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Addressing Common Method Variance: Guidelines for Survey Research on Information Technology, Operations, and Supply Chain Management

机译:解决通用方法差异:信息技术,运营和供应链管理调查研究指南

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摘要

Common method variance (CMV) is the amount of spurious correlation between variables that is created by using the same method—often a survey—to measure each variable. CMV may lead to erroneous conclusions about relationships between variables by inflating or deflating findings. We analyzed recent survey research in IEEE Transactions on Engineering Management, Journal of Operations Management, and Production and Operations Management to assess if and how scholars address CMV. We found that two-thirds of the relevant articles published between 2001 and 2009 did not formally address CMV, and many that did address CMV relied on relatively weak remedies. These findings have troubling implications for efforts to build knowledge within information technology, operations and supply chain management research. In an effort to strengthen future research designs, we provide recommendations to help scholars to better address CMV. Given the potentially severe effects of CMV, authors should apply the recommended CMV remedies within their survey-based studies, and reviewers should hold authors accountable when they fail to do so.
机译:常用方法方差(CMV)是变量之间的虚假相关量,这些变量是通过使用相同的方法(通常是调查)来测量每个变量而创建的。通过夸大或缩小发现,CMV可能导致有关变量之间关系的错误结论。我们分析了IEEE事务中有关工程管理,运维管理杂志以及生产和运维管理的最新调查研究,以评估学者是否以及如何解决CMV。我们发现,在2001年至2009年之间发表的相关文章中,有三分之二没有正式提及CMV,许多确实针对CMV的文章都依赖相对较弱的补救措施。这些发现对于在信息技术,运营和供应链管理研究中建立知识的努力具有令人担忧的影响。为了加强未来的研究设计,我们提供了一些建议,以帮助学者更好地解决CMV问题。考虑到CMV可能造成的严重影响,作者应在基于调查的研究中应用推荐的CMV补救措施,而当审稿人未这样做时,审稿人应追究作者的责任。

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