Attitude Toward the Color Blue: An Ideal Marker Variable

IF 8.9 2区 管理学 Q1 MANAGEMENT
B. Miller, Marcia J. Simmering
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引用次数: 27

Abstract

Researchers often turn to post hoc statistical techniques to identify common method variance (CMV) in same source data and one viable option is to use a marker variable. The choice of marker variable is important, yet these variables are difficult to find, primarily because they must be theoretically unrelated to study variables but measured in the same way (e.g., perceptual; on a Likert scale). This manuscript uses scale development best practices to create a marker variable—attitude toward the color blue—that can be applied in a wide variety of social science research. Scale reliability and validity are addressed, discriminant validity with other measures that detect CMV is tested, and the Confirmatory Factor Analysis Marker Technique is applied with this scale. An experiment designed to analyze the effect of the placement of the scale in surveys is reported. Recommendations to researchers for use of this new scale to detect CMV are provided.
对蓝色的态度:一个理想的标记变量
研究人员经常求助于事后统计技术来识别同一来源数据中的常见方法方差(CMV),一个可行的选择是使用标记变量。标记变量的选择很重要,但这些变量很难找到,主要是因为它们在理论上与研究变量无关,但以相同的方式测量(例如,感知;在Likert量表上)。这份手稿使用量表开发的最佳实践来创建一个标记变量——对蓝色的态度——可以应用于各种社会科学研究。对量表的信度和有效性进行了研究,并与其他检测CMV的指标进行了判别有效性测试,并将确证因子分析标记技术应用于该量表。报告了一项旨在分析调查中使用量表的效果的实验。建议研究人员使用这种新的量表来检测CMV。
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来源期刊
CiteScore
23.20
自引率
3.20%
发文量
17
期刊介绍: Organizational Research Methods (ORM) was founded with the aim of introducing pertinent methodological advancements to researchers in organizational sciences. The objective of ORM is to promote the application of current and emerging methodologies to advance both theory and research practices. Articles are expected to be comprehensible to readers with a background consistent with the methodological and statistical training provided in contemporary organizational sciences doctoral programs. The text should be presented in a manner that facilitates accessibility. For instance, highly technical content should be placed in appendices, and authors are encouraged to include example data and computer code when relevant. Additionally, authors should explicitly outline how their contribution has the potential to advance organizational theory and research practice.
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