Goal: This paper aims to carry a bibliometric study to map how data mining and operations research techniques are being applied to Supply Chain Risk Management. Design/Methodology/Approach: We conducted a bibliometric analysis implemented in R language (bibliometrix package) using Systematic Literature Review approach to conduct the search. Results: As the main results we highlight the gap we found in the literature considering Data Mining techniques in Supply Chain Risk Management and we set a full panorama of this stream of research. Limitations of the Investigation: We used Scopus database which allows recovering peer-reviewed texts from dozens of strong databases, nevertheless, we can not guarantee that all relevant documents were recovered. In addition, we considered only full published papers published in English language. Practical Implications: Managers and companies that are related in a supply chain must gradually redesign processes to include Data Mining techniques to support SCRM processes and activities along the SC. Originality / Value: The paper showed the updated panorama of Data Mining implementation regarding SCRM. We did not find any similar studies, which shows our unique contribution.

中文翻译：

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供应链风险管理中的数据挖掘和运筹学技术：一项文献计量研究

目标：本文旨在进行文献计量研究，以映射如何将数据挖掘和运筹学技术应用于供应链风险管理。设计/方法/方法：我们使用系统语言文献综述方法进行了用R语言（书目套件）进行的文献计量分析。结果：作为主要结果，我们着重指出了我们在文献中考虑到供应链风险管理中的数据挖掘技术所存在的差距，并且为这一研究流设置了完整的全景图。调查的局限性：我们使用了Scopus数据库，该数据库可以从数十个强大的数据库中恢复经过同行评审的文本，但是，我们不能保证所有相关文档都已被恢复。此外，我们只考虑了以英语发表的完整论文。实际影响：与供应链相关的经理和公司必须逐步重新设计流程，以包括数据挖掘技术来支持SCRM的SCRM流程和活动。原创性/价值：本文显示了有关SCRM的数据挖掘实施的最新情况。我们没有发现任何类似的研究，这表明了我们的独特贡献。