需的程度)来概括为启用系统的任务中固有的协同依赖性。这些依赖项在一起创造了代表性的复杂性,这会计解用户在启用系统的任务中实现有效使用,并且可以通过学习努力的变化来解释实现有效利用的差异。从本研究中出现的概念和洞察力为研究人员和从业者提供了更深入地了解复杂性手段以及为什么在某些情况下,学习如何使用系统需要更长时间。

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