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Possible negative effects of big data on decision quality in firms: The role of knowledge hiding behaviours

机译：大数据对公司决策质量的可能性的负面影响：知识隐藏行为的作用

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摘要

While common wisdom suggests that big data facilitates better decisions, we posit that it may not always be the case, as big data aspects can also afford and motivate knowledge hiding. To examine this possibility, we integrate adaptive cost theory with the resource-based view of the firm. This integration suggests that the effect of big data characteristics (i.e., data variety, volume, and velocity) on firm decision quality can be explained, in part, by data analysts' perceived knowledge hiding behaviours, including evasive hiding, playing dumb, and rationalized hiding. We examined this model with survey data from 149 data analysts in firms that use big data to varying degrees. The findings show that big data characteristics have distinct effects on knowledge hiding behaviours. While data volume and velocity enhance knowledge hiding, data variety reduces it Moreover, evasive hiding, playing dumb, and rationalized hiding have varying effects on firm decision quality. Whereas evasive hiding reduces firm decision-making quality, playing dumb does not affect it, and rationalized hiding improves it These results are further validated with applicability checks. Ultimately, these results can explain inconsistent past findings regarding the return on investment in big data and provide a unique look into the potential "dark sides" of big data.
机译：虽然常见的智慧表明，大数据有助于更好的决策，但我们证明它可能并不总是如此，因为大数据方面也可以提供和激励知识隐藏。为了检查这种可能性，我们将自适应成本理论与公司的资源视图集成。这种集成表明，可以通过数据分析师的感知知识隐藏行为来解释大数据特征（即数据品种，体积和速度）对公司决策质量的影响，包括避免隐藏，哑巴和合理化隐藏。我们将该模型与来自149个数据分析师的调查数据进行了调查数据，该数据在使用大数据到不同程度的公司。调查结果表明，大数据特征对知识隐藏行为具有明显的影响。虽然数据量和速度增强了知识隐藏，但数据变量缩短了，躲避隐藏，哑铃和合理化隐藏对坚实的决策质量有不同影响。虽然避免隐藏降低了坚定的决策质量，但哑铃不会影响它，并且合理化隐藏改善了它这些结果进一步验证了适用性检查。最终，这些结果可以解释关于大数据投资回报的过去的结果，并提供了大数据的潜在“黑侧”的独特观察。

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