A Fitting Approach to Construct and Measurement Alignment: The Role of Big Data in Advancing Dynamic Theories

Margaret M. Luciano; John E. Mathieu; Semin Park; Scott I. Tannenbaum

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A Fitting Approach to Construct and Measurement Alignment: The Role of Big Data in Advancing Dynamic Theories

机译：构建和度量对齐的拟合方法：大数据在推进动态理论中的作用

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Many phenomena of interest to management and psychology scholars are dynamic and change over time. One of the primary impediments to the examination of dynamic phenomena has been challenges associated with collecting data at a sufficient frequency and duration to accurately model such changes. Emerging technologies that produce nearly continuous streams of big data offer great promise to address those challenges; however, they introduce new methodological challenges and construct validity concerns. We seek to integrate the emerging big data technologies into the existing repertoire of measurement techniques and advance an iterative process to enhance their measurement fit. First, we provide an overview of dynamic constructs and temporal frameworks, highlighting their measurement implications. Second, we discuss different data streams and feature emerging technologies that leverage big data as a means to index dynamic constructs. Third, we integrate the previous sections and advance an iterative approach to achieving measurement fit, highlighting factors that make some measurement choices more suitable and viable than others. In so doing, we hope to accelerate the advancement of dynamic theories and methods.

机译：管理和心理学学者感兴趣的许多现象是动态的，并且会随着时间而变化。检查动态现象的主要障碍之一是与以足够的频率和持续时间收集数据以准确地对此类变化进行建模相关的挑战。产生近乎连续的大数据流的新兴技术为解决这些挑战提供了广阔的前景。但是，它们带来了新的方法挑战，并构造了有效性问题。我们力求将新兴的大数据技术整合到现有的测量技术中，并推进迭代过程以增强其测量适合性。首先，我们对动态结构和时间框架进行了概述，突出了它们的度量含义。其次，我们讨论了不同的数据流，并介绍了利用大数据作为索引动态结构的一种新兴技术。第三，我们整合了前面的部分，并提出了一种迭代的方法来实现测量拟合，重点介绍了使某些测量选择比其他选择更合适和可行的因素。通过这样做，我们希望加快动态理论和方法的发展。

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来源
《Organizational Research Methods》 |2018年第3期|592-632|共41页
作者
Margaret M. Luciano; John E. Mathieu; Semin Park; Scott I. Tannenbaum;
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作者单位

Arizona State University, Tempe, AZ, USA;

University of Connecticut, Storrs, CT, USA;

University of Connecticut, Storrs, CT, USA;

The Group for Organizational Effectiveness, Inc., Albany, NY, USA;

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正文语种 eng
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关键词
dynamics; measurement fit; big data; construct validity;

机译：动力学;度量拟合;大数据;构造效度;

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A Fitting Approach to Construct and Measurement Alignment: The Role of Big Data in Advancing Dynamic Theories

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