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The Effect of Machine Learning on Knowledge-Intensive R&D in the Technology Industry

机译:机器学习对技术产业知识密集型研发的影响

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The impact of such current state-of-the-art technology as machine learning (ML) on organizational knowledge integration is indisputable. This paper synergizes investigations of knowledge integration and ML in technologically advanced and innovative companies, in order to elucidate the value of these approaches to organizational performance. The analyses are based on the premise that, to fully benefit from the latest technological advances, entity interpretation is essential to fully define what has been learned. Findings yielded by a single case study involving one technological firm indicate that tacit and explicit knowledge integration can occur simultaneously using ML, when a data analysis method is applied to transcribe spoken words. Although the main contribution of this study stems from the greater understanding of the applicability of machine learning in organizational contexts, general recommendations for use of this analytical method to facilitate integration of tacit and explicit knowledge are also provided.
机译:这种现有技术的影响为机器学习(ML)的组织知识集成是无可争辩的。本文根据技术先进和创新公司在技术先进和创新公司中协调了知识集成和ML的调查,以阐明这些方法的价值。分析基于前提,使得能够完全受益于最新的技术进步,实体解释对于完全定义已经学到的内容至关重要。涉及一个技术公司的单个案例研究产生的结果表明,当应用数据分析方法以转换口语单词时,可以同时发生默契和明确的知识集成。虽然本研究的主要贡献源于机器学习在组织背景下的适用性的理解,但还提供了使用这种分析方法的一般建议,以促进默契和明确知识的整合。

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