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Avoiding epistemological silos and empirical elephants in OM: How to combine empirical and simulation methods?

机译:在OM中避免认识论孤岛和经验象:如何结合经验和模拟方法?

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摘要

Progression of knowledge in operations management (OM) relies on researchers building and testing theories using data from practice. However, standalone empirical research designs have inherent limitations and may not adequately capture complex OM problems. This may result in researchers narrowing the scope of the problems that they create epistemological silos and study empirical elephants. In this introductory article to the special issue, we look at the ways simulation methods can augment and answer questions that are not addressed through traditional empirical methods. We offer a framework regarding how and when to use simulation methods for a given research objectives and design. We conclude by discussing the contingencies of using these methods as well as the role of reviewers and editors in evaluating papers that involve such methods.
机译:运筹学(OM)知识的进步取决于研究人员使用实践数据建立和测试理论。但是,独立的经验研究设计具有固有的局限性,可能无法充分解决复杂的OM问题。这可能导致研究人员缩小创建认识论筒仓和研究经验象的问题的范围。在本期特刊的介绍性文章中,我们着眼于模拟方法可以扩大和回答传统经验方法无法解决的问题的方式。我们提供了有关如何以及何时使用模拟方法实现给定研究目标和设计的框架。最后,我们讨论了使用这些方法的偶然性,以及审稿人和编辑在评估涉及此类方法的论文中的作用。

著录项

  • 来源
    《Journal of operations management》 |2018年第11期|1-5|共5页
  • 作者单位

    Center for Operational Excellence The Ohio State University;

    Curtis L. Carlson Professor in Supply Chain and Operations University of Minnesota;

    Chaired Professor of Supply Chain Management Strategy and Innovation University of Cologne Erasmus University Rotterdam;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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